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}/stereoDisparity"
}
]
}

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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 :=
################################################################################
#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 $(GCCVERSION)` \>= 51000)
ifeq ($(IS_MIN_VERSION), 1)
$(info >>> GCC Version is greater or equal to 5.1.0 <<<)
else
$(info >>> Waiving build. Minimum GCC version required is 5.1.0<<<)
SAMPLE_ENABLED := 0
endif
endif
# Gencode arguments
ifeq ($(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 ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: stereoDisparity
check.deps:
ifeq ($(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
stereoDisparity.o:stereoDisparity.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
stereoDisparity: stereoDisparity.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
$(EXEC) ./stereoDisparity
clean:
rm -f stereoDisparity stereoDisparity.o *.pgm
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/stereoDisparity
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>stereoDisparity</name>
<cleanextras>
<clean>*.pgm</clean>
</cleanextras>
<description><![CDATA[A CUDA program that demonstrates how to compute a stereo disparity map using SIMD SAD (Sum of Absolute Difference) intrinsics. Requires Compute Capability 2.0 or higher.]]></description>
<devicecompilation>whole</devicecompilation>
<files>
<file>data\stereo.im0.640x533.ppm</file>
<file>data\stereo.im1.640x533.ppm</file>
</files>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../Common</path>
</includepaths>
<keyconcepts>
<concept level="advanced">Image Processing</concept>
<concept level="advanced">Video Intrinsics</concept>
</keyconcepts>
<keywords>
<keyword>CUDA</keyword>
<keyword>GPGPU</keyword>
<keyword>atomic</keyword>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>stereoDisparity.cu</primary_file>
<scopes>
<scope>2:Graphics Interop</scope>
<scope>1:CUDA Advanced Topics</scope>
<scope>2:Image Processing</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>Stereo Disparity Computation (SAD SIMD Intrinsics)</title>
<type>exe</type>
</entry>

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# stereoDisparity - Stereo Disparity Computation (SAD SIMD Intrinsics)
## Description
A CUDA program that demonstrates how to compute a stereo disparity map using SIMD SAD (Sum of Absolute Difference) intrinsics. Requires Compute Capability 2.0 or higher.
## Key Concepts
Image Processing, Video Intrinsics
## 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
## 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.
*/
/* A CUDA program that demonstrates how to compute a stereo disparity map using
* SIMD SAD (Sum of Absolute Difference) intrinsics
*/
// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
// includes, kernels
#include <cuda_runtime.h>
#include "stereoDisparity_kernel.cuh"
// includes, project
#include <helper_functions.h> // helper for shared that are common to CUDA Samples
#include <helper_cuda.h> // helper for checking cuda initialization and error checking
#include <helper_string.h> // helper functions for string parsing
static const char *sSDKsample = "[stereoDisparity]\0";
int iDivUp(int a, int b) { return ((a % b) != 0) ? (a / b + 1) : (a / b); }
////////////////////////////////////////////////////////////////////////////////
// declaration, forward
void runTest(int argc, char **argv);
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
printf("%s Starting...\n\n", sSDKsample);
runTest(argc, argv);
}
////////////////////////////////////////////////////////////////////////////////
//! CUDA Sample for calculating depth maps
////////////////////////////////////////////////////////////////////////////////
void runTest(int argc, char **argv) {
cudaDeviceProp deviceProp;
deviceProp.major = 0;
deviceProp.minor = 0;
int dev = 0;
// This will pick the best possible CUDA capable device
dev = findCudaDevice(argc, (const char **)argv);
checkCudaErrors(cudaGetDeviceProperties(&deviceProp, dev));
// Statistics about the GPU device
printf(
"> GPU device has %d Multi-Processors, SM %d.%d compute capabilities\n\n",
deviceProp.multiProcessorCount, deviceProp.major, deviceProp.minor);
StopWatchInterface *timer;
sdkCreateTimer(&timer);
// Search parameters
int minDisp = -16;
int maxDisp = 0;
// Load image data
// allocate mem for the images on host side
// initialize pointers to NULL to request lib call to allocate as needed
// PPM images are loaded into 4 byte/pixel memory (RGBX)
unsigned char *h_img0 = NULL;
unsigned char *h_img1 = NULL;
unsigned int w, h;
char *fname0 = sdkFindFilePath("stereo.im0.640x533.ppm", argv[0]);
char *fname1 = sdkFindFilePath("stereo.im1.640x533.ppm", argv[0]);
printf("Loaded <%s> as image 0\n", fname0);
if (!sdkLoadPPM4ub(fname0, &h_img0, &w, &h)) {
fprintf(stderr, "Failed to load <%s>\n", fname0);
}
printf("Loaded <%s> as image 1\n", fname1);
if (!sdkLoadPPM4ub(fname1, &h_img1, &w, &h)) {
fprintf(stderr, "Failed to load <%s>\n", fname1);
}
dim3 numThreads = dim3(blockSize_x, blockSize_y, 1);
dim3 numBlocks = dim3(iDivUp(w, numThreads.x), iDivUp(h, numThreads.y));
unsigned int numData = w * h;
unsigned int memSize = sizeof(int) * numData;
// allocate mem for the result on host side
unsigned int *h_odata = (unsigned int *)malloc(memSize);
// initialize the memory
for (unsigned int i = 0; i < numData; i++) h_odata[i] = 0;
// allocate device memory for result
unsigned int *d_odata, *d_img0, *d_img1;
checkCudaErrors(cudaMalloc((void **)&d_odata, memSize));
checkCudaErrors(cudaMalloc((void **)&d_img0, memSize));
checkCudaErrors(cudaMalloc((void **)&d_img1, memSize));
// copy host memory to device to initialize to zeros
checkCudaErrors(cudaMemcpy(d_img0, h_img0, memSize, cudaMemcpyHostToDevice));
checkCudaErrors(cudaMemcpy(d_img1, h_img1, memSize, cudaMemcpyHostToDevice));
checkCudaErrors(
cudaMemcpy(d_odata, h_odata, memSize, cudaMemcpyHostToDevice));
cudaChannelFormatDesc ca_desc0 = cudaCreateChannelDesc<unsigned int>();
cudaChannelFormatDesc ca_desc1 = cudaCreateChannelDesc<unsigned int>();
cudaTextureObject_t tex2Dleft, tex2Dright;
cudaResourceDesc texRes;
memset(&texRes, 0, sizeof(cudaResourceDesc));
texRes.resType = cudaResourceTypePitch2D;
texRes.res.pitch2D.devPtr = d_img0;
texRes.res.pitch2D.desc = ca_desc0;
texRes.res.pitch2D.width = w;
texRes.res.pitch2D.height = h;
texRes.res.pitch2D.pitchInBytes = w * 4;
cudaTextureDesc texDescr;
memset(&texDescr, 0, sizeof(cudaTextureDesc));
texDescr.normalizedCoords = false;
texDescr.filterMode = cudaFilterModePoint;
texDescr.addressMode[0] = cudaAddressModeClamp;
texDescr.addressMode[1] = cudaAddressModeClamp;
texDescr.readMode = cudaReadModeElementType;
checkCudaErrors(
cudaCreateTextureObject(&tex2Dleft, &texRes, &texDescr, NULL));
memset(&texRes, 0, sizeof(cudaResourceDesc));
texRes.resType = cudaResourceTypePitch2D;
texRes.res.pitch2D.devPtr = d_img1;
texRes.res.pitch2D.desc = ca_desc1;
texRes.res.pitch2D.width = w;
texRes.res.pitch2D.height = h;
texRes.res.pitch2D.pitchInBytes = w * 4;
memset(&texDescr, 0, sizeof(cudaTextureDesc));
texDescr.normalizedCoords = false;
texDescr.filterMode = cudaFilterModePoint;
texDescr.addressMode[0] = cudaAddressModeClamp;
texDescr.addressMode[1] = cudaAddressModeClamp;
texDescr.readMode = cudaReadModeElementType;
checkCudaErrors(
cudaCreateTextureObject(&tex2Dright, &texRes, &texDescr, NULL));
// First run the warmup kernel (which we'll use to get the GPU in the correct
// max power state
stereoDisparityKernel<<<numBlocks, numThreads>>>(
d_img0, d_img1, d_odata, w, h, minDisp, maxDisp, tex2Dleft, tex2Dright);
cudaDeviceSynchronize();
// Allocate CUDA events that we'll use for timing
cudaEvent_t start, stop;
checkCudaErrors(cudaEventCreate(&start));
checkCudaErrors(cudaEventCreate(&stop));
printf("Launching CUDA stereoDisparityKernel()\n");
// Record the start event
checkCudaErrors(cudaEventRecord(start, NULL));
// launch the stereoDisparity kernel
stereoDisparityKernel<<<numBlocks, numThreads>>>(
d_img0, d_img1, d_odata, w, h, minDisp, maxDisp, tex2Dleft, tex2Dright);
// Record the stop event
checkCudaErrors(cudaEventRecord(stop, NULL));
// Wait for the stop event to complete
checkCudaErrors(cudaEventSynchronize(stop));
// Check to make sure the kernel didn't fail
getLastCudaError("Kernel execution failed");
float msecTotal = 0.0f;
checkCudaErrors(cudaEventElapsedTime(&msecTotal, start, stop));
// Copy result from device to host for verification
checkCudaErrors(
cudaMemcpy(h_odata, d_odata, memSize, cudaMemcpyDeviceToHost));
printf("Input Size [%dx%d], ", w, h);
printf("Kernel size [%dx%d], ", (2 * RAD + 1), (2 * RAD + 1));
printf("Disparities [%d:%d]\n", minDisp, maxDisp);
printf("GPU processing time : %.4f (ms)\n", msecTotal);
printf("Pixel throughput : %.3f Mpixels/sec\n",
((float)(w * h * 1000.f) / msecTotal) / 1000000);
// calculate sum of resultant GPU image
unsigned int checkSum = 0;
for (unsigned int i = 0; i < w * h; i++) {
checkSum += h_odata[i];
}
printf("GPU Checksum = %u, ", checkSum);
// write out the resulting disparity image.
unsigned char *dispOut = (unsigned char *)malloc(numData);
int mult = 20;
const char *fnameOut = "output_GPU.pgm";
for (unsigned int i = 0; i < numData; i++) {
dispOut[i] = (int)h_odata[i] * mult;
}
printf("GPU image: <%s>\n", fnameOut);
sdkSavePGM(fnameOut, dispOut, w, h);
// compute reference solution
printf("Computing CPU reference...\n");
cpu_gold_stereo((unsigned int *)h_img0, (unsigned int *)h_img1,
(unsigned int *)h_odata, w, h, minDisp, maxDisp);
unsigned int cpuCheckSum = 0;
for (unsigned int i = 0; i < w * h; i++) {
cpuCheckSum += h_odata[i];
}
printf("CPU Checksum = %u, ", cpuCheckSum);
const char *cpuFnameOut = "output_CPU.pgm";
for (unsigned int i = 0; i < numData; i++) {
dispOut[i] = (int)h_odata[i] * mult;
}
printf("CPU image: <%s>\n", cpuFnameOut);
sdkSavePGM(cpuFnameOut, dispOut, w, h);
// cleanup memory
checkCudaErrors(cudaFree(d_odata));
checkCudaErrors(cudaFree(d_img0));
checkCudaErrors(cudaFree(d_img1));
if (h_odata != NULL) free(h_odata);
if (h_img0 != NULL) free(h_img0);
if (h_img1 != NULL) free(h_img1);
if (dispOut != NULL) free(dispOut);
sdkDeleteTimer(&timer);
exit((checkSum == cpuCheckSum) ? EXIT_SUCCESS : EXIT_FAILURE);
}

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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.
*/
/* Simple kernel computes a Stereo Disparity using CUDA SIMD SAD intrinsics. */
#ifndef _STEREODISPARITY_KERNEL_H_
#define _STEREODISPARITY_KERNEL_H_
#define blockSize_x 32
#define blockSize_y 8
// RAD is the radius of the region of support for the search
#define RAD 8
// STEPS is the number of loads we must perform to initialize the shared memory
// area (see convolution CUDA Sample for example)
#define STEPS 3
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
////////////////////////////////////////////////////////////////////////////////
// This function applies the video intrinsic operations to compute a
// sum of absolute differences. The absolute differences are computed
// and the optional .add instruction is used to sum the lanes.
//
// For more information, see also the documents:
// "Using_Inline_PTX_Assembly_In_CUDA.pdf"
// and also the PTX ISA documentation for the architecture in question, e.g.:
// "ptx_isa_3.0K.pdf"
// included in the NVIDIA GPU Computing Toolkit
////////////////////////////////////////////////////////////////////////////////
__device__ unsigned int __usad4(unsigned int A, unsigned int B,
unsigned int C = 0) {
unsigned int result;
// Kepler (SM 3.x) and higher supports a 4 vector SAD SIMD
asm(
"vabsdiff4.u32.u32.u32.add"
" %0, %1, %2, %3;"
: "=r"(result)
: "r"(A), "r"(B), "r"(C));
return result;
}
////////////////////////////////////////////////////////////////////////////////
//! Simple stereo disparity kernel to test atomic instructions
//! Algorithm Explanation:
//! For stereo disparity this performs a basic block matching scheme.
//! The sum of abs. diffs between and area of the candidate pixel in the left
//! images
//! is computed against different horizontal shifts of areas from the right.
//! The shift at which the difference is minimum is taken as how far that pixel
//! moved between left/right image pairs. The recovered motion is the
//! disparity map
//! More motion indicates more parallax indicates a closer object.
//! @param g_img1 image 1 in global memory, RGBA, 4 bytes/pixel
//! @param g_img2 image 2 in global memory
//! @param g_odata disparity map output in global memory, unsigned int
//! output/pixel
//! @param w image width in pixels
//! @param h image height in pixels
//! @param minDisparity leftmost search range
//! @param maxDisparity rightmost search range
////////////////////////////////////////////////////////////////////////////////
__global__ void stereoDisparityKernel(unsigned int *g_img0,
unsigned int *g_img1,
unsigned int *g_odata, int w, int h,
int minDisparity, int maxDisparity,
cudaTextureObject_t tex2Dleft,
cudaTextureObject_t tex2Dright) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// access thread id
const int tidx = blockDim.x * blockIdx.x + threadIdx.x;
const int tidy = blockDim.y * blockIdx.y + threadIdx.y;
const unsigned int sidx = threadIdx.x + RAD;
const unsigned int sidy = threadIdx.y + RAD;
unsigned int imLeft;
unsigned int imRight;
unsigned int cost;
unsigned int bestCost = 9999999;
unsigned int bestDisparity = 0;
__shared__ unsigned int diff[blockSize_y + 2 * RAD][blockSize_x + 2 * RAD];
// store needed values for left image into registers (constant indexed local
// vars)
unsigned int imLeftA[STEPS];
unsigned int imLeftB[STEPS];
for (int i = 0; i < STEPS; i++) {
int offset = -RAD + i * RAD;
imLeftA[i] = tex2D<unsigned int>(tex2Dleft, tidx - RAD, tidy + offset);
imLeftB[i] =
tex2D<unsigned int>(tex2Dleft, tidx - RAD + blockSize_x, tidy + offset);
}
// for a fixed camera system this could be hardcoded and loop unrolled
for (int d = minDisparity; d <= maxDisparity; d++) {
// LEFT
#pragma unroll
for (int i = 0; i < STEPS; i++) {
int offset = -RAD + i * RAD;
// imLeft = tex2D( tex2Dleft, tidx-RAD, tidy+offset );
imLeft = imLeftA[i];
imRight = tex2D<unsigned int>(tex2Dright, tidx - RAD + d, tidy + offset);
cost = __usad4(imLeft, imRight);
diff[sidy + offset][sidx - RAD] = cost;
}
// RIGHT
#pragma unroll
for (int i = 0; i < STEPS; i++) {
int offset = -RAD + i * RAD;
if (threadIdx.x < 2 * RAD) {
// imLeft = tex2D( tex2Dleft, tidx-RAD+blockSize_x, tidy+offset );
imLeft = imLeftB[i];
imRight = tex2D<unsigned int>(tex2Dright, tidx - RAD + blockSize_x + d,
tidy + offset);
cost = __usad4(imLeft, imRight);
diff[sidy + offset][sidx - RAD + blockSize_x] = cost;
}
}
cg::sync(cta);
// sum cost horizontally
#pragma unroll
for (int j = 0; j < STEPS; j++) {
int offset = -RAD + j * RAD;
cost = 0;
#pragma unroll
for (int i = -RAD; i <= RAD; i++) {
cost += diff[sidy + offset][sidx + i];
}
cg::sync(cta);
diff[sidy + offset][sidx] = cost;
cg::sync(cta);
}
// sum cost vertically
cost = 0;
#pragma unroll
for (int i = -RAD; i <= RAD; i++) {
cost += diff[sidy + i][sidx];
}
// see if it is better or not
if (cost < bestCost) {
bestCost = cost;
bestDisparity = d + 8;
}
cg::sync(cta);
}
if (tidy < h && tidx < w) {
g_odata[tidy * w + tidx] = bestDisparity;
}
}
void cpu_gold_stereo(unsigned int *img0, unsigned int *img1,
unsigned int *odata, int w, int h, int minDisparity,
int maxDisparity) {
for (int y = 0; y < h; y++) {
for (int x = 0; x < w; x++) {
unsigned int bestCost = 9999999;
unsigned int bestDisparity = 0;
for (int d = minDisparity; d <= maxDisparity; d++) {
unsigned int cost = 0;
for (int i = -RAD; i <= RAD; i++) {
for (int j = -RAD; j <= RAD; j++) {
// border clamping
int yy, xx, xxd;
yy = y + i;
if (yy < 0) yy = 0;
if (yy >= h) yy = h - 1;
xx = x + j;
if (xx < 0) xx = 0;
if (xx >= w) xx = w - 1;
xxd = x + j + d;
if (xxd < 0) xxd = 0;
if (xxd >= w) xxd = w - 1;
// sum abs diff across components
unsigned char *A = (unsigned char *)&img0[yy * w + xx];
unsigned char *B = (unsigned char *)&img1[yy * w + xxd];
unsigned int absdiff = 0;
for (int k = 0; k < 4; k++) {
absdiff += abs((int)(A[k] - B[k]));
}
cost += absdiff;
}
}
if (cost < bestCost) {
bestCost = cost;
bestDisparity = d + 8;
}
} // end for disparities
// store to best disparity
odata[y * w + x] = bestDisparity;
}
}
}
#endif // #ifndef _STEREODISPARITY_KERNEL_H_

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<None Include="stereoDisparity_kernel.cuh" />
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<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.5.targets" />
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