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Author SHA1 Message Date
Rob Nertney
755892b795 Removing stray cpp from v12.1 2023-05-31 17:46:09 +00:00
4975 changed files with 1029580 additions and 190116 deletions

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13
.gitignore vendored
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build
build-*/
test-results*/
.vs
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test
settings.json
launch.json
__pycache__/
*.py[co]
.pytest_cache/
.vscode/*

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# Copyright (c) 2024, NVIDIA CORPORATION.
ci:
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[pre-commit.ci] auto code formatting
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autoupdate_commit_msg: '[pre-commit.ci] pre-commit autoupdate'
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## Changelog
### CUDA 13.4
* Removed obsolete samples `simpleHyperQ`, `simpleOccupancy`, `mergeSort`, `simpleTemplates`, `template`, `p2pBandwidthLatencyTest`.
* Removed redundant `_nvrtc` sample variants (`clock_nvrtc`, `matrixMul_nvrtc`, `simpleAssert_nvrtc`, `simpleAtomicIntrinsics_nvrtc`, `inlinePTX_nvrtc`, `binomialOptions_nvrtc`, `BlackScholes_nvrtc`, `quasirandomGenerator_nvrtc`); `vectorAdd_nvrtc` remains as the canonical NVRTC example.
* Rewrote `cpp/0_Introduction/simpleMultiGPU` to replace the hand-written reduction with `cub::BlockReduce` and the SDK stopwatch timer with CUDA events, removed helper header dependencies and merged `simpleMultiGPU.h` into the `.cu` for a single-file sample, modernized the code to C++17 (`std::vector`, `constexpr`), and added a minimum two-GPU check; updated README accordingly.
* Modernized `cpp/3_CUDA_Features/simpleCudaGraphs`: dropped `helper_cuda.h`/`cooperative_groups.h`; used `cub::BlockReduce`; migrated to the unified `cudaGraphAddNode` API; split into `simpleCudaGraphs_explicit` and `simpleCudaGraphs_capture` sharing `simpleCudaGraphs.cuh`; added a graph-reuse demo (fresh input each launch); rewrote README.
* Rewrote `cpp/0_Introduction/simpleAtomicIntrinsics` to show race conditions by comparing non-atomic vs atomic kernels (`atomicAdd`, `atomicMax`, `atomicCAS`), removed helper header dependencies; updated README accordingly.
* Reorganized CMake build system for all C++ samples: centralized GPU architecture detection (`DetectCudaArch.cmake`) and common build setup (`CudaSampleCommon.cmake`) into shared modules. Samples with restricted arch support now declare a `SAMPLE_DISALLOW_ARCHS` list instead of hardcoding their own arch list, and are gracefully skipped at configure time when the requested arch is unsupported.
* Added `sm_103` to the default set of GPU architectures the C++ samples build for.
* Added `sm_107` to the default set of GPU architectures the C++ samples build for.
* Rewrote `cpp/0_Introduction/simpleCallback` to replace the deprecated `cudaStreamAddCallback` with `cudaLaunchHostFunc`, replaced the `multithreading.h/.cpp` helpers with standard C++ `std::thread`, and simplified to a single-GPU, single-workload C++17 example; updated README accordingly.
* Rewrote `cpp/0_Introduction/simpleStreams` to simplify code and remove helper header dependencies; updated README accordingly.
* Added `python/2_CoreConcepts/persistentProgramCache` to demonstrate persisting and reusing compiled CUDA artifacts with `cuda.core` and `FileStreamProgramCache`.
* Updated `cpp/0_Introduction/clock` to replace the manual shared-memory tree reduction with `cub::BlockReduce` min-reduction, removed dependency on `helper_cuda.h` and `helper_functions.h`, and updated README.
* Rewrote `cpp/0_Introduction/vectorAdd` to match the corresponding example in the CUDA Programming Guide. The sample now uses Unified Memory (`cudaMallocManaged`) instead of explicit `cudaMalloc`/`cudaMemcpy`.
* Restructured the `cpp/0_Introduction/simplePrintf` README with newer style and updated sample code by removing helper dependency.
* Updated the `cpp/0_Introduction/simpleAssert` README to newer style, simplified code for better understanding.
* Added `cpp/3_CUDA_Features/dmabufInterop` - a Linux-only CUDA dma-buf interoperability sample demonstrating three scenarios in a single binary: (1) same-process round-trip export/import, (2) cross-process IPC via `fork()` + `SCM_RIGHTS`, and (3) cross-GPU sharing across processes (self-skips on systems without a qualifying GPU pair).
* Removed the unnecessary `set(CMAKE_POSITION_INDEPENDENT_CODE ON)` from the C++ sample `CMakeLists.txt` files.
* Removed `CUDA_SEPARABLE_COMPILATION ON` from C++ samples that don't require relocatable device code (kept for the CDP samples).
* Removed 26 math library samples from `cpp/4_CUDA_Libraries/` that are maintained in the [CUDA Library Samples](https://github.com/NVIDIA/CUDALibrarySamples) repository: cuBLAS (`simpleCUBLAS`, `simpleCUBLAS_LU`, `simpleCUBLASXT`, `matrixMulCUBLAS`, `batchCUBLAS`), cuFFT (`simpleCUFFT`, `simpleCUFFT_MGPU`, `simpleCUFFT_2d_MGPU`, `simpleCUFFT_callback`), cuRAND (`MersenneTwisterGP11213`), cuSOLVER (`cuSolverDn_LinearSolver`, `cuSolverRf`, `cuSolverSp_LinearSolver`, `cuSolverSp_LowlevelCholesky`, `cuSolverSp_LowlevelQR`), cuSPARSE (`conjugateGradient`, `conjugateGradientPrecond`, `conjugateGradientUM`), NPP (`boxFilterNPP`, `cannyEdgeDetectorNPP`, `FilterBorderControlNPP`, `freeImageInteropNPP`, `histEqualizationNPP`, `watershedSegmentationNPP`), and nvJPEG (`nvJPEG`, `nvJPEG_encoder`).
* Lifted the LLVM 14 upper bound on `cpp/7_libNVVM/cuda-c-linking`, which now builds against LLVM 15 and newer.
* Added samples for locality domains in `cpp/3_CUDA_FEATURES/localityDomains` and `cpp/3_CUDA_FEATURES/localityDomainsDrv`.
* Added Windows on Arm support: `cpp/5_Domain_Specific/marchingCubes` now detects the `glew32` GLEW library name used on Windows on Arm, and `cpp/7_libNVVM` searches the `nvvm/lib/arm64` directory for libNVVM.
### CUDA 13.3
* Added **CUDA Tile C++** samples under `cpp/9_CUDA_Tile`.
* Added a set of **CCCL 3.3 feature samples** under `cpp/4_CUDA_Libraries/`, each built against CCCL fetched via CPM (pinned to v3.3.3, with an optional `CCCL_SOURCE_DIR` override):
* `cubDeviceFind` - `cub::DeviceFind::FindIf`, `LowerBound`, and `UpperBound` device-wide search algorithms.
* `cubDeviceSegmentedScan` - `cub::DeviceSegmentedScan::ExclusiveSegmentedSum` and `InclusiveSegmentedScan` with a custom binary operator.
* `cubDeviceTransform` - N-to-M `cub::DeviceTransform::Transform` where the op returns a `cuda::std::tuple`.
* `libcuxxRandom` - `cuda::pcg64` and `cuda::std::philox4x32` engines driving the uniform, normal, Poisson, and Bernoulli distributions from `<cuda/std/random>`.
* `libcuxxMdspan` - DLPack <-> `cuda::std::mdspan` bridging via `cuda::to_device_mdspan` / `cuda::to_dlpack_tensor`, plus `cuda::shared_memory_mdspan` for multi-dimensional views of shared memory.
* Added **cuda.compute 1.0 Python samples** under `python/2_CoreConcepts/`:
* `cudaComputeLambdas` - Python lambdas / regular callables driving `reduce_into`, `unary_transform`, and `inclusive_scan` in `cuda.compute` (from the `cuda-cccl` package).
* `binarySearch` - parallel `cuda.compute.upper_bound` / `lower_bound`, verified against `numpy.searchsorted`.
### CUDA 13.2 (update)
* Added **CUDA Python samples** under `python/`. These scripts use [CUDA Python](https://nvidia.github.io/cuda-python/) (including `cuda.core`) and are organized like the C++ tree: `1_GettingStarted`, `2_CoreConcepts`, `3_FrameworkInterop`, and `4_DistributedComputing`, plus shared helpers in `python/Utilities`. Each sample includes a `README.md` and `requirements.txt`. They are **not** built by the root CMake project; install dependencies with `pip install -r requirements.txt` in the sample directory, then run the corresponding `.py` file as documented in that samples README.
* Renamed top-level `Samples` directory to `cpp` to accommodate Python samples alongside existing C++ samples; updated path references in `CMakeLists.txt`, `README.md`, and `Common` headers accordingly.
### CUDA 13.2
* Added the MSVC compile flag `-Xcompiler=/Zc:preprocessor` in CMakeLists.txt to comply with CUDA13.2 CCCL. Previously, using the traditional preprocessor triggered the warning “MSVC/cl.exe with traditional preprocessor is used…”, which now leads to a build error.
### CUDA 13.1
* Minor bug fixes and enhancements, no structural or functional changes
### CUDA 13.0
* Updated the samples using the cudaDeviceProp fields which are deprecated and removed in CUDA 13.0, replacing the fields with the equivalents in "cudaDeviceGetAttribute":
* Deprecated "cudaDeviceProp" fields
`int clockRate; // - Replaced with "cudaDevAttrClockRate"`
`int deviceOverlap; // - Replaced with "cudaDevAttrGpuOverlap */`
`int kernelExecTimeoutEnabled; // - Replaced with "cudaDevAttrKernelExecTimeout`
`int computeMode; // - Replaced with "cudaDevAttrComputeMode" */`
`int memoryClockRate; // - Replaced with "cudaDevAttrMemoryClockRate"`
`int cooperativeMultiDeviceLaunch; // - Deprecated, cudaLaunchCooperativeKernelMultiDevice is deprecated.`
* `0_Introduction`
* `UnifiedMemoryStreams`
* `simpleHyperQ`
* `simpleIPC`
* `simpleMultiCopy`
* `systemWideAtomics`
* `1_Utilitie`
* `deviceQuery`
* `2_Concepts_and_Techniques`
* `streamOrderedAllocationIPC`
* `4_CUDA_Libraries`
* `simpleCUBLASXT`
* `5_Domain_Specific`
* `simpleVulkan`
* `vulkanImageCUDA`
* Updated the samples using the CUDA driver API "cuCtxCreate" with adding the parameter "CUctxCreateParams" as "cuCtxCreate" is updated to "cuCtxCreate_v4" by default in CUDA 13.0:
* `Common`
* `nvrtc_helper.h`
* `0_Introduction`
* `UnifiedMemoryStreams`
* `matrixMulDrv`
* `simpleTextureDrv`
* `vectorAddDrv`
* `vectorAddMMAP`
* `2_Concepts_and_Techniques`
* `EGLStream_CUDA_CrossGPU`
* `EGLStream_CUDA_Interop`
* `threadMigration`
* `3_CUDA_Features`
* `graphMemoryFootprint`
* `memMapIPCDrv`
* `4_CUDA_Libraries`
* `jitLto`
* `7_libNVVM`
* `cuda-c-linking`
* `device-side-launch`
* `simple`
* `uvmlite`
* `8_Platform_Specific/Tegra`
* `EGLSync_CUDAEvent_Interop`
* Updated the sample using CUDA API "cudaGraphAddNode"/"cudaStreamGetCaptureInfo" with adding "cudaGraphEdgeData" pointer parameter as they are updated to "cudaGraphAddNode_v2"/"cudaStreamGetCaptureInfo_v3" by default in CUDA 13.0:
* `3_CUDA_Features`
* `graphConditionalNodes`
* Updated the samples using CUDA API "cudaMemAdvise"/"cudaMemPrefetchAsync" with changing the parameter "int device" to "cudaMemLocation location" as they are updated to "cudaMemAdvise_v2"/"cudaMemPrefetchAsyn_v2" by default in CUDA 13.0.
* `4_CUDA_Libraries`
* `conjugateGradientMultiDeviceCG`
* `6_Performance`
* `UnifiedMemoryPerf`
* Replaced "thrust::identity<uint>()" with "cuda::std::identity()" as it is deprecated in CUDA 13.0.
* `2_Concepts_and_Techniques`
* `segmentationTreeThrust`
* Updated the the headers file and samples for CUFFT error codes update.
* Deprecated CUFFT errors:
* `CUFFT_INCOMPLETE_PARAMETER_LIST`
* `CUFFT_PARSE_ERROR`
* `CUFFT_LICENSE_ERROR`
* New added CUFFT errors:
* `CUFFT_MISSING_DEPENDENCY`
* `CUFFT_NVRTC_FAILURE`
* `CUFFT_NVJITLINK_FAILURE`
* `CUFFT_NVSHMEM_FAILURE`
* Header files and samples that are related with this change:
* `Common/helper_cuda.h`
* `4_CUDA_Libraries`
* `simpleCUFFT`
* `simpleCUFFT_2d_MGPU`
* `simpleCUFFT_MGPU`
* `simpleCUFFT_callback`
* Updated toolchain for cross-compilation for Tegra QNX platforms.
### CUDA 12.9
* Updated toolchain for cross-compilation for Tegra Linux platforms.
* Added `run_tests.py` utility to exercise all samples. See README.md for details
* Repository has been updated with consistent code formatting across all samples
* Many small code tweaks and bug fixes (see commit history for details)
* Removed the following outdated samples:
* `1_Utilities`
* `bandwidthTest` - this sample was out of date and did not produce accurate results. For bandwidth
testing of NVIDIA GPU platforms, please refer to [NVBandwidth](https://github.com/NVIDIA/nvbandwidth)
### CUDA 12.8
* Updated build system across the repository to CMake. Removed Visual Studio project files and Makefiles.
* Removed the following outdated samples:
* `0_Introduction`
* `c++11_cuda` demonstrating CUDA and C++ 11 interoperability (reason: obsolete)
* `concurrentKernels` demonstrating the ability to run multiple kernels simultaneously (reason: obsolete)
* `cppIntegration` demonstrating calling between .cu and .cpp files (reason: obsolete)
* `cppOverload` demonstrating C++ function overloading (reason: obsolete)
* `simpleSeparateCompilation` demonstrating NVCC compilation to a static library (reason: trivial)
* `simpleTemplates_nvrtc` demonstrating NVRTC usage for `simpleTemplates` sample (reason: redundant)
* `simpleVoteIntrinsics_nvrtc` demonstrating NVRTC usage for `simpleVoteIntrinsics` sample (reason: redundant)
* `2_Concepts_and_Techniques`
* `cuHook` demonstrating dlsym hooks. (reason: incompatible with modern `glibc`)
* `4_CUDA_Libraries`
* `batchedLabelMarkersAndLabelCompressionNPP` demonstrating NPP features (reason: some functionality removed from library)
* `5_Domain_Specific`
* Legacy Direct3D 9 and 10 interoperability samples:
* `fluidsD3D9`
* `simpleD3D10`
* `simpleD3D10RenderTarget`
* `simpleD3D10Texture`
* `simpleD3D9`
* `simpleD3D9Texture`
* `SLID3D10Texture`
* `VFlockingD3D10`
* `8_Platform_Specific/Tegra`
* Temporarily removed the following two samples pending updates:
* `nbody_screen` demonstrating the nbody sample in QNX
* `simpleGLES_screen` demonstrating GLES interop in QNX
* Moved the following Tegra-specific samples to a dedicated subdirectory: `8_Platform_Specific/Tegra`
* `EGLSync_CUDAEvent_Interop`
* `cuDLAErrorReporting`
* `cuDLAHybridMode`
* `cuDLALayerwiseStatsHybrid`
* `cuDLALayerwiseStatsStandalone`
* `cuDLAStandaloneMode`
* `cudaNvSciBufMultiplanar`
* `cudaNvSciNvMedia`
* `fluidsGLES`
* `nbody_opengles`
* `simpleGLES`
* `simpleGLES_EGLOutput`
### CUDA 12.5
### CUDA 12.4
* Added graphConditionalNodes Sample
### CUDA 12.3
* Added cuDLA samples
* Fixed jitLto regression
### CUDA 12.2
* libNVVM samples received updates
* Fixed jitLto Case issues
* Enabled HOST_COMPILER flag to the makefiles for GCC which is untested but may still work.
### CUDA 12.1
* Added new sample for Large Kernels
### CUDA 12.0
* Added new flags for JIT compiling
* Added new flags for JIT compiling
* Removed deprecated APIs in Hopper Architecture
### CUDA 11.6

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cmake_minimum_required(VERSION 3.20)
include(cmake/CudaSampleArchs.cmake)
# Default to all supported architectures if the user does not specify.
# Gated on CUDA_SAMPLES_ARCHS_DEFAULTED rather than CMAKE_CUDA_ARCHITECTURES so this
# decision is made once (on the first configure) and does not flip on reconfigure,
# when CMAKE_CUDA_ARCHITECTURES is already defined from our own cached default.
# The decision is revisited when the list itself moves, which the user can do with -D
# on any later configure of the same build directory. Keep the list each configure
# ends up with, so that such a change is told apart from our own cached default.
if(NOT DEFINED CUDA_SAMPLES_ARCHS_DEFAULTED)
if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
list(JOIN CUDA_SAMPLES_MASTER_ARCHS ";" _default_archs)
set(CMAKE_CUDA_ARCHITECTURES "${_default_archs}" CACHE STRING "CUDA architectures")
unset(_default_archs)
set(CUDA_SAMPLES_ARCHS_DEFAULTED TRUE CACHE INTERNAL "")
else()
set(CUDA_SAMPLES_ARCHS_DEFAULTED FALSE CACHE INTERNAL "")
endif()
elseif(NOT "${CMAKE_CUDA_ARCHITECTURES}" STREQUAL "${CUDA_SAMPLES_LAST_CONFIGURED_ARCHS}")
set(CUDA_SAMPLES_ARCHS_DEFAULTED FALSE CACHE INTERNAL "")
endif()
set(CUDA_SAMPLES_LAST_CONFIGURED_ARCHS "${CMAKE_CUDA_ARCHITECTURES}" CACHE INTERNAL "")
project(cuda-samples LANGUAGES C CXX CUDA)
include(cmake/CudaSampleCommon.cmake)
add_subdirectory(cpp)

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# Contributing to the CUDA Samples
Thank you for your interest in contributing to the CUDA Samples!
## Getting Started
1. **Fork & Clone the Repository**:
Fork the reporistory and clone the fork. For more information, check [GitHub's documentation on forking](https://docs.github.com/en/github/getting-started-with-github/fork-a-repo) and [cloning a repository](https://docs.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository).
## Making Changes
1. **Create a New Branch**:
```bash
git checkout -b your-feature-branch
```
2. **Make Changes**.
3. **Build and Test**:
Ensure changes don't break existing functionality by building and running tests.
For more details on building and testing, refer to the [Building and Testing](#building-and-testing) section below.
4. **Commit Changes**:
```bash
git commit -m "Brief description of the change"
```
## Building and Testing
For information on building a running tests on the samples, please refer to the main [README](README.md)
## Creating a Pull Request
1. Push changes to your fork
2. Create a pull request targeting the `master` branch of the original CUDA Samples repository. Refer to [GitHub's documentation](https://docs.github.com/en/github/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-pull-requests) for more information on creating a pull request.
3. Describe the purpose and context of the changes in the pull request description.
## Code Formatting (pre-commit hooks)
The CUDA Samples repository uses [pre-commit](https://pre-commit.com/) to execute all code linters and formatters. These
tools ensure a consistent coding style throughout the project. Using pre-commit ensures that linter
versions and options are aligned for all developers. Additionally, there is a CI check in place to
enforce that committed code follows our standards.
The linters used by the CUDA Samples are listed in `.pre-commit-config.yaml`.
For example, C++ and CUDA code is formatted with [`clang-format`](https://clang.llvm.org/docs/ClangFormat.html).
To use `pre-commit`, install via `conda` or `pip`:
```bash
conda config --add channels conda-forge
conda install pre-commit
```
```bash
pip install pre-commit
```
Then run pre-commit hooks before committing code:
```bash
pre-commit run
```
By default, pre-commit runs on staged files (only changes and additions that will be committed).
To run pre-commit checks on all files, execute:
```bash
pre-commit run --all-files
```
Optionally, you may set up the pre-commit hooks to run automatically when you make a git commit. This can be done by running:
```bash
pre-commit install
```
Now code linters and formatters will be run each time you commit changes.
You can skip these checks with `git commit --no-verify` or with the short version `git commit -n`, althoguh please note
that this may result in pull requests being rejected if subsequent checks fail.
## Review Process
Once submitted, maintainers will be automatically assigned to review the pull request. They might suggest changes or improvements. Constructive feedback is a part of the collaborative process, aimed at ensuring the highest quality code.
For constructive feedback and effective communication during reviews, we recommend following [Conventional Comments](https://conventionalcomments.org/).
Further recommended reading for successful PR reviews:
- [How to Do Code Reviews Like a Human (Part One)](https://mtlynch.io/human-code-reviews-1/)
- [How to Do Code Reviews Like a Human (Part Two)](https://mtlynch.io/human-code-reviews-2/)
## Thank You
Your contributions enhance the CUDA Samples for the entire community. We appreciate your effort and collaboration!

197
Common/UtilNPP/Exceptions.h Normal file
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_EXCEPTIONS_H
#define NV_UTIL_NPP_EXCEPTIONS_H
#include <string>
#include <sstream>
#include <iostream>
/// All npp related C++ classes are put into the npp namespace.
namespace npp
{
/// Exception base class.
/// This exception base class will be used for everything C++ throught
/// the NPP project.
/// The exception contains a string message, as well as data fields for a string
/// containing the name of the file as well as the line number where the exception was thrown.
/// The easiest way of throwing exceptions and providing filename and line number is
/// to use one of the ASSERT macros defined for that purpose.
class Exception
{
public:
/// Constructor.
/// \param rMessage A message with information as to why the exception was thrown.
/// \param rFileName The name of the file where the exception was thrown.
/// \param nLineNumber Line number in the file where the exception was thrown.
explicit
Exception(const std::string &rMessage = "", const std::string &rFileName = "", unsigned int nLineNumber = 0)
: sMessage_(rMessage), sFileName_(rFileName), nLineNumber_(nLineNumber)
{ };
Exception(const Exception &rException)
: sMessage_(rException.sMessage_), sFileName_(rException.sFileName_), nLineNumber_(rException.nLineNumber_)
{ };
virtual
~Exception()
{ };
/// Get the exception's message.
const
std::string &
message()
const
{
return sMessage_;
}
/// Get the exception's file info.
const
std::string &
fileName()
const
{
return sFileName_;
}
/// Get the exceptions's line info.
unsigned int
lineNumber()
const
{
return nLineNumber_;
}
/// Create a clone of this exception.
/// This creates a new Exception object on the heap. It is
/// the responsibility of the user of this function to free this memory
/// (delete x).
virtual
Exception *
clone()
const
{
return new Exception(*this);
}
/// Create a single string with all the exceptions information.
/// The virtual toString() method is used by the operator<<()
/// so that all exceptions derived from this base-class can print
/// their full information correctly even if a reference to their
/// exact type is not had at the time of printing (i.e. the basic
/// operator<<() is used).
virtual
std::string
toString()
const
{
std::ostringstream oOutputString;
oOutputString << fileName() << ":" << lineNumber() << ": " << message();
return oOutputString.str();
}
private:
std::string sMessage_; ///< Message regarding the cause of the exception.
std::string sFileName_; ///< Name of the file where the exception was thrown.
unsigned int nLineNumber_; ///< Line number in the file where the exception was thrown
};
/// Output stream inserter for Exception.
/// \param rOutputStream The stream the exception information is written to.
/// \param rException The exception that's being written.
/// \return Reference to the output stream being used.
std::ostream &
operator << (std::ostream &rOutputStream, const Exception &rException)
{
rOutputStream << rException.toString();
return rOutputStream;
}
/// Basic assert macro.
/// This macro should be used to enforce any kind of pre or post conditions.
/// Unlike the C-runtime assert macro, this macro does not abort execution, but throws
/// a C++ exception. The exception is automatically filled with information about the failing
/// condition, the filename and line number where the exception was thrown.
/// \note The macro is written in such a way that omitting a semicolon after its usage
/// causes a compiler error. The correct way to invoke this macro is:
/// NPP_ASSERT(n < MAX);
#define NPP_ASSERT(C) do {if (!(C)) throw npp::Exception(#C " assertion faild!", __FILE__, __LINE__);} while(false)
// ASSERT macro.
// Same functionality as the basic assert macro with the added ability to pass
// a message M. M should be a string literal.
// Note: Never use code inside ASSERT() that causes a side-effect ASSERT macros may get compiled
// out in release mode.
#define NPP_ASSERT_MSG(C, M) do {if (!(C)) throw npp::Exception(#C " assertion faild! Message: " M, __FILE__, __LINE__);} while(false)
#ifdef _DEBUG
/// Basic debug assert macro.
/// This macro is identical in every respect to NPP_ASSERT(C) but it does get compiled to a
/// no-op in release builds. It is therefor of utmost importance to not put statements into
/// this macro that cause side effects required for correct program execution.
#define NPP_DEBUG_ASSERT(C) do {if (!(C)) throw npp::Exception(#C " debug assertion faild!", __FILE__, __LINE__);} while(false)
#else
#define NPP_DEBUG_ASSERT(C)
#endif
/// ASSERT for null-pointer test.
/// It is safe to put code with side effects into this macro. Also: This macro never
/// gets compiled to a no-op because resource allocation may fail based on external causes not under
/// control of a software developer.
#define NPP_ASSERT_NOT_NULL(P) do {if ((P) == 0) throw npp::Exception(#P " not null assertion faild!", __FILE__, __LINE__);} while(false)
/// Macro for flagging methods as not implemented.
/// The macro throws an exception with a message that an implementation was missing
#define NPP_NOT_IMPLEMENTED() do {throw npp::Exception("Implementation missing!", __FILE__, __LINE__);} while(false)
/// Macro for checking error return code of CUDA (runtime) calls.
/// This macro never gets disabled.
#define NPP_CHECK_CUDA(S) do {cudaError_t eCUDAResult; \
eCUDAResult = S; \
if (eCUDAResult != cudaSuccess) std::cout << "NPP_CHECK_CUDA - eCUDAResult = " << eCUDAResult << std::endl; \
NPP_ASSERT(eCUDAResult == cudaSuccess);} while (false)
/// Macro for checking error return code for NPP calls.
#define NPP_CHECK_NPP(S) do {NppStatus eStatusNPP; \
eStatusNPP = S; \
if (eStatusNPP != NPP_SUCCESS) std::cout << "NPP_CHECK_NPP - eStatusNPP = " << _cudaGetErrorEnum(eStatusNPP) << "("<< eStatusNPP << ")" << std::endl; \
NPP_ASSERT(eStatusNPP == NPP_SUCCESS);} while (false)
/// Macro for checking error return codes from cuFFT calls.
#define NPP_CHECK_CUFFT(S) do {cufftResult eCUFFTResult; \
eCUFFTResult = S; \
if (eCUFFTResult != NPP_SUCCESS) std::cout << "NPP_CHECK_CUFFT - eCUFFTResult = " << eCUFFTResult << std::endl; \
NPP_ASSERT(eCUFFTResult == CUFFT_SUCCESS);} while (false)
} // npp namespace
#endif // NV_UTIL_NPP_EXCEPTIONS_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGE_H
#define NV_UTIL_NPP_IMAGE_H
#include <cstddef>
namespace npp
{
class Image
{
public:
struct Size
{
unsigned int nWidth;
unsigned int nHeight;
Size() : nWidth(0), nHeight(0)
{ };
Size(unsigned int nWidthNew, unsigned nHeightNew) : nWidth(nWidthNew), nHeight(nHeightNew)
{ };
Size(const Size &rSize) : nWidth(rSize.nWidth), nHeight(rSize.nHeight)
{ };
Size &
operator= (const Size &rSize)
{
if (&rSize == this)
{
return *this;
}
nWidth = rSize.nWidth;
nHeight = rSize.nHeight;
return *this;
}
void
swap(Size &rSize)
{
unsigned int nTemp;
nTemp = nWidth;
nWidth = rSize.nWidth;
rSize.nWidth = nTemp;
nTemp = nHeight;
nHeight = rSize.nHeight;
rSize.nHeight = nTemp;
}
};
Image()
{ };
Image(unsigned int nWidth, unsigned int nHeight) : oSize_(nWidth, nHeight)
{ };
Image(const Image::Size &rSize) : oSize_(rSize)
{ };
Image(const Image &rImage) : oSize_(rImage.oSize_)
{ };
virtual
~Image()
{ };
Image &
operator= (const Image &rImage)
{
if (&rImage == this)
{
return *this;
}
oSize_ = rImage.oSize_;
return *this;
};
unsigned int
width()
const
{
return oSize_.nWidth;
}
unsigned int
height()
const
{
return oSize_.nHeight;
}
Size
size()
const
{
return oSize_;
}
void
swap(Image &rImage)
{
oSize_.swap(rImage.oSize_);
}
private:
Size oSize_;
};
bool
operator== (const Image::Size &rFirst, const Image::Size &rSecond)
{
return rFirst.nWidth == rSecond.nWidth && rFirst.nHeight == rSecond.nHeight;
}
bool
operator!= (const Image::Size &rFirst, const Image::Size &rSecond)
{
return rFirst.nWidth != rSecond.nWidth || rFirst.nHeight != rSecond.nHeight;
}
} // npp namespace
#endif // NV_UTIL_NPP_IMAGE_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGE_ALLOCATORS_CPU_H
#define NV_UTIL_NPP_IMAGE_ALLOCATORS_CPU_H
#include "Exceptions.h"
namespace npp
{
template <typename D, size_t N>
class ImageAllocatorCPU
{
public:
static
D *
Malloc2D(unsigned int nWidth, unsigned int nHeight, unsigned int *pPitch)
{
NPP_ASSERT(nWidth * nHeight > 0);
D *pResult = new D[nWidth * N * nHeight];
*pPitch = nWidth * sizeof(D) * N;
return pResult;
};
static
void
Free2D(D *pPixels)
{
delete[] pPixels;
};
static
void
Copy2D(D *pDst, size_t nDstPitch, const D *pSrc, size_t nSrcPitch, size_t nWidth, size_t nHeight)
{
const void *pSrcLine = pSrc;
void *pDstLine = pDst;
for (size_t iLine = 0; iLine < nHeight; ++iLine)
{
// copy one line worth of data
memcpy(pDst, pSrc, nWidth * N * sizeof(D));
// move data pointers to next line
pDst += nDstPitch;
pSrc += nSrcPitch;
}
};
};
} // npp namespace
#endif // NV_UTIL_NPP_IMAGE_ALLOCATORS_CPU_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGE_IO_H
#define NV_UTIL_NPP_IMAGE_IO_H
#include "ImagesCPU.h"
#include "ImagesNPP.h"
#include "FreeImage.h"
#include "Exceptions.h"
#include <string>
#include "string.h"
// Error handler for FreeImage library.
// In case this handler is invoked, it throws an NPP exception.
void
FreeImageErrorHandler(FREE_IMAGE_FORMAT oFif, const char *zMessage)
{
throw npp::Exception(zMessage);
}
namespace npp
{
// Load a gray-scale image from disk.
void
loadImage(const std::string &rFileName, ImageCPU_8u_C1 &rImage)
{
// set your own FreeImage error handler
FreeImage_SetOutputMessage(FreeImageErrorHandler);
FREE_IMAGE_FORMAT eFormat = FreeImage_GetFileType(rFileName.c_str());
// no signature? try to guess the file format from the file extension
if (eFormat == FIF_UNKNOWN)
{
eFormat = FreeImage_GetFIFFromFilename(rFileName.c_str());
}
NPP_ASSERT(eFormat != FIF_UNKNOWN);
// check that the plugin has reading capabilities ...
FIBITMAP *pBitmap;
if (FreeImage_FIFSupportsReading(eFormat))
{
pBitmap = FreeImage_Load(eFormat, rFileName.c_str());
}
NPP_ASSERT(pBitmap != 0);
// make sure this is an 8-bit single channel image
NPP_ASSERT(FreeImage_GetColorType(pBitmap) == FIC_MINISBLACK);
NPP_ASSERT(FreeImage_GetBPP(pBitmap) == 8);
// create an ImageCPU to receive the loaded image data
ImageCPU_8u_C1 oImage(FreeImage_GetWidth(pBitmap), FreeImage_GetHeight(pBitmap));
// Copy the FreeImage data into the new ImageCPU
unsigned int nSrcPitch = FreeImage_GetPitch(pBitmap);
const Npp8u *pSrcLine = FreeImage_GetBits(pBitmap) + nSrcPitch * (FreeImage_GetHeight(pBitmap) -1);
Npp8u *pDstLine = oImage.data();
unsigned int nDstPitch = oImage.pitch();
for (size_t iLine = 0; iLine < oImage.height(); ++iLine)
{
memcpy(pDstLine, pSrcLine, oImage.width() * sizeof(Npp8u));
pSrcLine -= nSrcPitch;
pDstLine += nDstPitch;
}
// swap the user given image with our result image, effecively
// moving our newly loaded image data into the user provided shell
oImage.swap(rImage);
}
// Save an gray-scale image to disk.
void
saveImage(const std::string &rFileName, const ImageCPU_8u_C1 &rImage)
{
// create the result image storage using FreeImage so we can easily
// save
FIBITMAP *pResultBitmap = FreeImage_Allocate(rImage.width(), rImage.height(), 8 /* bits per pixel */);
NPP_ASSERT_NOT_NULL(pResultBitmap);
unsigned int nDstPitch = FreeImage_GetPitch(pResultBitmap);
Npp8u *pDstLine = FreeImage_GetBits(pResultBitmap) + nDstPitch * (rImage.height()-1);
const Npp8u *pSrcLine = rImage.data();
unsigned int nSrcPitch = rImage.pitch();
for (size_t iLine = 0; iLine < rImage.height(); ++iLine)
{
memcpy(pDstLine, pSrcLine, rImage.width() * sizeof(Npp8u));
pSrcLine += nSrcPitch;
pDstLine -= nDstPitch;
}
// now save the result image
bool bSuccess;
bSuccess = FreeImage_Save(FIF_PGM, pResultBitmap, rFileName.c_str(), 0) == TRUE;
NPP_ASSERT_MSG(bSuccess, "Failed to save result image.");
}
// Load a gray-scale image from disk.
void
loadImage(const std::string &rFileName, ImageNPP_8u_C1 &rImage)
{
ImageCPU_8u_C1 oImage;
loadImage(rFileName, oImage);
ImageNPP_8u_C1 oResult(oImage);
rImage.swap(oResult);
}
// Save an gray-scale image to disk.
void
saveImage(const std::string &rFileName, const ImageNPP_8u_C1 &rImage)
{
ImageCPU_8u_C1 oHostImage(rImage.size());
// copy the device result data
rImage.copyTo(oHostImage.data(), oHostImage.pitch());
saveImage(rFileName, oHostImage);
}
}
#endif // NV_UTIL_NPP_IMAGE_IO_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGE_PACKED_H
#define NV_UTIL_NPP_IMAGE_PACKED_H
#include "Image.h"
#include "Pixel.h"
namespace npp
{
template<typename D, size_t N, class A>
class ImagePacked: public npp::Image
{
public:
typedef npp::Pixel<D, N> tPixel;
typedef D tData;
static const size_t gnChannels = N;
typedef npp::Image::Size tSize;
ImagePacked(): aPixels_(0)
, nPitch_(0)
{
;
}
ImagePacked(unsigned int nWidth, unsigned int nHeight): Image(nWidth, nHeight)
, aPixels_(0)
, nPitch_(0)
{
aPixels_ = A::Malloc2D(width(), height(), &nPitch_);
}
ImagePacked(unsigned int nWidth, unsigned int nHeight, bool bTight): Image(nWidth, nHeight)
, aPixels_(0)
, nPitch_(0)
{
aPixels_ = A::Malloc2D(width(), height(), &nPitch_, bTight);
}
ImagePacked(const tSize &rSize): Image(rSize)
, aPixels_(0)
, nPitch_(0)
{
aPixels_ = A::Malloc2D(width(), height(), &nPitch_);
}
ImagePacked(const ImagePacked<D, N, A> &rImage): Image(rImage)
, aPixels_(0)
, nPitch_(rImage.pitch())
{
aPixels_ = A::Malloc2D(width(), height(), &nPitch_);
A::Copy2D(aPixels_, nPitch_, rImage.pixels(), rImage.pitch(), width(), height());
}
virtual
~ImagePacked()
{
A::Free2D(aPixels_);
}
ImagePacked &
operator= (const ImagePacked<D, N, A> &rImage)
{
// in case of self-assignment
if (&rImage == this)
{
return *this;
}
A::Free2D(aPixels_);
aPixels_ = 0;
nPitch_ = 0;
// assign parent class's data fields (width, height)
Image::operator =(rImage);
aPixels_ = A::Malloc2D(width(), height(), &nPitch_);
A::Copy2D(aPixels_, nPitch_, rImage.data(), rImage.pitch(), width(), height());
return *this;
}
unsigned int
pitch()
const
{
return nPitch_;
}
/// Get a pointer to the pixel array.
/// The result pointer can be offset to pixel at position (x, y) and
/// even negative offsets are allowed.
/// \param nX Horizontal pointer/array offset.
/// \param nY Vertical pointer/array offset.
/// \return Pointer to the pixel array (or first pixel in array with coordinates (nX, nY).
tPixel *
pixels(int nX = 0, int nY = 0)
{
return reinterpret_cast<tPixel *>(reinterpret_cast<unsigned char *>(aPixels_) + nY * pitch() + nX * gnChannels * sizeof(D));
}
const
tPixel *
pixels(int nX = 0, int nY = 0)
const
{
return reinterpret_cast<const tPixel *>(reinterpret_cast<unsigned char *>(aPixels_) + nY * pitch() + nX * gnChannels * sizeof(D));
}
D *
data(int nX = 0, int nY = 0)
{
return reinterpret_cast<D *>(pixels(nX, nY));
}
const
D *
data(int nX = 0, int nY = 0)
const
{
return reinterpret_cast<const D *>(pixels(nX, nY));
}
void
swap(ImagePacked<D, N, A> &rImage)
{
Image::swap(rImage);
tData *aTemp = aPixels_;
aPixels_ = rImage.aPixels_;
rImage.aPixels_ = aTemp;
unsigned int nTemp = nPitch_;
nPitch_ = rImage.nPitch_;
rImage.nPitch_ = nTemp;
}
private:
D *aPixels_;
unsigned int nPitch_;
};
} // npp namespace
#endif // NV_IMAGE_IPP_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGES_CPU_H
#define NV_UTIL_NPP_IMAGES_CPU_H
#include "ImagePacked.h"
#include "ImageAllocatorsCPU.h"
#include "Exceptions.h"
#include <npp.h>
namespace npp
{
template<typename D, unsigned int N, class A>
class ImageCPU: public npp::ImagePacked<D, N, A>
{
public:
ImageCPU()
{
;
}
ImageCPU(unsigned int nWidth, unsigned int nHeight): ImagePacked<D, N, A>(nWidth, nHeight)
{
;
}
explicit
ImageCPU(const npp::Image::Size &rSize): ImagePacked<D, N, A>(rSize)
{
;
}
ImageCPU(const ImageCPU<D, N, A> &rImage): Image(rImage)
{
;
}
virtual
~ImageCPU()
{
;
}
ImageCPU &
operator= (const ImageCPU<D, N, A> &rImage)
{
ImagePacked<D, N, A>::operator= (rImage);
return *this;
}
npp::Pixel<D, N> &
operator()(unsigned int iX, unsigned int iY)
{
return *ImagePacked<D, N, A>::pixels(iX, iY);
}
npp::Pixel<D, N>
operator()(unsigned int iX, unsigned int iY)
const
{
return *ImagePacked<D, N, A>::pixels(iX, iY);
}
};
typedef ImageCPU<Npp8u, 1, npp::ImageAllocatorCPU<Npp8u, 1> > ImageCPU_8u_C1;
typedef ImageCPU<Npp8u, 2, npp::ImageAllocatorCPU<Npp8u, 2> > ImageCPU_8u_C2;
typedef ImageCPU<Npp8u, 3, npp::ImageAllocatorCPU<Npp8u, 3> > ImageCPU_8u_C3;
typedef ImageCPU<Npp8u, 4, npp::ImageAllocatorCPU<Npp8u, 4> > ImageCPU_8u_C4;
typedef ImageCPU<Npp16u, 1, npp::ImageAllocatorCPU<Npp16u, 1> > ImageCPU_16u_C1;
typedef ImageCPU<Npp16u, 3, npp::ImageAllocatorCPU<Npp16u, 3> > ImageCPU_16u_C3;
typedef ImageCPU<Npp16u, 4, npp::ImageAllocatorCPU<Npp16u, 4> > ImageCPU_16u_C4;
typedef ImageCPU<Npp16s, 1, npp::ImageAllocatorCPU<Npp16s, 1> > ImageCPU_16s_C1;
typedef ImageCPU<Npp16s, 3, npp::ImageAllocatorCPU<Npp16s, 3> > ImageCPU_16s_C3;
typedef ImageCPU<Npp16s, 4, npp::ImageAllocatorCPU<Npp16s, 4> > ImageCPU_16s_C4;
typedef ImageCPU<Npp32s, 1, npp::ImageAllocatorCPU<Npp32s, 1> > ImageCPU_32s_C1;
typedef ImageCPU<Npp32s, 3, npp::ImageAllocatorCPU<Npp32s, 3> > ImageCPU_32s_C3;
typedef ImageCPU<Npp32s, 4, npp::ImageAllocatorCPU<Npp32s, 4> > ImageCPU_32s_C4;
typedef ImageCPU<Npp32f, 1, npp::ImageAllocatorCPU<Npp32f, 1> > ImageCPU_32f_C1;
typedef ImageCPU<Npp32f, 3, npp::ImageAllocatorCPU<Npp32f, 3> > ImageCPU_32f_C3;
typedef ImageCPU<Npp32f, 4, npp::ImageAllocatorCPU<Npp32f, 4> > ImageCPU_32f_C4;
} // npp namespace
#endif // NV_IMAGE_IPP_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_IMAGES_NPP_H
#define NV_UTIL_NPP_IMAGES_NPP_H
#include "Exceptions.h"
#include "ImagePacked.h"
#include "ImageAllocatorsNPP.h"
#include <cuda_runtime.h>
namespace npp
{
// forward declaration
template<typename D, unsigned int N, class A> class ImageCPU;
template<typename D, unsigned int N>
class ImageNPP: public npp::ImagePacked<D, N, npp::ImageAllocator<D, N> >
{
public:
ImageNPP()
{
;
}
ImageNPP(unsigned int nWidth, unsigned int nHeight, bool bTight = false): ImagePacked<D, N, npp::ImageAllocator<D, N> >(nWidth, nHeight, bTight)
{
;
}
ImageNPP(const npp::Image::Size &rSize): ImagePacked<D, N, npp::ImageAllocator<D, N> >(rSize)
{
;
}
ImageNPP(const ImageNPP<D, N> &rImage): Image(rImage)
{
;
}
template<class X>
explicit
ImageNPP(const ImageCPU<D, N, X> &rImage, bool bTight = false): ImagePacked<D, N, npp::ImageAllocator<D, N> >(rImage.width(), rImage.height(), bTight)
{
npp::ImageAllocator<D, N>::HostToDeviceCopy2D(ImagePacked<D, N, npp::ImageAllocator<D, N> >::data(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::pitch(),
rImage.data(),
rImage.pitch(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::width(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::height());
}
virtual
~ImageNPP()
{
;
}
ImageNPP &
operator= (const ImageNPP<D, N> &rImage)
{
ImagePacked<D, N, npp::ImageAllocator<D, N> >::operator= (rImage);
return *this;
}
void
copyTo(D *pData, unsigned int nPitch)
const
{
NPP_ASSERT((ImagePacked<D, N, npp::ImageAllocator<D, N> >::width() * sizeof(npp::Pixel<D, N>) <= nPitch));
npp::ImageAllocator<D, N>::DeviceToHostCopy2D(pData,
nPitch,
ImagePacked<D, N, npp::ImageAllocator<D, N> >::data(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::pitch(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::width(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::height());
}
void
copyFrom(D *pData, unsigned int nPitch)
{
NPP_ASSERT((ImagePacked<D, N, npp::ImageAllocator<D, N> >::width() * sizeof(npp::Pixel<D, N>) <= nPitch));
npp::ImageAllocator<D, N>::HostToDeviceCopy2D(ImagePacked<D, N, npp::ImageAllocator<D, N> >::data(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::pitch(),
pData,
nPitch,
ImagePacked<D, N, npp::ImageAllocator<D, N> >::width(),
ImagePacked<D, N, npp::ImageAllocator<D, N> >::height());
}
};
typedef ImageNPP<Npp8u, 1> ImageNPP_8u_C1;
typedef ImageNPP<Npp8u, 2> ImageNPP_8u_C2;
typedef ImageNPP<Npp8u, 3> ImageNPP_8u_C3;
typedef ImageNPP<Npp8u, 4> ImageNPP_8u_C4;
typedef ImageNPP<Npp16u, 1> ImageNPP_16u_C1;
typedef ImageNPP<Npp16u, 2> ImageNPP_16u_C2;
typedef ImageNPP<Npp16u, 3> ImageNPP_16u_C3;
typedef ImageNPP<Npp16u, 4> ImageNPP_16u_C4;
typedef ImageNPP<Npp16s, 1> ImageNPP_16s_C1;
typedef ImageNPP<Npp16s, 3> ImageNPP_16s_C3;
typedef ImageNPP<Npp16s, 4> ImageNPP_16s_C4;
typedef ImageNPP<Npp32s, 1> ImageNPP_32s_C1;
typedef ImageNPP<Npp32s, 3> ImageNPP_32s_C3;
typedef ImageNPP<Npp32s, 4> ImageNPP_32s_C4;
typedef ImageNPP<Npp32f, 1> ImageNPP_32f_C1;
typedef ImageNPP<Npp32f, 2> ImageNPP_32f_C2;
typedef ImageNPP<Npp32f, 3> ImageNPP_32f_C3;
typedef ImageNPP<Npp32f, 4> ImageNPP_32f_C4;
typedef ImageNPP<Npp64f, 1> ImageNPP_64f_C1;
typedef ImageNPP<Npp64f, 2> ImageNPP_64f_C2;
typedef ImageNPP<Npp64f, 3> ImageNPP_64f_C3;
typedef ImageNPP<Npp64f, 4> ImageNPP_64f_C4;
} // npp namespace
#endif // NV_UTIL_NPP_IMAGES_NPP_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_PIXEL_H
#define NV_UTIL_PIXEL_H
#include "Exceptions.h"
namespace npp
{
template <typename D, size_t N>
struct Pixel
{ };
template <typename D>
struct Pixel<D, 1>
{
D x;
const D &
operator[](size_t iChannel)
const
{
NPP_ASSERT(iChannel < 1);
return (&x)[iChannel];
}
D &
operator[](size_t iChannel)
{
NPP_ASSERT(iChannel < 1);
return (&x)[iChannel];
}
};
template <typename D>
struct Pixel<D, 2>
{
D x,y;
const D &
operator[](size_t iChannel)
const
{
NPP_ASSERT(iChannel < 2);
return (&x)[iChannel];
}
D &
operator[](size_t iChannel)
{
NPP_ASSERT(iChannel < 2);
return (&x)[iChannel];
}
};
template <typename D>
struct Pixel<D, 3>
{
D x,y,z;
const D &
operator[](size_t iChannel)
const
{
NPP_ASSERT(iChannel < 3);
return (&x)[iChannel];
}
D &
operator[](size_t iChannel)
{
NPP_ASSERT(iChannel < 3);
return (&x)[iChannel];
}
};
template <typename D>
struct Pixel<D, 4>
{
D x, y, z, w;
const D &
operator[](size_t iChannel)
const
{
NPP_ASSERT(iChannel < 4);
return (&x)[iChannel];
}
D &
operator[](size_t iChannel)
{
NPP_ASSERT(iChannel < 4);
return (&x)[iChannel];
}
};
} // npp namespace
#endif // NV_UTIL_PIXEL_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_SIGNAL_H
#define NV_UTIL_NPP_SIGNAL_H
#include <cstring>
namespace npp
{
class Signal
{
public:
Signal() : nSize_(0)
{ };
explicit
Signal(size_t nSize) : nSize_(nSize)
{ };
Signal(const Signal &rSignal) : nSize_(rSignal.nSize_)
{ };
virtual
~Signal()
{ }
Signal &
operator= (const Signal &rSignal)
{
nSize_ = rSignal.nSize_;
return *this;
}
size_t
size()
const
{
return nSize_;
}
void
swap(Signal &rSignal)
{
size_t nTemp = nSize_;
nSize_ = rSignal.nSize_;
rSignal.nSize_ = nTemp;
}
private:
size_t nSize_;
};
template<typename D, class A>
class SignalTemplate: public Signal
{
public:
typedef D tData;
SignalTemplate(): aValues_(0)
{
;
}
SignalTemplate(size_t nSize): Signal(nSize)
, aValues_(0)
{
aValues_ = A::Malloc1D(size());
}
SignalTemplate(const SignalTemplate<D, A> &rSignal): Signal(rSignal)
, aValues_(0)
{
aValues_ = A::Malloc1D(size());
A::Copy1D(aValues_, rSignal.values(), size());
}
virtual
~SignalTemplate()
{
A::Free1D(aValues_);
}
SignalTemplate &
operator= (const SignalTemplate<D, A> &rSignal)
{
// in case of self-assignment
if (&rSignal == this)
{
return *this;
}
A::Free1D(aValues_);
this->aPixels_ = 0;
// assign parent class's data fields (width, height)
Signal::operator =(rSignal);
aValues_ = A::Malloc1D(size());
A::Copy1D(aValues_, rSignal.value(), size());
return *this;
}
/// Get a pointer to the pixel array.
/// The result pointer can be offset to pixel at position (x, y) and
/// even negative offsets are allowed.
/// \param nX Horizontal pointer/array offset.
/// \param nY Vertical pointer/array offset.
/// \return Pointer to the pixel array (or first pixel in array with coordinates (nX, nY).
tData *
values(int i = 0)
{
return aValues_ + i;
}
const
tData *
values(int i = 0)
const
{
return aValues_ + i;
}
void
swap(SignalTemplate<D, A> &rSignal)
{
Signal::swap(rSignal);
tData *aTemp = this->aValues_;
this->aValues_ = rSignal.aValues_;
rSignal.aValues_ = aTemp;
}
private:
D *aValues_;
};
} // npp namespace
#endif // NV_UTIL_NPP_SIGNAL_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_SIGNAL_ALLOCATORS_CPU_H
#define NV_UTIL_NPP_SIGNAL_ALLOCATORS_CPU_H
#include "Exceptions.h"
namespace npp
{
template <typename D>
class SignalAllocatorCPU
{
public:
static
D *
Malloc1D(unsigned int nSize)
{
return new D[nSize];;
};
static
void
Free1D(D *pPixels)
{
delete[] pPixels;
};
static
void
Copy1D(D *pDst, const D *pSrc, size_t nSize)
{
memcpy(pDst, pSrc, nSize * sizeof(D));
};
};
} // npp namespace
#endif // NV_UTIL_NPP_SIGNAL_ALLOCATORS_CPU_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_SIGNAL_ALLOCATORS_NPP_H
#define NV_UTIL_NPP_SIGNAL_ALLOCATORS_NPP_H
#include "Exceptions.h"
#include <npps.h>
#include <cuda_runtime.h>
namespace npp
{
template <typename D>
class SignalAllocator
{
};
template<>
class SignalAllocator<Npp8u>
{
public:
static
Npp8u *
Malloc1D(size_t nSize)
{
Npp8u *pResult = nppsMalloc_8u(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp8u *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp8u *pDst, const Npp8u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp8u),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp8u *pDst, const Npp8u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp8u), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp8u *pDst, const Npp8u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp8u), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp16s>
{
public:
static
Npp16s *
Malloc1D(size_t nSize)
{
Npp16s *pResult = nppsMalloc_16s(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp16s *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp16s *pDst, const Npp16s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16s),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp16s *pDst, const Npp16s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16s), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp16s *pDst, const Npp16s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16s), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp16u>
{
public:
static
Npp16u *
Malloc1D(size_t nSize)
{
Npp16u *pResult = nppsMalloc_16u(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp16u *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp16u *pDst, const Npp16u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16u),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp16u *pDst, const Npp16u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16u), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp16u *pDst, const Npp16u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16u), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp16sc>
{
public:
static
Npp16sc *
Malloc1D(size_t nSize)
{
Npp16sc *pResult = nppsMalloc_16sc(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp16sc *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp16sc *pDst, const Npp16sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16sc),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp16sc *pDst, const Npp16sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16sc), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp16sc *pDst, const Npp16sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp16sc), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp32u>
{
public:
static
Npp32u *
Malloc1D(size_t nSize)
{
Npp32u *pResult = nppsMalloc_32u(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp32u *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp32u *pDst, const Npp32u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32u),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp32u *pDst, const Npp32u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32u), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp32u *pDst, const Npp32u *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32u), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp32s>
{
public:
static
Npp32s *
Malloc1D(size_t nSize)
{
Npp32s *pResult = nppsMalloc_32s(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp32s *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp32s *pDst, const Npp32s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32s),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp32s *pDst, const Npp32s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32s), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp32s *pDst, const Npp32s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32s), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp32sc>
{
public:
static
Npp32sc *
Malloc1D(size_t nSize)
{
Npp32sc *pResult = nppsMalloc_32sc(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp32sc *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp32sc *pDst, const Npp32sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32sc),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp32sc *pDst, const Npp32sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32sc), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp32sc *pDst, const Npp32sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32sc), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp32f>
{
public:
static
Npp32f *
Malloc1D(size_t nSize)
{
Npp32f *pResult = nppsMalloc_32f(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp32f *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp32f *pDst, const Npp32f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32f),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp32f *pDst, const Npp32f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32f), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp32f *pDst, const Npp32f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32f), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp32fc>
{
public:
static
Npp32fc *
Malloc1D(size_t nSize)
{
Npp32fc *pResult = nppsMalloc_32fc(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp32fc *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp32fc *pDst, const Npp32fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32fc),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp32fc *pDst, const Npp32fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32fc), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp32fc *pDst, const Npp32fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp32fc), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp64s>
{
public:
static
Npp64s *
Malloc1D(size_t nSize)
{
Npp64s *pResult = nppsMalloc_64s(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp64s *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp64s *pDst, const Npp64s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64s),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp64s *pDst, const Npp64s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64s), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp64s *pDst, const Npp64s *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64s), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp64sc>
{
public:
static
Npp64sc *
Malloc1D(size_t nSize)
{
Npp64sc *pResult = nppsMalloc_64sc(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp64sc *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp64sc *pDst, const Npp64sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64sc),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp64sc *pDst, const Npp64sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64sc), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp64sc *pDst, const Npp64sc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64sc), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp64f>
{
public:
static
Npp64f *
Malloc1D(size_t nSize)
{
Npp64f *pResult = nppsMalloc_64f(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp64f *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp64f *pDst, const Npp64f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64f),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp64f *pDst, const Npp64f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64f), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp64f *pDst, const Npp64f *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64f), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
template<>
class SignalAllocator<Npp64fc>
{
public:
static
Npp64fc *
Malloc1D(size_t nSize)
{
Npp64fc *pResult = nppsMalloc_64fc(static_cast<int>(nSize));
NPP_ASSERT(pResult != 0);
return pResult;
};
static
void
Free1D(Npp64fc *pValues)
{
nppsFree(pValues);
};
static
void
Copy1D(Npp64fc *pDst, const Npp64fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64fc),cudaMemcpyDeviceToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
HostToDeviceCopy1D(Npp64fc *pDst, const Npp64fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64fc), cudaMemcpyHostToDevice);
NPP_ASSERT(cudaSuccess == eResult);
};
static
void
DeviceToHostCopy1D(Npp64fc *pDst, const Npp64fc *pSrc, size_t nSize)
{
cudaError_t eResult;
eResult = cudaMemcpy(pDst, pSrc, nSize * sizeof(Npp64fc), cudaMemcpyDeviceToHost);
NPP_ASSERT(cudaSuccess == eResult);
};
};
} // npp namespace
#endif // NV_UTIL_NPP_SIGNAL_ALLOCATORS_NPP_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_SIGNALS_CPU_H
#define NV_UTIL_NPP_SIGNALS_CPU_H
#include "Signal.h"
#include "SignalAllocatorsCPU.h"
#include "Exceptions.h"
#include <npp.h>
namespace npp
{
template<typename D, class A>
class SignalCPU: public npp::SignalTemplate<D, A>
{
public:
typedef typename npp::SignalTemplate<D, A>::tData tData;
SignalCPU()
{
;
}
SignalCPU(size_t nSize): SignalTemplate<D, A>(nSize)
{
;
}
SignalCPU(const SignalCPU<D, A> &rSignal): SignalTemplate<D, A>(rSignal)
{
;
}
virtual
~SignalCPU()
{
;
}
SignalCPU &
operator= (const SignalCPU<D,A> &rSignal)
{
SignalTemplate<D, A>::operator= (rSignal);
return *this;
}
tData &
operator [](unsigned int i)
{
return *SignalTemplate<D, A>::values(i);
}
tData
operator [](unsigned int i)
const
{
return *SignalTemplate<D, A>::values(i);
}
};
typedef SignalCPU<Npp8u, npp::SignalAllocatorCPU<Npp8u> > SignalCPU_8u;
typedef SignalCPU<Npp32s, npp::SignalAllocatorCPU<Npp32s> > SignalCPU_32s;
typedef SignalCPU<Npp16s, npp::SignalAllocatorCPU<Npp16s> > SignalCPU_16s;
typedef SignalCPU<Npp16sc, npp::SignalAllocatorCPU<Npp16sc> > SignalCPU_16sc;
typedef SignalCPU<Npp32sc, npp::SignalAllocatorCPU<Npp32sc> > SignalCPU_32sc;
typedef SignalCPU<Npp32f, npp::SignalAllocatorCPU<Npp32f> > SignalCPU_32f;
typedef SignalCPU<Npp32fc, npp::SignalAllocatorCPU<Npp32fc> > SignalCPU_32fc;
typedef SignalCPU<Npp64s, npp::SignalAllocatorCPU<Npp64s> > SignalCPU_64s;
typedef SignalCPU<Npp64sc, npp::SignalAllocatorCPU<Npp64sc> > SignalCPU_64sc;
typedef SignalCPU<Npp64f, npp::SignalAllocatorCPU<Npp64f> > SignalCPU_64f;
typedef SignalCPU<Npp64fc, npp::SignalAllocatorCPU<Npp64fc> > SignalCPU_64fc;
} // npp namespace
#endif // NV_UTIL_NPP_SIGNALS_CPU_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef NV_UTIL_NPP_SIGNALS_NPP_H
#define NV_UTIL_NPP_SIGNALS_NPP_H
#include "Exceptions.h"
#include "Signal.h"
#include "SignalAllocatorsNPP.h"
#include <cuda_runtime.h>
namespace npp
{
// forward declaration
template<typename D, class A> class SignalCPU;
template<typename D>
class SignalNPP: public npp::SignalTemplate<D, npp::SignalAllocator<D> >
{
public:
SignalNPP()
{
;
}
explicit
SignalNPP(size_t nSize): SignalTemplate<D, npp::SignalAllocator<D> >(nSize)
{
;
}
SignalNPP(const SignalNPP<D> &rSignal): SignalTemplate<D, npp::SignalAllocator<D> >(rSignal)
{
;
}
template<class X>
explicit
SignalNPP(const SignalCPU<D, X> &rSignal): SignalTemplate<D, npp::SignalAllocator<D> >(rSignal.size())
{
npp::SignalAllocator<D>::HostToDeviceCopy1D(SignalTemplate<D, npp::SignalAllocator<D> >::values(),
rSignal.values(), SignalTemplate<D, npp::SignalAllocator<D> >::size());
}
virtual
~SignalNPP()
{
;
}
SignalNPP &
operator= (const SignalNPP<D> &rSignal)
{
SignalTemplate<D, npp::SignalAllocator<D> >::operator= (rSignal);
return *this;
}
void
copyTo(D *pValues)
const
{
npp::SignalAllocator<D>::DeviceToHostCopy1D(pValues, SignalTemplate<D, npp::SignalAllocator<D> >::values(), SignalTemplate<D, npp::SignalAllocator<D> >::size());
}
void
copyFrom(D *pValues)
{
npp::SignalAllocator<D>::HostToDeviceCopy1D(SignalTemplate<D, npp::SignalAllocator<D> >::values(), pValues, SignalTemplate<D, npp::SignalAllocator<D> >::size());
}
};
typedef SignalNPP<Npp8u> SignalNPP_8u;
typedef SignalNPP<Npp16s> SignalNPP_16s;
typedef SignalNPP<Npp16sc> SignalNPP_16sc;
typedef SignalNPP<Npp32s> SignalNPP_32s;
typedef SignalNPP<Npp32sc> SignalNPP_32sc;
typedef SignalNPP<Npp32f> SignalNPP_32f;
typedef SignalNPP<Npp32fc> SignalNPP_32fc;
typedef SignalNPP<Npp64s> SignalNPP_64s;
typedef SignalNPP<Npp64sc> SignalNPP_64sc;
typedef SignalNPP<Npp64f> SignalNPP_64f;
typedef SignalNPP<Npp64fc> SignalNPP_64fc;
} // npp namespace
#endif // NV_UTIL_NPP_SIGNALS_NPP_H

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
//--------------------------------------------------------------------------------------
// File: dynlink_d3d10.h
//
// Shortcut macros and functions for using DX objects
//
// Copyright (c) Microsoft Corporation. All rights reserved
//--------------------------------------------------------------------------------------
#ifndef _DYNLINK_D3D10_H_
#define _DYNLINK_D3D10_H_
// Standard Windows includes
#include <windows.h>
#include <initguid.h>
#include <assert.h>
#include <wchar.h>
#include <mmsystem.h>
#include <commctrl.h> // for InitCommonControls()
#include <shellapi.h> // for ExtractIcon()
#include <new.h> // for placement new
#include <shlobj.h>
#include <math.h>
#include <limits.h>
#include <stdio.h>
// CRT's memory leak detection
#if defined(DEBUG) || defined(_DEBUG)
#include <crtdbg.h>
#endif
// Direct3D9 includes
#include <d3d9.h>
// Direct3D10 includes
#include <dxgi.h>
#include <d3d10_1.h>
#include <d3d10.h>
// XInput includes
#include <xinput.h>
// strsafe.h deprecates old unsecure string functions. If you
// really do not want to it to (not recommended), then uncomment the next line
//#define STRSAFE_NO_DEPRECATE
#ifndef STRSAFE_NO_DEPRECATE
#pragma deprecated("strncpy")
#pragma deprecated("wcsncpy")
#pragma deprecated("_tcsncpy")
#pragma deprecated("wcsncat")
#pragma deprecated("strncat")
#pragma deprecated("_tcsncat")
#endif
#pragma warning( disable : 4996 ) // disable deprecated warning
#include <strsafe.h>
#pragma warning( default : 4996 )
#include <DirectXMath.h>
using namespace DirectX;
//--------------------------------------------------------------------------------------
// Structs
//--------------------------------------------------------------------------------------
struct DXUTD3D9DeviceSettings
{
UINT AdapterOrdinal;
D3DDEVTYPE DeviceType;
D3DFORMAT AdapterFormat;
DWORD BehaviorFlags;
D3DPRESENT_PARAMETERS pp;
};
struct DXUTD3D10DeviceSettings
{
UINT AdapterOrdinal;
D3D10_DRIVER_TYPE DriverType;
UINT Output;
DXGI_SWAP_CHAIN_DESC sd;
UINT32 CreateFlags;
UINT32 SyncInterval;
DWORD PresentFlags;
bool AutoCreateDepthStencil; // DXUT will create the a depth stencil resource and view if true
DXGI_FORMAT AutoDepthStencilFormat;
};
enum DXUTDeviceVersion { DXUT_D3D9_DEVICE, DXUT_D3D10_DEVICE };
struct DXUTDeviceSettings
{
DXUTDeviceVersion ver;
union
{
DXUTD3D9DeviceSettings d3d9; // only valid if ver == DXUT_D3D9_DEVICE
DXUTD3D10DeviceSettings d3d10; // only valid if ver == DXUT_D3D10_DEVICE
};
};
//--------------------------------------------------------------------------------------
// Error codes
//--------------------------------------------------------------------------------------
#define DXUTERR_NODIRECT3D MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0901)
#define DXUTERR_NOCOMPATIBLEDEVICES MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0902)
#define DXUTERR_MEDIANOTFOUND MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0903)
#define DXUTERR_NONZEROREFCOUNT MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0904)
#define DXUTERR_CREATINGDEVICE MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0905)
#define DXUTERR_RESETTINGDEVICE MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0906)
#define DXUTERR_CREATINGDEVICEOBJECTS MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0907)
#define DXUTERR_RESETTINGDEVICEOBJECTS MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x0908)
#define DXUTERR_DEVICEREMOVED MAKE_HRESULT(SEVERITY_ERROR, FACILITY_ITF, 0x090A)
typedef HRESULT(WINAPI *LPCREATEDXGIFACTORY)(REFIID, void **);
typedef HRESULT(WINAPI *LPD3D10CREATEDEVICE)(IDXGIAdapter *, D3D10_DRIVER_TYPE, HMODULE, UINT, UINT32,
ID3D10Device **);
typedef HRESULT(WINAPI *LPD3D10CREATEDEVICE1)(IDXGIAdapter *, D3D10_DRIVER_TYPE, HMODULE, UINT,
D3D10_FEATURE_LEVEL1, UINT, ID3D10Device1 **);
typedef HRESULT(WINAPI *LPD3D10CREATESTATEBLOCK)(ID3D10Device *pDevice, D3D10_STATE_BLOCK_MASK *pStateBlockMask,
ID3D10StateBlock **ppStateBlock);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKUNION)(D3D10_STATE_BLOCK_MASK *pA, D3D10_STATE_BLOCK_MASK *pB,
D3D10_STATE_BLOCK_MASK *pResult);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKINTERSECT)(D3D10_STATE_BLOCK_MASK *pA, D3D10_STATE_BLOCK_MASK *pB,
D3D10_STATE_BLOCK_MASK *pResult);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKDIFFERENCE)(D3D10_STATE_BLOCK_MASK *pA, D3D10_STATE_BLOCK_MASK *pB,
D3D10_STATE_BLOCK_MASK *pResult);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKENABLECAPTURE)(D3D10_STATE_BLOCK_MASK *pMask,
D3D10_DEVICE_STATE_TYPES StateType, UINT RangeStart,
UINT RangeLength);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKDISABLECAPTURE)(D3D10_STATE_BLOCK_MASK *pMask,
D3D10_DEVICE_STATE_TYPES StateType, UINT RangeStart,
UINT RangeLength);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKENABLEALL)(D3D10_STATE_BLOCK_MASK *pMask);
typedef HRESULT(WINAPI *LPD3D10STATEBLOCKMASKDISABLEALL)(D3D10_STATE_BLOCK_MASK *pMask);
typedef BOOL (WINAPI *LPD3D10STATEBLOCKMASKGETSETTING)(D3D10_STATE_BLOCK_MASK *pMask,
D3D10_DEVICE_STATE_TYPES StateType, UINT Entry);
typedef HRESULT(WINAPI *LPD3D10COMPILEEFFECTFROMMEMORY)(void *pData, SIZE_T DataLength, LPCSTR pSrcFileName,
CONST D3D10_SHADER_MACRO *pDefines,
ID3D10Include *pInclude, UINT HLSLFlags, UINT FXFlags,
ID3D10Blob **ppCompiledEffect, ID3D10Blob **ppErrors);
typedef HRESULT(WINAPI *LPD3D10CREATEEFFECTFROMMEMORY)(void *pData, SIZE_T DataLength, UINT FXFlags,
ID3D10Device *pDevice,
ID3D10EffectPool *pEffectPool,
ID3D10Effect **ppEffect);
typedef HRESULT(WINAPI *LPD3D10CREATEEFFECTPOOLFROMMEMORY)(void *pData, SIZE_T DataLength, UINT FXFlags,
ID3D10Device *pDevice, ID3D10EffectPool **ppEffectPool);
typedef HRESULT(WINAPI *LPD3D10CREATEDEVICEANDSWAPCHAIN)(IDXGIAdapter *pAdapter,
D3D10_DRIVER_TYPE DriverType,
HMODULE Software,
UINT Flags,
UINT SDKVersion,
DXGI_SWAP_CHAIN_DESC *pSwapChainDesc,
IDXGISwapChain **ppSwapChain,
ID3D10Device **ppDevice);
typedef HRESULT(WINAPI *LPD3D10CREATEDEVICEANDSWAPCHAIN1)(IDXGIAdapter *pAdapter,
D3D10_DRIVER_TYPE DriverType,
HMODULE Software,
UINT Flags,
D3D10_FEATURE_LEVEL1 HardwareLevel,
UINT SDKVersion,
DXGI_SWAP_CHAIN_DESC *pSwapChainDesc,
IDXGISwapChain **ppSwapChain,
ID3D10Device1 **ppDevice);
// Module and function pointers
static HMODULE g_hModDXGI = NULL;
static HMODULE g_hModD3D10 = NULL;
static HMODULE g_hModD3D101 = NULL;
static LPCREATEDXGIFACTORY sFnPtr_CreateDXGIFactory = NULL;
static LPD3D10CREATESTATEBLOCK sFnPtr_D3D10CreateStateBlock = NULL;
static LPD3D10CREATEDEVICE sFnPtr_D3D10CreateDevice = NULL;
static LPD3D10CREATEDEVICE1 sFnPtr_D3D10CreateDevice1 = NULL;
static LPD3D10STATEBLOCKMASKUNION sFnPtr_D3D10StateBlockMaskUnion = NULL;
static LPD3D10STATEBLOCKMASKINTERSECT sFnPtr_D3D10StateBlockMaskIntersect = NULL;
static LPD3D10STATEBLOCKMASKDIFFERENCE sFnPtr_D3D10StateBlockMaskDifference = NULL;
static LPD3D10STATEBLOCKMASKENABLECAPTURE sFnPtr_D3D10StateBlockMaskEnableCapture = NULL;
static LPD3D10STATEBLOCKMASKDISABLECAPTURE sFnPtr_D3D10StateBlockMaskDisableCapture = NULL;
static LPD3D10STATEBLOCKMASKENABLEALL sFnPtr_D3D10StateBlockMaskEnableAll = NULL;
static LPD3D10STATEBLOCKMASKDISABLEALL sFnPtr_D3D10StateBlockMaskDisableAll = NULL;
static LPD3D10STATEBLOCKMASKGETSETTING sFnPtr_D3D10StateBlockMaskGetSetting = NULL;
static LPD3D10COMPILEEFFECTFROMMEMORY sFnPtr_D3D10CompileEffectFromMemory = NULL;
static LPD3D10CREATEEFFECTFROMMEMORY sFnPtr_D3D10CreateEffectFromMemory = NULL;
static LPD3D10CREATEEFFECTPOOLFROMMEMORY sFnPtr_D3D10CreateEffectPoolFromMemory = NULL;
static LPD3D10CREATEDEVICEANDSWAPCHAIN sFnPtr_D3D10CreateDeviceAndSwapChain = NULL;
static LPD3D10CREATEDEVICEANDSWAPCHAIN1 sFnPtr_D3D10CreateDeviceAndSwapChain1 = NULL;
// unload the D3D10 DLLs
static bool dynlinkUnloadD3D10API(void)
{
if (g_hModD3D10)
{
FreeLibrary(g_hModD3D10);
g_hModD3D10 = NULL;
}
if (g_hModDXGI)
{
FreeLibrary(g_hModDXGI);
g_hModDXGI = NULL;
}
if (g_hModD3D101)
{
FreeLibrary(g_hModD3D101);
g_hModD3D101 = NULL;
}
return true;
}
// Dynamically load the D3D10 DLLs loaded and map the function pointers
static bool dynlinkLoadD3D10API(void)
{
// First check to see if the D3D10 Library is present.
// if it succeeds, then we can call GetProcAddress to grab all of the DX10 functions
g_hModD3D10 = LoadLibrary("d3d10.dll");
if (g_hModD3D10 != NULL)
{
sFnPtr_D3D10CreateStateBlock = (LPD3D10CREATESTATEBLOCK) GetProcAddress(g_hModD3D10, "D3D10CreateStateBlock");
sFnPtr_D3D10CreateDevice = (LPD3D10CREATEDEVICE) GetProcAddress(g_hModD3D10, "D3D10CreateDevice");
sFnPtr_D3D10StateBlockMaskUnion = (LPD3D10STATEBLOCKMASKUNION) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskUnion");
sFnPtr_D3D10StateBlockMaskIntersect = (LPD3D10STATEBLOCKMASKINTERSECT) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskIntersect");
sFnPtr_D3D10StateBlockMaskDifference = (LPD3D10STATEBLOCKMASKDIFFERENCE) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskDifference");
sFnPtr_D3D10StateBlockMaskEnableCapture = (LPD3D10STATEBLOCKMASKENABLECAPTURE) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskEnableCapture");
sFnPtr_D3D10StateBlockMaskDisableCapture = (LPD3D10STATEBLOCKMASKDISABLECAPTURE)GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskDisableCapture");
sFnPtr_D3D10StateBlockMaskEnableAll = (LPD3D10STATEBLOCKMASKENABLEALL) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskEnableAll");
sFnPtr_D3D10StateBlockMaskDisableAll = (LPD3D10STATEBLOCKMASKDISABLEALL) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskDisableAll");
sFnPtr_D3D10StateBlockMaskGetSetting = (LPD3D10STATEBLOCKMASKGETSETTING) GetProcAddress(g_hModD3D10, "D3D10StateBlockMaskGetSetting");
sFnPtr_D3D10CompileEffectFromMemory = (LPD3D10COMPILEEFFECTFROMMEMORY) GetProcAddress(g_hModD3D10, "D3D10CompileEffectFromMemory");
sFnPtr_D3D10CreateEffectFromMemory = (LPD3D10CREATEEFFECTFROMMEMORY) GetProcAddress(g_hModD3D10, "D3D10CreateEffectFromMemory");
sFnPtr_D3D10CreateEffectPoolFromMemory = (LPD3D10CREATEEFFECTPOOLFROMMEMORY) GetProcAddress(g_hModD3D10, "D3D10CreateEffectPoolFromMemory");
sFnPtr_D3D10CreateDeviceAndSwapChain = (LPD3D10CREATEDEVICEANDSWAPCHAIN) GetProcAddress(g_hModD3D10, "D3D10CreateDeviceAndSwapChain");
}
g_hModDXGI = LoadLibrary("dxgi.dll");
if (g_hModDXGI)
{
sFnPtr_CreateDXGIFactory = (LPCREATEDXGIFACTORY) GetProcAddress(g_hModDXGI , "CreateDXGIFactory");
}
// This may fail if this machine isn't Windows Vista SP1 or later
g_hModD3D101 = LoadLibrary("d3d10_1.dll");
if (g_hModD3D101 != NULL)
{
sFnPtr_D3D10CreateDevice1 = (LPD3D10CREATEDEVICE1) GetProcAddress(g_hModD3D101, "D3D10CreateDevice1");
sFnPtr_D3D10CreateDeviceAndSwapChain1 = (LPD3D10CREATEDEVICEANDSWAPCHAIN1) GetProcAddress(g_hModD3D101, "D3D10CreateDeviceAndSwapChain1");
}
if (g_hModD3D10 == NULL || g_hModDXGI == NULL || g_hModD3D101 == NULL)
{
dynlinkUnloadD3D10API();
return false;
}
return true;
}
#endif

View File

@ -138,29 +138,26 @@ static const char *_cudaGetErrorEnum(cufftResult error) {
case CUFFT_UNALIGNED_DATA:
return "CUFFT_UNALIGNED_DATA";
case CUFFT_INCOMPLETE_PARAMETER_LIST:
return "CUFFT_INCOMPLETE_PARAMETER_LIST";
case CUFFT_INVALID_DEVICE:
return "CUFFT_INVALID_DEVICE";
case CUFFT_PARSE_ERROR:
return "CUFFT_PARSE_ERROR";
case CUFFT_NO_WORKSPACE:
return "CUFFT_NO_WORKSPACE";
case CUFFT_NOT_IMPLEMENTED:
return "CUFFT_NOT_IMPLEMENTED";
case CUFFT_LICENSE_ERROR:
return "CUFFT_LICENSE_ERROR";
case CUFFT_NOT_SUPPORTED:
return "CUFFT_NOT_SUPPORTED";
case CUFFT_MISSING_DEPENDENCY:
return "CUFFT_MISSING_DEPENDENCY";
case CUFFT_NVRTC_FAILURE:
return "CUFFT_NVRTC_FAILURE";
case CUFFT_NVJITLINK_FAILURE:
return "CUFFT_NVJITLINK_FAILURE";
case CUFFT_NVSHMEM_FAILURE:
return "CUFFT_NVSHMEM_FAILURE";
}
return "<unknown>";
@ -671,13 +668,6 @@ inline int _ConvertSMVer2Cores(int major, int minor) {
{0x87, 128},
{0x89, 128},
{0x90, 128},
{0xa0, 128},
{0xa1, 128},
{0xa3, 128},
{0xa7, 128},
{0xb0, 128},
{0xc0, 128},
{0xc1, 128},
{-1, -1}};
int index = 0;
@ -727,13 +717,6 @@ inline const char* _ConvertSMVer2ArchName(int major, int minor) {
{0x87, "Ampere"},
{0x89, "Ada"},
{0x90, "Hopper"},
{0xa0, "Blackwell"},
{0xa1, "Blackwell"},
{0xa3, "Blackwell"},
{0xa7, "Rubin"},
{0xb0, "Blackwell"},
{0xc0, "Blackwell"},
{0xc1, "Blackwell"},
{-1, "Graphics Device"}};
int index = 0;

View File

@ -116,13 +116,6 @@ inline int _ConvertSMVer2CoresDRV(int major, int minor) {
{0x87, 128},
{0x89, 128},
{0x90, 128},
{0xa0, 128},
{0xa1, 128},
{0xa3, 128},
{0xa7, 128},
{0xb0, 128},
{0xc0, 128},
{0xc1, 128},
{-1, -1}};
int index = 0;
@ -245,7 +238,7 @@ inline int gpuGetMaxGflopsDeviceIdDRV() {
}
unsigned long long compute_perf =
((unsigned long long)multiProcessorCount * sm_per_multiproc *
(unsigned long long)(multiProcessorCount * sm_per_multiproc *
clockRate);
if (compute_perf > max_compute_perf) {
@ -412,3 +405,4 @@ bool inline findFatbinPath(const char *module_file, std::string &module_path, ch
// end of CUDA Helper Functions
#endif // COMMON_HELPER_CUDA_DRVAPI_H_

View File

@ -1143,16 +1143,10 @@ inline __host__ __device__ uint4 max(uint4 a, uint4 b)
// - linear interpolation between a and b, based on value t in [0, 1] range
////////////////////////////////////////////////////////////////////////////////
// std::lerp (C++20) is pulled into the global namespace by GCC's <cmath>;
// only define our own scalar overload when std::lerp is unavailable, to avoid
// a redeclaration / ambiguous-overload clash. (The float2/3/4 overloads below
// take distinct argument types and never conflict.)
#if !defined(__cplusplus) || (__cplusplus < 202002L)
inline __device__ __host__ float lerp(float a, float b, float t)
{
return a + t*(b-a);
}
#endif
inline __device__ __host__ float2 lerp(float2 a, float2 b, float t)
{
return a + t*(b-a);

View File

@ -168,7 +168,7 @@ int waitProcess(Process *process) {
#endif
}
#if defined(__linux__) || defined(__QNX__)
#if defined(__linux__)
int ipcCreateSocket(ipcHandle *&handle, const char *name,
const std::vector<Process> &processes) {
int server_fd;
@ -185,32 +185,25 @@ int ipcCreateSocket(ipcHandle *&handle, const char *name,
return -1;
}
char path_name[sizeof(servaddr.sun_path)];
unlink(name);
bzero(&servaddr, sizeof(servaddr));
servaddr.sun_family = AF_UNIX;
// Create unique name for the socket with path if SOCK_FOLDER is set.
int written = snprintf(path_name, sizeof(path_name), "%s/%u",
getSocketFolder().c_str(), getpid());
if (written < 0 || (size_t)written >= sizeof(path_name)) {
size_t len = strlen(name);
if (len > (sizeof(servaddr.sun_path) - 1)) {
perror("IPC failure: Cannot bind provided name to socket. Name too large");
close(server_fd);
delete handle;
handle = NULL;
return -1;
}
unlink(path_name);
memset(&servaddr, 0, sizeof(servaddr));
servaddr.sun_family = AF_UNIX;
strncpy(servaddr.sun_path, path_name, sizeof(servaddr.sun_path) - 1);
strncpy(servaddr.sun_path, name, len);
if (bind(server_fd, (struct sockaddr *)&servaddr, SUN_LEN(&servaddr)) < 0) {
perror("IPC failure: Binding socket failed");
return -1;
}
handle->socketName = new char[strlen(path_name) + 1];
strcpy(handle->socketName, path_name);
handle->socketName = new char[strlen(name) + 1];
strcpy(handle->socketName, name);
handle->socket = server_fd;
return 0;
}
@ -226,21 +219,13 @@ int ipcOpenSocket(ipcHandle *&handle) {
perror("IPC failure:Socket creation error");
return -1;
}
memset(&cliaddr, 0, sizeof(cliaddr));
cliaddr.sun_family = AF_UNIX;
char temp[sizeof(cliaddr.sun_path)];
// Create unique name for the socket with path if SOCK_FOLDER is set.
int written = snprintf(temp, sizeof(temp), "%s/%u", getSocketFolder().c_str(),
getpid());
if (written < 0 || (size_t)written >= sizeof(temp)) {
perror("IPC failure: Cannot bind provided name to socket. Name too large");
close(sock);
delete handle;
handle = NULL;
return -1;
}
bzero(&cliaddr, sizeof(cliaddr));
cliaddr.sun_family = AF_UNIX;
char temp[10];
// Create unique name for the socket.
sprintf(temp, "%u", getpid());
strcpy(cliaddr.sun_path, temp);
if (bind(sock, (struct sockaddr *)&cliaddr, sizeof(cliaddr)) < 0) {
@ -277,48 +262,41 @@ int ipcRecvShareableHandle(ipcHandle *handle, ShareableHandle *shHandle) {
// Union to guarantee alignment requirements for control array
union {
struct cmsghdr cm;
// This will not work on QNX as QNX CMSG_SPACE calls __cmsg_alignbytes
// And __cmsg_alignbytes is a runtime function instead of compile-time macros
// char control[CMSG_SPACE(sizeof(int))]
char* control;
char control[CMSG_SPACE(sizeof(int))];
} control_un;
size_t sizeof_control = CMSG_SPACE(sizeof(int)) * sizeof(char);
control_un.control = (char*) malloc(sizeof_control);
struct cmsghdr *cmptr;
ssize_t n;
int receivedfd;
char dummy_buffer[1];
ssize_t sendResult;
msg.msg_control = control_un.control;
msg.msg_controllen = sizeof_control;
msg.msg_controllen = sizeof(control_un.control);
iov[0].iov_base = (void *)dummy_buffer;
iov[0].iov_len = sizeof(dummy_buffer);
msg.msg_iov = iov;
msg.msg_iovlen = 1;
if ((n = recvmsg(handle->socket, &msg, 0)) <= 0) {
perror("IPC failure: Receiving data over socket failed");
free(control_un.control);
return -1;
}
if (((cmptr = CMSG_FIRSTHDR(&msg)) != NULL) &&
(cmptr->cmsg_len == CMSG_LEN(sizeof(int)))) {
if ((cmptr->cmsg_level != SOL_SOCKET) || (cmptr->cmsg_type != SCM_RIGHTS)) {
free(control_un.control);
return -1;
}
memmove(&receivedfd, CMSG_DATA(cmptr), sizeof(receivedfd));
*(int *)shHandle = receivedfd;
} else {
free(control_un.control);
return -1;
}
free(control_un.control);
return 0;
}
@ -341,7 +319,7 @@ int ipcSendDataToServer(ipcHandle *handle, const char *serverName,
ssize_t sendResult;
struct sockaddr_un serveraddr;
memset(&serveraddr, 0, sizeof(serveraddr));
bzero(&serveraddr, sizeof(serveraddr));
serveraddr.sun_family = AF_UNIX;
strncpy(serveraddr.sun_path, serverName, sizeof(serveraddr.sun_path) - 1);
@ -362,28 +340,19 @@ int ipcSendShareableHandle(ipcHandle *handle,
union {
struct cmsghdr cm;
char* control;
char control[CMSG_SPACE(sizeof(int))];
} control_un;
size_t sizeof_control = CMSG_SPACE(sizeof(int)) * sizeof(char);
control_un.control = (char*) malloc(sizeof_control);
struct cmsghdr *cmptr;
ssize_t readResult;
struct sockaddr_un cliaddr;
socklen_t len = sizeof(cliaddr);
// Construct client address to send this SHareable handle to
memset(&cliaddr, 0, sizeof(cliaddr));
bzero(&cliaddr, sizeof(cliaddr));
cliaddr.sun_family = AF_UNIX;
char temp[sizeof(cliaddr.sun_path)];
int written =
snprintf(temp, sizeof(temp), "%s/%u", getSocketFolder().c_str(), process);
if (written < 0 || (size_t)written >= sizeof(temp)) {
perror("IPC failure: Cannot address client socket. Name too large");
free(control_un.control);
return -1;
}
char temp[10];
sprintf(temp, "%u", process);
strcpy(cliaddr.sun_path, temp);
len = sizeof(cliaddr);
@ -391,7 +360,7 @@ int ipcSendShareableHandle(ipcHandle *handle,
int sendfd = (int)shareableHandles[data];
msg.msg_control = control_un.control;
msg.msg_controllen = sizeof_control;
msg.msg_controllen = sizeof(control_un.control);
cmptr = CMSG_FIRSTHDR(&msg);
cmptr->cmsg_len = CMSG_LEN(sizeof(int));
@ -411,11 +380,9 @@ int ipcSendShareableHandle(ipcHandle *handle,
ssize_t sendResult = sendmsg(handle->socket, &msg, 0);
if (sendResult <= 0) {
perror("IPC failure: Sending data over socket failed");
free(control_un.control);
return -1;
}
free(control_un.control);
return 0;
}

View File

@ -54,27 +54,6 @@
#endif
#include <vector>
// The Unix domain sockets creating folder on QNX has been restricted to qnx6-mounted directories since QNX SDP 8.0.3.
#if defined(__QNX__)
#include <string>
inline std::string getSocketFolder() {
return "/storage";
}
// Simple filesystem compatibility for GCC 8.x
#elif defined(__GNUC__) && __GNUC__ < 9
#include <cstdlib>
#include <string>
inline std::string getSocketFolder() {
const char* tmpdir = std::getenv("TMPDIR");
return tmpdir ? std::string(tmpdir) : "/tmp";
}
#else
#include <filesystem>
inline std::string getSocketFolder() {
return std::filesystem::temp_directory_path().string();
}
#endif
typedef struct sharedMemoryInfo_st {
void *addr;
size_t size;
@ -105,7 +84,7 @@ int waitProcess(Process *process);
#define checkIpcErrors(ipcFuncResult) \
if (ipcFuncResult == -1) { fprintf(stderr, "Failure at %u %s\n", __LINE__, __FILE__); exit(EXIT_FAILURE); }
#if defined(__linux__) || defined(__QNX__)
#if defined(__linux__)
struct ipcHandle_st {
int socket;
char *socketName;

View File

@ -400,9 +400,9 @@ int getInputDir(std::string &input_dir, const char *executable_path) {
std::string pathname = "";
const char *searchPath[] = {
"./images",
"../../../../cpp/4_CUDA_Libraries/<executable_name>/images",
"../../../cpp/4_CUDA_Libraries/<executable_name>/images",
"../../cpp/4_CUDA_Libraries/<executable_name>/images"};
"../../../../Samples/4_CUDA_Libraries/<executable_name>/images",
"../../../Samples/4_CUDA_Libraries/<executable_name>/images",
"../../Samples/4_CUDA_Libraries/<executable_name>/images"};
for (unsigned int i = 0; i < sizeof(searchPath) / sizeof(char *); ++i) {
std::string pathname(searchPath[i]);

View File

@ -288,79 +288,73 @@ inline char *sdkFindFilePath(const char *filename,
"./", // same dir
"./data/", // same dir
"../../../../cpp/<executable_name>/", // up 4 in tree
"../../../cpp/<executable_name>/", // up 3 in tree
"../../cpp/<executable_name>/", // up 2 in tree
"../../../../Samples/<executable_name>/", // up 4 in tree
"../../../Samples/<executable_name>/", // up 3 in tree
"../../Samples/<executable_name>/", // up 2 in tree
"../../../../cpp/<executable_name>/data/", // up 4 in tree
"../../../cpp/<executable_name>/data/", // up 3 in tree
"../../cpp/<executable_name>/data/", // up 2 in tree
"../../../../Samples/<executable_name>/data/", // up 4 in tree
"../../../Samples/<executable_name>/data/", // up 3 in tree
"../../Samples/<executable_name>/data/", // up 2 in tree
"../../../../cpp/0_Introduction/<executable_name>/", // up 4 in tree
"../../../cpp/0_Introduction/<executable_name>/", // up 3 in tree
"../../cpp/0_Introduction/<executable_name>/", // up 2 in tree
"../../../../Samples/0_Introduction/<executable_name>/", // up 4 in tree
"../../../Samples/0_Introduction/<executable_name>/", // up 3 in tree
"../../Samples/0_Introduction/<executable_name>/", // up 2 in tree
"../../../../cpp/1_Utilities/<executable_name>/", // up 4 in tree
"../../../cpp/1_Utilities/<executable_name>/", // up 3 in tree
"../../cpp/1_Utilities/<executable_name>/", // up 2 in tree
"../../../../Samples/1_Utilities/<executable_name>/", // up 4 in tree
"../../../Samples/1_Utilities/<executable_name>/", // up 3 in tree
"../../Samples/1_Utilities/<executable_name>/", // up 2 in tree
"../../../../cpp/2_Concepts_and_Techniques/<executable_name>/", // up 4 in tree
"../../../cpp/2_Concepts_and_Techniques/<executable_name>/", // up 3 in tree
"../../cpp/2_Concepts_and_Techniques/<executable_name>/", // up 2 in tree
"../../../../Samples/2_Concepts_and_Techniques/<executable_name>/", // up 4 in tree
"../../../Samples/2_Concepts_and_Techniques/<executable_name>/", // up 3 in tree
"../../Samples/2_Concepts_and_Techniques/<executable_name>/", // up 2 in tree
"../../../../cpp/3_CUDA_Features/<executable_name>/", // up 4 in tree
"../../../cpp/3_CUDA_Features/<executable_name>/", // up 3 in tree
"../../cpp/3_CUDA_Features/<executable_name>/", // up 2 in tree
"../../../../Samples/3_CUDA_Features/<executable_name>/", // up 4 in tree
"../../../Samples/3_CUDA_Features/<executable_name>/", // up 3 in tree
"../../Samples/3_CUDA_Features/<executable_name>/", // up 2 in tree
"../../../../cpp/4_CUDA_Libraries/<executable_name>/", // up 4 in tree
"../../../cpp/4_CUDA_Libraries/<executable_name>/", // up 3 in tree
"../../cpp/4_CUDA_Libraries/<executable_name>/", // up 2 in tree
"../../../../Samples/4_CUDA_Libraries/<executable_name>/", // up 4 in tree
"../../../Samples/4_CUDA_Libraries/<executable_name>/", // up 3 in tree
"../../Samples/4_CUDA_Libraries/<executable_name>/", // up 2 in tree
"../../../../cpp/5_Domain_Specific/<executable_name>/", // up 4 in tree
"../../../cpp/5_Domain_Specific/<executable_name>/", // up 3 in tree
"../../cpp/5_Domain_Specific/<executable_name>/", // up 2 in tree
"../../../../Samples/5_Domain_Specific/<executable_name>/", // up 4 in tree
"../../../Samples/5_Domain_Specific/<executable_name>/", // up 3 in tree
"../../Samples/5_Domain_Specific/<executable_name>/", // up 2 in tree
"../../../../cpp/6_Performance/<executable_name>/", // up 4 in tree
"../../../cpp/6_Performance/<executable_name>/", // up 3 in tree
"../../cpp/6_Performance/<executable_name>/", // up 2 in tree
"../../../../Samples/6_Performance/<executable_name>/", // up 4 in tree
"../../../Samples/6_Performance/<executable_name>/", // up 3 in tree
"../../Samples/6_Performance/<executable_name>/", // up 2 in tree
"../../../../cpp/0_Introduction/<executable_name>/data/", // up 4 in tree
"../../../cpp/0_Introduction/<executable_name>/data/", // up 3 in tree
"../../cpp/0_Introduction/<executable_name>/data/", // up 2 in tree
"../../../../Samples/0_Introduction/<executable_name>/data/", // up 4 in tree
"../../../Samples/0_Introduction/<executable_name>/data/", // up 3 in tree
"../../Samples/0_Introduction/<executable_name>/data/", // up 2 in tree
"../../../../cpp/1_Utilities/<executable_name>/data/", // up 4 in tree
"../../../cpp/1_Utilities/<executable_name>/data/", // up 3 in tree
"../../cpp/1_Utilities/<executable_name>/data/", // up 2 in tree
"../../../../Samples/1_Utilities/<executable_name>/data/", // up 4 in tree
"../../../Samples/1_Utilities/<executable_name>/data/", // up 3 in tree
"../../Samples/1_Utilities/<executable_name>/data/", // up 2 in tree
"../../../../cpp/2_Concepts_and_Techniques/<executable_name>/data/", // up 4 in tree
"../../../cpp/2_Concepts_and_Techniques/<executable_name>/data/", // up 3 in tree
"../../cpp/2_Concepts_and_Techniques/<executable_name>/data/", // up 2 in tree
"../../../../Samples/2_Concepts_and_Techniques/<executable_name>/data/", // up 4 in tree
"../../../Samples/2_Concepts_and_Techniques/<executable_name>/data/", // up 3 in tree
"../../Samples/2_Concepts_and_Techniques/<executable_name>/data/", // up 2 in tree
"../../../../cpp/3_CUDA_Features/<executable_name>/data/", // up 4 in tree
"../../../cpp/3_CUDA_Features/<executable_name>/data/", // up 3 in tree
"../../cpp/3_CUDA_Features/<executable_name>/data/", // up 2 in tree
"../../../../Samples/3_CUDA_Features/<executable_name>/data/", // up 4 in tree
"../../../Samples/3_CUDA_Features/<executable_name>/data/", // up 3 in tree
"../../Samples/3_CUDA_Features/<executable_name>/data/", // up 2 in tree
"../../../../cpp/4_CUDA_Libraries/<executable_name>/data/", // up 4 in tree
"../../../cpp/4_CUDA_Libraries/<executable_name>/data/", // up 3 in tree
"../../cpp/4_CUDA_Libraries/<executable_name>/data/", // up 2 in tree
"../../../../Samples/4_CUDA_Libraries/<executable_name>/data/", // up 4 in tree
"../../../Samples/4_CUDA_Libraries/<executable_name>/data/", // up 3 in tree
"../../Samples/4_CUDA_Libraries/<executable_name>/data/", // up 2 in tree
"../../../../cpp/5_Domain_Specific/<executable_name>/data/", // up 4 in tree
"../../../cpp/5_Domain_Specific/<executable_name>/data/", // up 3 in tree
"../../cpp/5_Domain_Specific/<executable_name>/data/", // up 2 in tree
"../../../../Samples/5_Domain_Specific/<executable_name>/data/", // up 4 in tree
"../../../Samples/5_Domain_Specific/<executable_name>/data/", // up 3 in tree
"../../Samples/5_Domain_Specific/<executable_name>/data/", // up 2 in tree
"../../../../cpp/6_Performance/<executable_name>/data/", // up 4 in tree
"../../../cpp/6_Performance/<executable_name>/data/", // up 3 in tree
"../../cpp/6_Performance/<executable_name>/data/", // up 2 in tree
"../../../../Samples/6_Performance/<executable_name>/data/", // up 4 in tree
"../../../Samples/6_Performance/<executable_name>/data/", // up 3 in tree
"../../Samples/6_Performance/<executable_name>/data/", // up 2 in tree
"../../../../Common/data/", // up 4 in tree
"../../../Common/data/", // up 3 in tree
"../../Common/data/", // up 2 in tree
"../../../../cpp/9_CUDA_Tile/<executable_name>/", // up 4 in tree
"../../../cpp/9_CUDA_Tile/<executable_name>/", // up 3 in tree
"../../cpp/9_CUDA_Tile/<executable_name>/", // up 2 in tree
"../cpp/9_CUDA_Tile/<executable_name>/", // up 1 in tree
"./cpp/9_CUDA_Tile/<executable_name>/" // up 0 in tree
"../../Common/data/" // up 2 in tree
};
// Extract the executable name

View File

@ -258,7 +258,7 @@ namespace nv
s[2] = &r3[0];
s[3] = &r4[0];
int i,j,p,jj;
register int i,j,p,jj;
for (i=0; i<4; i++)
{

View File

@ -187,7 +187,6 @@ CUmodule loadCUBIN(char *cubin, int argc, char **argv) {
CUcontext context;
int major = 0, minor = 0;
char deviceName[256];
CUctxCreateParams ctxCreateParams = {};
// Picks the best CUDA device available
CUdevice cuDevice = findCudaDeviceDRV(argc, (const char **)argv);
@ -201,7 +200,7 @@ CUmodule loadCUBIN(char *cubin, int argc, char **argv) {
printf("> GPU Device has SM %d.%d compute capability\n", major, minor);
checkCudaErrors(cuInit(0));
checkCudaErrors(cuCtxCreate(&context, &ctxCreateParams, 0, cuDevice));
checkCudaErrors(cuCtxCreate(&context, 0, cuDevice));
checkCudaErrors(cuModuleLoadData(&module, cubin));
free(cubin);

View File

@ -0,0 +1,128 @@
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
////////////////////////////////////////////////////////////////////////////////
//
// Utility funcs to wrap up saving a surface or the back buffer as a PPM file
// In addition, wraps up a threshold comparision of two PPMs.
//
// These functions are designed to be used to implement an automated QA testing
// for SDK samples.
//
// Author: Bryan Dudash
// Email: sdkfeedback@nvidia.com
//
// Copyright (c) NVIDIA Corporation. All rights reserved.
////////////////////////////////////////////////////////////////////////////////
#include <helper_functions.h>
#include <rendercheck_d3d10.h>
HRESULT CheckRenderD3D10::ActiveRenderTargetToPPM(ID3D10Device *pDevice,
const char *zFileName) {
ID3D10RenderTargetView *pRTV = NULL;
pDevice->OMGetRenderTargets(1, &pRTV, NULL);
ID3D10Resource *pSourceResource = NULL;
pRTV->GetResource(&pSourceResource);
return ResourceToPPM(pDevice, pSourceResource, zFileName);
}
HRESULT CheckRenderD3D10::ResourceToPPM(ID3D10Device *pDevice,
ID3D10Resource *pResource,
const char *zFileName) {
D3D10_RESOURCE_DIMENSION rType;
pResource->GetType(&rType);
if (rType != D3D10_RESOURCE_DIMENSION_TEXTURE2D) {
printf("SurfaceToPPM: pResource is not a 2D texture! Aborting...\n");
return E_FAIL;
}
ID3D10Texture2D *pSourceTexture = (ID3D10Texture2D *)pResource;
ID3D10Texture2D *pTargetTexture = NULL;
D3D10_TEXTURE2D_DESC desc;
pSourceTexture->GetDesc(&desc);
desc.BindFlags = 0;
desc.CPUAccessFlags = D3D10_CPU_ACCESS_READ;
desc.Usage = D3D10_USAGE_STAGING;
if (FAILED(pDevice->CreateTexture2D(&desc, NULL, &pTargetTexture))) {
printf(
"SurfaceToPPM: Unable to create target Texture resoruce! Aborting... "
"\n");
return E_FAIL;
}
pDevice->CopyResource(pTargetTexture, pSourceTexture);
D3D10_MAPPED_TEXTURE2D mappedTex2D;
pTargetTexture->Map(0, D3D10_MAP_READ, 0, &mappedTex2D);
// Need to convert from dx pitch to pitch=width
unsigned char *pPPMData = new unsigned char[desc.Width * desc.Height * 4];
for (unsigned int iHeight = 0; iHeight < desc.Height; iHeight++) {
memcpy(
&(pPPMData[iHeight * desc.Width * 4]),
(unsigned char *)(mappedTex2D.pData) + iHeight * mappedTex2D.RowPitch,
desc.Width * 4);
}
pTargetTexture->Unmap(0);
// Prepends the PPM header info and bumps byte data afterwards
sdkSavePPM4ub(zFileName, pPPMData, desc.Width, desc.Height);
delete[] pPPMData;
pTargetTexture->Release();
return S_OK;
}
bool CheckRenderD3D10::PPMvsPPM(const char *src_file, const char *ref_file,
const char *exec_path, const float epsilon,
const float threshold) {
char *ref_file_path = sdkFindFilePath(ref_file, exec_path);
if (ref_file_path == NULL) {
printf(
"CheckRenderD3D10::PPMvsPPM unable to find <%s> in <%s> Aborting "
"comparison!\n",
ref_file, exec_path);
printf(">>> Check info.xml and [project//data] folder <%s> <<<\n",
ref_file);
printf("Aborting comparison!\n");
printf(" FAILURE!\n");
return false;
}
return (sdkComparePPM(src_file, ref_file_path, epsilon, threshold, true) ==
true);
}

View File

@ -0,0 +1,53 @@
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#ifndef _RENDERCHECK_D3D10_H_
#define _RENDERCHECK_D3D10_H_
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <d3d10.h>
class CheckRenderD3D10 {
public:
CheckRenderD3D10() {}
static HRESULT ActiveRenderTargetToPPM(ID3D10Device *pDevice,
const char *zFileName);
static HRESULT ResourceToPPM(ID3D10Device *pDevice, ID3D10Resource *pResource,
const char *zFileName);
static bool PPMvsPPM(const char *src_file, const char *ref_file,
const char *exec_path, const float epsilon,
const float threshold = 0.0f);
};
#endif

167
Common/rendercheck_d3d9.cpp Normal file
View File

@ -0,0 +1,167 @@
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
////////////////////////////////////////////////////////////////////////////////
//
// Utility funcs to wrap up savings a surface or the back buffer as a PPM file
// In addition, wraps up a threshold comparision of two PPMs.
//
// These functions are designed to be used to implement an automated QA testing
// for SDK samples.
//
// Author: Bryan Dudash
// Email: sdkfeedback@nvidia.com
//
// Copyright (c) NVIDIA Corporation. All rights reserved.
////////////////////////////////////////////////////////////////////////////////
#include <helper_functions.h>
#include <rendercheck_d3d9.h>
// originally copied from checkrender_gl.cpp and slightly modified
bool CheckRenderD3D9::PPMvsPPM(const char *src_file, const char *ref_file,
const char *exec_path, const float epsilon,
const float threshold) {
char *ref_file_path = sdkFindFilePath(ref_file, exec_path);
if (ref_file_path == NULL) {
printf(
"CheckRenderD3D9::PPMvsPPM unable to find <%s> in <%s> Aborting "
"comparison!\n",
ref_file, exec_path);
printf(">>> Check info.xml and [project//data] folder <%s> <<<\n",
ref_file);
printf("Aborting comparison!\n");
printf(" FAILURE!\n");
return false;
}
return (sdkComparePPM(src_file, ref_file_path, epsilon, threshold, true) ==
true);
};
HRESULT CheckRenderD3D9::BackbufferToPPM(IDirect3DDevice9 *pDevice,
const char *zFileName) {
IDirect3DSurface9 *pSurface = NULL;
if (FAILED(
pDevice->GetBackBuffer(0, 0, D3DBACKBUFFER_TYPE_MONO, &pSurface))) {
printf("Unable to get the back buffer. Aborting...\n");
return E_FAIL;
}
// D3DXSaveSurfaceToFile("C:\\bing.dds",D3DXIFF_DDS,pSurface,NULL,NULL);
HRESULT hr = S_OK;
hr = SurfaceToPPM(pDevice, pSurface, zFileName);
pSurface->Release();
return hr;
}
HRESULT CheckRenderD3D9::SurfaceToPPM(IDirect3DDevice9 *pDevice,
IDirect3DSurface9 *pSurface,
const char *zFileName) {
D3DSURFACE_DESC pDesc;
pSurface->GetDesc(&pDesc);
// $$ For now only support common 8bit formats. TODO: support for more
// complex formats via conversion?
if (!(pDesc.Format == D3DFMT_A8R8G8B8 || pDesc.Format == D3DFMT_X8R8G8B8)) {
return E_INVALIDARG;
}
IDirect3DTexture9 *pTargetTex = NULL;
if (FAILED(pDevice->CreateTexture(pDesc.Width, pDesc.Height, 1,
D3DUSAGE_DYNAMIC, pDesc.Format,
D3DPOOL_SYSTEMMEM, &pTargetTex, NULL))) {
printf("Unable to create texture for surface transfer! Aborting...\n");
return E_FAIL;
}
IDirect3DSurface9 *pTargetSurface = NULL;
if (FAILED(pTargetTex->GetSurfaceLevel(0, &pTargetSurface))) {
printf("Unable to get surface for surface transfer! Aborting...\n");
return E_FAIL;
}
// This is required because we cannot lock a D3DPOOL_DEAULT surface directly.
// So, we copy to our sysmem surface.
if (FAILED(pDevice->GetRenderTargetData(pSurface, pTargetSurface))) {
printf(
"Unable to GetRenderTargetData() for surface transfer! Aborting...\n");
return E_FAIL;
}
D3DLOCKED_RECT lockedRect;
HRESULT hr = pTargetSurface->LockRect(&lockedRect, NULL, 0);
// Need to convert from dx pitch to pitch=width
//
// $ PPM is BGR and not RGB it seems. Saved image looks "funny" in viewer(red
// and blue swapped), but since ref will be dumped using same method, this is
// ok.
// however, if we want the saved image to be properly colored, then we
// can swizzle the color bytes here.
unsigned char *pPPMData = new unsigned char[pDesc.Width * pDesc.Height * 4];
for (unsigned int iHeight = 0; iHeight < pDesc.Height; iHeight++) {
#if 1 // swizzle to implment RGB to BGR conversion.
for (unsigned int iWidth = 0; iWidth < pDesc.Width; iWidth++) {
DWORD color = *(DWORD *)((unsigned char *)(lockedRect.pBits) +
iHeight * lockedRect.Pitch + iWidth * 4);
// R<->B, [7:0] <-> [23:16], swizzle
color = ((color & 0xFF) << 16) | (color & 0xFF00) |
((color & 0xFF0000) >> 16) | (color & 0xFF000000);
memcpy(&(pPPMData[(iHeight * pDesc.Width + iWidth) * 4]),
(unsigned char *)&color, 4);
}
#else
memcpy(&(pPPMData[iHeight * pDesc.Width * 4]),
(unsigned char *)(lockedRect.pBits) + iHeight * lockedRect.Pitch,
pDesc.Width * 4);
#endif
}
pTargetSurface->UnlockRect();
// Prepends the PPM header info and bumps byte data afterwards
sdkSavePPM4ub(zFileName, pPPMData, pDesc.Width, pDesc.Height);
delete[] pPPMData;
pTargetSurface->Release();
pTargetTex->Release();
return S_OK;
}

54
Common/rendercheck_d3d9.h Normal file
View File

@ -0,0 +1,54 @@
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#ifndef _RENDERCHECK_D3D9_H_
#define _RENDERCHECK_D3D9_H_
#include <assert.h>
#include <d3d9.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
class CheckRenderD3D9 {
public:
CheckRenderD3D9() {}
static HRESULT BackbufferToPPM(IDirect3DDevice9 *pDevice,
const char *zFileName);
static HRESULT SurfaceToPPM(IDirect3DDevice9 *pDevice,
IDirect3DSurface9 *pSurface,
const char *zFileName);
static bool PPMvsPPM(const char *src_file, const char *ref_file,
const char *exec_path, const float epsilon,
const float threshold = 0.0f);
};
#endif

69
Makefile Normal file
View File

@ -0,0 +1,69 @@
###############################################################################
#
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
###############################################################################
#
# CUDA Samples
#
###############################################################################
TARGET_ARCH ?= $(shell uname -m)
# Project folders that contain CUDA samples
PROJECTS ?= $(shell find Samples -name Makefile)
FILTER_OUT :=
PROJECTS := $(filter-out $(FILTER_OUT),$(PROJECTS))
%.ph_build :
+@$(MAKE) -C $(dir $*) $(MAKECMDGOALS)
%.ph_test :
+@$(MAKE) -C $(dir $*) testrun
%.ph_clean :
+@$(MAKE) -C $(dir $*) clean $(USE_DEVICE)
%.ph_clobber :
+@$(MAKE) -C $(dir $*) clobber $(USE_DEVICE)
all: $(addsuffix .ph_build,$(PROJECTS))
@echo "Finished building CUDA samples"
build: $(addsuffix .ph_build,$(PROJECTS))
test : $(addsuffix .ph_test,$(PROJECTS))
tidy:
@find * | egrep "#" | xargs rm -f
@find * | egrep "\~" | xargs rm -f
clean: tidy $(addsuffix .ph_clean,$(PROJECTS))
clobber: clean $(addsuffix .ph_clobber,$(PROJECTS))

566
README.md
View File

@ -1,20 +1,22 @@
# CUDA Samples
Samples for CUDA Developers which demonstrates features in CUDA Toolkit. This version supports [CUDA Toolkit 13.4](https://developer.nvidia.com/cuda-downloads).
Samples for CUDA Developers which demonstrates features in CUDA Toolkit. This version supports [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads).
## Release Notes
This section describes the release notes for the CUDA Samples on GitHub only.
### Change Log
### CUDA 12.1
* Added JIT LTO Sample
* Adding Large Kernel Sample
### [Revision History](./CHANGELOG.md)
### [older versions...](./CHANGELOG.md)
## Getting Started
### Prerequisites
Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
For system requirements and installation instructions of cuda toolkit, please refer to the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/), and the [Windows Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html).
### Getting the CUDA Samples
@ -28,518 +30,67 @@ Without using git the easiest way to use these samples is to download the zip fi
## Building CUDA Samples
The CUDA Samples are built using CMake. Follow the instructions below for building on Linux, Windows, and for cross-compilation to Tegra devices.
### Linux
Ensure that CMake (version 3.20 or later) is installed. Install it using your package manager if necessary:
e.g.
```sudo apt install cmake```
Navigate to the root of the cloned repository and create a build directory:
```
mkdir build && cd build
```
Configure the project with CMake:
```
cmake ..
```
Build the samples:
```
make -j$(nproc)
```
By default, samples are compiled for all GPU architectures supported by this release. If you only need to target a specific GPU, you can override this to build for a single architecture and reduce build time considerably:
```
cmake -DCMAKE_CUDA_ARCHITECTURES=<arch> ..
```
Replace `<arch>` with your GPU's SM version (e.g. `90` for sm_90).
Run the samples from their respective directories in the build folder.
### Building a Single Sample
To build just one sample, configure CMake from within the sample's directory. You must explicitly specify a GPU architecture — standalone builds have no top-level default:
```bash
cd cpp/<category>/<sampleName>
mkdir -p build && cd build
cmake -DCMAKE_CUDA_ARCHITECTURES=<arch> ..
make
```
Replace `<arch>` with your GPU's SM version (e.g. `90` for sm_90).
### Windows
Language services for CMake are available in Visual Studio 2019 version 16.5 or later, and you can directly import the CUDA samples repository from either the root level or from any
subdirectory or individual sample.
To build from the command line, open the `x64 Native Tools Command Prompt for VS` provided with your Visual Studio installation.
Navigate to the root of the cloned repository and create a build directory:
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
mkdir build && cd build
*_vs<version>.sln - for Visual Studio <version>
```
Configure the project with CMake - for example:
Complete samples solution files exist at parent directory of the repo:
Each individual sample has its own set of solution files at:
`<CUDA_SAMPLES_REPO>\Samples\<sample_dir>\`
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
cmake .. -G "Visual Studio 16 2019" -A x64
$ cd <sample_dir>
$ make
```
Open the generated solution file CUDA_Samples.sln in Visual Studio. Build the samples by selecting the desired configuration (e.g., Debug or Release) and pressing F7 (Build Solution).
Run the samples from the output directories specified in Visual Studio.
### Enabling On-GPU Debugging
NVIDIA GPUs support on-GPU debugging through cuda-gdb. Enabling this may significantly affect application performance as certain compiler optimizations are disabled
in this configuration, hence it's not on by default. Enablement of on-device debugging is controlled via the `-G` switch to nvcc.
To enable cuda-gdb for samples builds, define the `ENABLE_CUDA_DEBUG` flag on the CMake command line. For example:
```
cmake -DENABLE_CUDA_DEBUG=True ...
```
### Platform-Specific Samples
Some CUDA samples are specific to certain platforms, and require passing flags into CMake to enable. In particular, we define the following platform-specific flags:
* `BUILD_TEGRA` - for Tegra-specific samples
To build these samples, set the variables either on the command line or through your CMake GUI. For example:
```
cmake -DBUILD_TEGRA=True ..
```
### Cross-Compilation for Tegra Platforms
Install the NVIDIA toolchain and cross-compilation environment for Tegra devices as described in the Tegra Development Guide.
Ensure that CMake (version 3.20 or later) is installed.
Navigate to the root of the cloned repository and create a build directory:
```
mkdir build && cd build
```
Configure the project with CMake, specifying the Tegra toolchain file. And you can use -DTARGET_FS to point to the target file system root path for necessary include and library files:
```
cmake .. -DCMAKE_TOOLCHAIN_FILE=../cmake/toolchains/toolchain-aarch64-linux.cmake -DTARGET_FS=/path/to/target/system/file/system
```
Build the samples:
```
make -j$(nproc)
```
Transfer the built binaries to the Tegra device and execute them there.
### Cross Building for Automotive Linux Platforms from the DriveOS Docker containers
To build CUDA samples to the target platform from the DriveOS Docker containers, use the following instructions.
Mount the target Root Filesystem (RFS) in the container so that the CUDA cmake process has the correct paths to CUDA and other system libraries required to build the samples.
Create a temporary directory, `<temp>` is any temporary directory of your choosing, for example, you can use `/drive/temp`:
```
$ mkdir /drive/<temp>
```
Mount the filesystem by running the following command:
```
$ mount /drive/drive-linux/filesystem/targetfs-images/dev_nsr_desktop_ubuntu-24.04_thor_rfs.img /drive/temp
```
Configure the project by running the following cmake command:
```
$ mkdir build && cd build
$ cmake .. -DBUILD_TEGRA=True \
-DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \
-DCMAKE_TOOLCHAIN_FILE=../cmake/toolchains/toolchain-aarch64-linux.cmake \
-DTARGET_FS=/drive/temp \
-DCMAKE_LIBRARY_PATH=/drive/temp/usr/local/cuda-13.1/thor/lib64/ \
-DCMAKE_INCLUDE_PATH=/drive/temp/usr/local/cuda-13.1/thor/include/
```
Please note that the following libraries are not pre-installed in the DriveOS dev-nsr target filesystem:
* libdrm-dev
* Vulkan
This causes the cmake command to throw errors related to the missing files, and as a result, the related samples will not build in later steps. This issue will be addressed in a future DriveOS release.
To build the samples with ignore the error mentioned above, you can use `--ignore-errors`/`--keep-going` or comment out the comment out the corresponding `add_subdirectory` command in the CMakeLists.txt in the parent folder for the samples requiring Vulkan and libdrm_dev:
```
$ make -j$(nproc) --ignore-errors # or --keep-going
```
```
# In cpp/5_Domain_Specific/CMakeList.txt
# add_subdirectory(simpleGL)
# add_subdirectory(simpleVulkan)
# add_subdirectory(simpleVulkanMMAP)
# In cpp/8_Platform_Specific/Tegra/CMakeList.txt
# add_subdirectory(simpleGLES_EGLOutput)
```
### QNX
Cross-compilation for QNX with CMake is supported in the CUDA 13.0 samples release and newer.
Set up the QNX SDP paths:
```bash
export QNX_HOST=/path/to/qnx/host
export QNX_TARGET=/path/to/qnx/target
```
Build the samples for the Tegra Thor QNX platform:
```bash
mkdir -p build && cd build
cmake .. \
-DBUILD_TEGRA=True \
-DCMAKE_CUDA_COMPILER=/usr/local/cuda-13.3/bin/nvcc \
-DCMAKE_TOOLCHAIN_FILE=../cmake/toolchains/toolchain-aarch64-qnx.cmake \
-DTARGET_FS=/path/to/qnx/targetfs \
-DCMAKE_LIBRARY_PATH=/usr/local/cuda-13.3/thor/targets/aarch64-qnx/lib/stubs/ \
-DCMAKE_INCLUDE_PATH=/usr/local/cuda-13.3/thor/targets/aarch64-qnx/include/
cmake --build .
```
`TARGET_FS` is the QNX target filesystem of your board. The `cudaNvSci` sample needs it, because the NvSci headers and libraries ship with the target filesystem and not with the CUDA toolkit. Without `TARGET_FS` the build reports `NvSCI not found` and skips the sample.
The target filesystem is part of the NVIDIA DRIVE OS QNX SDK, which registered users download from [NVONLINE](https://partners.nvidia.com). After the SDK is installed, the filesystem is in the DRIVE OS workspace: `<NV_WORKSPACE>/drive-qnx` for the standard SDK and `<NV_WORKSPACE>/drive-qnx-safety` for the safety SDK. See the [DRIVE OS documentation](https://docs.nvidia.com/drive/) for the installation guides.
For both QNX toolchains the build looks for `nvscibuf.h` in `<TARGET_FS>/include`, `<TARGET_FS>/../include` and `<TARGET_FS>/usr/include`, and for `libnvscibuf.so` in `<TARGET_FS>/lib-target`, `<TARGET_FS>/usr/libnvidia` and `<TARGET_FS>/usr/lib`. If your filesystem uses a different layout, set `NVSCIBUF_INCLUDE_DIR`, `NVSCISYNC_INCLUDE_DIR`, `NVSCIBUF_LIBRARY` and `NVSCISYNC_LIBRARY` on the cmake command line instead.
### QNX Safety (CUDA Safe toolkit)
Cross-compilation for **QNX Safety** uses the CUDA Safe toolkit (for example `/usr/local/cuda-13.3-safe`).
Set up the QNX SDP and Safe toolkit paths:
```bash
export QNX_HOST=/path/to/qnx/host
export QNX_TARGET=/path/to/qnx/target
export CUDA_PATH=/usr/local/cuda-13.3-safe
export PATH=$CUDA_PATH/nvvm/bin:$PATH
```
Build a single sample (standalone configure from the sample directory).
```bash
mkdir -p build && cd build
cmake .. \
-DCMAKE_TOOLCHAIN_FILE=../../../cmake/toolchains/toolchain-aarch64-qnx-safe.cmake \
-DCMAKE_CUDA_COMPILER=$CUDA_PATH/bin/nvcc \
-DCMAKE_CUDA_ARCHITECTURES=110 \
-DTARGET_FS=/path/to/qnx/safety/targetfs
cmake --build .
```
The safe toolchain sets `-safety-compat`, links shared `libcudart` and `libcuda`, and uses QNX `q++` as the CUDA host compiler (`CMAKE_CUDA_HOST_COMPILER`). Set `CMAKE_CUDA_ARCHITECTURES` to match your GPU (`87` for Orin, `110` for Thor).
Supported QNX Safety samples: `matrixMul`, `cudaNvSci`.
`TARGET_FS` is only needed for `cudaNvSci`, which links the NvSci libraries from the safety target filesystem (`<NV_WORKSPACE>/drive-qnx-safety`, part of the DRIVE OS QNX Safety SDK). `matrixMul` builds without it. The NvSci search paths are the same as for the standard QNX build above.
### Forward Compatibility
To build samples with new CUDA Toolkit(CUDA 13.0 or later) and UMD(Version 580 or later) and old KMD(Version 550 or earlier)you need to set the `CMAKE_PREFIX_PATH` for using new driver library, the command might like this:
```
cmake -DCMAKE_PREFIX_PATH=/usr/local/cuda/lib64/stubs/ ..
```
## CUDA Python samples
The repository includes **Python** examples under the [`python/`](./python) directory. **These samples are cuda.corefocused:** they use [CUDA Python](https://nvidia.github.io/cuda-python/), with [`cuda.core`](https://nvidia.github.io/cuda-python/cuda-core/latest/) for devices, programs, launches, and memory, alongside NumPy, CuPy, or framework interop where each sample notes.
**Layout (same themes as the C++ samples):**
| Directory | Contents |
|-----------|----------|
| `python/1_GettingStarted/` | Introductory scripts (e.g. `vectorAdd`, `deviceQuery`, `systemInfo`, image blur with unified memory, NumPy vs CuPy). |
| `python/2_CoreConcepts/` | Algorithms and techniques (e.g. reductions, histograms, FFT, stream overlap, `memoryResources`, `cudaGraphs`, `jitLtoLinking`, `tmaTensorMap`). |
| `python/3_FrameworkInterop/` | Integration with PyTorch and TensorFlow. |
| `python/4_DistributedComputing/` | Multi-GPU, peer-to-peer, and IPC patterns (`ipcMemoryPool`). |
| `python/Utilities/` | Shared helpers imported by some samples. |
**How to run:** The top-level CMake build does **not** compile these samples. For each sample, use a Python 3.10+ environment with a matching [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) (the samples target CUDA 13.x and document exact package pins in `requirements.txt`):
```bash
cd python/<category>/<sampleName>
pip install -r requirements.txt
python <sampleScript>.py
```
Use each samples `README.md` for prerequisites, CLI options, and expected output.
## Install Samples
### Installation Path Structure
The installation system automatically organizes samples into a structured directory layout based on:
- **Target Architecture**: ${CMAKE_SYSTEM_PROCESSOR}, e.g. `x64`, `aarch64`, `amd64`, etc.
- **Target OS**: `linux`, `windows`, `darwin`, `qnx`
- **Build Type**: `release`, `debug`, etc.
The default installation path is: `build/bin/${TARGET_ARCH}/${TARGET_OS}/${BUILD_TYPE}`
**Examples:**
- Linux x86_64 Release: `build/bin/x64/linux/release`
- Linux aarch64 Release: `build/bin/aarch64/linux/release`
- Windows amd64 Release: `build/bin/amd64/windows/release`
### Customizing Installation Paths
You can customize the installation location using CMake variables during the configuration step:
- `CMAKE_INSTALL_PREFIX`: Changes the root installation directory (default: `build/bin`)
```
cmake -DCMAKE_INSTALL_PREFIX=/custom/path ..
```
This will install to: `/custom/path/${TARGET_ARCH}/${TARGET_OS}/${BUILD_TYPE}`
- `CUDA_SAMPLES_INSTALL_DIR`: Specifies the exact final installation directory (overrides the structured path)
```
cmake -DCUDA_SAMPLES_INSTALL_DIR=/exact/install/path ..
```
### Install Samples on Linux
**Prerequisites:** You must first configure the project with CMake as described in the [Building CUDA Samples - Linux](#linux) or [Building]section.
After configuring and building, install the samples:
```
cd build/
make install
```
### Install Samples on Windows
**Prerequisites:** You must first configure the project with CMake as described in the [Building CUDA Samples - Windows](#windows) section.
#### Using Command Line
After configuring with CMake, build and install from the `x64 Native Tools Command Prompt for VS`:
```cmd
cd build
cmake --build . --config Release
cmake --install . --config Release
```
**Note:** Replace `Release` with `Debug` if you want to install debug builds. For multi-configuration generators (like Visual Studio), the `--config` flag determines which build type to install.
#### Using Visual Studio IDE
Alternatively, open the generated solution file `CUDA_Samples.sln` in Visual Studio:
1. Select the desired configuration (`Release` or `Debug`)
2. Build the solution (F7 or Build > Build Solution)
3. Right-click on the `INSTALL` target under `CMakePredefinedTargets` in Solution Explorer
4. Select "Build"
## Running All Samples as Tests
It's important to note that the CUDA samples are _not_ intended as a validation suite for CUDA. They do not cover corner cases, they do not completely cover the
runtime and driver APIs, are not intended for performance benchmarking, etc. That said, it can sometimes be useful to run all of the samples as a quick sanity check and
we provide a script to do so, `run_tests.py`.
This Python3 script finds all executables in a subdirectory you choose, matching application names with command line arguments specified in `test_args.json`. It accepts
the following command line arguments:
| Switch | Purpose | Example |
| ---------- | -------------------------------------------------------------------------------------------------------------- | ----------------------- |
| --dir | Specify the root directory to search for executables (recursively) | --dir ./build/cpp |
| --config | JSON configuration file for executable arguments | --config test_args.json |
| --output | Output directory for test results (stdout saved to .txt files - directory will be created if it doesn't exist) | --output ./test |
| --args | Global arguments to pass to all executables (not currently used) | --args arg_1 arg_2 ... |
| --parallel | Number of applications to execute in parallel. | --parallel 8 |
Application configurations are loaded from `test_args.json` and matched against executable names (discarding the `.exe` extension on Windows).
The script returns 0 on success, or the first non-zero error code encountered during testing on failure. It will also print a condensed list of samples that failed, if any.
There are three primary modes of configuration:
**Skip**
An executable configured with "skip" will not be executed. These generally rely on having attached graphical displays and are not suited to this kind of automation.
Configuration example:
```json
"fluidsGL": {
"skip": true
}
```
You will see:
```
Skipping fluidsGL (marked as skip in config)
```
**Single Run**
For executables to run one time only with arguments, specify each argument as a list entry. Each entry in the JSON file will be appended to the command line, separated
by a space.
All applications execute from their current directory, so all paths are relative to the application's location.
Note that if an application needs no arguments, this entry is optional. An executable found without a matching entry in the JSON will just run as `./application` from its
current directory.
Configuration example:
```json
"ptxgen": {
"args": [
"test.ll",
"-arch=compute_75"
]
}
```
You will see:
```
Running ptxgen
Command: ./ptxgen test.ll -arch=compute_75
Test completed with return code 0
```
**Multiple Runs**
For executables to run multiple times with different command line arguments, specify any number of sets of args within a "runs" list.
As with single runs, all applications execute from their current directory, so all paths are relative to the application's location.
Configuration example:
```json
"recursiveGaussian": {
"runs": [
{
"args": [
"-sigma=10",
"-file=data/ref_10.ppm"
]
},
{
"args": [
"-sigma=14",
"-file=data/ref_14.ppm"
]
},
{
"args": [
"-sigma=18",
"-file=data/ref_18.ppm"
]
},
{
"args": [
"-sigma=22",
"-file=data/ref_22.ppm"
]
}
]
}
```
You will see:
```
Running recursiveGaussian (run 1/4)
Command: ./recursiveGaussian -sigma=10 -file=data/ref_10.ppm
Test completed with return code 0
Running recursiveGaussian (run 2/4)
Command: ./recursiveGaussian -sigma=14 -file=data/ref_14.ppm
Test completed with return code 0
Running recursiveGaussian (run 3/4)
Command: ./recursiveGaussian -sigma=18 -file=data/ref_18.ppm
Test completed with return code 0
Running recursiveGaussian (run 4/4)
Command: ./recursiveGaussian -sigma=22 -file=data/ref_22.ppm
Test completed with return code 0
```
### Example Usage
Here is an example set of commands to build and test all of the samples.
First, build:
```bash
mkdir build
cd build
cmake ..
make -j$(nproc)
```
Now, return to the samples root directory and run the test script:
```bash
cd ..
python3 run_tests.py --output ./test --dir ./build/cpp --config test_args.json
```
If all applications run successfully, you will see something similar to this (the specific number of samples will depend on your build type
and system configuration):
```
Test Summary:
Ran 199 test runs for 180 executables.
All test runs passed!
```
If some samples fail, you will see something like this:
```
Test Summary:
Ran 199 test runs for 180 executables.
Failed runs (2):
bicubicTexture (run 1/5): Failed (code 1)
Mandelbrot (run 1/2): Failed (code 1)
```
You can inspect the stdout logs in the output directory (generally `APM_<application_name>.txt` or `APM_<application_name>.run<n>.txt`) to help
determine what may have gone wrong from the output logs. Please file issues against the samples repository if you believe a sample is failing
incorrectly on your system.
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l, aarch64.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/> `$ make TARGET_ARCH=aarch64` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details on cross platform compilation of cuda samples.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## Samples list
### [0. Introduction](./cpp/0_Introduction/README.md)
### [0. Introduction](./Samples/0_Introduction/README.md)
Basic CUDA samples for beginners that illustrate key concepts with using CUDA and CUDA runtime APIs.
### [1. Utilities](./cpp/1_Utilities/README.md)
### [1. Utilities](./Samples/1_Utilities/README.md)
Utility samples that demonstrate how to query device capabilities and measure GPU/CPU bandwidth.
### [2. Concepts and Techniques](./cpp/2_Concepts_and_Techniques/README.md)
### [2. Concepts and Techniques](./Samples/2_Concepts_and_Techniques/README.md)
Samples that demonstrate CUDA related concepts and common problem solving techniques.
### [3. CUDA Features](./cpp/3_CUDA_Features/README.md)
### [3. CUDA Features](./Samples/3_CUDA_Features/README.md)
Samples that demonstrate CUDA Features (Cooperative Groups, CUDA Dynamic Parallelism, CUDA Graphs etc).
### [4. CUDA Libraries](./cpp/4_CUDA_Libraries/README.md)
### [4. CUDA Libraries](./Samples/4_CUDA_Libraries/README.md)
Samples that demonstrate how to use CUDA platform libraries (NPP, NVJPEG, NVGRAPH cuBLAS, cuFFT, cuSPARSE, cuSOLVER and cuRAND).
### [5. Domain Specific](./cpp/5_Domain_Specific/README.md)
### [5. Domain Specific](./Samples/5_Domain_Specific/README.md)
Samples that are specific to domain (Graphics, Finance, Image Processing).
### [6. Performance](./cpp/6_Performance/README.md)
### [6. Performance](./Samples/6_Performance/README.md)
Samples that demonstrate performance optimization.
### [7. libNVVM](./cpp/7_libNVVM/README.md)
Samples that demonstrate the use of libNVVVM and NVVM IR.
### [8. Platform Specific](./cpp/8_Platform_Specific/Tegra/README.md)
Samples that are specific to certain platforms (Tegra, cuDLA, NvMedia, NvSci, OpenGL ES).
### [9. CUDA Tile](./cpp/9_CUDA_Tile/README.md)
Samples that demonstrate how to use CUDA Tile C++.
## Dependencies
Some CUDA Samples rely on third-party applications and/or libraries, or features provided by the CUDA Toolkit and Driver, to either build or execute. These dependencies are listed below.
@ -556,7 +107,7 @@ These third-party dependencies are required by some CUDA samples. If available,
FreeImage is an open source imaging library. FreeImage can usually be installed on Linux using your distribution's package manager system. FreeImage can also be downloaded from the FreeImage website.
To set up FreeImage on a Windows system, extract the FreeImage DLL distribution into the folder `./Common/FreeImage/Dist/x64` such that it contains the .h and .lib files. Copy the .dll file to the Release/ Debug/ execution folder or pass the FreeImage folder when cmake configuring with the `-DFreeImage_INCLUDE_DIR` and `-DFreeImage_LIBRARY` options.
To set up FreeImage on a Windows system, extract the FreeImage DLL distribution into the folder `../../../Common/FreeImage/Dist/x64` such that it contains the .h and .lib files. Copy the .dll file to root level `bin/win64/Debug` and `bin/win64/Release` folder.
#### Message Passing Interface
@ -582,27 +133,13 @@ OpenGL is a graphics library used for 2D and 3D rendering. On systems which supp
OpenGL ES is an embedded systems graphics library used for 2D and 3D rendering. On systems which support OpenGL ES, NVIDIA's OpenGL ES implementation is provided with the CUDA Driver.
#### Freeglut
Freeglut is an open-source software library that serves as a replacement for the original OpenGL Utility Toolkit (GLUT). Its primary purpose is to make it easier for developers to create and manage windows containing OpenGL contexts, as well as handle input from devices like the mouse, keyboard, and joystick, across a wide range of platforms. To set up Freeglut on a Windowson on ARM system, you need to download the source from [Freeglut website](https://freeglut.sourceforge.net/), build freeglut on your system, and copy the freeglut.lib into the folder `./Common/lib/x64` and copy the freeglut.dll file into the `./bin/win64/${BUILD_TYPE}` execution folder.
#### Vulkan
Vulkan is a low-overhead, cross-platform 3D graphics and compute API. Vulkan targets high-performance realtime 3D graphics applications such as video games and interactive media across all platforms. On systems which support Vulkan, NVIDIA's Vulkan implementation is provided with the CUDA Driver. For building and running Vulkan applications one needs to install the [Vulkan SDK](https://www.lunarg.com/vulkan-sdk/).
#### GLEW
GLEW (OpenGL Extension Wrangler Library) is a cross-platform, open-source C/C++ library designed to simplify the process of using modern OpenGL features and extensions. Its main function is to dynamically load OpenGL function pointers at runtime, allowing developers to access both core OpenGL functions and additional features provided by hardware vendors, known as extensions. To set up GLEW on a Windows on ARM system, you need to download the source from [GLEW website](https://glew.sourceforge.net/), build GLEW on your system, and copy the glew32.lib into the folder `./Common/lib/x64` and the glew32.dll into the `./bin/win64/${BUILD_TYPE}` execution folder.
#### GLFW
GLFW is a lightweight, open-source library designed for managing OpenGL, OpenGL ES, and Vulkan contexts. It simplifies the process of creating and managing windows, handling user input (keyboard, mouse, and joystick), and working with multiple monitors in a cross-platform manner.
To set up GLFW on a Windows system, Download the pre-built binaries from [GLFW website](https://www.glfw.org/download.html) and extract the zip file into the folder, pass the GLFW include header folder as `-DGLFW_INCLUDE_DIR` and lib folder as `-DGLFW_LIB_DIR` for cmake configuring.
#### OpenMP
OpenMP is an API for multiprocessing programming. OpenMP can be installed using your Linux distribution's package manager system. It usually comes preinstalled with GCC. It can also be found at the [OpenMP website](http://openmp.org/). For compilers such as clang, make sure OpenMP is enabled when building LLVM by including `openmp` in `LLVM_ENABLE_PROJECTS`. If you use clang (from an installed prefix or directly from an LLVM build tree) with OpenMP enabled, set CMAKE_CXX_COMPILER and CMAKE_CUDA_HOST_COMPILER to that clang++ and let CMake detect OpenMP; extra OpenMP_* CMake variables are usually not needed. When using clang++ directly from an LLVM build tree, you may need to copy the generated `omp.h` into the `include/` directory under the path reported by `clang++ --print-resource-dir` before building the samples. When using an installed clang with OpenMP, if you see libomp.so: cannot open shared object file at runtime, add the directory that contains libomp.so to LD_LIBRARY_PATH (or configure it via ld.so.conf.d) so the dynamic linker can locate the OpenMP runtime.
OpenMP is an API for multiprocessing programming. OpenMP can be installed using your Linux distribution's package manager system. It usually comes preinstalled with GCC. It can also be found at the [OpenMP website](http://openmp.org/).
#### Screen
@ -692,11 +229,6 @@ NVJPEG library provides high-performance, GPU accelerated JPEG decoding function
NVRTC (CUDA RunTime Compilation) is a runtime compilation library for CUDA C++.
#### NVJITLINK
NVJITLINK is a CUDA runtime library that links multiple GPU device code objects at runtime and enables justintime linktime optimization (JIT LTO).
It can take device code from tools such as NVCC and NVRTC, link and optimize it on the fly, and produce the final GPU binary.For more details, see: https://docs.nvidia.com/cuda/nvjitlink/index.html
#### Stream Priorities
Stream Priorities allows the creation of streams with specified priorities. Stream Priorities is only available on GPUs with SM architecture of 3.5 or above.
@ -713,10 +245,6 @@ FP16 is a 16-bit floating-point format. One bit is used for the sign, five bits
NVCC support of [C++11 features](https://en.wikipedia.org/wiki/C++11).
#### CMake
The libNVVM samples are built using [CMake](https://cmake.org/) 3.10 or later.
## Contributors Guide
We welcome your input on issues and suggestions for samples. At this time we are not accepting contributions from the public, check back here as we evolve our contribution model.
@ -729,7 +257,7 @@ Answers to frequently asked questions about CUDA can be found at http://develope
## References
* [CUDA Programming Guide](https://docs.nvidia.com/cuda/cuda-programming-guide/index.html)
* [CUDA Programming Guide](http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html)
* [Accelerated Computing Blog](https://developer.nvidia.com/blog/?tags=accelerated-computing)
## Attributions

View File

@ -0,0 +1,162 @@
# 0. Introduction
### [asyncAPI](./asyncAPI)
This sample illustrates the usage of CUDA events for both GPU timing and overlapping CPU and GPU execution. Events are inserted into a stream of CUDA calls. Since CUDA stream calls are asynchronous, the CPU can perform computations while GPU is executing (including DMA memcopies between the host and device). CPU can query CUDA events to determine whether GPU has completed tasks.
### [c++11_cuda](./c++11_cuda)
This sample demonstrates C++11 feature support in CUDA. It scans a input text file and prints no. of occurrences of x, y, z, w characters.
### [clock](./clock)
This example shows how to use the clock function to measure the performance of block of threads of a kernel accurately.
### [clock_nvrtc](./clock_nvrtc)
This example shows how to use the clock function using libNVRTC to measure the performance of block of threads of a kernel accurately.
### [concurrentKernels](./concurrentKernels)
This sample demonstrates the use of CUDA streams for concurrent execution of several kernels on GPU device. It also illustrates how to introduce dependencies between CUDA streams with the new cudaStreamWaitEvent function.
### [cppIntegration](./cppIntegration)
This example demonstrates how to integrate CUDA into an existing C++ application, i.e. the CUDA entry point on host side is only a function which is called from C++ code and only the file containing this function is compiled with nvcc. It also demonstrates that vector types can be used from cpp.
### [cppOverload](./cppOverload)
This sample demonstrates how to use C++ function overloading on the GPU.
### [cudaOpenMP](./cudaOpenMP)
This sample demonstrates how to use OpenMP API to write an application for multiple GPUs.
### [fp16ScalarProduct](./fp16ScalarProduct)
Calculates scalar product of two vectors of FP16 numbers.
### [matrixMul](./matrixMul)
This sample implements matrix multiplication and is exactly the same as Chapter 6 of the programming guide. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. To illustrate GPU performance for matrix multiply, this sample also shows how to use the new CUDA 4.0 interface for CUBLAS to demonstrate high-performance performance for matrix multiplication.
### [matrixMul_nvrtc](./matrixMul_nvrtc)
This sample implements matrix multiplication and is exactly the same as Chapter 6 of the programming guide. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. To illustrate GPU performance for matrix multiply, this sample also shows how to use the new CUDA 4.0 interface for CUBLAS to demonstrate high-performance performance for matrix multiplication.
### [matrixMulDrv](./matrixMulDrv)
This sample implements matrix multiplication and uses the new CUDA 4.0 kernel launch Driver API. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.
### [matrixMulDynlinkJIT](./matrixMulDynlinkJIT)
This sample revisits matrix multiplication using the CUDA driver API. It demonstrates how to link to CUDA driver at runtime and how to use JIT (just-in-time) compilation from PTX code. It has been written for clarity of exposition to illustrate various CUDA programming principles, not with the goal of providing the most performant generic kernel for matrix multiplication. CUBLAS provides high-performance matrix multiplication.
### [mergeSort](./mergeSort)
This sample implements a merge sort (also known as Batcher's sort), algorithms belonging to the class of sorting networks. While generally subefficient on large sequences compared to algorithms with better asymptotic algorithmic complexity (i.e. merge sort or radix sort), may be the algorithms of choice for sorting batches of short- to mid-sized (key, value) array pairs. Refer to the excellent tutorial by H. W. Lang http://www.iti.fh-flensburg.de/lang/algorithmen/sortieren/networks/indexen.htm
### [simpleAssert](./simpleAssert)
This CUDA Runtime API sample is a very basic sample that implements how to use the assert function in the device code. Requires Compute Capability 2.0 .
### [simpleAssert_nvrtc](./simpleAssert_nvrtc)
This CUDA Runtime API sample is a very basic sample that implements how to use the assert function in the device code. Requires Compute Capability 2.0 .
### [simpleAtomicIntrinsics](./simpleAtomicIntrinsics)
A simple demonstration of global memory atomic instructions.
### [simpleAtomicIntrinsics_nvrtc](./simpleAtomicIntrinsics_nvrtc)
A simple demonstration of global memory atomic instructions.This sample makes use of NVRTC for Runtime Compilation.
### [simpleAttributes](./simpleAttributes)
This CUDA Runtime API sample is a very basic example that implements how to use the stream attributes that affect L2 locality. Performance improvement due to use of L2 access policy window can only be noticed on Compute capability 8.0 or higher.
### [simpleAWBarrier](./simpleAWBarrier)
A simple demonstration of arrive wait barriers.
### [simpleCallback](./simpleCallback)
This sample implements multi-threaded heterogeneous computing workloads with the new CPU callbacks for CUDA streams and events introduced with CUDA 5.0.
### [simpleCooperativeGroups](./simpleCooperativeGroups)
This sample is a simple code that illustrates basic usage of cooperative groups within the thread block.
### [simpleCubemapTexture](./simpleCubemapTexture)
Simple example that demonstrates how to use a new CUDA 4.1 feature to support cubemap Textures in CUDA C.
### [simpleCUDA2GL](./simpleCUDA2GL)
This sample shows how to copy CUDA image back to OpenGL using the most efficient methods.
### [simpleDrvRuntime](./simpleDrvRuntime)
A simple example which demonstrates how CUDA Driver and Runtime APIs can work together to load cuda fatbinary of vector add kernel and performing vector addition.
### [simpleHyperQ](./simpleHyperQ)
This sample demonstrates the use of CUDA streams for concurrent execution of several kernels on devices which provide HyperQ (SM 3.5). Devices without HyperQ (SM 2.0 and SM 3.0) will run a maximum of two kernels concurrently.
### [simpleIPC](./simpleIPC)
This CUDA Runtime API sample is a very basic sample that demonstrates Inter Process Communication with one process per GPU for computation. Requires Compute Capability 3.0 or higher and a Linux Operating System, or a Windows Operating System with TCC enabled GPUs
### [simpleLayeredTexture](./simpleLayeredTexture)
Simple example that demonstrates how to use a new CUDA 4.0 feature to support layered Textures in CUDA C.
### [simpleMPI](./simpleMPI)
Simple example demonstrating how to use MPI in combination with CUDA.
### [simpleMultiCopy](./simpleMultiCopy)
Supported in GPUs with Compute Capability 1.1, overlapping compute with one memcopy is possible from the host system. For Quadro and Tesla GPUs with Compute Capability 2.0, a second overlapped copy operation in either direction at full speed is possible (PCI-e is symmetric). This sample illustrates the usage of CUDA streams to achieve overlapping of kernel execution with data copies to and from the device.
### [simpleMultiGPU](./simpleMultiGPU)
This application demonstrates how to use the new CUDA 4.0 API for CUDA context management and multi-threaded access to run CUDA kernels on multiple-GPUs.
### [simpleOccupancy](./simpleOccupancy)
This sample demonstrates the basic usage of the CUDA occupancy calculator and occupancy-based launch configurator APIs by launching a kernel with the launch configurator, and measures the utilization difference against a manually configured launch.
### [simpleP2P](./simpleP2P)
This application demonstrates CUDA APIs that support Peer-To-Peer (P2P) copies, Peer-To-Peer (P2P) addressing, and Unified Virtual Memory Addressing (UVA) between multiple GPUs. In general, P2P is supported between two same GPUs with some exceptions, such as some Tesla and Quadro GPUs.
### [simplePitchLinearTexture](./simplePitchLinearTexture)
Use of Pitch Linear Textures
### [simplePrintf](./simplePrintf)
This basic CUDA Runtime API sample demonstrates how to use the printf function in the device code.
### [simpleSeparateCompilation](./simpleSeparateCompilation)
This sample demonstrates a CUDA 5.0 feature, the ability to create a GPU device static library and use it within another CUDA kernel. This example demonstrates how to pass in a GPU device function (from the GPU device static library) as a function pointer to be called. This sample requires devices with compute capability 2.0 or higher.
### [simpleStreams](./simpleStreams)
This sample uses CUDA streams to overlap kernel executions with memory copies between the host and a GPU device. This sample uses a new CUDA 4.0 feature that supports pinning of generic host memory. Requires Compute Capability 2.0 or higher.
### [simpleSurfaceWrite](./simpleSurfaceWrite)
Simple example that demonstrates the use of 2D surface references (Write-to-Texture)
### [simpleTemplates](./simpleTemplates)
This sample is a templatized version of the template project. It also shows how to correctly templatize dynamically allocated shared memory arrays.
### [simpleTemplates_nvrtc](./simpleTemplates_nvrtc)
This sample is a templatized version of the template project. It also shows how to correctly templatize dynamically allocated shared memory arrays.
### [simpleTexture](./simpleTexture)
Simple example that demonstrates use of Textures in CUDA.
### [simpleTexture3D](./simpleTexture3D)
Simple example that demonstrates use of 3D Textures in CUDA.
### [simpleTextureDrv](./simpleTextureDrv)
Simple example that demonstrates use of Textures in CUDA. This sample uses the new CUDA 4.0 kernel launch Driver API.
### [simpleVoteIntrinsics](./simpleVoteIntrinsics)
Simple program which demonstrates how to use the Vote (__any_sync, __all_sync) intrinsic instruction in a CUDA kernel.
### [simpleVoteIntrinsics_nvrtc](./simpleVoteIntrinsics_nvrtc)
Simple program which demonstrates how to use the Vote (any, all) intrinsic instruction in a CUDA kernel with runtime compilation using NVRTC APIs. Requires Compute Capability 2.0 or higher.
### [simpleZeroCopy](./simpleZeroCopy)
This sample illustrates how to use Zero MemCopy, kernels can read and write directly to pinned system memory.
### [systemWideAtomics](./systemWideAtomics)
A simple demonstration of system wide atomic instructions.
### [template](./template)
A trivial template project that can be used as a starting point to create new CUDA projects.
### [UnifiedMemoryStreams](./UnifiedMemoryStreams)
This sample demonstrates the use of OpenMP and streams with Unified Memory on a single GPU.
### [vectorAdd](./vectorAdd)
This CUDA Runtime API sample is a very basic sample that implements element by element vector addition. It is the same as the sample illustrating Chapter 3 of the programming guide with some additions like error checking.
### [vectorAdd_nvrtc](./vectorAdd_nvrtc)
This CUDA Driver API sample uses NVRTC for runtime compilation of vector addition kernel. Vector addition kernel demonstrated is the same as the sample illustrating Chapter 3 of the programming guide.
### [vectorAddDrv](./vectorAddDrv)
This Vector Addition sample is a basic sample that is implemented element by element. It is the same as the sample illustrating Chapter 3 of the programming guide with some additions like error checking. This sample also uses the new CUDA 4.0 kernel launch Driver API.
### [vectorAddMMAP](./vectorAddMMAP)
This sample replaces the device allocation in the vectorAddDrv sample with cuMemMap-ed allocations. This sample demonstrates that the cuMemMap api allows the user to specify the physical properties of their memory while retaining the contiguous nature of their access, thus not requiring a change in their program structure.

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{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

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@ -0,0 +1,7 @@
{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

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@ -0,0 +1,10 @@
{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/UnifiedMemoryStreams"
}
]
}

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@ -0,0 +1,15 @@
{
"version": "2.0.0",
"tasks": [
{
"label": "sample",
"type": "shell",
"command": "make dbg=1",
"problemMatcher": ["$nvcc"],
"group": {
"kind": "build",
"isDefault": true
}
}
]
}

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@ -0,0 +1,381 @@
################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
UBUNTU = $(shell lsb_release -i -s 2>/dev/null | grep -i ubuntu)
SAMPLE_ENABLED := 1
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - UnifiedMemoryStreams is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
# Attempt to compile a minimal OpenMP application. If a.out exists, OpenMP is properly set up.
ifneq (,$(filter $(TARGET_OS),linux android))
ifneq (,$(filter $(TARGET_OS), android))
LIBRARIES += -lomp
else
LIBRARIES += -lgomp
endif
ALL_CCFLAGS += -Xcompiler -fopenmp
$(shell echo "#include <omp.h>" > test.c ; echo "int main() { omp_get_num_threads(); return 0; }" >> test.c ; $(HOST_COMPILER) -fopenmp test.c)
OPENMP ?= $(shell find a.out 2>/dev/null)
ifeq ($(OPENMP),)
$(info -----------------------------------------------------------------------------------------------)
$(info WARNING - OpenMP is unable to compile)
$(info -----------------------------------------------------------------------------------------------)
$(info This CUDA Sample cannot be built if the OpenMP compiler is not set up correctly.)
$(info This will be a dry-run of the Makefile.)
$(info For more information on how to set up your environment to build and run this )
$(info sample, please refer the CUDA Samples documentation and release notes)
$(info -----------------------------------------------------------------------------------------------)
SAMPLE_ENABLED := 0
endif
$(shell rm a.out test.c 2>/dev/null)
else
LIBRARIES += -lpthread
ALL_CCFLAGS += -DUSE_PTHREADS
endif
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
SMS ?= 53 61 70 72 75 80 86 87 90
else
SMS ?= 50 52 60 61 70 75 80 86 89 90
endif
ifeq ($(SMS),)
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
HIGHEST_SM := $(lastword $(sort $(SMS)))
ifneq ($(HIGHEST_SM),)
GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
endif
endif
ALL_CCFLAGS += --threads 0 --std=c++11
LIBRARIES += -lcublas
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: UnifiedMemoryStreams
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
UnifiedMemoryStreams.o:UnifiedMemoryStreams.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
UnifiedMemoryStreams: UnifiedMemoryStreams.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./UnifiedMemoryStreams
testrun: build
clean:
rm -f UnifiedMemoryStreams UnifiedMemoryStreams.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/UnifiedMemoryStreams
clobber: clean

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@ -0,0 +1,88 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>UnifiedMemoryStreams</name>
<cuda_api_list>
<toolkit>cudaStreamDestroy</toolkit>
<toolkit>cudaFree</toolkit>
<toolkit>cudaMallocManaged</toolkit>
<toolkit>cudaStreamAttachMemAsync</toolkit>
<toolkit>cudaSetDevice</toolkit>
<toolkit>cudaDeviceSynchronize</toolkit>
<toolkit>cudaStreamSynchronize</toolkit>
<toolkit>cudaStreamCreate</toolkit>
<toolkit>cudaGetDeviceProperties</toolkit>
</cuda_api_list>
<description><![CDATA[This sample demonstrates the use of OpenMP and streams with Unified Memory on a single GPU.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../../Common</path>
</includepaths>
<keyconcepts>
<concept level="basic">CUDA Systems Integration</concept>
<concept level="basic">OpenMP</concept>
<concept level="basic">CUBLAS</concept>
<concept level="basic">Multithreading</concept>
<concept level="basic">Unified Memory</concept>
<concept level="basic">CUDA Streams and Events</concept>
</keyconcepts>
<keywords>
<keyword>CUDA</keyword>
<keyword>CUBLAS</keyword>
<keyword>OpenMP</keyword>
<keyword>cluster</keyword>
<keyword>multi-GPU Support</keyword>
<keyword>Unified Memory</keyword>
<keyword>UVM</keyword>
<keyword>openMP</keyword>
<keyword>Streams</keyword>
<keyword>pthreads</keyword>
</keywords>
<libraries>
<library>cublas</library>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>UnifiedMemoryStreams.cu</primary_file>
<required_dependencies>
<dependency>OpenMP</dependency>
<dependency>UVM</dependency>
<dependency>CUBLAS</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>1:CUDA Systems Integration</scope>
<scope>1:Unified Memory</scope>
</scopes>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>macosx</platform>
</env>
<env>
<platform>windows7</platform>
</env>
<env>
<arch>arm</arch>
</env>
<env>
<arch>sbsa</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<from>3.5</from>
</supported_sm_architectures>
<title>Unified Memory Streams</title>
<type>exe</type>
</entry>

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@ -0,0 +1,72 @@
# UnifiedMemoryStreams - Unified Memory Streams
## Description
This sample demonstrates the use of OpenMP and streams with Unified Memory on a single GPU.
## Key Concepts
CUDA Systems Integration, OpenMP, CUBLAS, Multithreading, Unified Memory, CUDA Streams and Events
## Supported SM Architectures
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaStreamDestroy, cudaFree, cudaMallocManaged, cudaStreamAttachMemAsync, cudaSetDevice, cudaDeviceSynchronize, cudaStreamSynchronize, cudaStreamCreate, cudaGetDeviceProperties
## Dependencies needed to build/run
[OpenMP](../../../README.md#openmp), [UVM](../../../README.md#uvm), [CUBLAS](../../../README.md#cublas)
## Prerequisites
Download and install the [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## References (for more details)

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This sample implements a simple task consumer using threads and streams
* with all data in Unified Memory, and tasks consumed by both host and device
*/
// system includes
#include <cstdio>
#include <ctime>
#include <vector>
#include <algorithm>
#ifdef USE_PTHREADS
#include <pthread.h>
#else
#include <omp.h>
#endif
#include <stdlib.h>
// cuBLAS
#include <cublas_v2.h>
// utilities
#include <helper_cuda.h>
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
// SRAND48 and DRAND48 don't exist on windows, but these are the equivalent
// functions
void srand48(long seed) { srand((unsigned int)seed); }
double drand48() { return double(rand()) / RAND_MAX; }
#endif
const char *sSDKname = "UnifiedMemoryStreams";
// simple task
template <typename T>
struct Task {
unsigned int size, id;
T *data;
T *result;
T *vector;
Task() : size(0), id(0), data(NULL), result(NULL), vector(NULL){};
Task(unsigned int s) : size(s), id(0), data(NULL), result(NULL) {
// allocate unified memory -- the operation performed in this example will
// be a DGEMV
checkCudaErrors(cudaMallocManaged(&data, sizeof(T) * size * size));
checkCudaErrors(cudaMallocManaged(&result, sizeof(T) * size));
checkCudaErrors(cudaMallocManaged(&vector, sizeof(T) * size));
checkCudaErrors(cudaDeviceSynchronize());
}
~Task() {
// ensure all memory is deallocated
checkCudaErrors(cudaDeviceSynchronize());
checkCudaErrors(cudaFree(data));
checkCudaErrors(cudaFree(result));
checkCudaErrors(cudaFree(vector));
}
void allocate(const unsigned int s, const unsigned int unique_id) {
// allocate unified memory outside of constructor
id = unique_id;
size = s;
checkCudaErrors(cudaMallocManaged(&data, sizeof(T) * size * size));
checkCudaErrors(cudaMallocManaged(&result, sizeof(T) * size));
checkCudaErrors(cudaMallocManaged(&vector, sizeof(T) * size));
checkCudaErrors(cudaDeviceSynchronize());
// populate data with random elements
for (unsigned int i = 0; i < size * size; i++) {
data[i] = drand48();
}
for (unsigned int i = 0; i < size; i++) {
result[i] = 0.;
vector[i] = drand48();
}
}
};
#ifdef USE_PTHREADS
struct threadData_t {
int tid;
Task<double> *TaskListPtr;
cudaStream_t *streams;
cublasHandle_t *handles;
int taskSize;
};
typedef struct threadData_t threadData;
#endif
// simple host dgemv: assume data is in row-major format and square
template <typename T>
void gemv(int m, int n, T alpha, T *A, T *x, T beta, T *result) {
// rows
for (int i = 0; i < n; i++) {
result[i] *= beta;
for (int j = 0; j < n; j++) {
result[i] += A[i * n + j] * x[j];
}
}
}
// execute a single task on either host or device depending on size
#ifdef USE_PTHREADS
void *execute(void *inpArgs) {
threadData *dataPtr = (threadData *)inpArgs;
cudaStream_t *stream = dataPtr->streams;
cublasHandle_t *handle = dataPtr->handles;
int tid = dataPtr->tid;
for (int i = 0; i < dataPtr->taskSize; i++) {
Task<double> &t = dataPtr->TaskListPtr[i];
if (t.size < 100) {
// perform on host
printf("Task [%d], thread [%d] executing on host (%d)\n", t.id, tid,
t.size);
// attach managed memory to a (dummy) stream to allow host access while
// the device is running
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.data, 0, cudaMemAttachHost));
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.vector, 0, cudaMemAttachHost));
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.result, 0, cudaMemAttachHost));
// necessary to ensure Async cudaStreamAttachMemAsync calls have finished
checkCudaErrors(cudaStreamSynchronize(stream[0]));
// call the host operation
gemv(t.size, t.size, 1.0, t.data, t.vector, 0.0, t.result);
} else {
// perform on device
printf("Task [%d], thread [%d] executing on device (%d)\n", t.id, tid,
t.size);
double one = 1.0;
double zero = 0.0;
// attach managed memory to my stream
checkCudaErrors(cublasSetStream(handle[tid + 1], stream[tid + 1]));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.data, 0,
cudaMemAttachSingle));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.vector, 0,
cudaMemAttachSingle));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.result, 0,
cudaMemAttachSingle));
// call the device operation
checkCudaErrors(cublasDgemv(handle[tid + 1], CUBLAS_OP_N, t.size, t.size,
&one, t.data, t.size, t.vector, 1, &zero,
t.result, 1));
}
}
pthread_exit(NULL);
}
#else
template <typename T>
void execute(Task<T> &t, cublasHandle_t *handle, cudaStream_t *stream,
int tid) {
if (t.size < 100) {
// perform on host
printf("Task [%d], thread [%d] executing on host (%d)\n", t.id, tid,
t.size);
// attach managed memory to a (dummy) stream to allow host access while the
// device is running
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.data, 0, cudaMemAttachHost));
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.vector, 0, cudaMemAttachHost));
checkCudaErrors(
cudaStreamAttachMemAsync(stream[0], t.result, 0, cudaMemAttachHost));
// necessary to ensure Async cudaStreamAttachMemAsync calls have finished
checkCudaErrors(cudaStreamSynchronize(stream[0]));
// call the host operation
gemv(t.size, t.size, 1.0, t.data, t.vector, 0.0, t.result);
} else {
// perform on device
printf("Task [%d], thread [%d] executing on device (%d)\n", t.id, tid,
t.size);
double one = 1.0;
double zero = 0.0;
// attach managed memory to my stream
checkCudaErrors(cublasSetStream(handle[tid + 1], stream[tid + 1]));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.data, 0,
cudaMemAttachSingle));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.vector, 0,
cudaMemAttachSingle));
checkCudaErrors(cudaStreamAttachMemAsync(stream[tid + 1], t.result, 0,
cudaMemAttachSingle));
// call the device operation
checkCudaErrors(cublasDgemv(handle[tid + 1], CUBLAS_OP_N, t.size, t.size,
&one, t.data, t.size, t.vector, 1, &zero,
t.result, 1));
}
}
#endif
// populate a list of tasks with random sizes
template <typename T>
void initialise_tasks(std::vector<Task<T> > &TaskList) {
for (unsigned int i = 0; i < TaskList.size(); i++) {
// generate random size
int size;
size = std::max((int)(drand48() * 1000.0), 64);
TaskList[i].allocate(size, i);
}
}
int main(int argc, char **argv) {
// set device
cudaDeviceProp device_prop;
int dev_id = findCudaDevice(argc, (const char **)argv);
checkCudaErrors(cudaGetDeviceProperties(&device_prop, dev_id));
if (!device_prop.managedMemory) {
// This samples requires being run on a device that supports Unified Memory
fprintf(stderr, "Unified Memory not supported on this device\n");
exit(EXIT_WAIVED);
}
if (device_prop.computeMode == cudaComputeModeProhibited) {
// This sample requires being run with a default or process exclusive mode
fprintf(stderr,
"This sample requires a device in either default or process "
"exclusive mode\n");
exit(EXIT_WAIVED);
}
// randomise task sizes
int seed = (int)time(NULL);
srand48(seed);
// set number of threads
const int nthreads = 4;
// number of streams = number of threads
cudaStream_t *streams = new cudaStream_t[nthreads + 1];
cublasHandle_t *handles = new cublasHandle_t[nthreads + 1];
for (int i = 0; i < nthreads + 1; i++) {
checkCudaErrors(cudaStreamCreate(&streams[i]));
checkCudaErrors(cublasCreate(&handles[i]));
}
// create list of N tasks
unsigned int N = 40;
std::vector<Task<double> > TaskList(N);
initialise_tasks(TaskList);
printf("Executing tasks on host / device\n");
// run through all tasks using threads and streams
#ifdef USE_PTHREADS
pthread_t threads[nthreads];
threadData *InputToThreads = new threadData[nthreads];
for (int i = 0; i < nthreads; i++) {
checkCudaErrors(cudaSetDevice(dev_id));
InputToThreads[i].tid = i;
InputToThreads[i].streams = streams;
InputToThreads[i].handles = handles;
if ((TaskList.size() / nthreads) == 0) {
InputToThreads[i].taskSize = (TaskList.size() / nthreads);
InputToThreads[i].TaskListPtr =
&TaskList[i * (TaskList.size() / nthreads)];
} else {
if (i == nthreads - 1) {
InputToThreads[i].taskSize =
(TaskList.size() / nthreads) + (TaskList.size() % nthreads);
InputToThreads[i].TaskListPtr =
&TaskList[i * (TaskList.size() / nthreads) +
(TaskList.size() % nthreads)];
} else {
InputToThreads[i].taskSize = (TaskList.size() / nthreads);
InputToThreads[i].TaskListPtr =
&TaskList[i * (TaskList.size() / nthreads)];
}
}
pthread_create(&threads[i], NULL, &execute, &InputToThreads[i]);
}
for (int i = 0; i < nthreads; i++) {
pthread_join(threads[i], NULL);
}
#else
omp_set_num_threads(nthreads);
#pragma omp parallel for schedule(dynamic)
for (int i = 0; i < TaskList.size(); i++) {
checkCudaErrors(cudaSetDevice(dev_id));
int tid = omp_get_thread_num();
execute(TaskList[i], handles, streams, tid);
}
#endif
cudaDeviceSynchronize();
// Destroy CUDA Streams, cuBlas handles
for (int i = 0; i < nthreads + 1; i++) {
cudaStreamDestroy(streams[i]);
cublasDestroy(handles[i]);
}
// Free TaskList
std::vector<Task<double> >().swap(TaskList);
printf("All Done!\n");
exit(EXIT_SUCCESS);
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
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{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
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<PropertyGroup>
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<IncludePath>$(IncludePath)</IncludePath>
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<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
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</Link>
<CudaCompile>
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Microsoft Visual Studio Solution File, Format Version 12.00
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{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
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@ -0,0 +1,20 @@

Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2022
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "UnifiedMemoryStreams", "UnifiedMemoryStreams_vs2022.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
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Global
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Release|x64 = Release|x64
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GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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@ -0,0 +1,109 @@
<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>UnifiedMemoryStreams_vs2022</RootNamespace>
<ProjectName>UnifiedMemoryStreams</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v143</PlatformToolset>
<WindowsTargetPlatformVersion>10.0</WindowsTargetPlatformVersion>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;$(CudaToolkitIncludeDir);</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cublas.lib;cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/UnifiedMemoryStreams.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
<AdditionalCompilerOptions>/openmp</AdditionalCompilerOptions>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="UnifiedMemoryStreams.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

View File

@ -0,0 +1,18 @@
{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

View File

@ -0,0 +1,7 @@
{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

View File

@ -0,0 +1,10 @@
{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/asyncAPI"
}
]
}

View File

@ -0,0 +1,15 @@
{
"version": "2.0.0",
"tasks": [
{
"label": "sample",
"type": "shell",
"command": "make dbg=1",
"problemMatcher": ["$nvcc"],
"group": {
"kind": "build",
"isDefault": true
}
}
]
}

View File

@ -0,0 +1,341 @@
################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
SMS ?= 53 61 70 72 75 80 86 87 90
else
SMS ?= 50 52 60 61 70 75 80 86 89 90
endif
ifeq ($(SMS),)
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
HIGHEST_SM := $(lastword $(sort $(SMS)))
ifneq ($(HIGHEST_SM),)
GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
endif
endif
ALL_CCFLAGS += --threads 0 --std=c++11
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: asyncAPI
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
asyncAPI.o:asyncAPI.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
asyncAPI: asyncAPI.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./asyncAPI
testrun: build
$(EXEC) ./asyncAPI --dummy-test-param
clean:
rm -f asyncAPI asyncAPI.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/asyncAPI
clobber: clean

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@ -0,0 +1,90 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>asyncAPI</name>
<cuda_api_list>
<toolkit>cudaProfilerStop</toolkit>
<toolkit>cudaMalloc</toolkit>
<toolkit>cudaMemcpyAsync</toolkit>
<toolkit>cudaFree</toolkit>
<toolkit>cudaMallocHost</toolkit>
<toolkit>cudaProfilerStart</toolkit>
<toolkit>cudaDeviceSynchronize</toolkit>
<toolkit>cudaEventRecord</toolkit>
<toolkit>cudaFreeHost</toolkit>
<toolkit>cudaMemset</toolkit>
<toolkit>cudaEventDestroy</toolkit>
<toolkit>cudaEventQuery</toolkit>
<toolkit>cudaEventElapsedTime</toolkit>
<toolkit>cudaGetDeviceProperties</toolkit>
<toolkit>cudaEventCreate</toolkit>
</cuda_api_list>
<description><![CDATA[This sample illustrates the usage of CUDA events for both GPU timing and overlapping CPU and GPU execution. Events are inserted into a stream of CUDA calls. Since CUDA stream calls are asynchronous, the CPU can perform computations while GPU is executing (including DMA memcopies between the host and device). CPU can query CUDA events to determine whether GPU has completed tasks.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../../Common</path>
</includepaths>
<keyconcepts>
<concept level="basic">Asynchronous Data Transfers</concept>
<concept level="basic">CUDA Streams and Events</concept>
</keyconcepts>
<keywords>
<keyword>GPGPU</keyword>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>asyncAPI.cu</primary_file>
<qatests>
<qatest>--dummy-test-param</qatest>
</qatests>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>1:Performance Strategies</scope>
</scopes>
<sm-arch>sm50</sm-arch>
<sm-arch>sm52</sm-arch>
<sm-arch>sm53</sm-arch>
<sm-arch>sm60</sm-arch>
<sm-arch>sm61</sm-arch>
<sm-arch>sm70</sm-arch>
<sm-arch>sm72</sm-arch>
<sm-arch>sm75</sm-arch>
<sm-arch>sm80</sm-arch>
<sm-arch>sm86</sm-arch>
<sm-arch>sm87</sm-arch>
<sm-arch>sm89</sm-arch>
<sm-arch>sm90</sm-arch>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<platform>windows7</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>macosx</platform>
</env>
<env>
<arch>arm</arch>
</env>
<env>
<arch>sbsa</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>asyncAPI</title>
<type>exe</type>
</entry>

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@ -0,0 +1,70 @@
# asyncAPI - asyncAPI
## Description
This sample illustrates the usage of CUDA events for both GPU timing and overlapping CPU and GPU execution. Events are inserted into a stream of CUDA calls. Since CUDA stream calls are asynchronous, the CPU can perform computations while GPU is executing (including DMA memcopies between the host and device). CPU can query CUDA events to determine whether GPU has completed tasks.
## Key Concepts
Asynchronous Data Transfers, CUDA Streams and Events
## Supported SM Architectures
[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](https://developer.nvidia.com/cuda-gpus) [SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 8.9 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaProfilerStop, cudaMalloc, cudaMemcpyAsync, cudaFree, cudaMallocHost, cudaProfilerStart, cudaDeviceSynchronize, cudaEventRecord, cudaFreeHost, cudaMemset, cudaEventDestroy, cudaEventQuery, cudaEventElapsedTime, cudaGetDeviceProperties, cudaEventCreate
## Prerequisites
Download and install the [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## References (for more details)

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This sample illustrates the usage of CUDA events for both GPU timing and
* overlapping CPU and GPU execution. Events are inserted into a stream
* of CUDA calls. Since CUDA stream calls are asynchronous, the CPU can
* perform computations while GPU is executing (including DMA memcopies
* between the host and device). CPU can query CUDA events to determine
* whether GPU has completed tasks.
*/
// includes, system
#include <stdio.h>
// includes CUDA Runtime
#include <cuda_runtime.h>
#include <cuda_profiler_api.h>
// includes, project
#include <helper_cuda.h>
#include <helper_functions.h> // helper utility functions
__global__ void increment_kernel(int *g_data, int inc_value) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
g_data[idx] = g_data[idx] + inc_value;
}
bool correct_output(int *data, const int n, const int x) {
for (int i = 0; i < n; i++)
if (data[i] != x) {
printf("Error! data[%d] = %d, ref = %d\n", i, data[i], x);
return false;
}
return true;
}
int main(int argc, char *argv[]) {
int devID;
cudaDeviceProp deviceProps;
printf("[%s] - Starting...\n", argv[0]);
// This will pick the best possible CUDA capable device
devID = findCudaDevice(argc, (const char **)argv);
// get device name
checkCudaErrors(cudaGetDeviceProperties(&deviceProps, devID));
printf("CUDA device [%s]\n", deviceProps.name);
int n = 16 * 1024 * 1024;
int nbytes = n * sizeof(int);
int value = 26;
// allocate host memory
int *a = 0;
checkCudaErrors(cudaMallocHost((void **)&a, nbytes));
memset(a, 0, nbytes);
// allocate device memory
int *d_a = 0;
checkCudaErrors(cudaMalloc((void **)&d_a, nbytes));
checkCudaErrors(cudaMemset(d_a, 255, nbytes));
// set kernel launch configuration
dim3 threads = dim3(512, 1);
dim3 blocks = dim3(n / threads.x, 1);
// create cuda event handles
cudaEvent_t start, stop;
checkCudaErrors(cudaEventCreate(&start));
checkCudaErrors(cudaEventCreate(&stop));
StopWatchInterface *timer = NULL;
sdkCreateTimer(&timer);
sdkResetTimer(&timer);
checkCudaErrors(cudaDeviceSynchronize());
float gpu_time = 0.0f;
// asynchronously issue work to the GPU (all to stream 0)
checkCudaErrors(cudaProfilerStart());
sdkStartTimer(&timer);
cudaEventRecord(start, 0);
cudaMemcpyAsync(d_a, a, nbytes, cudaMemcpyHostToDevice, 0);
increment_kernel<<<blocks, threads, 0, 0>>>(d_a, value);
cudaMemcpyAsync(a, d_a, nbytes, cudaMemcpyDeviceToHost, 0);
cudaEventRecord(stop, 0);
sdkStopTimer(&timer);
checkCudaErrors(cudaProfilerStop());
// have CPU do some work while waiting for stage 1 to finish
unsigned long int counter = 0;
while (cudaEventQuery(stop) == cudaErrorNotReady) {
counter++;
}
checkCudaErrors(cudaEventElapsedTime(&gpu_time, start, stop));
// print the cpu and gpu times
printf("time spent executing by the GPU: %.2f\n", gpu_time);
printf("time spent by CPU in CUDA calls: %.2f\n", sdkGetTimerValue(&timer));
printf("CPU executed %lu iterations while waiting for GPU to finish\n",
counter);
// check the output for correctness
bool bFinalResults = correct_output(a, n, value);
// release resources
checkCudaErrors(cudaEventDestroy(start));
checkCudaErrors(cudaEventDestroy(stop));
checkCudaErrors(cudaFreeHost(a));
checkCudaErrors(cudaFree(d_a));
exit(bFinalResults ? EXIT_SUCCESS : EXIT_FAILURE);
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "asyncAPI", "asyncAPI_vs2017.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>asyncAPI_vs2017</RootNamespace>
<ProjectName>asyncAPI</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<PropertyGroup Condition="'$(WindowsTargetPlatformVersion)'==''">
<LatestTargetPlatformVersion>$([Microsoft.Build.Utilities.ToolLocationHelper]::GetLatestSDKTargetPlatformVersion('Windows', '10.0'))</LatestTargetPlatformVersion>
<WindowsTargetPlatformVersion Condition="'$(WindowsTargetPlatformVersion)' == ''">$(LatestTargetPlatformVersion)</WindowsTargetPlatformVersion>
<TargetPlatformVersion>$(WindowsTargetPlatformVersion)</TargetPlatformVersion>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v141</PlatformToolset>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/asyncAPI.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="asyncAPI.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

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@ -0,0 +1,20 @@

Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2019
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "asyncAPI", "asyncAPI_vs2019.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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@ -0,0 +1,108 @@
<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>asyncAPI_vs2019</RootNamespace>
<ProjectName>asyncAPI</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v142</PlatformToolset>
<WindowsTargetPlatformVersion>10.0</WindowsTargetPlatformVersion>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/asyncAPI.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="asyncAPI.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

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@ -0,0 +1,20 @@

Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2022
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "asyncAPI", "asyncAPI_vs2022.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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@ -0,0 +1,108 @@
<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>asyncAPI_vs2022</RootNamespace>
<ProjectName>asyncAPI</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v143</PlatformToolset>
<WindowsTargetPlatformVersion>10.0</WindowsTargetPlatformVersion>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/asyncAPI.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="asyncAPI.cu" />
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<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

View File

@ -0,0 +1,18 @@
{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

View File

@ -0,0 +1,7 @@
{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

View File

@ -0,0 +1,10 @@
{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/c++11_cuda"
}
]
}

View File

@ -0,0 +1,15 @@
{
"version": "2.0.0",
"tasks": [
{
"label": "sample",
"type": "shell",
"command": "make dbg=1",
"problemMatcher": ["$nvcc"],
"group": {
"kind": "build",
"isDefault": true
}
}
]
}

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@ -0,0 +1,371 @@
################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - c++11_cuda is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
#Detect if installed version of GCC supports required C++11
ifeq ($(TARGET_OS),linux)
empty :=
space := $(empty) $(empty)
GCCVERSIONSTRING := $(shell expr `$(HOST_COMPILER) -dumpversion`)
#Create version number without "."
GCCVERSION := $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f1 -d.)
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f2 -d.)
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f3 -d.)
# Make sure the version number has at least 3 decimals
GCCVERSION += 00
# Remove spaces from the version number
GCCVERSION := $(subst $(space),$(empty),$(GCCVERSION))
#$(warning $(GCCVERSION))
IS_MIN_VERSION := $(shell expr `echo $(GCCVERSION)` \>= 47000)
ifeq ($(IS_MIN_VERSION), 1)
$(info >>> GCC Version is greater or equal to 4.7.0 <<<)
else
$(info >>> Waiving build. Minimum GCC version required is 4.7.0<<<)
SAMPLE_ENABLED := 0
endif
endif
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
SMS ?= 53 61 70 72 75 80 86 87 90
else
SMS ?= 50 52 60 61 70 75 80 86 89 90
endif
ifeq ($(SMS),)
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
HIGHEST_SM := $(lastword $(sort $(SMS)))
ifneq ($(HIGHEST_SM),)
GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
endif
endif
ALL_CCFLAGS += --std=c++11 --threads 0
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: c++11_cuda
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
c++11_cuda.o:c++11_cuda.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
c++11_cuda: c++11_cuda.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./c++11_cuda
testrun: build
clean:
rm -f c++11_cuda c++11_cuda.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/c++11_cuda
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>c++11_cuda</name>
<cflags>
<flag>--std=c++11</flag>
</cflags>
<cuda_api_list>
<toolkit>cudaMalloc</toolkit>
<toolkit>cudaMemcpy</toolkit>
<toolkit>cudaMemset</toolkit>
<toolkit>cudaFree</toolkit>
</cuda_api_list>
<description><![CDATA[This sample demonstrates C++11 feature support in CUDA. It scans a input text file and prints no. of occurrences of x, y, z, w characters. ]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../../Common</path>
</includepaths>
<keyconcepts>
<concept level="advanced">CPP11 CUDA</concept>
</keyconcepts>
<keywords>
<keyword>GPGPU</keyword>
<keyword>CPP11</keyword>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>c++11_cuda.cu</primary_file>
<required_dependencies>
<dependency>CPP11</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Advanced Topics</scope>
<scope>1:C++11 CUDA</scope>
</scopes>
<sm-arch>sm50</sm-arch>
<sm-arch>sm52</sm-arch>
<sm-arch>sm53</sm-arch>
<sm-arch>sm60</sm-arch>
<sm-arch>sm61</sm-arch>
<sm-arch>sm70</sm-arch>
<sm-arch>sm72</sm-arch>
<sm-arch>sm75</sm-arch>
<sm-arch>sm80</sm-arch>
<sm-arch>sm86</sm-arch>
<sm-arch>sm87</sm-arch>
<sm-arch>sm89</sm-arch>
<sm-arch>sm90</sm-arch>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>macosx</platform>
</env>
<env>
<arch>arm</arch>
</env>
<env>
<arch>sbsa</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
<env>
<platform>windows7</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>C++11 CUDA</title>
<type>exe</type>
</entry>

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# c++11_cuda - C++11 CUDA
## Description
This sample demonstrates C++11 feature support in CUDA. It scans a input text file and prints no. of occurrences of x, y, z, w characters.
## Key Concepts
CPP11 CUDA
## Supported SM Architectures
[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](https://developer.nvidia.com/cuda-gpus) [SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 8.9 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaMalloc, cudaMemcpy, cudaMemset, cudaFree
## Dependencies needed to build/run
[CPP11](../../../README.md#cpp11)
## Prerequisites
Download and install the [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## References (for more details)

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <thrust/device_ptr.h>
#include <thrust/count.h>
#include <thrust/execution_policy.h>
#include <iostream>
#include <helper_cuda.h>
/////////////////////////////////////////////////////////////////
// Some utility code to define grid_stride_range
// Normally this would be in a header but it's here
// for didactic purposes. Uses
#include "range.hpp"
using namespace util::lang;
// type alias to simplify typing...
template <typename T>
using step_range = typename range_proxy<T>::step_range_proxy;
template <typename T>
__device__ step_range<T> grid_stride_range(T begin, T end) {
begin += blockDim.x * blockIdx.x + threadIdx.x;
return range(begin, end).step(gridDim.x * blockDim.x);
}
/////////////////////////////////////////////////////////////////
template <typename T, typename Predicate>
__device__ void count_if(int *count, T *data, int n, Predicate p) {
for (auto i : grid_stride_range(0, n)) {
if (p(data[i])) atomicAdd(count, 1);
}
}
// Use count_if with a lambda function that searches for x, y, z or w
// Note the use of range-based for loop and initializer_list inside the functor
// We use auto so we don't have to know the type of the functor or array
__global__ void xyzw_frequency(int *count, char *text, int n) {
const char letters[]{'x', 'y', 'z', 'w'};
count_if(count, text, n, [&](char c) {
for (const auto x : letters)
if (c == x) return true;
return false;
});
}
__global__ void xyzw_frequency_thrust_device(int *count, char *text, int n) {
const char letters[]{'x', 'y', 'z', 'w'};
*count = thrust::count_if(thrust::device, text, text + n, [=](char c) {
for (const auto x : letters)
if (c == x) return true;
return false;
});
}
// a bug in Thrust 1.8 causes warnings when this is uncommented
// so commented out by default -- fixed in Thrust master branch
#if 0
void xyzw_frequency_thrust_host(int *count, char *text, int n)
{
const char letters[] { 'x','y','z','w' };
*count = thrust::count_if(thrust::host, text, text+n, [&](char c) {
for (const auto x : letters)
if (c == x) return true;
return false;
});
}
#endif
int main(int argc, char **argv) {
const char *filename = sdkFindFilePath("warandpeace.txt", argv[0]);
int numBytes = 16 * 1048576;
char *h_text = (char *)malloc(numBytes);
// find first CUDA device
int devID = findCudaDevice(argc, (const char **)argv);
char *d_text;
checkCudaErrors(cudaMalloc((void **)&d_text, numBytes));
FILE *fp = fopen(filename, "r");
if (fp == NULL) {
printf("Cannot find the input text file\n. Exiting..\n");
return EXIT_FAILURE;
}
int len = (int)fread(h_text, sizeof(char), numBytes, fp);
fclose(fp);
std::cout << "Read " << len << " byte corpus from " << filename << std::endl;
checkCudaErrors(cudaMemcpy(d_text, h_text, len, cudaMemcpyHostToDevice));
int count = 0;
int *d_count;
checkCudaErrors(cudaMalloc(&d_count, sizeof(int)));
checkCudaErrors(cudaMemset(d_count, 0, sizeof(int)));
// Try uncommenting one kernel call at a time
xyzw_frequency<<<8, 256>>>(d_count, d_text, len);
xyzw_frequency_thrust_device<<<1, 1>>>(d_count, d_text, len);
checkCudaErrors(
cudaMemcpy(&count, d_count, sizeof(int), cudaMemcpyDeviceToHost));
// xyzw_frequency_thrust_host(&count, h_text, len);
std::cout << "counted " << count
<< " instances of 'x', 'y', 'z', or 'w' in \"" << filename << "\""
<< std::endl;
checkCudaErrors(cudaFree(d_count));
checkCudaErrors(cudaFree(d_text));
return EXIT_SUCCESS;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "c++11_cuda", "c++11_cuda_vs2017.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef UTIL_LANG_RANGE_HPP
#define UTIL_LANG_RANGE_HPP
#include <iterator>
#include <type_traits>
// Make these ranges usable inside CUDA C++ device code
#ifdef __CUDACC__
#define DEVICE_CALLABLE __host__ __device__
#else
#define DEVICE_CALLABLE
#endif
namespace util {
namespace lang {
namespace detail {
template <typename T>
struct range_iter_base : std::iterator<std::input_iterator_tag, T> {
DEVICE_CALLABLE
range_iter_base(T current) : current(current) {}
DEVICE_CALLABLE
T operator*() const { return current; }
DEVICE_CALLABLE
T const* operator->() const { return &current; }
DEVICE_CALLABLE
range_iter_base& operator++() {
++current;
return *this;
}
DEVICE_CALLABLE
range_iter_base operator++(int) {
auto copy = *this;
++*this;
return copy;
}
DEVICE_CALLABLE
bool operator==(range_iter_base const& other) const {
return current == other.current;
}
DEVICE_CALLABLE
bool operator!=(range_iter_base const& other) const {
return not(*this == other);
}
protected:
T current;
};
} // namespace detail
template <typename T>
struct range_proxy {
struct iter : detail::range_iter_base<T> {
DEVICE_CALLABLE
iter(T current) : detail::range_iter_base<T>(current) {}
};
struct step_range_proxy {
struct iter : detail::range_iter_base<T> {
DEVICE_CALLABLE
iter(T current, T step)
: detail::range_iter_base<T>(current), step(step) {}
using detail::range_iter_base<T>::current;
DEVICE_CALLABLE
iter& operator++() {
current += step;
return *this;
}
DEVICE_CALLABLE
iter operator++(int) {
auto copy = *this;
++*this;
return copy;
}
// Loses commutativity. Iterator-based ranges are simply broken. :-(
DEVICE_CALLABLE
bool operator==(iter const& other) const {
return step > 0 ? current >= other.current : current < other.current;
}
DEVICE_CALLABLE
bool operator!=(iter const& other) const { return !(*this == other); }
private:
T step;
};
DEVICE_CALLABLE
step_range_proxy(T begin, T end, T step)
: begin_(begin, step), end_(end, step) {}
DEVICE_CALLABLE
iter begin() const { return begin_; }
DEVICE_CALLABLE
iter end() const { return end_; }
private:
iter begin_;
iter end_;
};
DEVICE_CALLABLE
range_proxy(T begin, T end) : begin_(begin), end_(end) {}
DEVICE_CALLABLE
step_range_proxy step(T step) { return {*begin_, *end_, step}; }
DEVICE_CALLABLE
iter begin() const { return begin_; }
DEVICE_CALLABLE
iter end() const { return end_; }
private:
iter begin_;
iter end_;
};
template <typename T>
struct infinite_range_proxy {
struct iter : detail::range_iter_base<T> {
DEVICE_CALLABLE
iter(T current = T()) : detail::range_iter_base<T>(current) {}
DEVICE_CALLABLE
bool operator==(iter const&) const { return false; }
DEVICE_CALLABLE
bool operator!=(iter const&) const { return true; }
};
struct step_range_proxy {
struct iter : detail::range_iter_base<T> {
DEVICE_CALLABLE
iter(T current = T(), T step = T())
: detail::range_iter_base<T>(current), step(step) {}
using detail::range_iter_base<T>::current;
DEVICE_CALLABLE
iter& operator++() {
current += step;
return *this;
}
DEVICE_CALLABLE
iter operator++(int) {
auto copy = *this;
++*this;
return copy;
}
DEVICE_CALLABLE
bool operator==(iter const&) const { return false; }
DEVICE_CALLABLE
bool operator!=(iter const&) const { return true; }
private:
T step;
};
DEVICE_CALLABLE
step_range_proxy(T begin, T step) : begin_(begin, step) {}
DEVICE_CALLABLE
iter begin() const { return begin_; }
DEVICE_CALLABLE
iter end() const { return iter(); }
private:
iter begin_;
};
DEVICE_CALLABLE
infinite_range_proxy(T begin) : begin_(begin) {}
DEVICE_CALLABLE
step_range_proxy step(T step) { return step_range_proxy(*begin_, step); }
DEVICE_CALLABLE
iter begin() const { return begin_; }
DEVICE_CALLABLE
iter end() const { return iter(); }
private:
iter begin_;
};
template <typename T>
DEVICE_CALLABLE range_proxy<T> range(T begin, T end) {
return {begin, end};
}
template <typename T>
DEVICE_CALLABLE infinite_range_proxy<T> range(T begin) {
return {begin};
}
namespace traits {
template <typename C>
struct has_size {
template <typename T>
static constexpr auto check(T*) ->
typename std::is_integral<decltype(std::declval<T const>().size())>::type;
template <typename>
static constexpr auto check(...) -> std::false_type;
using type = decltype(check<C>(0));
static constexpr bool value = type::value;
};
} // namespace traits
template <typename C,
typename = typename std::enable_if<traits::has_size<C>::value>>
DEVICE_CALLABLE auto indices(C const& cont)
-> range_proxy<decltype(cont.size())> {
return {0, cont.size()};
}
template <typename T, std::size_t N>
DEVICE_CALLABLE range_proxy<std::size_t> indices(T(&)[N]) {
return {0, N};
}
template <typename T>
range_proxy<typename std::initializer_list<T>::size_type> DEVICE_CALLABLE
indices(std::initializer_list<T>&& cont) {
return {0, cont.size()};
}
}
} // namespace util::lang
#endif // ndef UTIL_LANG_RANGE_HPP

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################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
SMS ?= 53 61 70 72 75 80 86 87 90
else
SMS ?= 50 52 60 61 70 75 80 86 89 90
endif
ifeq ($(SMS),)
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
HIGHEST_SM := $(lastword $(sort $(SMS)))
ifneq ($(HIGHEST_SM),)
GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
endif
endif
ALL_CCFLAGS += --threads 0 --std=c++11
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: clock
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
clock.o:clock.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
clock: clock.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./clock
testrun: build
clean:
rm -f clock clock.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/clock
clobber: clean

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@ -0,0 +1,78 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>clock</name>
<cuda_api_list>
<toolkit>cudaMalloc</toolkit>
<toolkit>cudaMemcpy</toolkit>
<toolkit>cudaFree</toolkit>
</cuda_api_list>
<description><![CDATA[This example shows how to use the clock function to measure the performance of block of threads of a kernel accurately.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../../Common</path>
</includepaths>
<keyconcepts>
<concept level="basic">Performance Strategies</concept>
</keyconcepts>
<keywords>
<keyword>performance</keyword>
<keyword>timing</keyword>
<keyword>CUDA</keyword>
<keyword>clock</keyword>
<keyword>timer</keyword>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>clock.cu</primary_file>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>1:Performance Strategies</scope>
</scopes>
<sm-arch>sm50</sm-arch>
<sm-arch>sm52</sm-arch>
<sm-arch>sm53</sm-arch>
<sm-arch>sm60</sm-arch>
<sm-arch>sm61</sm-arch>
<sm-arch>sm70</sm-arch>
<sm-arch>sm72</sm-arch>
<sm-arch>sm75</sm-arch>
<sm-arch>sm80</sm-arch>
<sm-arch>sm86</sm-arch>
<sm-arch>sm87</sm-arch>
<sm-arch>sm89</sm-arch>
<sm-arch>sm90</sm-arch>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<platform>windows7</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>macosx</platform>
</env>
<env>
<arch>arm</arch>
</env>
<env>
<arch>sbsa</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>Clock</title>
<type>exe</type>
</entry>

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@ -0,0 +1,70 @@
# clock - Clock
## Description
This example shows how to use the clock function to measure the performance of block of threads of a kernel accurately.
## Key Concepts
Performance Strategies
## Supported SM Architectures
[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](https://developer.nvidia.com/cuda-gpus) [SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 8.9 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaMalloc, cudaMemcpy, cudaFree
## Prerequisites
Download and install the [CUDA Toolkit 12.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## References (for more details)

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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This example shows how to use the clock function to measure the performance
* of block of threads of a kernel accurately. Blocks are executed in parallel
* and out of order. Since there's no synchronization mechanism between blocks,
* we measure the clock once for each block. The clock samples are written to
* device memory.
*/
// System includes
#include <assert.h>
#include <stdint.h>
#include <stdio.h>
// CUDA runtime
#include <cuda_runtime.h>
// helper functions and utilities to work with CUDA
#include <helper_cuda.h>
#include <helper_functions.h>
// This kernel computes a standard parallel reduction and evaluates the
// time it takes to do that for each block. The timing results are stored
// in device memory.
__global__ static void timedReduction(const float *input, float *output,
clock_t *timer) {
// __shared__ float shared[2 * blockDim.x];
extern __shared__ float shared[];
const int tid = threadIdx.x;
const int bid = blockIdx.x;
if (tid == 0) timer[bid] = clock();
// Copy input.
shared[tid] = input[tid];
shared[tid + blockDim.x] = input[tid + blockDim.x];
// Perform reduction to find minimum.
for (int d = blockDim.x; d > 0; d /= 2) {
__syncthreads();
if (tid < d) {
float f0 = shared[tid];
float f1 = shared[tid + d];
if (f1 < f0) {
shared[tid] = f1;
}
}
}
// Write result.
if (tid == 0) output[bid] = shared[0];
__syncthreads();
if (tid == 0) timer[bid + gridDim.x] = clock();
}
#define NUM_BLOCKS 64
#define NUM_THREADS 256
// It's interesting to change the number of blocks and the number of threads to
// understand how to keep the hardware busy.
//
// Here are some numbers I get on my G80:
// blocks - clocks
// 1 - 3096
// 8 - 3232
// 16 - 3364
// 32 - 4615
// 64 - 9981
//
// With less than 16 blocks some of the multiprocessors of the device are idle.
// With more than 16 you are using all the multiprocessors, but there's only one
// block per multiprocessor and that doesn't allow you to hide the latency of
// the memory. With more than 32 the speed scales linearly.
// Start the main CUDA Sample here
int main(int argc, char **argv) {
printf("CUDA Clock sample\n");
// This will pick the best possible CUDA capable device
int dev = findCudaDevice(argc, (const char **)argv);
float *dinput = NULL;
float *doutput = NULL;
clock_t *dtimer = NULL;
clock_t timer[NUM_BLOCKS * 2];
float input[NUM_THREADS * 2];
for (int i = 0; i < NUM_THREADS * 2; i++) {
input[i] = (float)i;
}
checkCudaErrors(
cudaMalloc((void **)&dinput, sizeof(float) * NUM_THREADS * 2));
checkCudaErrors(cudaMalloc((void **)&doutput, sizeof(float) * NUM_BLOCKS));
checkCudaErrors(
cudaMalloc((void **)&dtimer, sizeof(clock_t) * NUM_BLOCKS * 2));
checkCudaErrors(cudaMemcpy(dinput, input, sizeof(float) * NUM_THREADS * 2,
cudaMemcpyHostToDevice));
timedReduction<<<NUM_BLOCKS, NUM_THREADS, sizeof(float) * 2 * NUM_THREADS>>>(
dinput, doutput, dtimer);
checkCudaErrors(cudaMemcpy(timer, dtimer, sizeof(clock_t) * NUM_BLOCKS * 2,
cudaMemcpyDeviceToHost));
checkCudaErrors(cudaFree(dinput));
checkCudaErrors(cudaFree(doutput));
checkCudaErrors(cudaFree(dtimer));
long double avgElapsedClocks = 0;
for (int i = 0; i < NUM_BLOCKS; i++) {
avgElapsedClocks += (long double)(timer[i + NUM_BLOCKS] - timer[i]);
}
avgElapsedClocks = avgElapsedClocks / NUM_BLOCKS;
printf("Average clocks/block = %Lf\n", avgElapsedClocks);
return EXIT_SUCCESS;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "clock", "clock_vs2017.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>clock_vs2017</RootNamespace>
<ProjectName>clock</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<PropertyGroup Condition="'$(WindowsTargetPlatformVersion)'==''">
<LatestTargetPlatformVersion>$([Microsoft.Build.Utilities.ToolLocationHelper]::GetLatestSDKTargetPlatformVersion('Windows', '10.0'))</LatestTargetPlatformVersion>
<WindowsTargetPlatformVersion Condition="'$(WindowsTargetPlatformVersion)' == ''">$(LatestTargetPlatformVersion)</WindowsTargetPlatformVersion>
<TargetPlatformVersion>$(WindowsTargetPlatformVersion)</TargetPlatformVersion>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v141</PlatformToolset>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/clock.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="clock.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2019
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "clock", "clock_vs2019.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>clock_vs2019</RootNamespace>
<ProjectName>clock</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v142</PlatformToolset>
<WindowsTargetPlatformVersion>10.0</WindowsTargetPlatformVersion>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/clock.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="clock.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2022
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "clock", "clock_vs2022.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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@ -0,0 +1,108 @@
<?xml version="1.0" encoding="utf-8"?>
<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<PropertyGroup>
<CUDAPropsPath Condition="'$(CUDAPropsPath)'==''">$(VCTargetsPath)\BuildCustomizations</CUDAPropsPath>
</PropertyGroup>
<ItemGroup Label="ProjectConfigurations">
<ProjectConfiguration Include="Debug|x64">
<Configuration>Debug</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
<ProjectConfiguration Include="Release|x64">
<Configuration>Release</Configuration>
<Platform>x64</Platform>
</ProjectConfiguration>
</ItemGroup>
<PropertyGroup Label="Globals">
<ProjectGuid>{997E0757-EA74-4A4E-A0FC-47D8C8831A15}</ProjectGuid>
<RootNamespace>clock_vs2022</RootNamespace>
<ProjectName>clock</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v143</PlatformToolset>
<WindowsTargetPlatformVersion>10.0</WindowsTargetPlatformVersion>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
<WholeProgramOptimization>true</WholeProgramOptimization>
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
</ImportGroup>
<PropertyGroup Label="UserMacros" />
<PropertyGroup>
<IntDir>$(Platform)/$(Configuration)/</IntDir>
<IncludePath>$(IncludePath)</IncludePath>
<CodeAnalysisRuleSet>AllRules.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRules />
<CodeAnalysisRuleAssemblies />
</PropertyGroup>
<PropertyGroup Condition="'$(Platform)'=='x64'">
<OutDir>../../../bin/win64/$(Configuration)/</OutDir>
</PropertyGroup>
<ItemDefinitionGroup>
<ClCompile>
<WarningLevel>Level3</WarningLevel>
<PreprocessorDefinitions>WIN32;_MBCS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
<AdditionalIncludeDirectories>./;$(CudaToolkitDir)/include;../../../Common;</AdditionalIncludeDirectories>
</ClCompile>
<Link>
<SubSystem>Console</SubSystem>
<AdditionalDependencies>cudart_static.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
<AdditionalLibraryDirectories>$(CudaToolkitLibDir);</AdditionalLibraryDirectories>
<OutputFile>$(OutDir)/clock.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;compute_89,sm_89;compute_90,sm_90;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" --threads 0 </AdditionalOptions>
<Include>./;../../../Common</Include>
<Defines>WIN32</Defines>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Debug'">
<ClCompile>
<Optimization>Disabled</Optimization>
<RuntimeLibrary>MultiThreadedDebug</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>true</GenerateDebugInformation>
<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MTd</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemDefinitionGroup Condition="'$(Configuration)'=='Release'">
<ClCompile>
<Optimization>MaxSpeed</Optimization>
<RuntimeLibrary>MultiThreaded</RuntimeLibrary>
</ClCompile>
<Link>
<GenerateDebugInformation>false</GenerateDebugInformation>
<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
</Link>
<CudaCompile>
<Runtime>MT</Runtime>
<TargetMachinePlatform>64</TargetMachinePlatform>
</CudaCompile>
</ItemDefinitionGroup>
<ItemGroup>
<CudaCompile Include="clock.cu" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 12.1.targets" />
</ImportGroup>
</Project>

View File

@ -0,0 +1,18 @@
{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

View File

@ -0,0 +1,7 @@
{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

View File

@ -0,0 +1,10 @@
{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/clock_nvrtc"
}
]
}

View File

@ -0,0 +1,15 @@
{
"version": "2.0.0",
"tasks": [
{
"label": "sample",
"type": "shell",
"command": "make dbg=1",
"problemMatcher": ["$nvcc"],
"group": {
"kind": "build",
"isDefault": true
}
}
]
}

View File

@ -0,0 +1,392 @@
################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
UBUNTU = $(shell lsb_release -i -s 2>/dev/null | grep -i ubuntu)
SAMPLE_ENABLED := 1
# This sample is not supported on ARMv7
ifeq ($(TARGET_ARCH),armv7l)
$(info >>> WARNING - clock_nvrtc is not supported on ARMv7 - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
# libNVRTC specific libraries
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -L$(CUDA_PATH)/lib -F/Library/Frameworks -framework CUDA
endif
ifeq ($(TARGET_OS),darwin)
ALL_LDFLAGS += -Xcompiler -F/Library/Frameworks -Xlinker -framework -Xlinker CUDA
else
ifeq ($(TARGET_ARCH),x86_64)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/lib64/stubs
CUDA_SEARCH_PATH += $(CUDA_PATH)/lib/stubs
CUDA_SEARCH_PATH += $(CUDA_PATH)/targets/x86_64-linux/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/armv7-linux-gnueabihf/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/aarch64-linux/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/sbsa-linux/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/armv7-linux-androideabi/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/aarch64-linux-androideabi/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/ARMv7-linux-QNX/lib/stubs
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/aarch64-qnx/lib/stubs
ifdef TARGET_OVERRIDE
CUDA_SEARCH_PATH := $(CUDA_PATH)/targets/$(TARGET_OVERRIDE)/lib/stubs
endif
endif
ifeq ($(TARGET_ARCH),ppc64le)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/ppc64le-linux/lib/stubs
endif
ifeq ($(HOST_ARCH),ppc64le)
CUDA_SEARCH_PATH += $(CUDA_PATH)/lib64/stubs
endif
CUDALIB ?= $(shell find -L $(CUDA_SEARCH_PATH) -maxdepth 1 -name libcuda.so 2> /dev/null)
ifeq ("$(CUDALIB)","")
$(info >>> WARNING - libcuda.so not found, CUDA Driver is not installed. Please re-install the driver. <<<)
SAMPLE_ENABLED := 0
else
CUDALIB := $(shell echo $(CUDALIB) | sed "s/ .*//" | sed "s/\/libcuda.so//" )
LIBRARIES += -L$(CUDALIB) -lcuda
endif
endif
ALL_CCFLAGS += --threads 0 --std=c++11
INCLUDES += -I$(CUDA_PATH)/include
LIBRARIES += -lnvrtc
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: clock_nvrtc
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
clock.o:clock.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
clock_nvrtc: clock.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./clock_nvrtc
testrun: build
clean:
rm -f clock_nvrtc clock.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/clock_nvrtc
clobber: clean

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