add and update samples for CUDA 11.5

This commit is contained in:
Rutwik Choughule
2021-10-21 16:34:49 +05:30
parent 3342d604fe
commit 1f76a2d110
2796 changed files with 1511725 additions and 827 deletions

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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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{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

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{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/simpleStreams"
}
]
}

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

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################################################################################
# Copyright (c) 2019, 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 += --qpp-config 5.4.0,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 $(TARGET_ARCH),armv7l aarch64))
SMS ?= 35 37 50 52 60 61 70 72 75 80 86
else
SMS ?= 35 37 50 52 60 61 70 75 80 86
endif
ifeq ($(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 ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: simpleStreams
check.deps:
ifeq ($(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
simpleStreams.o:simpleStreams.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
simpleStreams: simpleStreams.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
$(EXEC) ./simpleStreams
clean:
rm -f simpleStreams simpleStreams.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/simpleStreams
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>simpleStreams</name>
<cuda_api_list>
<toolkit>cudaEventCreate</toolkit>
<toolkit>cudaEventRecord</toolkit>
<toolkit>cudaEventQuery</toolkit>
<toolkit>cudaEventDestroy</toolkit>
<toolkit>cudaEventElapsedTime</toolkit>
<toolkit>cudaMemcpyAsync</toolkit>
</cuda_api_list>
<description><![CDATA[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.]]></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>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>simpleStreams.cu</primary_file>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>1:Performance Strategies</scope>
</scopes>
<sm-arch>sm35</sm-arch>
<sm-arch>sm37</sm-arch>
<sm-arch>sm50</sm-arch>
<sm-arch>sm52</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>
<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>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>simpleStreams</title>
<type>exe</type>
</entry>

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# simpleStreams - simpleStreams
## Description
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.
## Key Concepts
Asynchronous Data Transfers, CUDA Streams and Events
## Supported SM Architectures
[SM 3.5 ](https://developer.nvidia.com/cuda-gpus) [SM 3.7 ](https://developer.nvidia.com/cuda-gpus) [SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](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)
## 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)
cudaEventCreate, cudaEventRecord, cudaEventQuery, cudaEventDestroy, cudaEventElapsedTime, cudaMemcpyAsync
## Prerequisites
Download and install the [CUDA Toolkit 11.5](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) 2021, 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 streams for overlapping
* kernel execution with device/host memcopies. The kernel is used to
* initialize an array to a specific value, after which the array is
* copied to the host (CPU) memory. To increase performance, multiple
* kernel/memcopy pairs are launched asynchronously, each pair in its
* own stream. Devices with Compute Capability 1.1 can overlap a kernel
* and a memcopy as long as they are issued in different streams. Kernels
* are serialized. Thus, if n pairs are launched, streamed approach
* can reduce the memcopy cost to the (1/n)th of a single copy of the entire
* data set.
*
* Additionally, this sample uses CUDA events to measure elapsed time for
* CUDA calls. Events are a part of CUDA API and provide a system independent
* way to measure execution times on CUDA devices with approximately 0.5
* microsecond precision.
*
* Elapsed times are averaged over nreps repetitions (10 by default).
*
*/
const char *sSDKsample = "simpleStreams";
const char *sEventSyncMethod[] = {"cudaEventDefault", "cudaEventBlockingSync",
"cudaEventDisableTiming", NULL};
const char *sDeviceSyncMethod[] = {
"cudaDeviceScheduleAuto", "cudaDeviceScheduleSpin",
"cudaDeviceScheduleYield", "INVALID",
"cudaDeviceScheduleBlockingSync", NULL};
// System includes
#include <stdio.h>
#include <assert.h>
// CUDA runtime
#include <cuda_runtime.h>
// helper functions and utilities to work with CUDA
#include <helper_functions.h>
#include <helper_cuda.h>
#ifndef WIN32
#include <sys/mman.h> // for mmap() / munmap()
#endif
// Macro to aligned up to the memory size in question
#define MEMORY_ALIGNMENT 4096
#define ALIGN_UP(x, size) (((size_t)x + (size - 1)) & (~(size - 1)))
__global__ void init_array(int *g_data, int *factor, int num_iterations) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
for (int i = 0; i < num_iterations; i++) {
g_data[idx] += *factor; // non-coalesced on purpose, to burn time
}
}
bool correct_data(int *a, const int n, const int c) {
for (int i = 0; i < n; i++) {
if (a[i] != c) {
printf("%d: %d %d\n", i, a[i], c);
return false;
}
}
return true;
}
inline void AllocateHostMemory(bool bPinGenericMemory, int **pp_a,
int **ppAligned_a, int nbytes) {
#if CUDART_VERSION >= 4000
#if !defined(__arm__) && !defined(__aarch64__)
if (bPinGenericMemory) {
// allocate a generic page-aligned chunk of system memory
#ifdef WIN32
printf(
"> VirtualAlloc() allocating %4.2f Mbytes of (generic page-aligned "
"system memory)\n",
(float)nbytes / 1048576.0f);
*pp_a = (int *)VirtualAlloc(NULL, (nbytes + MEMORY_ALIGNMENT),
MEM_RESERVE | MEM_COMMIT, PAGE_READWRITE);
#else
printf(
"> mmap() allocating %4.2f Mbytes (generic page-aligned system "
"memory)\n",
(float)nbytes / 1048576.0f);
*pp_a = (int *)mmap(NULL, (nbytes + MEMORY_ALIGNMENT),
PROT_READ | PROT_WRITE, MAP_PRIVATE | MAP_ANON, -1, 0);
#endif
*ppAligned_a = (int *)ALIGN_UP(*pp_a, MEMORY_ALIGNMENT);
printf(
"> cudaHostRegister() registering %4.2f Mbytes of generic allocated "
"system memory\n",
(float)nbytes / 1048576.0f);
// pin allocate memory
checkCudaErrors(
cudaHostRegister(*ppAligned_a, nbytes, cudaHostRegisterMapped));
} else
#endif
#endif
{
printf("> cudaMallocHost() allocating %4.2f Mbytes of system memory\n",
(float)nbytes / 1048576.0f);
// allocate host memory (pinned is required for achieve asynchronicity)
checkCudaErrors(cudaMallocHost((void **)pp_a, nbytes));
*ppAligned_a = *pp_a;
}
}
inline void FreeHostMemory(bool bPinGenericMemory, int **pp_a,
int **ppAligned_a, int nbytes) {
#if CUDART_VERSION >= 4000
#if !defined(__arm__) && !defined(__aarch64__)
// CUDA 4.0 support pinning of generic host memory
if (bPinGenericMemory) {
// unpin and delete host memory
checkCudaErrors(cudaHostUnregister(*ppAligned_a));
#ifdef WIN32
VirtualFree(*pp_a, 0, MEM_RELEASE);
#else
munmap(*pp_a, nbytes);
#endif
} else
#endif
#endif
{
cudaFreeHost(*pp_a);
}
}
static const char *sSyncMethod[] = {
"0 (Automatic Blocking)",
"1 (Spin Blocking)",
"2 (Yield Blocking)",
"3 (Undefined Blocking Method)",
"4 (Blocking Sync Event) = low CPU utilization",
NULL};
void printHelp() {
printf("Usage: %s [options below]\n", sSDKsample);
printf("\t--sync_method=n for CPU/GPU synchronization\n");
printf("\t n=%s\n", sSyncMethod[0]);
printf("\t n=%s\n", sSyncMethod[1]);
printf("\t n=%s\n", sSyncMethod[2]);
printf("\t <Default> n=%s\n", sSyncMethod[4]);
printf(
"\t--use_generic_memory (default) use generic page-aligned for system "
"memory\n");
printf(
"\t--use_cuda_malloc_host (optional) use cudaMallocHost to allocate "
"system memory\n");
}
#if defined(__APPLE__) || defined(MACOSX)
#define DEFAULT_PINNED_GENERIC_MEMORY false
#else
#define DEFAULT_PINNED_GENERIC_MEMORY true
#endif
int main(int argc, char **argv) {
int cuda_device = 0;
int nstreams = 4; // number of streams for CUDA calls
int nreps = 10; // number of times each experiment is repeated
int n = 16 * 1024 * 1024; // number of ints in the data set
int nbytes = n * sizeof(int); // number of data bytes
dim3 threads, blocks; // kernel launch configuration
float elapsed_time, time_memcpy, time_kernel; // timing variables
float scale_factor = 1.0f;
// allocate generic memory and pin it laster instead of using cudaHostAlloc()
bool bPinGenericMemory =
DEFAULT_PINNED_GENERIC_MEMORY; // we want this to be the default behavior
int device_sync_method =
cudaDeviceBlockingSync; // by default we use BlockingSync
int niterations; // number of iterations for the loop inside the kernel
printf("[ %s ]\n\n", sSDKsample);
if (checkCmdLineFlag(argc, (const char **)argv, "help")) {
printHelp();
return EXIT_SUCCESS;
}
if ((device_sync_method = getCmdLineArgumentInt(argc, (const char **)argv,
"sync_method")) >= 0) {
if (device_sync_method == 0 || device_sync_method == 1 ||
device_sync_method == 2 || device_sync_method == 4) {
printf("Device synchronization method set to = %s\n",
sSyncMethod[device_sync_method]);
printf("Setting reps to 100 to demonstrate steady state\n");
nreps = 100;
} else {
printf("Invalid command line option sync_method=\"%d\"\n",
device_sync_method);
return EXIT_FAILURE;
}
} else {
printHelp();
return EXIT_SUCCESS;
}
if (checkCmdLineFlag(argc, (const char **)argv, "use_generic_memory")) {
#if defined(__APPLE__) || defined(MACOSX)
bPinGenericMemory = false; // Generic Pinning of System Paged memory not
// currently supported on Mac OSX
#else
bPinGenericMemory = true;
#endif
}
if (checkCmdLineFlag(argc, (const char **)argv, "use_cuda_malloc_host")) {
bPinGenericMemory = false;
}
printf("\n> ");
cuda_device = findCudaDevice(argc, (const char **)argv);
// check the compute capability of the device
int num_devices = 0;
checkCudaErrors(cudaGetDeviceCount(&num_devices));
if (0 == num_devices) {
printf(
"your system does not have a CUDA capable device, waiving test...\n");
return EXIT_WAIVED;
}
// check if the command-line chosen device ID is within range, exit if not
if (cuda_device >= num_devices) {
printf(
"cuda_device=%d is invalid, must choose device ID between 0 and %d\n",
cuda_device, num_devices - 1);
return EXIT_FAILURE;
}
checkCudaErrors(cudaSetDevice(cuda_device));
// Checking for compute capabilities
cudaDeviceProp deviceProp;
checkCudaErrors(cudaGetDeviceProperties(&deviceProp, cuda_device));
niterations = 5;
// Check if GPU can map host memory (Generic Method), if not then we override
// bPinGenericMemory to be false
if (bPinGenericMemory) {
printf("Device: <%s> canMapHostMemory: %s\n", deviceProp.name,
deviceProp.canMapHostMemory ? "Yes" : "No");
if (deviceProp.canMapHostMemory == 0) {
printf(
"Using cudaMallocHost, CUDA device does not support mapping of "
"generic host memory\n");
bPinGenericMemory = false;
}
}
// Anything that is less than 32 Cores will have scaled down workload
scale_factor =
max((32.0f / (_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) *
(float)deviceProp.multiProcessorCount)),
1.0f);
n = (int)rint((float)n / scale_factor);
printf("> CUDA Capable: SM %d.%d hardware\n", deviceProp.major,
deviceProp.minor);
printf("> %d Multiprocessor(s) x %d (Cores/Multiprocessor) = %d (Cores)\n",
deviceProp.multiProcessorCount,
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) *
deviceProp.multiProcessorCount);
printf("> scale_factor = %1.4f\n", 1.0f / scale_factor);
printf("> array_size = %d\n\n", n);
// enable use of blocking sync, to reduce CPU usage
printf("> Using CPU/GPU Device Synchronization method (%s)\n",
sDeviceSyncMethod[device_sync_method]);
checkCudaErrors(cudaSetDeviceFlags(
device_sync_method | (bPinGenericMemory ? cudaDeviceMapHost : 0)));
// allocate host memory
int c = 5; // value to which the array will be initialized
int *h_a = 0; // pointer to the array data in host memory
int *hAligned_a = 0; // pointer to the array data in host memory (aligned to
// MEMORY_ALIGNMENT)
// Allocate Host memory (could be using cudaMallocHost or VirtualAlloc/mmap if
// using the new CUDA 4.0 features
AllocateHostMemory(bPinGenericMemory, &h_a, &hAligned_a, nbytes);
// allocate device memory
int *d_a = 0,
*d_c = 0; // pointers to data and init value in the device memory
checkCudaErrors(cudaMalloc((void **)&d_a, nbytes));
checkCudaErrors(cudaMemset(d_a, 0x0, nbytes));
checkCudaErrors(cudaMalloc((void **)&d_c, sizeof(int)));
checkCudaErrors(cudaMemcpy(d_c, &c, sizeof(int), cudaMemcpyHostToDevice));
printf("\nStarting Test\n");
// allocate and initialize an array of stream handles
cudaStream_t *streams =
(cudaStream_t *)malloc(nstreams * sizeof(cudaStream_t));
for (int i = 0; i < nstreams; i++) {
checkCudaErrors(cudaStreamCreate(&(streams[i])));
}
// create CUDA event handles
// use blocking sync
cudaEvent_t start_event, stop_event;
int eventflags =
((device_sync_method == cudaDeviceBlockingSync) ? cudaEventBlockingSync
: cudaEventDefault);
checkCudaErrors(cudaEventCreateWithFlags(&start_event, eventflags));
checkCudaErrors(cudaEventCreateWithFlags(&stop_event, eventflags));
// time memcopy from device
checkCudaErrors(cudaEventRecord(start_event, 0)); // record in stream-0, to
// ensure that all previous
// CUDA calls have
// completed
checkCudaErrors(cudaMemcpyAsync(hAligned_a, d_a, nbytes,
cudaMemcpyDeviceToHost, streams[0]));
checkCudaErrors(cudaEventRecord(stop_event, 0));
checkCudaErrors(cudaEventSynchronize(
stop_event)); // block until the event is actually recorded
checkCudaErrors(cudaEventElapsedTime(&time_memcpy, start_event, stop_event));
printf("memcopy:\t%.2f\n", time_memcpy);
// time kernel
threads = dim3(512, 1);
blocks = dim3(n / threads.x, 1);
checkCudaErrors(cudaEventRecord(start_event, 0));
init_array<<<blocks, threads, 0, streams[0]>>>(d_a, d_c, niterations);
checkCudaErrors(cudaEventRecord(stop_event, 0));
checkCudaErrors(cudaEventSynchronize(stop_event));
checkCudaErrors(cudaEventElapsedTime(&time_kernel, start_event, stop_event));
printf("kernel:\t\t%.2f\n", time_kernel);
//////////////////////////////////////////////////////////////////////
// time non-streamed execution for reference
threads = dim3(512, 1);
blocks = dim3(n / threads.x, 1);
checkCudaErrors(cudaEventRecord(start_event, 0));
for (int k = 0; k < nreps; k++) {
init_array<<<blocks, threads>>>(d_a, d_c, niterations);
checkCudaErrors(
cudaMemcpy(hAligned_a, d_a, nbytes, cudaMemcpyDeviceToHost));
}
checkCudaErrors(cudaEventRecord(stop_event, 0));
checkCudaErrors(cudaEventSynchronize(stop_event));
checkCudaErrors(cudaEventElapsedTime(&elapsed_time, start_event, stop_event));
printf("non-streamed:\t%.2f\n", elapsed_time / nreps);
//////////////////////////////////////////////////////////////////////
// time execution with nstreams streams
threads = dim3(512, 1);
blocks = dim3(n / (nstreams * threads.x), 1);
memset(hAligned_a, 255,
nbytes); // set host memory bits to all 1s, for testing correctness
checkCudaErrors(cudaMemset(
d_a, 0, nbytes)); // set device memory to all 0s, for testing correctness
checkCudaErrors(cudaEventRecord(start_event, 0));
for (int k = 0; k < nreps; k++) {
// asynchronously launch nstreams kernels, each operating on its own portion
// of data
for (int i = 0; i < nstreams; i++) {
init_array<<<blocks, threads, 0, streams[i]>>>(d_a + i * n / nstreams,
d_c, niterations);
}
// asynchronously launch nstreams memcopies. Note that memcopy in stream x
// will only
// commence executing when all previous CUDA calls in stream x have
// completed
for (int i = 0; i < nstreams; i++) {
checkCudaErrors(cudaMemcpyAsync(hAligned_a + i * n / nstreams,
d_a + i * n / nstreams, nbytes / nstreams,
cudaMemcpyDeviceToHost, streams[i]));
}
}
checkCudaErrors(cudaEventRecord(stop_event, 0));
checkCudaErrors(cudaEventSynchronize(stop_event));
checkCudaErrors(cudaEventElapsedTime(&elapsed_time, start_event, stop_event));
printf("%d streams:\t%.2f\n", nstreams, elapsed_time / nreps);
// check whether the output is correct
printf("-------------------------------\n");
bool bResults = correct_data(hAligned_a, n, c * nreps * niterations);
// release resources
for (int i = 0; i < nstreams; i++) {
checkCudaErrors(cudaStreamDestroy(streams[i]));
}
checkCudaErrors(cudaEventDestroy(start_event));
checkCudaErrors(cudaEventDestroy(stop_event));
// Free cudaMallocHost or Generic Host allocated memory (from CUDA 4.0)
FreeHostMemory(bPinGenericMemory, &h_a, &hAligned_a, nbytes);
checkCudaErrors(cudaFree(d_a));
checkCudaErrors(cudaFree(d_c));
return bResults ? EXIT_SUCCESS : EXIT_FAILURE;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
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EndGlobalSection
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<PropertyGroup>
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</ClCompile>
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<LinkTimeCodeGeneration>UseLinkTimeCodeGeneration</LinkTimeCodeGeneration>
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View File

@@ -0,0 +1,20 @@

Microsoft Visual Studio Solution File, Format Version 12.00
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@@ -0,0 +1,109 @@
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