Add and update samples for cuda 10.2 support

This commit is contained in:
Mahesh Doijade
2019-10-23 19:00:39 +05:30
parent 489d9f7b1f
commit 6be514679b
305 changed files with 78239 additions and 518 deletions

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@@ -30,7 +30,7 @@ cuDeviceGet, cuDeviceGetAttribute, cuDeviceComputeCapability, cuDeviceGetCount,
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

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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 $(TARGET_ARCH),x86_64 aarch64 ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 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 ?= $(QNX_HOST)/usr/bin/aarch64-unknown-nto-qnx7.0.0-g++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
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)/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
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
endif
ifeq ($(TARGET_OS),qnx)
CCFLAGS += -DWIN_INTERFACE_CUSTOM
LDFLAGS += -lsocket
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),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))
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
SMS ?=
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_$(sm)))
ifeq ($(SMS),)
# Generate PTX code from SM 30
GENCODE_FLAGS += -gencode arch=compute_30,code=compute_30
endif
# 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
LIBRARIES += -lcurand_static -lculibos
################################################################################
# Target rules
all: build
build: MersenneTwisterGP11213
MersenneTwister.o:MersenneTwister.cpp
$(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
MersenneTwisterGP11213: MersenneTwister.o
$(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
mkdir -p ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
cp $@ ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
./MersenneTwisterGP11213
clean:
rm -f MersenneTwisterGP11213 MersenneTwister.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/MersenneTwisterGP11213
clobber: clean

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@@ -0,0 +1,184 @@
/* 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.
*/
/*
* This sample demonstrates the use of CURAND to generate
* random numbers on GPU and CPU.
*/
// Utilities and system includes
// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <curand.h>
// Utilities and system includes
#include <helper_functions.h>
#include <helper_cuda.h>
#include <cuda_runtime.h>
#include <curand.h>
float compareResults(int rand_n, float *h_RandGPU, float *h_RandCPU);
const int DEFAULT_RAND_N = 2400000;
const unsigned int DEFAULT_SEED = 777;
///////////////////////////////////////////////////////////////////////////////
// Main program
///////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv)
{
// Start logs
printf("%s Starting...\n\n", argv[0]);
// initialize the GPU, either identified by --device
// or by picking the device with highest flop rate.
int devID = findCudaDevice(argc, (const char **)argv);
// parsing the number of random numbers to generate
int rand_n = DEFAULT_RAND_N;
if (checkCmdLineFlag(argc, (const char **) argv, "count"))
{
rand_n = getCmdLineArgumentInt(argc, (const char **) argv, "count");
}
printf("Allocating data for %i samples...\n", rand_n);
// parsing the seed
int seed = DEFAULT_SEED;
if (checkCmdLineFlag(argc, (const char **) argv, "seed"))
{
seed = getCmdLineArgumentInt(argc, (const char **) argv, "seed");
}
printf("Seeding with %i ...\n", seed);
cudaStream_t stream;
checkCudaErrors(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
float *d_Rand;
checkCudaErrors(cudaMalloc((void **)&d_Rand, rand_n * sizeof(float)));
curandGenerator_t prngGPU;
checkCudaErrors(curandCreateGenerator(&prngGPU, CURAND_RNG_PSEUDO_MTGP32));
checkCudaErrors(curandSetStream(prngGPU, stream));
checkCudaErrors(curandSetPseudoRandomGeneratorSeed(prngGPU, seed));
curandGenerator_t prngCPU;
checkCudaErrors(curandCreateGeneratorHost(&prngCPU, CURAND_RNG_PSEUDO_MTGP32));
checkCudaErrors(curandSetPseudoRandomGeneratorSeed(prngCPU, seed));
//
// Example 1: Compare random numbers generated on GPU and CPU
float *h_RandGPU = (float *)malloc(rand_n * sizeof(float));
printf("Generating random numbers on GPU...\n\n");
checkCudaErrors(curandGenerateUniform(prngGPU, (float *) d_Rand, rand_n));
printf("\nReading back the results...\n");
checkCudaErrors(cudaMemcpyAsync(h_RandGPU, d_Rand, rand_n * sizeof(float), cudaMemcpyDeviceToHost, stream));
float *h_RandCPU = (float *)malloc(rand_n * sizeof(float));
printf("Generating random numbers on CPU...\n\n");
checkCudaErrors(curandGenerateUniform(prngCPU, (float *) h_RandCPU, rand_n));
checkCudaErrors(cudaStreamSynchronize(stream));
printf("Comparing CPU/GPU random numbers...\n\n");
float L1norm = compareResults(rand_n, h_RandGPU, h_RandCPU);
//
// Example 2: Timing of random number generation on GPU
const int numIterations = 10;
int i;
StopWatchInterface *hTimer;
sdkCreateTimer(&hTimer);
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
for (i = 0; i < numIterations; i++)
{
checkCudaErrors(curandGenerateUniform(prngGPU, (float *) d_Rand, rand_n));
}
checkCudaErrors(cudaStreamSynchronize(stream));
sdkStopTimer(&hTimer);
double gpuTime = 1.0e-3 * sdkGetTimerValue(&hTimer)/(double)numIterations;
printf("MersenneTwisterGP11213, Throughput = %.4f GNumbers/s, Time = %.5f s, Size = %u Numbers\n",
1.0e-9 * rand_n / gpuTime, gpuTime, rand_n);
printf("Shutting down...\n");
checkCudaErrors(curandDestroyGenerator(prngGPU));
checkCudaErrors(curandDestroyGenerator(prngCPU));
checkCudaErrors(cudaStreamDestroy(stream));
checkCudaErrors(cudaFree(d_Rand));
sdkDeleteTimer(&hTimer);
free(h_RandGPU);
free(h_RandCPU);
exit(L1norm < 1e-6 ? EXIT_SUCCESS : EXIT_FAILURE);
}
float compareResults(int rand_n, float *h_RandGPU, float *h_RandCPU)
{
int i;
float rCPU, rGPU, delta;
float max_delta = 0.;
float sum_delta = 0.;
float sum_ref = 0.;
for (i = 0; i < rand_n; i++)
{
rCPU = h_RandCPU[i];
rGPU = h_RandGPU[i];
delta = fabs(rCPU - rGPU);
sum_delta += delta;
sum_ref += fabs(rCPU);
if (delta >= max_delta)
{
max_delta = delta;
}
}
float L1norm = (float)(sum_delta / sum_ref);
printf("Max absolute error: %E\n", max_delta);
printf("L1 norm: %E\n\n", L1norm);
return L1norm;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2012
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "MersenneTwisterGP11213", "MersenneTwisterGP11213_vs2012.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>MersenneTwisterGP11213_vs2012</RootNamespace>
<ProjectName>MersenneTwisterGP11213</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v110</PlatformToolset>
</PropertyGroup>
<PropertyGroup Condition="'$(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="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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>curand.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)/MersenneTwisterGP11213.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_30,compute_30;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</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>
<ClCompile Include="MersenneTwister.cpp" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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

Microsoft Visual Studio Solution File, Format Version 13.00
# Visual Studio 2013
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "MersenneTwisterGP11213", "MersenneTwisterGP11213_vs2013.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 +1,107 @@
<?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>MersenneTwisterGP11213_vs2013</RootNamespace>
<ProjectName>MersenneTwisterGP11213</ProjectName>
<CudaToolkitCustomDir />
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
<PropertyGroup>
<ConfigurationType>Application</ConfigurationType>
<CharacterSet>MultiByte</CharacterSet>
<PlatformToolset>v120</PlatformToolset>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Debug'">
<UseDebugLibraries>true</UseDebugLibraries>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)'=='Release'">
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<keywords>
<keyword>CUDA</keyword>
<keyword>CURAND</keyword>
<keyword>Monte-Carlo</keyword>
<keyword>random number generation</keyword>
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# MersenneTwisterGP11213 - MersenneTwisterGP11213
## Description
This sample demonstrates the Mersenne Twister random number generator GP11213 in cuRAND.
## Key Concepts
CURAND Library
## Supported SM Architectures
[SM 3.0 ](https://developer.nvidia.com/cuda-gpus) [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)
## Supported OSes
Linux, Windows, MacOSX
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
## Dependencies needed to build/run
[CURAND](../../README.md#curand)
## Prerequisites
Download and install the [CUDA Toolkit 10.2](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++
```
### Mac
The Mac samples are built using makefiles. To use the makefiles, change directory into the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **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="A B ..."
```
* **HOST_COMPILER=<host_compiler>** - override the default clang host compiler. See the [Mac Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-mac-os-x/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=clang
```
## References (for more details)

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -107,6 +107,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -107,6 +107,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -107,6 +107,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -108,6 +108,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -27,7 +27,7 @@ cudaMemcpy2D, cudaMallocManaged
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

View File

@@ -30,7 +30,7 @@ cudaMallocManaged, cudaStreamAttachMemAsync, cudaMemcpyAsync, cudaMallocHost, cu
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -105,6 +105,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -105,6 +105,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -105,6 +105,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -110,6 +110,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -106,6 +106,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -27,7 +27,7 @@ cudaSetDevice, cudaHostAlloc, cudaFree, cudaMallocHost, cudaFreeHost, cudaMemcpy
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -107,6 +107,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -117,6 +117,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -113,6 +113,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -112,6 +112,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -117,6 +117,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -113,6 +113,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -30,7 +30,7 @@ cudaStreamBeginCapture, cudaStreamEndCapture, cudaGraphCreate, cudaGraphLaunch,
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
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<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -107,6 +107,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -27,7 +27,7 @@ x86_64, ppc64le
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -108,6 +108,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -104,6 +104,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -30,7 +30,7 @@ cudaMemAdvise, cudaMemPrefetchAsync, cudaLaunchCooperativeKernelMultiDevice, cud
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -103,6 +103,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -108,6 +108,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -104,6 +104,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -0,0 +1,82 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>cuSolverDn_LinearSolver</name>
<description><![CDATA[A CUDA Sample that demonstrates cuSolverDN's LU, QR and Cholesky factorization.]]></description>
<devicecompilation>whole</devicecompilation>
<files>
<file>gr_900_900_crg.mtx</file>
<file>lap3D_7pt_n20.mtx</file>
</files>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../common/inc</path>
</includepaths>
<keyconcepts>
<concept level="basic">Linear Algebra</concept>
<concept level="basic">CUSOLVER Library</concept>
</keyconcepts>
<keywords>
<keyword>CUSOLVER</keyword>
<keyword>Linear Algebra</keyword>
</keywords>
<libraries>
<library>cusolver</library>
<library>cublas</library>
<library>cusparse</library>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>cuSolverDn_LinearSolver.cpp</primary_file>
<qatests>
<qatest>-R=qr</qatest>
<qatest>-R=chol</qatest>
<qatest>-R=lu</qatest>
</qatests>
<required_dependencies>
<dependency>CUSOLVER</dependency>
<dependency>CUBLAS</dependency>
<dependency>CUSPARSE</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>3:Linear Algebra</scope>
</scopes>
<sm-arch>sm30</sm-arch>
<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>
<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>ppc64le</arch>
<platform>linux</platform>
</env>
<env>
<arch>aarch64</arch>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>cuSolverDn Linear Solver </title>
<type>exe</type>
</entry>

View File

@@ -27,7 +27,7 @@ x86_64, ppc64le, aarch64
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -104,6 +104,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -104,6 +104,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -104,6 +104,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -109,6 +109,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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@@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -105,6 +105,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -0,0 +1,316 @@
################################################################################
# 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 $(TARGET_ARCH),x86_64 aarch64 ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 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 ?= $(QNX_HOST)/usr/bin/aarch64-unknown-nto-qnx7.0.0-g++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
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)/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
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
endif
ifeq ($(TARGET_OS),qnx)
CCFLAGS += -DWIN_INTERFACE_CUSTOM
LDFLAGS += -lsocket
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),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
ifeq ($(TARGET_OS),linux)
ALL_CCFLAGS += -Xcompiler \"-Wl,--no-as-needed\"
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 :=
################################################################################
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64))
SMS ?= 30 35 37 50 52 60 61 70 72 75
else
SMS ?= 30 35 37 50 52 60 61 70 75
endif
ifeq ($(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
LIBRARIES += -lcusolver -lcusparse
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: cuSolverSp_LinearSolver
check.deps:
ifeq ($(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
cuSolverSp_LinearSolver.o:cuSolverSp_LinearSolver.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
mmio.c.o:mmio.c
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
mmio_wrapper.o:mmio_wrapper.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
cuSolverSp_LinearSolver: cuSolverSp_LinearSolver.o mmio.c.o mmio_wrapper.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
$(EXEC) ./cuSolverSp_LinearSolver
clean:
rm -f cuSolverSp_LinearSolver cuSolverSp_LinearSolver.o mmio.c.o mmio_wrapper.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/cuSolverSp_LinearSolver
clobber: clean

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@@ -0,0 +1,83 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>cuSolverSp_LinearSolver</name>
<description><![CDATA[A CUDA Sample that demonstrates cuSolverSP's LU, QR and Cholesky factorization.]]></description>
<devicecompilation>whole</devicecompilation>
<files>
<file>lap2D_5pt_n100.mtx</file>
<file>lap3D_7pt_n20.mtx</file>
</files>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../common/inc</path>
</includepaths>
<keyconcepts>
<concept level="basic">Linear Algebra</concept>
<concept level="basic">CUSOLVER Library</concept>
</keyconcepts>
<keywords>
<keyword>CUSOLVER</keyword>
<keyword>Linear Algebra</keyword>
</keywords>
<libraries>
<library>cusolver</library>
<library>cusparse</library>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>cuSolverSp_LinearSolver.cpp</primary_file>
<qatests>
<qatest>-R=qr</qatest>
<qatest>-R=chol</qatest>
<qatest>-R=lu</qatest>
<qatest>-R=qr -P=symamd</qatest>
<qatest>-R=chol -P=symamd</qatest>
<qatest>-R=lu -P=symamd</qatest>
</qatests>
<required_dependencies>
<dependency>CUSOLVER</dependency>
<dependency>CUSPARSE</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>3:Linear Algebra</scope>
</scopes>
<sm-arch>sm30</sm-arch>
<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>
<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>ppc64le</arch>
<platform>linux</platform>
</env>
<env>
<arch>arm</arch>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>cuSolverSp Linear Solver </title>
<type>exe</type>
</entry>

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# cuSolverSp_LinearSolver - cuSolverSp Linear Solver
## Description
A CUDA Sample that demonstrates cuSolverSP's LU, QR and Cholesky factorization.
## Key Concepts
Linear Algebra, CUSOLVER Library
## Supported SM Architectures
[SM 3.0 ](https://developer.nvidia.com/cuda-gpus) [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)
## Supported OSes
Linux, Windows, MacOSX
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
## Dependencies needed to build/run
[CUSOLVER](../../README.md#cusolver), [CUSPARSE](../../README.md#cusparse)
## Prerequisites
Download and install the [CUDA Toolkit 10.2](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++
```
### Mac
The Mac samples are built using makefiles. To use the makefiles, change directory into the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **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="A B ..."
```
* **HOST_COMPILER=<host_compiler>** - override the default clang host compiler. See the [Mac Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-mac-os-x/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=clang
```
## References (for more details)

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@@ -0,0 +1,654 @@
/* 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.
*/
/*
* Test three linear solvers, including Cholesky, LU and QR.
* The user has to prepare a sparse matrix of "matrix market format" (with extension .mtx).
* For example, the user can download matrices in Florida Sparse Matrix Collection.
* (http://www.cise.ufl.edu/research/sparse/matrices/)
*
* The user needs to choose a solver by the switch -R<solver> and
* to provide the path of the matrix by the switch -F<file>, then
* the program solves
* A*x = b
* and reports relative error
* |b-A*x|/(|A|*|x|+|b|)
*
* How does it work?
* The example solves A*x = b by the following steps
* step 1: B = A(Q,Q)
* Q is the ordering to minimize zero fill-in.
* The user can choose symrcm or symamd.
* step 2: solve B*z = Q*b
* step 3: x = inv(Q)*z
*
* Above three steps can be combined by the formula
* (Q*A*Q')*(Q*x) = (Q*b)
*
* The elapsed time is also reported so the user can compare efficiency of different solvers.
*
* How to use
/cuSolverSp_LinearSolver // Default: Cholesky, symrcm & file=lap2D_5pt_n100.mtx
* ./cuSolverSp_LinearSolver -R=chol -file=<file> // cholesky factorization
* ./cuSolverSp_LinearSolver -R=lu -P=symrcm -file=<file> // symrcm + LU with partial pivoting
* ./cuSolverSp_LinearSolver -R=qr -P=symamd -file=<file> // symamd + QR factorization
*
*
* Remark: the absolute error on solution x is meaningless without knowing condition number of A.
* The relative error on residual should be close to machine zero, i.e. 1.e-15.
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <ctype.h>
#include <assert.h>
#include <cuda_runtime.h>
#include "cusparse.h"
#include "cusolverSp.h"
#include "helper_cuda.h"
#include "helper_cusolver.h"
template <typename T_ELEM>
int loadMMSparseMatrix(char *filename, char elem_type, bool csrFormat, int *m,
int *n, int *nnz, T_ELEM **aVal, int **aRowInd,
int **aColInd, int extendSymMatrix);
void UsageSP(void) {
printf("<options>\n");
printf("-h : display this help\n");
printf("-R=<name> : choose a linear solver\n");
printf(" chol (cholesky factorization), this is default\n");
printf(" qr (QR factorization)\n");
printf(" lu (LU factorization)\n");
printf("-P=<name> : choose a reordering\n");
printf(" symrcm (Reverse Cuthill-McKee)\n");
printf(" symamd (Approximate Minimum Degree)\n");
printf(" metis (nested dissection)\n");
printf("-file=<filename> : filename containing a matrix in MM format\n");
printf("-device=<device_id> : <device_id> if want to run on specific GPU\n");
exit(0);
}
void parseCommandLineArguments(int argc, char *argv[], struct testOpts &opts) {
memset(&opts, 0, sizeof(opts));
if (checkCmdLineFlag(argc, (const char **)argv, "-h")) {
UsageSP();
}
if (checkCmdLineFlag(argc, (const char **)argv, "R")) {
char *solverType = NULL;
getCmdLineArgumentString(argc, (const char **)argv, "R", &solverType);
if (solverType) {
if ((STRCASECMP(solverType, "chol") != 0) &&
(STRCASECMP(solverType, "lu") != 0) &&
(STRCASECMP(solverType, "qr") != 0)) {
printf("\nIncorrect argument passed to -R option\n");
UsageSP();
} else {
opts.testFunc = solverType;
}
}
}
if (checkCmdLineFlag(argc, (const char **)argv, "P")) {
char *reorderType = NULL;
getCmdLineArgumentString(argc, (const char **)argv, "P", &reorderType);
if (reorderType) {
if ((STRCASECMP(reorderType, "symrcm") != 0) &&
(STRCASECMP(reorderType, "symamd") != 0) &&
(STRCASECMP(reorderType, "metis") != 0)) {
printf("\nIncorrect argument passed to -P option\n");
UsageSP();
} else {
opts.reorder = reorderType;
}
}
}
if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
char *fileName = 0;
getCmdLineArgumentString(argc, (const char **)argv, "file", &fileName);
if (fileName) {
opts.sparse_mat_filename = fileName;
} else {
printf("\nIncorrect filename passed to -file \n ");
UsageSP();
}
}
}
int main(int argc, char *argv[]) {
struct testOpts opts;
cusolverSpHandle_t handle = NULL;
cusparseHandle_t cusparseHandle = NULL; /* used in residual evaluation */
cudaStream_t stream = NULL;
cusparseMatDescr_t descrA = NULL;
int rowsA = 0; /* number of rows of A */
int colsA = 0; /* number of columns of A */
int nnzA = 0; /* number of nonzeros of A */
int baseA = 0; /* base index in CSR format */
/* CSR(A) from I/O */
int *h_csrRowPtrA = NULL;
int *h_csrColIndA = NULL;
double *h_csrValA = NULL;
double *h_z = NULL; /* z = B \ (Q*b) */
double *h_x = NULL; /* x = A \ b */
double *h_b = NULL; /* b = ones(n,1) */
double *h_Qb = NULL; /* Q*b */
double *h_r = NULL; /* r = b - A*x */
int *h_Q = NULL; /* <int> n */
/* reorder to reduce zero fill-in */
/* Q = symrcm(A) or Q = symamd(A) */
/* B = Q*A*Q' or B = A(Q,Q) by MATLAB notation */
int *h_csrRowPtrB = NULL; /* <int> n+1 */
int *h_csrColIndB = NULL; /* <int> nnzA */
double *h_csrValB = NULL; /* <double> nnzA */
int *h_mapBfromA = NULL; /* <int> nnzA */
size_t size_perm = 0;
void *buffer_cpu = NULL; /* working space for permutation: B = Q*A*Q^T */
/* device copy of A: used in residual evaluation */
int *d_csrRowPtrA = NULL;
int *d_csrColIndA = NULL;
double *d_csrValA = NULL;
/* device copy of B: used in B*z = Q*b */
int *d_csrRowPtrB = NULL;
int *d_csrColIndB = NULL;
double *d_csrValB = NULL;
int *d_Q = NULL; /* device copy of h_Q */
double *d_z = NULL; /* z = B \ Q*b */
double *d_x = NULL; /* x = A \ b */
double *d_b = NULL; /* a copy of h_b */
double *d_Qb = NULL; /* a copy of h_Qb */
double *d_r = NULL; /* r = b - A*x */
double tol = 1.e-12;
const int reorder = 0; /* no reordering */
int singularity = 0; /* -1 if A is invertible under tol. */
/* the constants are used in residual evaluation, r = b - A*x */
const double minus_one = -1.0;
const double one = 1.0;
double b_inf = 0.0;
double x_inf = 0.0;
double r_inf = 0.0;
double A_inf = 0.0;
int errors = 0;
int issym = 0;
double start, stop;
double time_solve_cpu;
double time_solve_gpu;
parseCommandLineArguments(argc, argv, opts);
if (NULL == opts.testFunc) {
opts.testFunc =
"chol"; /* By default running Cholesky as NO solver selected with -R
option. */
}
findCudaDevice(argc, (const char **)argv);
if (opts.sparse_mat_filename == NULL) {
opts.sparse_mat_filename = sdkFindFilePath("lap2D_5pt_n100.mtx", argv[0]);
if (opts.sparse_mat_filename != NULL)
printf("Using default input file [%s]\n", opts.sparse_mat_filename);
else
printf("Could not find lap2D_5pt_n100.mtx\n");
} else {
printf("Using input file [%s]\n", opts.sparse_mat_filename);
}
printf("step 1: read matrix market format\n");
if (opts.sparse_mat_filename == NULL) {
fprintf(stderr, "Error: input matrix is not provided\n");
return EXIT_FAILURE;
}
if (loadMMSparseMatrix<double>(opts.sparse_mat_filename, 'd', true, &rowsA,
&colsA, &nnzA, &h_csrValA, &h_csrRowPtrA,
&h_csrColIndA, true)) {
exit(EXIT_FAILURE);
}
baseA = h_csrRowPtrA[0]; // baseA = {0,1}
printf("sparse matrix A is %d x %d with %d nonzeros, base=%d\n", rowsA, colsA,
nnzA, baseA);
if (rowsA != colsA) {
fprintf(stderr, "Error: only support square matrix\n");
return 1;
}
checkCudaErrors(cusolverSpCreate(&handle));
checkCudaErrors(cusparseCreate(&cusparseHandle));
checkCudaErrors(cudaStreamCreate(&stream));
/* bind stream to cusparse and cusolver*/
checkCudaErrors(cusolverSpSetStream(handle, stream));
checkCudaErrors(cusparseSetStream(cusparseHandle, stream));
/* configure matrix descriptor*/
checkCudaErrors(cusparseCreateMatDescr(&descrA));
checkCudaErrors(cusparseSetMatType(descrA, CUSPARSE_MATRIX_TYPE_GENERAL));
if (baseA) {
checkCudaErrors(cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ONE));
} else {
checkCudaErrors(cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ZERO));
}
h_z = (double *)malloc(sizeof(double) * colsA);
h_x = (double *)malloc(sizeof(double) * colsA);
h_b = (double *)malloc(sizeof(double) * rowsA);
h_Qb = (double *)malloc(sizeof(double) * rowsA);
h_r = (double *)malloc(sizeof(double) * rowsA);
h_Q = (int *)malloc(sizeof(int) * colsA);
h_csrRowPtrB = (int *)malloc(sizeof(int) * (rowsA + 1));
h_csrColIndB = (int *)malloc(sizeof(int) * nnzA);
h_csrValB = (double *)malloc(sizeof(double) * nnzA);
h_mapBfromA = (int *)malloc(sizeof(int) * nnzA);
assert(NULL != h_z);
assert(NULL != h_x);
assert(NULL != h_b);
assert(NULL != h_Qb);
assert(NULL != h_r);
assert(NULL != h_Q);
assert(NULL != h_csrRowPtrB);
assert(NULL != h_csrColIndB);
assert(NULL != h_csrValB);
assert(NULL != h_mapBfromA);
checkCudaErrors(
cudaMalloc((void **)&d_csrRowPtrA, sizeof(int) * (rowsA + 1)));
checkCudaErrors(cudaMalloc((void **)&d_csrColIndA, sizeof(int) * nnzA));
checkCudaErrors(cudaMalloc((void **)&d_csrValA, sizeof(double) * nnzA));
checkCudaErrors(
cudaMalloc((void **)&d_csrRowPtrB, sizeof(int) * (rowsA + 1)));
checkCudaErrors(cudaMalloc((void **)&d_csrColIndB, sizeof(int) * nnzA));
checkCudaErrors(cudaMalloc((void **)&d_csrValB, sizeof(double) * nnzA));
checkCudaErrors(cudaMalloc((void **)&d_Q, sizeof(int) * colsA));
checkCudaErrors(cudaMalloc((void **)&d_z, sizeof(double) * colsA));
checkCudaErrors(cudaMalloc((void **)&d_x, sizeof(double) * colsA));
checkCudaErrors(cudaMalloc((void **)&d_b, sizeof(double) * rowsA));
checkCudaErrors(cudaMalloc((void **)&d_Qb, sizeof(double) * rowsA));
checkCudaErrors(cudaMalloc((void **)&d_r, sizeof(double) * rowsA));
/* verify if A has symmetric pattern or not */
checkCudaErrors(cusolverSpXcsrissymHost(handle, rowsA, nnzA, descrA,
h_csrRowPtrA, h_csrRowPtrA + 1,
h_csrColIndA, &issym));
if (0 == strcmp(opts.testFunc, "chol")) {
if (!issym) {
printf("Error: A has no symmetric pattern, please use LU or QR \n");
exit(EXIT_FAILURE);
}
}
printf("step 2: reorder the matrix A to minimize zero fill-in\n");
printf(
" if the user choose a reordering by -P=symrcm, -P=symamd or "
"-P=metis\n");
if (NULL != opts.reorder) {
if (0 == strcmp(opts.reorder, "symrcm")) {
printf("step 2.1: Q = symrcm(A) \n");
checkCudaErrors(cusolverSpXcsrsymrcmHost(
handle, rowsA, nnzA, descrA, h_csrRowPtrA, h_csrColIndA, h_Q));
} else if (0 == strcmp(opts.reorder, "symamd")) {
printf("step 2.1: Q = symamd(A) \n");
checkCudaErrors(cusolverSpXcsrsymamdHost(
handle, rowsA, nnzA, descrA, h_csrRowPtrA, h_csrColIndA, h_Q));
} else if (0 == strcmp(opts.reorder, "metis")) {
printf("step 2.1: Q = metis(A) \n");
checkCudaErrors(cusolverSpXcsrmetisndHost(handle, rowsA, nnzA, descrA,
h_csrRowPtrA, h_csrColIndA,
NULL, /* default setting. */
h_Q));
} else {
fprintf(stderr, "Error: %s is unknown reordering\n", opts.reorder);
return 1;
}
} else {
printf("step 2.1: no reordering is chosen, Q = 0:n-1 \n");
for (int j = 0; j < rowsA; j++) {
h_Q[j] = j;
}
}
printf("step 2.2: B = A(Q,Q) \n");
memcpy(h_csrRowPtrB, h_csrRowPtrA, sizeof(int) * (rowsA + 1));
memcpy(h_csrColIndB, h_csrColIndA, sizeof(int) * nnzA);
checkCudaErrors(cusolverSpXcsrperm_bufferSizeHost(
handle, rowsA, colsA, nnzA, descrA, h_csrRowPtrB, h_csrColIndB, h_Q, h_Q,
&size_perm));
if (buffer_cpu) {
free(buffer_cpu);
}
buffer_cpu = (void *)malloc(sizeof(char) * size_perm);
assert(NULL != buffer_cpu);
/* h_mapBfromA = Identity */
for (int j = 0; j < nnzA; j++) {
h_mapBfromA[j] = j;
}
checkCudaErrors(cusolverSpXcsrpermHost(handle, rowsA, colsA, nnzA, descrA,
h_csrRowPtrB, h_csrColIndB, h_Q, h_Q,
h_mapBfromA, buffer_cpu));
/* B = A( mapBfromA ) */
for (int j = 0; j < nnzA; j++) {
h_csrValB[j] = h_csrValA[h_mapBfromA[j]];
}
printf("step 3: b(j) = 1 + j/n \n");
for (int row = 0; row < rowsA; row++) {
h_b[row] = 1.0 + ((double)row) / ((double)rowsA);
}
/* h_Qb = b(Q) */
for (int row = 0; row < rowsA; row++) {
h_Qb[row] = h_b[h_Q[row]];
}
printf("step 4: prepare data on device\n");
checkCudaErrors(cudaMemcpyAsync(d_csrRowPtrA, h_csrRowPtrA,
sizeof(int) * (rowsA + 1),
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_csrColIndA, h_csrColIndA,
sizeof(int) * nnzA, cudaMemcpyHostToDevice,
stream));
checkCudaErrors(cudaMemcpyAsync(d_csrValA, h_csrValA, sizeof(double) * nnzA,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_csrRowPtrB, h_csrRowPtrB,
sizeof(int) * (rowsA + 1),
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_csrColIndB, h_csrColIndB,
sizeof(int) * nnzA, cudaMemcpyHostToDevice,
stream));
checkCudaErrors(cudaMemcpyAsync(d_csrValB, h_csrValB, sizeof(double) * nnzA,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_b, h_b, sizeof(double) * rowsA,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_Qb, h_Qb, sizeof(double) * rowsA,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_Q, h_Q, sizeof(int) * rowsA,
cudaMemcpyHostToDevice, stream));
printf("step 5: solve A*x = b on CPU \n");
start = second();
/* solve B*z = Q*b */
if (0 == strcmp(opts.testFunc, "chol")) {
checkCudaErrors(cusolverSpDcsrlsvcholHost(
handle, rowsA, nnzA, descrA, h_csrValB, h_csrRowPtrB, h_csrColIndB,
h_Qb, tol, reorder, h_z, &singularity));
} else if (0 == strcmp(opts.testFunc, "lu")) {
checkCudaErrors(cusolverSpDcsrlsvluHost(
handle, rowsA, nnzA, descrA, h_csrValB, h_csrRowPtrB, h_csrColIndB,
h_Qb, tol, reorder, h_z, &singularity));
} else if (0 == strcmp(opts.testFunc, "qr")) {
checkCudaErrors(cusolverSpDcsrlsvqrHost(
handle, rowsA, nnzA, descrA, h_csrValB, h_csrRowPtrB, h_csrColIndB,
h_Qb, tol, reorder, h_z, &singularity));
} else {
fprintf(stderr, "Error: %s is unknown function\n", opts.testFunc);
return 1;
}
/* Q*x = z */
for (int row = 0; row < rowsA; row++) {
h_x[h_Q[row]] = h_z[row];
}
if (0 <= singularity) {
printf("WARNING: the matrix is singular at row %d under tol (%E)\n",
singularity, tol);
}
stop = second();
time_solve_cpu = stop - start;
printf("step 6: evaluate residual r = b - A*x (result on CPU)\n");
checkCudaErrors(cudaMemcpyAsync(d_r, d_b, sizeof(double) * rowsA,
cudaMemcpyDeviceToDevice, stream));
checkCudaErrors(cudaMemcpyAsync(d_x, h_x, sizeof(double) * colsA,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cusparseDcsrmv(cusparseHandle,
CUSPARSE_OPERATION_NON_TRANSPOSE, rowsA, colsA,
nnzA, &minus_one, descrA, d_csrValA,
d_csrRowPtrA, d_csrColIndA, d_x, &one, d_r));
checkCudaErrors(cudaMemcpyAsync(h_r, d_r, sizeof(double) * rowsA,
cudaMemcpyDeviceToHost, stream));
/* wait until h_r is ready */
checkCudaErrors(cudaDeviceSynchronize());
b_inf = vec_norminf(rowsA, h_b);
x_inf = vec_norminf(colsA, h_x);
r_inf = vec_norminf(rowsA, h_r);
A_inf = csr_mat_norminf(rowsA, colsA, nnzA, descrA, h_csrValA, h_csrRowPtrA,
h_csrColIndA);
printf("(CPU) |b - A*x| = %E \n", r_inf);
printf("(CPU) |A| = %E \n", A_inf);
printf("(CPU) |x| = %E \n", x_inf);
printf("(CPU) |b| = %E \n", b_inf);
printf("(CPU) |b - A*x|/(|A|*|x| + |b|) = %E \n",
r_inf / (A_inf * x_inf + b_inf));
printf("step 7: solve A*x = b on GPU\n");
start = second();
/* solve B*z = Q*b */
if (0 == strcmp(opts.testFunc, "chol")) {
checkCudaErrors(cusolverSpDcsrlsvchol(
handle, rowsA, nnzA, descrA, d_csrValB, d_csrRowPtrB, d_csrColIndB,
d_Qb, tol, reorder, d_z, &singularity));
} else if (0 == strcmp(opts.testFunc, "lu")) {
printf("WARNING: no LU available on GPU \n");
} else if (0 == strcmp(opts.testFunc, "qr")) {
checkCudaErrors(cusolverSpDcsrlsvqr(handle, rowsA, nnzA, descrA, d_csrValB,
d_csrRowPtrB, d_csrColIndB, d_Qb, tol,
reorder, d_z, &singularity));
} else {
fprintf(stderr, "Error: %s is unknow function\n", opts.testFunc);
return 1;
}
checkCudaErrors(cudaDeviceSynchronize());
if (0 <= singularity) {
printf("WARNING: the matrix is singular at row %d under tol (%E)\n",
singularity, tol);
}
/* Q*x = z */
checkCudaErrors(cusparseDsctr(cusparseHandle, rowsA, d_z, d_Q, d_x,
CUSPARSE_INDEX_BASE_ZERO));
checkCudaErrors(cudaDeviceSynchronize());
stop = second();
time_solve_gpu = stop - start;
printf("step 8: evaluate residual r = b - A*x (result on GPU)\n");
checkCudaErrors(cudaMemcpyAsync(d_r, d_b, sizeof(double) * rowsA,
cudaMemcpyDeviceToDevice, stream));
checkCudaErrors(cusparseDcsrmv(cusparseHandle,
CUSPARSE_OPERATION_NON_TRANSPOSE, rowsA, colsA,
nnzA, &minus_one, descrA, d_csrValA,
d_csrRowPtrA, d_csrColIndA, d_x, &one, d_r));
checkCudaErrors(cudaMemcpyAsync(h_x, d_x, sizeof(double) * colsA,
cudaMemcpyDeviceToHost, stream));
checkCudaErrors(cudaMemcpyAsync(h_r, d_r, sizeof(double) * rowsA,
cudaMemcpyDeviceToHost, stream));
/* wait until h_x and h_r are ready */
checkCudaErrors(cudaDeviceSynchronize());
b_inf = vec_norminf(rowsA, h_b);
x_inf = vec_norminf(colsA, h_x);
r_inf = vec_norminf(rowsA, h_r);
if (0 != strcmp(opts.testFunc, "lu")) {
// only cholesky and qr have GPU version
printf("(GPU) |b - A*x| = %E \n", r_inf);
printf("(GPU) |A| = %E \n", A_inf);
printf("(GPU) |x| = %E \n", x_inf);
printf("(GPU) |b| = %E \n", b_inf);
printf("(GPU) |b - A*x|/(|A|*|x| + |b|) = %E \n",
r_inf / (A_inf * x_inf + b_inf));
}
fprintf(stdout, "timing %s: CPU = %10.6f sec , GPU = %10.6f sec\n",
opts.testFunc, time_solve_cpu, time_solve_gpu);
if (0 != strcmp(opts.testFunc, "lu")) {
printf("show last 10 elements of solution vector (GPU) \n");
printf("consistent result for different reordering and solver \n");
for (int j = rowsA - 10; j < rowsA; j++) {
printf("x[%d] = %E\n", j, h_x[j]);
}
}
if (handle) {
checkCudaErrors(cusolverSpDestroy(handle));
}
if (cusparseHandle) {
checkCudaErrors(cusparseDestroy(cusparseHandle));
}
if (stream) {
checkCudaErrors(cudaStreamDestroy(stream));
}
if (descrA) {
checkCudaErrors(cusparseDestroyMatDescr(descrA));
}
if (h_csrValA) {
free(h_csrValA);
}
if (h_csrRowPtrA) {
free(h_csrRowPtrA);
}
if (h_csrColIndA) {
free(h_csrColIndA);
}
if (h_z) {
free(h_z);
}
if (h_x) {
free(h_x);
}
if (h_b) {
free(h_b);
}
if (h_Qb) {
free(h_Qb);
}
if (h_r) {
free(h_r);
}
if (h_Q) {
free(h_Q);
}
if (h_csrRowPtrB) {
free(h_csrRowPtrB);
}
if (h_csrColIndB) {
free(h_csrColIndB);
}
if (h_csrValB) {
free(h_csrValB);
}
if (h_mapBfromA) {
free(h_mapBfromA);
}
if (buffer_cpu) {
free(buffer_cpu);
}
if (d_csrValA) {
checkCudaErrors(cudaFree(d_csrValA));
}
if (d_csrRowPtrA) {
checkCudaErrors(cudaFree(d_csrRowPtrA));
}
if (d_csrColIndA) {
checkCudaErrors(cudaFree(d_csrColIndA));
}
if (d_csrValB) {
checkCudaErrors(cudaFree(d_csrValB));
}
if (d_csrRowPtrB) {
checkCudaErrors(cudaFree(d_csrRowPtrB));
}
if (d_csrColIndB) {
checkCudaErrors(cudaFree(d_csrColIndB));
}
if (d_Q) {
checkCudaErrors(cudaFree(d_Q));
}
if (d_z) {
checkCudaErrors(cudaFree(d_z));
}
if (d_x) {
checkCudaErrors(cudaFree(d_x));
}
if (d_b) {
checkCudaErrors(cudaFree(d_b));
}
if (d_Qb) {
checkCudaErrors(cudaFree(d_Qb));
}
if (d_r) {
checkCudaErrors(cudaFree(d_r));
}
return 0;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
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Microsoft Visual Studio Solution File, Format Version 13.00
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View File

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

Microsoft Visual Studio Solution File, Format Version 14.00
# Visual Studio 2015
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "cuSolverSp_LinearSolver", "cuSolverSp_LinearSolver_vs2015.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
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{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
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GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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@@ -0,0 +1,109 @@
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/*
* Matrix Market I/O library for ANSI C
*
* See http://math.nist.gov/MatrixMarket for details.
*
*
*/
/* avoid Windows warnings (for example: strcpy, fscanf, etc.) */
#if defined(_WIN32)
#define _CRT_SECURE_NO_WARNINGS
#endif
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <ctype.h>
#include "mmio.h"
int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_,
double **val_, int **I_, int **J_)
{
FILE *f;
MM_typecode matcode;
int M, N, nz;
int i;
double *val;
int *I, *J;
if ((f = fopen(fname, "r")) == NULL)
return -1;
if (mm_read_banner(f, &matcode) != 0)
{
printf("mm_read_unsymetric: Could not process Matrix Market banner ");
printf(" in file [%s]\n", fname);
return -1;
}
if ( !(mm_is_real(matcode) && mm_is_matrix(matcode) &&
mm_is_sparse(matcode)))
{
fprintf(stderr, "Sorry, this application does not support ");
fprintf(stderr, "Market Market type: [%s]\n",
mm_typecode_to_str(matcode));
return -1;
}
/* find out size of sparse matrix: M, N, nz .... */
if (mm_read_mtx_crd_size(f, &M, &N, &nz) !=0)
{
fprintf(stderr, "read_unsymmetric_sparse(): could not parse matrix size.\n");
return -1;
}
*M_ = M;
*N_ = N;
*nz_ = nz;
/* reserve memory for matrices */
I = (int *) malloc(nz * sizeof(int));
J = (int *) malloc(nz * sizeof(int));
val = (double *) malloc(nz * sizeof(double));
*val_ = val;
*I_ = I;
*J_ = J;
/* NOTE: when reading in doubles, ANSI C requires the use of the "l" */
/* specifier as in "%lg", "%lf", "%le", otherwise errors will occur */
/* (ANSI C X3.159-1989, Sec. 4.9.6.2, p. 136 lines 13-15) */
for (i=0; i<nz; i++)
{
if (fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i]) != 3) {
return -1;
}
I[i]--; /* adjust from 1-based to 0-based */
J[i]--;
}
fclose(f);
return 0;
}
int mm_is_valid(MM_typecode matcode)
{
if (!mm_is_matrix(matcode)) return 0;
if (mm_is_dense(matcode) && mm_is_pattern(matcode)) return 0;
if (mm_is_real(matcode) && mm_is_hermitian(matcode)) return 0;
if (mm_is_pattern(matcode) && (mm_is_hermitian(matcode) ||
mm_is_skew(matcode))) return 0;
return 1;
}
int mm_read_banner(FILE *f, MM_typecode *matcode)
{
char line[MM_MAX_LINE_LENGTH];
char banner[MM_MAX_TOKEN_LENGTH];
char mtx[MM_MAX_TOKEN_LENGTH];
char crd[MM_MAX_TOKEN_LENGTH];
char data_type[MM_MAX_TOKEN_LENGTH];
char storage_scheme[MM_MAX_TOKEN_LENGTH];
char *p;
mm_clear_typecode(matcode);
if (fgets(line, MM_MAX_LINE_LENGTH, f) == NULL)
return MM_PREMATURE_EOF;
if (sscanf(line, "%s %s %s %s %s", banner, mtx, crd, data_type,
storage_scheme) != 5)
return MM_PREMATURE_EOF;
for (p=mtx; *p!='\0'; *p=tolower(*p),p++); /* convert to lower case */
for (p=crd; *p!='\0'; *p=tolower(*p),p++);
for (p=data_type; *p!='\0'; *p=tolower(*p),p++);
for (p=storage_scheme; *p!='\0'; *p=tolower(*p),p++);
/* check for banner */
if (strncmp(banner, MatrixMarketBanner, strlen(MatrixMarketBanner)) != 0)
return MM_NO_HEADER;
/* first field should be "mtx" */
if (strcmp(mtx, MM_MTX_STR) != 0)
return MM_UNSUPPORTED_TYPE;
mm_set_matrix(matcode);
/* second field describes whether this is a sparse matrix (in coordinate
storage) or a dense array */
if (strcmp(crd, MM_SPARSE_STR) == 0)
mm_set_sparse(matcode);
else
if (strcmp(crd, MM_DENSE_STR) == 0)
mm_set_dense(matcode);
else
return MM_UNSUPPORTED_TYPE;
/* third field */
if (strcmp(data_type, MM_REAL_STR) == 0)
mm_set_real(matcode);
else
if (strcmp(data_type, MM_COMPLEX_STR) == 0)
mm_set_complex(matcode);
else
if (strcmp(data_type, MM_PATTERN_STR) == 0)
mm_set_pattern(matcode);
else
if (strcmp(data_type, MM_INT_STR) == 0)
mm_set_integer(matcode);
else
return MM_UNSUPPORTED_TYPE;
/* fourth field */
if (strcmp(storage_scheme, MM_GENERAL_STR) == 0)
mm_set_general(matcode);
else
if (strcmp(storage_scheme, MM_SYMM_STR) == 0)
mm_set_symmetric(matcode);
else
if (strcmp(storage_scheme, MM_HERM_STR) == 0)
mm_set_hermitian(matcode);
else
if (strcmp(storage_scheme, MM_SKEW_STR) == 0)
mm_set_skew(matcode);
else
return MM_UNSUPPORTED_TYPE;
return 0;
}
int mm_write_mtx_crd_size(FILE *f, int M, int N, int nz)
{
if (fprintf(f, "%d %d %d\n", M, N, nz) != 3)
return MM_COULD_NOT_WRITE_FILE;
else
return 0;
}
int mm_read_mtx_crd_size(FILE *f, int *M, int *N, int *nz )
{
char line[MM_MAX_LINE_LENGTH];
int num_items_read;
/* set return null parameter values, in case we exit with errors */
*M = *N = *nz = 0;
/* now continue scanning until you reach the end-of-comments */
do
{
if (fgets(line,MM_MAX_LINE_LENGTH,f) == NULL)
return MM_PREMATURE_EOF;
}while (line[0] == '%');
/* line[] is either blank or has M,N, nz */
if (sscanf(line, "%d %d %d", M, N, nz) == 3)
return 0;
else
do
{
num_items_read = fscanf(f, "%d %d %d", M, N, nz);
if (num_items_read == EOF) return MM_PREMATURE_EOF;
}
while (num_items_read != 3);
return 0;
}
int mm_read_mtx_array_size(FILE *f, int *M, int *N)
{
char line[MM_MAX_LINE_LENGTH];
int num_items_read;
/* set return null parameter values, in case we exit with errors */
*M = *N = 0;
/* now continue scanning until you reach the end-of-comments */
do
{
if (fgets(line,MM_MAX_LINE_LENGTH,f) == NULL)
return MM_PREMATURE_EOF;
}while (line[0] == '%');
/* line[] is either blank or has M,N, nz */
if (sscanf(line, "%d %d", M, N) == 2)
return 0;
else /* we have a blank line */
do
{
num_items_read = fscanf(f, "%d %d", M, N);
if (num_items_read == EOF) return MM_PREMATURE_EOF;
}
while (num_items_read != 2);
return 0;
}
int mm_write_mtx_array_size(FILE *f, int M, int N)
{
if (fprintf(f, "%d %d\n", M, N) != 2)
return MM_COULD_NOT_WRITE_FILE;
else
return 0;
}
/*-------------------------------------------------------------------------*/
/******************************************************************/
/* use when I[], J[], and val[]J, and val[] are already allocated */
/******************************************************************/
int mm_read_mtx_crd_data(FILE *f, int M, int N, int nz, int I[], int J[],
double val[], MM_typecode matcode)
{
int i;
if (mm_is_complex(matcode))
{
for (i=0; i<nz; i++)
if (fscanf(f, "%d %d %lg %lg", &I[i], &J[i], &val[2*i], &val[2*i+1])
!= 4) return MM_PREMATURE_EOF;
}
else if (mm_is_real(matcode) || mm_is_integer(matcode))
{
for (i=0; i<nz; i++)
{
if (fscanf(f, "%d %d %lg\n", &I[i], &J[i], &val[i])
!= 3) return MM_PREMATURE_EOF;
}
}
else if (mm_is_pattern(matcode))
{
for (i=0; i<nz; i++)
if (fscanf(f, "%d %d", &I[i], &J[i])
!= 2) return MM_PREMATURE_EOF;
}
else
return MM_UNSUPPORTED_TYPE;
return 0;
}
int mm_read_mtx_crd_entry(FILE *f, int *I, int *J,
double *real, double *imag, MM_typecode matcode)
{
if (mm_is_complex(matcode))
{
if (fscanf(f, "%d %d %lg %lg", I, J, real, imag)
!= 4) return MM_PREMATURE_EOF;
}
else if (mm_is_real(matcode) || mm_is_integer(matcode))
{
if (fscanf(f, "%d %d %lg\n", I, J, real)
!= 3) return MM_PREMATURE_EOF;
}
else if (mm_is_pattern(matcode))
{
if (fscanf(f, "%d %d", I, J) != 2) return MM_PREMATURE_EOF;
}
else
return MM_UNSUPPORTED_TYPE;
return 0;
}
/************************************************************************
mm_read_mtx_crd() fills M, N, nz, array of values, and return
type code, e.g. 'MCRS'
if matrix is complex, values[] is of size 2*nz,
(nz pairs of real/imaginary values)
************************************************************************/
int mm_read_mtx_crd(char *fname, int *M, int *N, int *nz, int **I, int **J,
double **val, MM_typecode *matcode)
{
int ret_code;
FILE *f;
if (strcmp(fname, "stdin") == 0) f=stdin;
else
if ((f = fopen(fname, "r")) == NULL)
return MM_COULD_NOT_READ_FILE;
if ((ret_code = mm_read_banner(f, matcode)) != 0)
return ret_code;
if (!(mm_is_valid(*matcode) && mm_is_sparse(*matcode) &&
mm_is_matrix(*matcode)))
return MM_UNSUPPORTED_TYPE;
if ((ret_code = mm_read_mtx_crd_size(f, M, N, nz)) != 0)
return ret_code;
*I = (int *) malloc(*nz * sizeof(int));
*J = (int *) malloc(*nz * sizeof(int));
*val = NULL;
if (mm_is_complex(*matcode))
{
*val = (double *) malloc(*nz * 2 * sizeof(double));
ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
*matcode);
if (ret_code != 0) return ret_code;
}
else if (mm_is_real(*matcode) || mm_is_integer(*matcode))
{
*val = (double *) malloc(*nz * sizeof(double));
ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
*matcode);
if (ret_code != 0) return ret_code;
}
else if (mm_is_pattern(*matcode))
{
ret_code = mm_read_mtx_crd_data(f, *M, *N, *nz, *I, *J, *val,
*matcode);
if (ret_code != 0) return ret_code;
}
if (f != stdin) fclose(f);
return 0;
}
int mm_write_banner(FILE *f, MM_typecode matcode)
{
char *str = mm_typecode_to_str(matcode);
int ret_code;
ret_code = fprintf(f, "%s %s\n", MatrixMarketBanner, str);
free(str);
if (ret_code !=2 )
return MM_COULD_NOT_WRITE_FILE;
else
return 0;
}
int mm_write_mtx_crd(char fname[], int M, int N, int nz, int I[], int J[],
double val[], MM_typecode matcode)
{
FILE *f;
int i;
if (strcmp(fname, "stdout") == 0)
f = stdout;
else
if ((f = fopen(fname, "w")) == NULL)
return MM_COULD_NOT_WRITE_FILE;
/* print banner followed by typecode */
fprintf(f, "%s ", MatrixMarketBanner);
fprintf(f, "%s\n", mm_typecode_to_str(matcode));
/* print matrix sizes and nonzeros */
fprintf(f, "%d %d %d\n", M, N, nz);
/* print values */
if (mm_is_pattern(matcode))
for (i=0; i<nz; i++)
fprintf(f, "%d %d\n", I[i], J[i]);
else
if (mm_is_integer(matcode))
for (i=0; i<nz; i++)
fprintf(f, "%d %d %d\n", I[i], J[i], (int)val[i]);
else
if (mm_is_real(matcode))
for (i=0; i<nz; i++)
fprintf(f, "%d %d %20.16g\n", I[i], J[i], val[i]);
else
if (mm_is_complex(matcode))
for (i=0; i<nz; i++)
fprintf(f, "%d %d %20.16g %20.16g\n", I[i], J[i], val[2*i],
val[2*i+1]);
else
{
if (f != stdout) fclose(f);
return MM_UNSUPPORTED_TYPE;
}
if (f !=stdout) fclose(f);
return 0;
}
/**
* Create a new copy of a string s. mm_strdup() is a common routine, but
* not part of ANSI C, so it is included here. Used by mm_typecode_to_str().
*
*/
static char *mm_strdup(const char *s)
{
size_t len = strlen(s);
char *s2 = (char *) malloc((len+1)*sizeof(char));
return strcpy(s2, s);
}
char *mm_typecode_to_str(MM_typecode matcode)
{
char buffer[MM_MAX_LINE_LENGTH];
char *types[4];
//char *mm_strdup(const char *);
//int error =0;
/* check for MTX type */
if (mm_is_matrix(matcode))
types[0] = MM_MTX_STR;
else
return NULL; // error=1;
/* check for CRD or ARR matrix */
if (mm_is_sparse(matcode))
types[1] = MM_SPARSE_STR;
else
if (mm_is_dense(matcode))
types[1] = MM_DENSE_STR;
else
return NULL;
/* check for element data type */
if (mm_is_real(matcode))
types[2] = MM_REAL_STR;
else
if (mm_is_complex(matcode))
types[2] = MM_COMPLEX_STR;
else
if (mm_is_pattern(matcode))
types[2] = MM_PATTERN_STR;
else
if (mm_is_integer(matcode))
types[2] = MM_INT_STR;
else
return NULL;
/* check for symmetry type */
if (mm_is_general(matcode))
types[3] = MM_GENERAL_STR;
else
if (mm_is_symmetric(matcode))
types[3] = MM_SYMM_STR;
else
if (mm_is_hermitian(matcode))
types[3] = MM_HERM_STR;
else
if (mm_is_skew(matcode))
types[3] = MM_SKEW_STR;
else
return NULL;
sprintf(buffer,"%s %s %s %s", types[0], types[1], types[2], types[3]);
return mm_strdup(buffer);
}

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@@ -0,0 +1,141 @@
/*
* Matrix Market I/O library for ANSI C
*
* See http://math.nist.gov/MatrixMarket for details.
*
*
*/
#ifndef MM_IO_H
#define MM_IO_H
#if defined(__cplusplus)
extern "C" {
#endif /* __cplusplus */
#define MM_MAX_LINE_LENGTH 1025
#define MatrixMarketBanner "%%MatrixMarket"
#define MM_MAX_TOKEN_LENGTH 64
typedef char MM_typecode[4];
char *mm_typecode_to_str(MM_typecode matcode);
int mm_read_banner(FILE *f, MM_typecode *matcode);
int mm_read_mtx_crd_size(FILE *f, int *M, int *N, int *nz);
int mm_read_mtx_array_size(FILE *f, int *M, int *N);
int mm_write_banner(FILE *f, MM_typecode matcode);
int mm_write_mtx_crd_size(FILE *f, int M, int N, int nz);
int mm_write_mtx_array_size(FILE *f, int M, int N);
/********************* MM_typecode query fucntions ***************************/
#define mm_is_matrix(typecode) ((typecode)[0]=='M')
#define mm_is_sparse(typecode) ((typecode)[1]=='C')
#define mm_is_coordinate(typecode)((typecode)[1]=='C')
#define mm_is_dense(typecode) ((typecode)[1]=='A')
#define mm_is_array(typecode) ((typecode)[1]=='A')
#define mm_is_complex(typecode) ((typecode)[2]=='C')
#define mm_is_real(typecode) ((typecode)[2]=='R')
#define mm_is_pattern(typecode) ((typecode)[2]=='P')
#define mm_is_integer(typecode) ((typecode)[2]=='I')
#define mm_is_symmetric(typecode)((typecode)[3]=='S')
#define mm_is_general(typecode) ((typecode)[3]=='G')
#define mm_is_skew(typecode) ((typecode)[3]=='K')
#define mm_is_hermitian(typecode)((typecode)[3]=='H')
int mm_is_valid(MM_typecode matcode); /* too complex for a macro */
/********************* MM_typecode modify fucntions ***************************/
#define mm_set_matrix(typecode) ((*typecode)[0]='M')
#define mm_set_coordinate(typecode) ((*typecode)[1]='C')
#define mm_set_array(typecode) ((*typecode)[1]='A')
#define mm_set_dense(typecode) mm_set_array(typecode)
#define mm_set_sparse(typecode) mm_set_coordinate(typecode)
#define mm_set_complex(typecode)((*typecode)[2]='C')
#define mm_set_real(typecode) ((*typecode)[2]='R')
#define mm_set_pattern(typecode)((*typecode)[2]='P')
#define mm_set_integer(typecode)((*typecode)[2]='I')
#define mm_set_symmetric(typecode)((*typecode)[3]='S')
#define mm_set_general(typecode)((*typecode)[3]='G')
#define mm_set_skew(typecode) ((*typecode)[3]='K')
#define mm_set_hermitian(typecode)((*typecode)[3]='H')
#define mm_clear_typecode(typecode) ((*typecode)[0]=(*typecode)[1]= \
(*typecode)[2]=' ',(*typecode)[3]='G')
#define mm_initialize_typecode(typecode) mm_clear_typecode(typecode)
/********************* Matrix Market error codes ***************************/
#define MM_COULD_NOT_READ_FILE 11
#define MM_PREMATURE_EOF 12
#define MM_NOT_MTX 13
#define MM_NO_HEADER 14
#define MM_UNSUPPORTED_TYPE 15
#define MM_LINE_TOO_LONG 16
#define MM_COULD_NOT_WRITE_FILE 17
/******************** Matrix Market internal definitions ********************
MM_matrix_typecode: 4-character sequence
ojbect sparse/ data storage
dense type scheme
string position: [0] [1] [2] [3]
Matrix typecode: M(atrix) C(oord) R(eal) G(eneral)
A(array) C(omplex) H(ermitian)
P(attern) S(ymmetric)
I(nteger) K(kew)
***********************************************************************/
#define MM_MTX_STR "matrix"
#define MM_ARRAY_STR "array"
#define MM_DENSE_STR "array"
#define MM_COORDINATE_STR "coordinate"
#define MM_SPARSE_STR "coordinate"
#define MM_COMPLEX_STR "complex"
#define MM_REAL_STR "real"
#define MM_INT_STR "integer"
#define MM_GENERAL_STR "general"
#define MM_SYMM_STR "symmetric"
#define MM_HERM_STR "hermitian"
#define MM_SKEW_STR "skew-symmetric"
#define MM_PATTERN_STR "pattern"
/* high level routines */
int mm_read_mtx_crd(char *fname, int *M, int *N, int *nz, int **I, int **J,
double **val, MM_typecode *matcode);
int mm_write_mtx_crd(char fname[], int M, int N, int nz, int I[], int J[],
double val[], MM_typecode matcode);
int mm_read_mtx_crd_data(FILE *f, int M, int N, int nz, int I[], int J[],
double val[], MM_typecode matcode);
int mm_read_mtx_crd_entry(FILE *f, int *I, int *J, double *real, double *img,
MM_typecode matcode);
int mm_read_unsymmetric_sparse(const char *fname, int *M_, int *N_, int *nz_,
double **val_, int **I_, int **J_);
#if defined(__cplusplus)
}
#endif /* __cplusplus */
#endif

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@@ -0,0 +1,529 @@
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "mmio.h"
#include <cusolverDn.h>
/* avoid Windows warnings (for example: strcpy, fscanf, etc.) */
#if defined(_WIN32)
#define _CRT_SECURE_NO_WARNINGS
#endif
/* various __inline__ __device__ function to initialize a T_ELEM */
template <typename T_ELEM> __inline__ T_ELEM cuGet (int );
template <> __inline__ float cuGet<float >(int x)
{
return float(x);
}
template <> __inline__ double cuGet<double>(int x)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(int x)
{
return (make_cuComplex( float(x), 0.0f ));
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(int x)
{
return (make_cuDoubleComplex( double(x), 0.0 ));
}
template <typename T_ELEM> __inline__ T_ELEM cuGet (int , int );
template <> __inline__ float cuGet<float >(int x, int y)
{
return float(x);
}
template <> __inline__ double cuGet<double>(int x, int y)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(int x, int y)
{
return make_cuComplex( float(x), float(y) );
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(int x, int y)
{
return (make_cuDoubleComplex( double(x), double(y) ));
}
template <typename T_ELEM> __inline__ T_ELEM cuGet (float );
template <> __inline__ float cuGet<float >(float x)
{
return float(x);
}
template <> __inline__ double cuGet<double>(float x)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(float x)
{
return (make_cuComplex( float(x), 0.0f ));
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(float x)
{
return (make_cuDoubleComplex( double(x), 0.0 ));
}
template <typename T_ELEM> __inline__ T_ELEM cuGet (float, float );
template <> __inline__ float cuGet<float >(float x, float y)
{
return float(x);
}
template <> __inline__ double cuGet<double>(float x, float y)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(float x, float y)
{
return (make_cuComplex( float(x), float(y) ));
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(float x, float y)
{
return (make_cuDoubleComplex( double(x), double(y) ));
}
template <typename T_ELEM> __inline__ T_ELEM cuGet (double );
template <> __inline__ float cuGet<float >(double x)
{
return float(x);
}
template <> __inline__ double cuGet<double>(double x)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(double x)
{
return (make_cuComplex( float(x), 0.0f ));
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(double x)
{
return (make_cuDoubleComplex( double(x), 0.0 ));
}
template <typename T_ELEM> __inline__ T_ELEM cuGet (double, double );
template <> __inline__ float cuGet<float >(double x, double y)
{
return float(x);
}
template <> __inline__ double cuGet<double>(double x, double y)
{
return double(x);
}
template <> __inline__ cuComplex cuGet<cuComplex>(double x, double y)
{
return (make_cuComplex( float(x), float(y) ));
}
template <> __inline__ cuDoubleComplex cuGet<cuDoubleComplex>(double x, double y)
{
return (make_cuDoubleComplex( double(x), double(y) ));
}
static void compress_index(
const int *Ind,
int nnz,
int m,
int *Ptr,
int base)
{
int i;
/* initialize everything to zero */
for(i=0; i<m+1; i++){
Ptr[i]=0;
}
/* count elements in every row */
Ptr[0]=base;
for(i=0; i<nnz; i++){
Ptr[Ind[i]+(1-base)]++;
}
/* add all the values */
for(i=0; i<m; i++){
Ptr[i+1]+=Ptr[i];
}
}
struct cooFormat {
int i ;
int j ;
int p ; // permutation
};
int cmp_cooFormat_csr( struct cooFormat *s, struct cooFormat *t)
{
if ( s->i < t->i ){
return -1 ;
}
else if ( s->i > t->i ){
return 1 ;
}
else{
return s->j - t->j ;
}
}
int cmp_cooFormat_csc( struct cooFormat *s, struct cooFormat *t)
{
if ( s->j < t->j ){
return -1 ;
}
else if ( s->j > t->j ){
return 1 ;
}
else{
return s->i - t->i ;
}
}
typedef int (*FUNPTR) (const void*, const void*) ;
typedef int (*FUNPTR2) ( struct cooFormat *s, struct cooFormat *t) ;
static FUNPTR2 fptr_array[2] = {
cmp_cooFormat_csr,
cmp_cooFormat_csc,
};
static int verify_pattern(
int m,
int nnz,
int *csrRowPtr,
int *csrColInd)
{
int i, col, start, end, base_index;
int error_found = 0;
if (nnz != (csrRowPtr[m] - csrRowPtr[0])){
fprintf(stderr, "Error (nnz check failed): (csrRowPtr[%d]=%d - csrRowPtr[%d]=%d) != (nnz=%d)\n", 0, csrRowPtr[0], m, csrRowPtr[m], nnz);
error_found = 1;
}
base_index = csrRowPtr[0];
if ((0 != base_index) && (1 != base_index)){
fprintf(stderr, "Error (base index check failed): base index = %d\n", base_index);
error_found = 1;
}
for (i=0; (!error_found) && (i<m); i++){
start = csrRowPtr[i ] - base_index;
end = csrRowPtr[i+1] - base_index;
if (start > end){
fprintf(stderr, "Error (corrupted row): csrRowPtr[%d] (=%d) > csrRowPtr[%d] (=%d)\n", i, start+base_index, i+1, end+base_index);
error_found = 1;
}
for (col=start; col<end; col++){
if (csrColInd[col] < base_index){
fprintf(stderr, "Error (column vs. base index check failed): csrColInd[%d] < %d\n", col, base_index);
error_found = 1;
}
if ((col < (end-1)) && (csrColInd[col] >= csrColInd[col+1])){
fprintf(stderr, "Error (sorting of the column indecis check failed): (csrColInd[%d]=%d) >= (csrColInd[%d]=%d)\n", col, csrColInd[col], col+1, csrColInd[col+1]);
error_found = 1;
}
}
}
return error_found ;
}
template <typename T_ELEM>
int loadMMSparseMatrix(
char *filename,
char elem_type,
bool csrFormat,
int *m,
int *n,
int *nnz,
T_ELEM **aVal,
int **aRowInd,
int **aColInd,
int extendSymMatrix)
{
MM_typecode matcode;
double *tempVal;
int *tempRowInd,*tempColInd;
double *tval;
int *trow,*tcol;
int *csrRowPtr, *cscColPtr;
int i,j,error,base,count;
struct cooFormat *work;
/* read the matrix */
error = mm_read_mtx_crd(filename, m, n, nnz, &trow, &tcol, &tval, &matcode);
if (error) {
fprintf(stderr, "!!!! can not open file: '%s'\n", filename);
return 1;
}
/* start error checking */
if (mm_is_complex(matcode) && ((elem_type != 'z') && (elem_type != 'c'))) {
fprintf(stderr, "!!!! complex matrix requires type 'z' or 'c'\n");
return 1;
}
if (mm_is_dense(matcode) || mm_is_array(matcode) || mm_is_pattern(matcode) /*|| mm_is_integer(matcode)*/){
fprintf(stderr, "!!!! dense, array, pattern and integer matrices are not supported\n");
return 1;
}
/* if necessary symmetrize the pattern (transform from triangular to full) */
if ((extendSymMatrix) && (mm_is_symmetric(matcode) || mm_is_hermitian(matcode) || mm_is_skew(matcode))){
//count number of non-diagonal elements
count=0;
for(i=0; i<(*nnz); i++){
if (trow[i] != tcol[i]){
count++;
}
}
//allocate space for the symmetrized matrix
tempRowInd = (int *)malloc((*nnz + count) * sizeof(int));
tempColInd = (int *)malloc((*nnz + count) * sizeof(int));
if (mm_is_real(matcode) || mm_is_integer(matcode)){
tempVal = (double *)malloc((*nnz + count) * sizeof(double));
}
else{
tempVal = (double *)malloc(2 * (*nnz + count) * sizeof(double));
}
//copy the elements regular and transposed locations
for(j=0, i=0; i<(*nnz); i++){
tempRowInd[j]=trow[i];
tempColInd[j]=tcol[i];
if (mm_is_real(matcode) || mm_is_integer(matcode)){
tempVal[j]=tval[i];
}
else{
tempVal[2*j] =tval[2*i];
tempVal[2*j+1]=tval[2*i+1];
}
j++;
if (trow[i] != tcol[i]){
tempRowInd[j]=tcol[i];
tempColInd[j]=trow[i];
if (mm_is_real(matcode) || mm_is_integer(matcode)){
if (mm_is_skew(matcode)){
tempVal[j]=-tval[i];
}
else{
tempVal[j]= tval[i];
}
}
else{
if(mm_is_hermitian(matcode)){
tempVal[2*j] = tval[2*i];
tempVal[2*j+1]=-tval[2*i+1];
}
else{
tempVal[2*j] = tval[2*i];
tempVal[2*j+1]= tval[2*i+1];
}
}
j++;
}
}
(*nnz)+=count;
//free temporary storage
free(trow);
free(tcol);
free(tval);
}
else{
tempRowInd=trow;
tempColInd=tcol;
tempVal =tval;
}
// life time of (trow, tcol, tval) is over.
// please use COO format (tempRowInd, tempColInd, tempVal)
// use qsort to sort COO format
work = (struct cooFormat *)malloc(sizeof(struct cooFormat)*(*nnz));
if (NULL == work){
fprintf(stderr, "!!!! allocation error, malloc failed\n");
return 1;
}
for(i=0; i<(*nnz); i++){
work[i].i = tempRowInd[i];
work[i].j = tempColInd[i];
work[i].p = i; // permutation is identity
}
if (csrFormat){
/* create row-major ordering of indices (sorted by row and within each row by column) */
qsort(work, *nnz, sizeof(struct cooFormat), (FUNPTR)fptr_array[0] );
}else{
/* create column-major ordering of indices (sorted by column and within each column by row) */
qsort(work, *nnz, sizeof(struct cooFormat), (FUNPTR)fptr_array[1] );
}
// (tempRowInd, tempColInd) is sorted either by row-major or by col-major
for(i=0; i<(*nnz); i++){
tempRowInd[i] = work[i].i;
tempColInd[i] = work[i].j;
}
// setup base
// check if there is any row/col 0, if so base-0
// check if there is any row/col equal to matrix dimension m/n, if so base-1
int base0 = 0;
int base1 = 0;
for(i=0; i<(*nnz); i++){
const int row = tempRowInd[i];
const int col = tempColInd[i];
if ( (0 == row) || (0 == col) ){
base0 = 1;
}
if ( (*m == row) || (*n == col) ){
base1 = 1;
}
}
if ( base0 && base1 ){
printf("Error: input matrix is base-0 and base-1 \n");
return 1;
}
base = 0;
if (base1){
base = 1;
}
/* compress the appropriate indices */
if (csrFormat){
/* CSR format (assuming row-major format) */
csrRowPtr = (int *)malloc(((*m)+1) * sizeof(csrRowPtr[0]));
if (!csrRowPtr) return 1;
compress_index(tempRowInd, *nnz, *m, csrRowPtr, base);
*aRowInd = csrRowPtr;
*aColInd = (int *)malloc((*nnz) * sizeof(int));
}
else {
/* CSC format (assuming column-major format) */
cscColPtr = (int *)malloc(((*n)+1) * sizeof(cscColPtr[0]));
if (!cscColPtr) return 1;
compress_index(tempColInd, *nnz, *n, cscColPtr, base);
*aColInd = cscColPtr;
*aRowInd = (int *)malloc((*nnz) * sizeof(int));
}
/* transfrom the matrix values of type double into one of the cusparse library types */
*aVal = (T_ELEM *)malloc((*nnz) * sizeof(T_ELEM));
for (i=0; i<(*nnz); i++) {
if (csrFormat){
(*aColInd)[i] = tempColInd[i];
}
else{
(*aRowInd)[i] = tempRowInd[i];
}
if (mm_is_real(matcode) || mm_is_integer(matcode)){
(*aVal)[i] = cuGet<T_ELEM>( tempVal[ work[i].p ] );
}
else{
(*aVal)[i] = cuGet<T_ELEM>(tempVal[2*work[i].p], tempVal[2*work[i].p+1]);
}
}
/* check for corruption */
int error_found;
if (csrFormat){
error_found = verify_pattern(*m, *nnz, *aRowInd, *aColInd);
}else{
error_found = verify_pattern(*n, *nnz, *aColInd, *aRowInd);
}
if (error_found){
fprintf(stderr, "!!!! verify_pattern failed\n");
return 1;
}
/* cleanup and exit */
free(work);
free(tempVal);
free(tempColInd);
free(tempRowInd);
return 0;
}
/* specific instantiation */
template int loadMMSparseMatrix<float>(
char *filename,
char elem_type,
bool csrFormat,
int *m,
int *n,
int *nnz,
float **aVal,
int **aRowInd,
int **aColInd,
int extendSymMatrix);
template int loadMMSparseMatrix<double>(
char *filename,
char elem_type,
bool csrFormat,
int *m,
int *n,
int *nnz,
double **aVal,
int **aRowInd,
int **aColInd,
int extendSymMatrix);
template int loadMMSparseMatrix<cuComplex>(
char *filename,
char elem_type,
bool csrFormat,
int *m,
int *n,
int *nnz,
cuComplex **aVal,
int **aRowInd,
int **aColInd,
int extendSymMatrix);
template int loadMMSparseMatrix<cuDoubleComplex>(
char *filename,
char elem_type,
bool csrFormat,
int *m,
int *n,
int *nnz,
cuDoubleComplex **aVal,
int **aRowInd,
int **aColInd,
int extendSymMatrix);

407
Samples/cudaNvSci/Makefile Normal file
View File

@@ -0,0 +1,407 @@
################################################################################
# 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 $(TARGET_ARCH),x86_64 aarch64 ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 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 ?= $(QNX_HOST)/usr/bin/aarch64-unknown-nto-qnx7.0.0-g++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
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)/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
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
endif
ifeq ($(TARGET_OS),qnx)
CCFLAGS += -DWIN_INTERFACE_CUSTOM
LDFLAGS += -lsocket
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),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 = $(shell lsb_release -i -s 2>/dev/null | grep -i ubuntu)
SAMPLE_ENABLED := 1
# This sample is not supported on Mac OSX
ifeq ($(TARGET_OS),darwin)
$(info >>> WARNING - cudaNvSci is not supported on Mac OSX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on ARMv7
ifeq ($(TARGET_ARCH),armv7l)
$(info >>> WARNING - cudaNvSci is not supported on ARMv7 - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - cudaNvSci 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 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))
# Crop the version number to 3 decimals.
GCCVERSION := $(shell expr `echo $(GCCVERSION)` | cut -b1-3)
#$(warning $(GCCVERSION))
IS_MIN_VERSION := $(shell expr `echo $(GCCVERSION)` \>= 470)
ifeq ($(IS_MIN_VERSION), 1)
$(info >>> GCC Version is greater or equal to 4.7.0 <<<)
else
$(info >>> Waiving build. Minimum GCC version required for C++11 is 4.7.0 <<<)
SAMPLE_ENABLED := 0
endif
endif
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64))
SMS ?= 30 35 37 50 52 60 61 70 72 75
else
SMS ?= 30 35 37 50 52 60 61 70 75
endif
ifeq ($(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
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 += $(CUDA_PATH)/targets/x86_64-linux/lib/stubs
endif
ifeq ($(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),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 ?= $(CUDA_PATH)/targets/aarch64-qnx/lib/stubs
endif
ifeq ($(TARGET_ARCH),ppc64le)
CUDA_SEARCH_PATH ?= $(CUDA_PATH)/targets/ppc64le-linux/lib/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 += --std=c++11
LIBRARIES += -lnvscibuf -lnvscisync
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: cudaNvSci
check.deps:
ifeq ($(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
cudaNvSci.o:cudaNvSci.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
imageKernels.o:imageKernels.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
main.o:main.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
cudaNvSci: cudaNvSci.o imageKernels.o main.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
$(EXEC) ./cudaNvSci
clean:
rm -f cudaNvSci cudaNvSci.o imageKernels.o main.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/cudaNvSci
clobber: clean

View File

@@ -0,0 +1,70 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>cudaNvSci</name>
<cflags>
<flag>--std=c++11</flag>
</cflags>
<cuda_api_list>
<toolkit>cudaImportExternalMemory</toolkit>
<toolkit>cudaExternalMemoryGetMappedBuffer</toolkit>
<toolkit>cudaExternalMemoryGetMappedMipmappedArray</toolkit>
<toolkit>cudaImportExternalSemaphore</toolkit>
<toolkit>cudaSignalExternalSemaphoresAsync</toolkit>
<toolkit>cudaWaitExternalSemaphoresAsync</toolkit>
<toolkit>cudaDestroyExternalSemaphore</toolkit>
<toolkit>cudaDestroyExternalMemory</toolkit>
</cuda_api_list>
<description><![CDATA[This sample demonstrates CUDA-NvSciBuf/NvSciSync Interop. Two CPU threads import the NvSciBuf and NvSciSync into CUDA to perform two image processing algorithms on a ppm image - image rotation in 1st thread & rgba to grayscale conversion of rotated image in 2nd thread. Currently only supported on Ubuntu 18.04]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../common/inc</path>
</includepaths>
<keyconcepts>
<concept level="basic">CUDA NvSci Interop</concept>
<concept level="advanced">Data Parallel Algorithms</concept>
<concept level="advanced">Image Processing</concept>
</keyconcepts>
<keywords>
<keyword>CUDA</keyword>
<keyword>CPP11</keyword>
</keywords>
<libraries>
<library os="linux">cuda</library>
<library framework="true" os="macosx">CUDA</library>
<library>nvscibuf</library>
<library>nvscisync</library>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>main.cpp</primary_file>
<required_dependencies>
<dependency>NVSCI</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Advanced Topics</scope>
<scope>1:CUDA NvSciBuf/NvSciSync Interop</scope>
</scopes>
<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>
<supported_envs>
<env>
<platform>aarch64</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<from>6.0</from>
</supported_sm_architectures>
<title>CUDA NvSciBuf/NvSciSync Interop</title>
<type>exe</type>
</entry>

View File

@@ -0,0 +1,64 @@
# cudaNvSci - CUDA NvSciBuf/NvSciSync Interop
## Description
This sample demonstrates CUDA-NvSciBuf/NvSciSync Interop. Two CPU threads import the NvSciBuf and NvSciSync into CUDA to perform two image processing algorithms on a ppm image - image rotation in 1st thread & rgba to grayscale conversion of rotated image in 2nd thread. Currently only supported on Ubuntu 18.04
## Key Concepts
CUDA NvSci Interop, Data Parallel Algorithms, Image Processing
## Supported SM Architectures
[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)
## Supported OSes
Linux
## Supported CPU Architecture
x86_64, aarch64
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaImportExternalMemory, cudaExternalMemoryGetMappedBuffer, cudaExternalMemoryGetMappedMipmappedArray, cudaImportExternalSemaphore, cudaSignalExternalSemaphoresAsync, cudaWaitExternalSemaphoresAsync, cudaDestroyExternalSemaphore, cudaDestroyExternalMemory
## Dependencies needed to build/run
[NVSCI](../../README.md#nvsci)
## Prerequisites
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run
### 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, 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=aarch64` <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)

View File

@@ -0,0 +1,605 @@
/* 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.
*/
#include "cudaNvSci.h"
#include <cuda.h>
#include <condition_variable>
#include <iostream>
#include <thread>
std::mutex m_mutex;
std::condition_variable m_condVar;
bool workSubmitted = false;
class cudaNvSciSignal {
private:
NvSciSyncModule m_syncModule;
NvSciBufModule m_bufModule;
NvSciSyncAttrList m_syncAttrList;
NvSciSyncFence *m_fence;
NvSciBufAttrList m_rawBufAttrList;
NvSciBufAttrList m_imageBufAttrList;
NvSciBufAttrList m_buffAttrListOut[2];
NvSciBufAttrKeyValuePair pairArrayOut[10];
cudaExternalMemory_t extMemRawBuf, extMemImageBuf;
cudaMipmappedArray_t d_mipmapArray;
cudaArray_t d_mipLevelArray;
cudaTextureObject_t texObject;
cudaExternalSemaphore_t signalSem;
cudaStream_t streamToRun;
int m_cudaDeviceId;
CUuuid m_devUUID;
uint64_t m_imageWidth;
uint64_t m_imageHeight;
void *d_outputBuf;
size_t m_bufSize;
public:
cudaNvSciSignal(NvSciBufModule bufModule, NvSciSyncModule syncModule,
int cudaDeviceId, int bufSize, uint64_t imageWidth,
uint64_t imageHeight, NvSciSyncFence *fence)
: m_syncModule(syncModule),
m_bufModule(bufModule),
m_cudaDeviceId(cudaDeviceId),
d_outputBuf(NULL),
m_bufSize(bufSize),
m_imageWidth(imageWidth),
m_imageHeight(imageHeight),
m_fence(fence) {
initCuda();
checkNvSciErrors(NvSciSyncAttrListCreate(m_syncModule, &m_syncAttrList));
checkNvSciErrors(NvSciBufAttrListCreate(m_bufModule, &m_rawBufAttrList));
checkNvSciErrors(NvSciBufAttrListCreate(m_bufModule, &m_imageBufAttrList));
setRawBufAttrList(m_bufSize);
setImageBufAttrList(m_imageWidth, m_imageHeight);
checkCudaErrors(cudaDeviceGetNvSciSyncAttributes(
m_syncAttrList, m_cudaDeviceId, cudaNvSciSyncAttrSignal));
}
~cudaNvSciSignal() {
checkCudaErrors(cudaFreeArray(d_mipLevelArray));
checkCudaErrors(cudaFreeMipmappedArray(d_mipmapArray));
checkCudaErrors(cudaFree(d_outputBuf));
checkCudaErrors(cudaDestroyExternalSemaphore(signalSem));
checkCudaErrors(cudaDestroyExternalMemory(extMemRawBuf));
checkCudaErrors(cudaDestroyExternalMemory(extMemImageBuf));
checkCudaErrors(cudaDestroyTextureObject(texObject));
checkCudaErrors(cudaStreamDestroy(streamToRun));
}
void initCuda() {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
checkCudaErrors(
cudaStreamCreateWithFlags(&streamToRun, cudaStreamNonBlocking));
int major = 0, minor = 0;
checkCudaErrors(cudaDeviceGetAttribute(
&major, cudaDevAttrComputeCapabilityMajor, m_cudaDeviceId));
checkCudaErrors(cudaDeviceGetAttribute(
&minor, cudaDevAttrComputeCapabilityMinor, m_cudaDeviceId));
printf(
"[cudaNvSciSignal] GPU Device %d: \"%s\" with compute capability "
"%d.%d\n\n",
m_cudaDeviceId, _ConvertSMVer2ArchName(major, minor), major, minor);
CUresult res = cuDeviceGetUuid(&m_devUUID, m_cudaDeviceId);
if (res != CUDA_SUCCESS) {
fprintf(stderr, "Driver API error = %04d \n", res);
exit(EXIT_FAILURE);
}
}
void setRawBufAttrList(uint64_t size) {
NvSciBufType bufType = NvSciBufType_RawBuffer;
uint64_t tempAlignment = 0;
bool cpuAccess = false;
NvSciBufAttrValAccessPerm perm = NvSciBufAccessPerm_ReadWrite;
NvSciBufAttrKeyValuePair rawBufAttrs[] = {
{NvSciBufRawBufferAttrKey_Size, &size, sizeof(size)},
{NvSciBufRawBufferAttrKey_Align, &tempAlignment, sizeof(tempAlignment)},
{NvSciBufGeneralAttrKey_Types, &bufType, sizeof(bufType)},
{NvSciBufGeneralAttrKey_NeedCpuAccess, &cpuAccess, sizeof(cpuAccess)},
{NvSciBufGeneralAttrKey_RequiredPerm, &perm, sizeof(perm)},
{NvSciBufGeneralAttrKey_GpuId, &m_devUUID, sizeof(m_devUUID)},
};
checkNvSciErrors(NvSciBufAttrListSetAttrs(
m_rawBufAttrList, rawBufAttrs,
sizeof(rawBufAttrs) / sizeof(NvSciBufAttrKeyValuePair)));
}
void setImageBufAttrList(uint32_t width, uint32_t height) {
NvSciBufType bufType = NvSciBufType_Image;
NvSciBufAttrValImageLayoutType layout = NvSciBufImage_BlockLinearType;
NvSciBufAttrValAccessPerm perm = NvSciBufAccessPerm_ReadWrite;
uint32_t planeCount = 1;
uint32_t planeWidths[] = {width};
uint32_t planeHeights[] = {height};
uint64_t lrpad = 0, tbpad = 100;
bool cpuAccessFlag = false;
NvSciBufAttrValColorFmt planecolorfmts[] = {NvSciColor_B8G8R8A8};
NvSciBufAttrValColorStd planecolorstds[] = {NvSciColorStd_SRGB};
NvSciBufAttrValImageScanType planescantype[] = {NvSciBufScan_InterlaceType};
NvSciBufAttrKeyValuePair imgBufAttrs[] = {
{NvSciBufGeneralAttrKey_Types, &bufType, sizeof(bufType)},
{NvSciBufImageAttrKey_PlaneCount, &planeCount, sizeof(planeCount)},
{NvSciBufImageAttrKey_Layout, &layout, sizeof(layout)},
{NvSciBufImageAttrKey_TopPadding, &tbpad, sizeof(tbpad)},
{NvSciBufImageAttrKey_BottomPadding, &tbpad, sizeof(tbpad)},
{NvSciBufImageAttrKey_LeftPadding, &lrpad, sizeof(lrpad)},
{NvSciBufImageAttrKey_RightPadding, &lrpad, sizeof(lrpad)},
{NvSciBufImageAttrKey_PlaneColorFormat, planecolorfmts,
sizeof(planecolorfmts)},
{NvSciBufImageAttrKey_PlaneColorStd, planecolorstds,
sizeof(planecolorstds)},
{NvSciBufImageAttrKey_PlaneWidth, planeWidths, sizeof(planeWidths)},
{NvSciBufImageAttrKey_PlaneHeight, planeHeights, sizeof(planeHeights)},
{NvSciBufGeneralAttrKey_NeedCpuAccess, &cpuAccessFlag,
sizeof(cpuAccessFlag)},
{NvSciBufGeneralAttrKey_RequiredPerm, &perm, sizeof(perm)},
{NvSciBufImageAttrKey_PlaneScanType, planescantype,
sizeof(planescantype)},
{NvSciBufGeneralAttrKey_GpuId, &m_devUUID, sizeof(m_devUUID)},
};
checkNvSciErrors(NvSciBufAttrListSetAttrs(
m_imageBufAttrList, imgBufAttrs,
sizeof(imgBufAttrs) / sizeof(NvSciBufAttrKeyValuePair)));
}
NvSciSyncAttrList getNvSciSyncAttrList() { return m_syncAttrList; }
NvSciBufAttrList getNvSciRawBufAttrList() { return m_rawBufAttrList; }
NvSciBufAttrList getNvSciImageBufAttrList() { return m_imageBufAttrList; }
void runRotateImageAndSignal(unsigned char *imageData) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
copyDataToImageArray(imageData);
createTexture();
float angle = 0.5f; // angle to rotate image by (in radians)
rotateKernel(texObject, angle, (unsigned int *)d_outputBuf, m_imageWidth,
m_imageHeight, streamToRun);
signalExternalSemaphore();
}
void cudaImportNvSciSemaphore(NvSciSyncObj syncObj) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
cudaExternalSemaphoreHandleDesc extSemDesc;
memset(&extSemDesc, 0, sizeof(extSemDesc));
extSemDesc.type = cudaExternalSemaphoreHandleTypeNvSciSync;
extSemDesc.handle.nvSciSyncObj = (void *)syncObj;
checkCudaErrors(cudaImportExternalSemaphore(&signalSem, &extSemDesc));
}
void signalExternalSemaphore() {
cudaExternalSemaphoreSignalParams signalParams;
memset(&signalParams, 0, sizeof(signalParams));
// For cross-process signaler-waiter applications need to use NvSciIpc
// and NvSciSync[Export|Import] utilities to share the NvSciSyncFence
// across process. This step is optional in single-process.
signalParams.params.nvSciSync.fence = (void *)m_fence;
signalParams.flags = 0;
checkCudaErrors(cudaSignalExternalSemaphoresAsync(&signalSem, &signalParams,
1, streamToRun));
}
void cudaImportNvSciRawBuf(NvSciBufObj inputBufObj) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
checkNvSciErrors(
NvSciBufObjGetAttrList(inputBufObj, &m_buffAttrListOut[0]));
memset(pairArrayOut, 0, sizeof(NvSciBufAttrKeyValuePair) * 10);
pairArrayOut[0].key = NvSciBufRawBufferAttrKey_Size;
pairArrayOut[1].key = NvSciBufRawBufferAttrKey_Align;
checkNvSciErrors(
NvSciBufAttrListGetAttrs(m_buffAttrListOut[0], pairArrayOut, 2));
uint64_t size = *(uint64_t *)pairArrayOut[0].value;
uint64_t offset = *(uint64_t *)pairArrayOut[1].value;
cudaExternalMemoryHandleDesc memHandleDesc;
memset(&memHandleDesc, 0, sizeof(memHandleDesc));
memHandleDesc.type = cudaExternalMemoryHandleTypeNvSciBuf;
memHandleDesc.handle.nvSciBufObject = inputBufObj;
memHandleDesc.size = size;
checkCudaErrors(cudaImportExternalMemory(&extMemRawBuf, &memHandleDesc));
cudaExternalMemoryBufferDesc bufferDesc;
memset(&bufferDesc, 0, sizeof(bufferDesc));
bufferDesc.offset = offset;
bufferDesc.size = size;
m_bufSize = size;
checkCudaErrors(cudaExternalMemoryGetMappedBuffer(
&d_outputBuf, extMemRawBuf, &bufferDesc));
}
void cudaImportNvSciImage(NvSciBufObj inputBufObj) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
checkNvSciErrors(
NvSciBufObjGetAttrList(inputBufObj, &m_buffAttrListOut[1]));
memset(pairArrayOut, 0, sizeof(NvSciBufAttrKeyValuePair) * 10);
pairArrayOut[0].key = NvSciBufImageAttrKey_Size;
pairArrayOut[1].key = NvSciBufImageAttrKey_Alignment;
pairArrayOut[2].key = NvSciBufImageAttrKey_PlaneCount;
pairArrayOut[3].key = NvSciBufImageAttrKey_PlaneWidth;
pairArrayOut[4].key = NvSciBufImageAttrKey_PlaneHeight;
checkNvSciErrors(
NvSciBufAttrListGetAttrs(m_buffAttrListOut[1], pairArrayOut, 5));
uint64_t size = *(uint64_t *)pairArrayOut[0].value;
uint64_t alignment = *(uint64_t *)pairArrayOut[1].value;
uint64_t planeCount = *(uint64_t *)pairArrayOut[2].value;
uint64_t imageWidth = *(uint64_t *)pairArrayOut[3].value;
uint64_t imageHeight = *(uint64_t *)pairArrayOut[4].value;
cudaExternalMemoryHandleDesc memHandleDesc;
memset(&memHandleDesc, 0, sizeof(memHandleDesc));
memHandleDesc.type = cudaExternalMemoryHandleTypeNvSciBuf;
memHandleDesc.handle.nvSciBufObject = inputBufObj;
memHandleDesc.size = size;
checkCudaErrors(cudaImportExternalMemory(&extMemImageBuf, &memHandleDesc));
cudaExtent extent = {};
memset(&extent, 0, sizeof(extent));
extent.width = imageWidth;
extent.height = imageHeight;
extent.depth = 0;
cudaChannelFormatDesc desc;
desc.x = 8;
desc.y = 8;
desc.z = 8;
desc.w = 8;
desc.f = cudaChannelFormatKindUnsigned;
cudaExternalMemoryMipmappedArrayDesc mipmapDesc = {0};
mipmapDesc.offset = 0;
mipmapDesc.formatDesc = desc;
mipmapDesc.extent = extent;
mipmapDesc.flags = 0;
mipmapDesc.numLevels = 1;
checkCudaErrors(cudaExternalMemoryGetMappedMipmappedArray(
&d_mipmapArray, extMemImageBuf, &mipmapDesc));
}
void copyDataToImageArray(unsigned char *imageData) {
uint32_t mipLevelId = 0;
checkCudaErrors(cudaGetMipmappedArrayLevel(&d_mipLevelArray, d_mipmapArray,
mipLevelId));
checkCudaErrors(cudaMemcpy2DToArrayAsync(
d_mipLevelArray, 0, 0, imageData, m_imageWidth * sizeof(unsigned int),
m_imageWidth * sizeof(unsigned int), m_imageHeight,
cudaMemcpyHostToDevice, streamToRun));
}
void createTexture() {
cudaResourceDesc texRes;
memset(&texRes, 0, sizeof(cudaResourceDesc));
texRes.resType = cudaResourceTypeArray;
texRes.res.array.array = d_mipLevelArray;
cudaTextureDesc texDescr;
memset(&texDescr, 0, sizeof(cudaTextureDesc));
texDescr.normalizedCoords = true;
texDescr.filterMode = cudaFilterModeLinear;
texDescr.addressMode[0] = cudaAddressModeWrap;
texDescr.addressMode[1] = cudaAddressModeWrap;
texDescr.readMode = cudaReadModeNormalizedFloat;
checkCudaErrors(
cudaCreateTextureObject(&texObject, &texRes, &texDescr, NULL));
}
};
class cudaNvSciWait {
private:
NvSciSyncModule m_syncModule;
NvSciBufModule m_bufModule;
NvSciSyncAttrList m_syncAttrList;
NvSciBufAttrList m_rawBufAttrList;
NvSciBufAttrList m_buffAttrListOut;
NvSciBufAttrKeyValuePair pairArrayOut[10];
NvSciSyncFence *m_fence;
cudaExternalMemory_t extMemRawBuf;
cudaExternalSemaphore_t waitSem;
cudaStream_t streamToRun;
int m_cudaDeviceId;
CUuuid m_devUUID;
void *d_outputBuf;
size_t m_bufSize;
size_t imageWidth;
size_t imageHeight;
public:
cudaNvSciWait(NvSciBufModule bufModule, NvSciSyncModule syncModule,
int cudaDeviceId, int bufSize, NvSciSyncFence *fence)
: m_bufModule(bufModule),
m_syncModule(syncModule),
m_cudaDeviceId(cudaDeviceId),
m_bufSize(bufSize),
m_fence(fence) {
initCuda();
checkNvSciErrors(NvSciSyncAttrListCreate(m_syncModule, &m_syncAttrList));
checkNvSciErrors(NvSciBufAttrListCreate(m_bufModule, &m_rawBufAttrList));
setRawBufAttrList(m_bufSize);
checkCudaErrors(cudaDeviceGetNvSciSyncAttributes(
m_syncAttrList, m_cudaDeviceId, cudaNvSciSyncAttrWait));
}
~cudaNvSciWait() {
checkCudaErrors(cudaStreamDestroy(streamToRun));
checkCudaErrors(cudaDestroyExternalSemaphore(waitSem));
checkCudaErrors(cudaDestroyExternalMemory(extMemRawBuf));
checkCudaErrors(cudaFree(d_outputBuf));
}
void initCuda() {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
checkCudaErrors(
cudaStreamCreateWithFlags(&streamToRun, cudaStreamNonBlocking));
CUresult res = cuDeviceGetUuid(&m_devUUID, m_cudaDeviceId);
if (res != CUDA_SUCCESS) {
fprintf(stderr, "Driver API error = %04d \n", res);
exit(EXIT_FAILURE);
}
int major = 0, minor = 0;
checkCudaErrors(cudaDeviceGetAttribute(
&major, cudaDevAttrComputeCapabilityMajor, m_cudaDeviceId));
checkCudaErrors(cudaDeviceGetAttribute(
&minor, cudaDevAttrComputeCapabilityMinor, m_cudaDeviceId));
printf(
"[cudaNvSciWait] GPU Device %d: \"%s\" with compute capability "
"%d.%d\n\n",
m_cudaDeviceId, _ConvertSMVer2ArchName(major, minor), major, minor);
}
void setRawBufAttrList(uint64_t size) {
NvSciBufType bufType = NvSciBufType_RawBuffer;
uint64_t tempAlignment = 0;
bool cpuAccess = false;
NvSciBufAttrValAccessPerm perm = NvSciBufAccessPerm_ReadWrite;
NvSciBufAttrKeyValuePair rawBufAttrs[] = {
{NvSciBufRawBufferAttrKey_Size, &size, sizeof(size)},
{NvSciBufRawBufferAttrKey_Align, &tempAlignment, sizeof(tempAlignment)},
{NvSciBufGeneralAttrKey_Types, &bufType, sizeof(bufType)},
{NvSciBufGeneralAttrKey_NeedCpuAccess, &cpuAccess, sizeof(cpuAccess)},
{NvSciBufGeneralAttrKey_RequiredPerm, &perm, sizeof(perm)},
{NvSciBufGeneralAttrKey_GpuId, &m_devUUID, sizeof(m_devUUID)},
};
checkNvSciErrors(NvSciBufAttrListSetAttrs(
m_rawBufAttrList, rawBufAttrs,
sizeof(rawBufAttrs) / sizeof(NvSciBufAttrKeyValuePair)));
}
NvSciSyncAttrList getNvSciSyncAttrList() { return m_syncAttrList; }
NvSciBufAttrList getNvSciRawBufAttrList() { return m_rawBufAttrList; }
void runImageGrayscale(std::string image_filename, size_t imageWidth,
size_t imageHeight) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
waitExternalSemaphore();
launchGrayScaleKernel((unsigned int *)d_outputBuf, image_filename,
imageWidth, imageHeight, streamToRun);
}
void cudaImportNvSciSemaphore(NvSciSyncObj syncObj) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
cudaExternalSemaphoreHandleDesc extSemDesc;
memset(&extSemDesc, 0, sizeof(extSemDesc));
extSemDesc.type = cudaExternalSemaphoreHandleTypeNvSciSync;
extSemDesc.handle.nvSciSyncObj = (void *)syncObj;
checkCudaErrors(cudaImportExternalSemaphore(&waitSem, &extSemDesc));
}
void waitExternalSemaphore() {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
cudaExternalSemaphoreWaitParams waitParams;
memset(&waitParams, 0, sizeof(waitParams));
// For cross-process signaler-waiter applications need to use NvSciIpc
// and NvSciSync[Export|Import] utilities to share the NvSciSyncFence
// across process. This step is optional in single-process.
waitParams.params.nvSciSync.fence = (void *)m_fence;
waitParams.flags = 0;
checkCudaErrors(
cudaWaitExternalSemaphoresAsync(&waitSem, &waitParams, 1, streamToRun));
}
void cudaImportNvSciRawBuf(NvSciBufObj inputBufObj) {
checkCudaErrors(cudaSetDevice(m_cudaDeviceId));
checkNvSciErrors(NvSciBufObjGetAttrList(inputBufObj, &m_buffAttrListOut));
memset(pairArrayOut, 0, sizeof(NvSciBufAttrKeyValuePair) * 10);
pairArrayOut[0].key = NvSciBufRawBufferAttrKey_Size;
pairArrayOut[1].key = NvSciBufRawBufferAttrKey_Align;
checkNvSciErrors(
NvSciBufAttrListGetAttrs(m_buffAttrListOut, pairArrayOut, 2));
uint64_t size = *(uint64_t *)pairArrayOut[0].value;
uint64_t offset = *(uint64_t *)pairArrayOut[1].value;
cudaExternalMemoryHandleDesc memHandleDesc;
memset(&memHandleDesc, 0, sizeof(memHandleDesc));
memHandleDesc.type = cudaExternalMemoryHandleTypeNvSciBuf;
memHandleDesc.handle.nvSciBufObject = inputBufObj;
memHandleDesc.size = size;
checkCudaErrors(cudaImportExternalMemory(&extMemRawBuf, &memHandleDesc));
cudaExternalMemoryBufferDesc bufferDesc;
memset(&bufferDesc, 0, sizeof(bufferDesc));
bufferDesc.offset = offset;
bufferDesc.size = size;
m_bufSize = size;
checkCudaErrors(cudaExternalMemoryGetMappedBuffer(
&d_outputBuf, extMemRawBuf, &bufferDesc));
}
};
void thread_rotateAndSignal(cudaNvSciSignal *cudaNvSciSignalObj,
unsigned char *imageData) {
std::lock_guard<std::mutex> guard(m_mutex);
cudaNvSciSignalObj->runRotateImageAndSignal(imageData);
workSubmitted = true;
m_condVar.notify_one();
}
void thread_waitAndGrayscale(cudaNvSciWait *cudaNvSciWaitObj,
std::string image_filename, size_t imageWidth,
size_t imageHeight) {
// Acquire the lock
std::unique_lock<std::mutex> mlock(m_mutex);
m_condVar.wait(mlock, [] { return workSubmitted; });
cudaNvSciWaitObj->runImageGrayscale(image_filename, imageWidth, imageHeight);
}
cudaNvSci::cudaNvSci(int isMultiGPU, std::vector<int> &deviceIds,
unsigned char *imageData, size_t width, size_t height)
: m_isMultiGPU(isMultiGPU),
image_data(imageData),
imageWidth(width),
imageHeight(height) {
if (isMultiGPU) {
m_cudaNvSciSignalDeviceId = deviceIds[0];
m_cudaNvSciWaitDeviceId = deviceIds[1];
} else {
m_cudaNvSciSignalDeviceId = m_cudaNvSciWaitDeviceId = deviceIds[0];
}
m_bufSize = imageWidth * imageHeight * sizeof(unsigned int);
}
void cudaNvSci::initNvSci() {
checkNvSciErrors(NvSciSyncModuleOpen(&syncModule));
checkNvSciErrors(NvSciBufModuleOpen(&buffModule));
fence = (NvSciSyncFence *)calloc(1, sizeof(NvSciSyncFence));
}
void cudaNvSci::runCudaNvSci(std::string &image_filename) {
initNvSci();
cudaNvSciSignal rotateAndSignal(buffModule, syncModule,
m_cudaNvSciSignalDeviceId, m_bufSize,
imageWidth, imageHeight, fence);
cudaNvSciWait waitAndGrayscale(buffModule, syncModule,
m_cudaNvSciWaitDeviceId, m_bufSize, fence);
rawBufUnreconciledList[0] = rotateAndSignal.getNvSciRawBufAttrList();
rawBufUnreconciledList[1] = waitAndGrayscale.getNvSciRawBufAttrList();
createNvSciRawBufObj();
imageBufUnreconciledList[0] = rotateAndSignal.getNvSciImageBufAttrList();
createNvSciBufImageObj();
rotateAndSignal.cudaImportNvSciRawBuf(rawBufObj);
rotateAndSignal.cudaImportNvSciImage(imageBufObj);
waitAndGrayscale.cudaImportNvSciRawBuf(rawBufObj);
syncUnreconciledList[0] = rotateAndSignal.getNvSciSyncAttrList();
syncUnreconciledList[1] = waitAndGrayscale.getNvSciSyncAttrList();
createNvSciSyncObj();
rotateAndSignal.cudaImportNvSciSemaphore(syncObj);
waitAndGrayscale.cudaImportNvSciSemaphore(syncObj);
std::thread rotateThread(&thread_rotateAndSignal, &rotateAndSignal,
image_data);
std::thread grayscaleThread(&thread_waitAndGrayscale, &waitAndGrayscale,
image_filename, imageWidth, imageHeight);
rotateThread.join();
grayscaleThread.join();
}
void cudaNvSci::createNvSciRawBufObj() {
int numAttrList = 2;
checkNvSciErrors(NvSciBufAttrListReconcile(rawBufUnreconciledList,
numAttrList, &rawBufReconciledList,
&buffConflictList));
checkNvSciErrors(NvSciBufObjAlloc(rawBufReconciledList, &rawBufObj));
printf("created NvSciBufObj\n");
}
void cudaNvSci::createNvSciBufImageObj() {
int numAttrList = 1;
checkNvSciErrors(NvSciBufAttrListReconcile(
imageBufUnreconciledList, numAttrList, &imageBufReconciledList,
&imageBufConflictList));
checkNvSciErrors(NvSciBufObjAlloc(imageBufReconciledList, &imageBufObj));
printf("created NvSciBufImageObj\n");
}
void cudaNvSci::createNvSciSyncObj() {
int numAttrList = 2;
checkNvSciErrors(NvSciSyncAttrListReconcile(syncUnreconciledList, numAttrList,
&syncReconciledList,
&syncConflictList));
checkNvSciErrors(NvSciSyncObjAlloc(syncReconciledList, &syncObj));
printf("created NvSciSyncObj\n");
}

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@@ -0,0 +1,101 @@
/* 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.
*/
#ifndef CUDANVSCI_H
#define CUDANVSCI_H
#include <cuda_runtime.h>
#include <helper_cuda.h>
#include <nvscibuf.h>
#include <nvscisync.h>
#include <vector>
#define checkNvSciErrors(call) \
do { \
NvSciError _status = call; \
if (NvSciError_Success != _status) { \
printf( \
"NVSCI call in file '%s' in line %i returned" \
" %d, expected %d\n", \
__FILE__, __LINE__, _status, NvSciError_Success); \
fflush(stdout); \
exit(EXIT_FAILURE); \
} \
} while (0)
extern void rotateKernel(cudaTextureObject_t &texObj, const float angle,
unsigned int *d_outputData, const int imageWidth,
const int imageHeight, cudaStream_t stream);
extern void launchGrayScaleKernel(unsigned int *d_rgbaImage,
std::string image_filename, size_t imageWidth,
size_t imageHeight, cudaStream_t stream);
class cudaNvSci {
private:
int m_isMultiGPU;
int m_cudaNvSciSignalDeviceId;
int m_cudaNvSciWaitDeviceId;
unsigned char *image_data;
size_t m_bufSize;
size_t imageWidth;
size_t imageHeight;
public:
NvSciSyncModule syncModule;
NvSciBufModule buffModule;
NvSciSyncAttrList syncUnreconciledList[2];
NvSciSyncAttrList syncReconciledList;
NvSciSyncAttrList syncConflictList;
NvSciBufAttrList rawBufUnreconciledList[2];
NvSciBufAttrList imageBufUnreconciledList[2];
NvSciBufAttrList rawBufReconciledList;
NvSciBufAttrList buffConflictList;
NvSciBufAttrList imageBufReconciledList;
NvSciBufAttrList imageBufConflictList;
NvSciBufAttrList buffAttrListOut;
NvSciSyncObj syncObj;
NvSciBufObj rawBufObj;
NvSciBufObj imageBufObj;
NvSciSyncFence *fence;
cudaNvSci(int isMultiGPU, std::vector<int> &deviceIds,
unsigned char *image_data, size_t imageWidth, size_t imageHeight);
void initNvSci();
void runCudaNvSci(std::string &image_filename);
void createNvSciRawBufObj();
void createNvSciSyncObj();
void createNvSciBufImageObj();
};
#endif // CUDANVSCI_H

View File

@@ -0,0 +1,120 @@
/* 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.
*/
#include <cuda.h>
#include <helper_cuda.h>
#include <helper_image.h>
// convert floating point rgba color to 32-bit integer
__device__ unsigned int rgbaFloatToInt(float4 rgba) {
rgba.x = __saturatef(rgba.x); // clamp to [0.0, 1.0]
rgba.y = __saturatef(rgba.y);
rgba.z = __saturatef(rgba.z);
rgba.w = __saturatef(rgba.w);
return ((unsigned int)(rgba.w * 255.0f) << 24) |
((unsigned int)(rgba.z * 255.0f) << 16) |
((unsigned int)(rgba.y * 255.0f) << 8) |
((unsigned int)(rgba.x * 255.0f));
}
////////////////////////////////////////////////////////////////////////////////
//! Rotate an image using texture lookups
//! @param outputData output data in global memory
////////////////////////////////////////////////////////////////////////////////
static __global__ void transformKernel(unsigned int *outputData, int width,
int height, float theta,
cudaTextureObject_t tex) {
// calculate normalized texture coordinates
unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
unsigned int y = blockIdx.y * blockDim.y + threadIdx.y;
float u = (float)x - (float)width / 2;
float v = (float)y - (float)height / 2;
float tu = u * cosf(theta) - v * sinf(theta);
float tv = v * cosf(theta) + u * sinf(theta);
tu /= (float)width;
tv /= (float)height;
// read from texture and write to global memory
float4 pix = tex2D<float4>(tex, tu + 0.5f, tv + 0.5f);
unsigned int pixelInt = rgbaFloatToInt(pix);
outputData[y * width + x] = pixelInt;
}
static __global__ void rgbToGrayscaleKernel(unsigned int *rgbaImage,
size_t imageWidth,
size_t imageHeight) {
size_t gidX = blockDim.x * blockIdx.x + threadIdx.x;
uchar4 *pixArray = (uchar4 *)rgbaImage;
for (int pixId = gidX; pixId < imageWidth * imageHeight;
pixId += gridDim.x * blockDim.x) {
uchar4 dataA = pixArray[pixId];
unsigned char grayscale =
(unsigned char)(dataA.x * 0.3 + dataA.y * 0.59 + dataA.z * 0.11);
uchar4 dataB = make_uchar4(grayscale, grayscale, grayscale, 0);
pixArray[pixId] = dataB;
}
}
void launchGrayScaleKernel(unsigned int *d_rgbaImage,
std::string image_filename, size_t imageWidth,
size_t imageHeight, cudaStream_t stream) {
int numThreadsPerBlock = 1024;
int numOfBlocks = (imageWidth * imageHeight) / numThreadsPerBlock;
rgbToGrayscaleKernel<<<numOfBlocks, numThreadsPerBlock, 0, stream>>>(
d_rgbaImage, imageWidth, imageHeight);
unsigned int *outputData =
(unsigned int *)malloc(sizeof(unsigned int) * imageWidth * imageHeight);
checkCudaErrors(cudaMemcpyAsync(
outputData, d_rgbaImage, sizeof(unsigned int) * imageWidth * imageHeight,
cudaMemcpyDeviceToHost, stream));
checkCudaErrors(cudaStreamSynchronize(stream));
char outputFilename[1024];
strcpy(outputFilename, image_filename.c_str());
strcpy(outputFilename + image_filename.length() - 4, "_out.ppm");
sdkSavePPM4ub(outputFilename, (unsigned char *)outputData, imageWidth,
imageHeight);
printf("Wrote '%s'\n", outputFilename);
free(outputData);
}
void rotateKernel(cudaTextureObject_t &texObj, const float angle,
unsigned int *d_outputData, const int imageWidth,
const int imageHeight, cudaStream_t stream) {
dim3 dimBlock(8, 8, 1);
dim3 dimGrid(imageWidth / dimBlock.x, imageHeight / dimBlock.y, 1);
transformKernel<<<dimGrid, dimBlock, 0, stream>>>(d_outputData, imageWidth,
imageHeight, angle, texObj);
}

File diff suppressed because one or more lines are too long

101
Samples/cudaNvSci/main.cpp Normal file
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@@ -0,0 +1,101 @@
/* 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.
*/
#include <cuda.h>
#include <vector>
#include "cudaNvSci.h"
#include <helper_cuda.h>
#include <helper_image.h>
void loadImageData(const std::string &filename, const char **argv,
unsigned char **image_data, uint32_t &imageWidth,
uint32_t &imageHeight) {
// load image (needed so we can get the width and height before we create
// the window
char *image_path = sdkFindFilePath(filename.c_str(), argv[0]);
if (image_path == 0) {
printf("Error finding image file '%s'\n", filename.c_str());
exit(EXIT_FAILURE);
}
sdkLoadPPM4(image_path, image_data, &imageWidth, &imageHeight);
if (!image_data) {
printf("Error opening file '%s'\n", image_path);
exit(EXIT_FAILURE);
}
printf("Loaded '%s', %d x %d pixels\n", image_path, imageWidth, imageHeight);
}
int main(int argc, const char **argv) {
int numOfGPUs = 0;
std::vector<int> deviceIds;
checkCudaErrors(cudaGetDeviceCount(&numOfGPUs));
printf("%d GPUs found\n", numOfGPUs);
if (!numOfGPUs) {
exit(EXIT_WAIVED);
} else {
for (int devID = 0; devID < numOfGPUs; devID++) {
int major = 0, minor = 0;
checkCudaErrors(cudaDeviceGetAttribute(
&major, cudaDevAttrComputeCapabilityMajor, devID));
checkCudaErrors(cudaDeviceGetAttribute(
&minor, cudaDevAttrComputeCapabilityMinor, devID));
if (major >= 6) {
deviceIds.push_back(devID);
}
}
if (deviceIds.size() == 0) {
printf(
"cudaNvSci requires one or more GPUs of Pascal(SM 6.0) or higher "
"archs\nWaiving..\n");
exit(EXIT_WAIVED);
}
}
std::string image_filename = "lenaRGB.ppm";
if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
getCmdLineArgumentString(argc, (const char **)argv, "file",
(char **)&image_filename);
}
uint32_t imageWidth = 0;
uint32_t imageHeight = 0;
unsigned char *image_data = NULL;
loadImageData(image_filename, argv, &image_data, imageWidth, imageHeight);
cudaNvSci cudaNvSciApp(deviceIds.size() > 1, deviceIds, image_data,
imageWidth, imageHeight);
cudaNvSciApp.runCudaNvSci(image_filename);
return EXIT_SUCCESS;
}

View File

@@ -31,7 +31,7 @@ cudaMallocManaged, cudaDeviceSynchronize, cudaFuncSetAttribute, cudaEventCreate,
## Prerequisites
Download and install the [CUDA Toolkit 10.1](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

View File

@@ -33,7 +33,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.props" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@@ -102,6 +102,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 10.1.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 10.2.targets" />
</ImportGroup>
</Project>

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