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add and update samples with CUDA 11.3 support

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Rutwik Choughule 2021-04-16 11:54:26 +05:30
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README.md
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@ -1,11 +1,17 @@
# CUDA Samples
Samples for CUDA Developers which demonstrates features in CUDA Toolkit. This version supports [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads).
Samples for CUDA Developers which demonstrates features in CUDA Toolkit. This version supports [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads).
## Release Notes
This section describes the release notes for the CUDA Samples on GitHub only.
### CUDA 11.3
* Added `streamOrderedAllocationIPC`. Demonstrates Inter Process Communication using one process per GPU for computation.
* Added `simpleCUBLAS_LU`. Demonstrates batched matrix LU decomposition using cuBLAS API `cublas<t>getrfBatched()`
* Updated `simpleVulkan`. Demonstrates use of timeline semaphore.
* Updated multiple samples to use pinned memory using `cudaMallocHost()`.
### CUDA 11.2
* Added `streamOrderedAllocation`. Demonstrates stream ordered memory allocation on a GPU using cudaMallocAsync and cudaMemPool family of APIs.
* Added `streamOrderedAllocationP2P`. Demonstrates peer-to-peer access of stream ordered memory allocated using cudaMallocAsync and cudaMemPool family of APIs.
@ -103,7 +109,7 @@ This is the first release of CUDA Samples on GitHub:
### Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
For system requirements and installation instructions of cuda toolkit, please refer to the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/), and the [Windows Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html).
### Getting the CUDA Samples
@ -160,38 +166,39 @@ The samples makefiles can take advantage of certain options:
### Samples by OS
#### Linux
**[warpAggregatedAtomicsCG](./Samples/warpAggregatedAtomicsCG)** | **[boxFilterNPP](./Samples/boxFilterNPP)** | **[streamOrderedAllocationP2P](./Samples/streamOrderedAllocationP2P)** | **[binaryPartitionCG](./Samples/binaryPartitionCG)** |
**[bandwidthTest](./Samples/bandwidthTest)** | **[batchedLabelMarkersAndLabelCompressionNPP](./Samples/batchedLabelMarkersAndLabelCompressionNPP)** | **[bf16TensorCoreGemm](./Samples/bf16TensorCoreGemm)** | **[binaryPartitionCG](./Samples/binaryPartitionCG)** |
---|---|---|---|
**[dmmaTensorCoreGemm](./Samples/dmmaTensorCoreGemm)** | **[EGLStream_CUDA_Interop](./Samples/EGLStream_CUDA_Interop)** | **[conjugateGradientMultiBlockCG](./Samples/conjugateGradientMultiBlockCG)** | **[simpleIPC](./Samples/simpleIPC)** |
**[memMapIPCDrv](./Samples/memMapIPCDrv)** | **[vectorAddMMAP](./Samples/vectorAddMMAP)** | **[shfl_scan](./Samples/shfl_scan)** | **[simpleZeroCopy](./Samples/simpleZeroCopy)** |
**[conjugateGradientCudaGraphs](./Samples/conjugateGradientCudaGraphs)** | **[globalToShmemAsyncCopy](./Samples/globalToShmemAsyncCopy)** | **[cudaNvSciNvMedia](./Samples/cudaNvSciNvMedia)** | **[nvJPEG](./Samples/nvJPEG)** |
**[batchedLabelMarkersAndLabelCompressionNPP](./Samples/batchedLabelMarkersAndLabelCompressionNPP)** | **[watershedSegmentationNPP](./Samples/watershedSegmentationNPP)** | **[simpleCudaGraphs](./Samples/simpleCudaGraphs)** | **[streamOrderedAllocation](./Samples/streamOrderedAllocation)** |
**[deviceQuery](./Samples/deviceQuery)** | **[simpleVoteIntrinsics](./Samples/simpleVoteIntrinsics)** | **[simpleCUBLASXT](./Samples/simpleCUBLASXT)** | **[simpleAttributes](./Samples/simpleAttributes)** |
**[cudaNvSci](./Samples/cudaNvSci)** | **[tf32TensorCoreGemm](./Samples/tf32TensorCoreGemm)** | **[UnifiedMemoryPerf](./Samples/UnifiedMemoryPerf)** | **[cudaCompressibleMemory](./Samples/cudaCompressibleMemory)** |
**[bf16TensorCoreGemm](./Samples/bf16TensorCoreGemm)** | **[cuSolverDn_LinearSolver](./Samples/cuSolverDn_LinearSolver)** | **[vulkanImageCUDA](./Samples/vulkanImageCUDA)** | **[conjugateGradientMultiDeviceCG](./Samples/conjugateGradientMultiDeviceCG)** |
**[matrixMulDrv](./Samples/matrixMulDrv)** | **[cuSolverSp_LinearSolver](./Samples/cuSolverSp_LinearSolver)** | **[simpleCUFFT](./Samples/simpleCUFFT)** | **[reduction](./Samples/reduction)** |
**[nvJPEG_encoder](./Samples/nvJPEG_encoder)** | **[simpleDrvRuntime](./Samples/simpleDrvRuntime)** | **[MersenneTwisterGP11213](./Samples/MersenneTwisterGP11213)** | **[simpleAWBarrier](./Samples/simpleAWBarrier)** |
**[immaTensorCoreGemm](./Samples/immaTensorCoreGemm)** | **[bandwidthTest](./Samples/bandwidthTest)** | **[concurrentKernels](./Samples/concurrentKernels)** | **[simpleCUBLAS](./Samples/simpleCUBLAS)** |
**[NV12toBGRandResize](./Samples/NV12toBGRandResize)** | **[simpleGL](./Samples/simpleGL)** | **[cudaTensorCoreGemm](./Samples/cudaTensorCoreGemm)** | **[jacobiCudaGraphs](./Samples/jacobiCudaGraphs)** |
**[simpleVulkan](./Samples/simpleVulkan)** | **[vectorAdd_nvrtc](./Samples/vectorAdd_nvrtc)** | **[cannyEdgeDetectorNPP](./Samples/cannyEdgeDetectorNPP)** | **[p2pBandwidthLatencyTest](./Samples/p2pBandwidthLatencyTest)** |
**[simpleVulkanMMAP](./Samples/simpleVulkanMMAP)** | **[cudaOpenMP](./Samples/cudaOpenMP)** | **[matrixMul](./Samples/matrixMul)** | **[systemWideAtomics](./Samples/systemWideAtomics)** |
**[boxFilterNPP](./Samples/boxFilterNPP)** | **[cannyEdgeDetectorNPP](./Samples/cannyEdgeDetectorNPP)** | **[concurrentKernels](./Samples/concurrentKernels)** | **[conjugateGradientCudaGraphs](./Samples/conjugateGradientCudaGraphs)** |
**[conjugateGradientMultiBlockCG](./Samples/conjugateGradientMultiBlockCG)** | **[conjugateGradientMultiDeviceCG](./Samples/conjugateGradientMultiDeviceCG)** | **[cudaCompressibleMemory](./Samples/cudaCompressibleMemory)** | **[cudaNvSci](./Samples/cudaNvSci)** |
**[cudaNvSciNvMedia](./Samples/cudaNvSciNvMedia)** | **[cudaOpenMP](./Samples/cudaOpenMP)** | **[cudaTensorCoreGemm](./Samples/cudaTensorCoreGemm)** | **[cuSolverDn_LinearSolver](./Samples/cuSolverDn_LinearSolver)** |
**[cuSolverSp_LinearSolver](./Samples/cuSolverSp_LinearSolver)** | **[deviceQuery](./Samples/deviceQuery)** | **[dmmaTensorCoreGemm](./Samples/dmmaTensorCoreGemm)** | **[EGLStream_CUDA_Interop](./Samples/EGLStream_CUDA_Interop)** |
**[globalToShmemAsyncCopy](./Samples/globalToShmemAsyncCopy)** | **[immaTensorCoreGemm](./Samples/immaTensorCoreGemm)** | **[jacobiCudaGraphs](./Samples/jacobiCudaGraphs)** | **[matrixMul](./Samples/matrixMul)** |
**[matrixMulDrv](./Samples/matrixMulDrv)** | **[memMapIPCDrv](./Samples/memMapIPCDrv)** | **[MersenneTwisterGP11213](./Samples/MersenneTwisterGP11213)** | **[NV12toBGRandResize](./Samples/NV12toBGRandResize)** |
**[nvJPEG](./Samples/nvJPEG)** | **[nvJPEG_encoder](./Samples/nvJPEG_encoder)** | **[p2pBandwidthLatencyTest](./Samples/p2pBandwidthLatencyTest)** | **[reduction](./Samples/reduction)** |
**[shfl_scan](./Samples/shfl_scan)** | **[simpleAttributes](./Samples/simpleAttributes)** | **[simpleAWBarrier](./Samples/simpleAWBarrier)** | **[simpleCUBLAS](./Samples/simpleCUBLAS)** |
**[simpleCUBLASXT](./Samples/simpleCUBLASXT)** | **[simpleCUBLAS_LU](./Samples/simpleCUBLAS_LU)** | **[simpleCudaGraphs](./Samples/simpleCudaGraphs)** | **[simpleCUFFT](./Samples/simpleCUFFT)** |
**[simpleDrvRuntime](./Samples/simpleDrvRuntime)** | **[simpleGL](./Samples/simpleGL)** | **[simpleIPC](./Samples/simpleIPC)** | **[simpleVoteIntrinsics](./Samples/simpleVoteIntrinsics)** |
**[simpleVulkan](./Samples/simpleVulkan)** | **[simpleVulkanMMAP](./Samples/simpleVulkanMMAP)** | **[simpleZeroCopy](./Samples/simpleZeroCopy)** | **[streamOrderedAllocation](./Samples/streamOrderedAllocation)** |
**[streamOrderedAllocationIPC](./Samples/streamOrderedAllocationIPC)** | **[streamOrderedAllocationP2P](./Samples/streamOrderedAllocationP2P)** | **[systemWideAtomics](./Samples/systemWideAtomics)** | **[tf32TensorCoreGemm](./Samples/tf32TensorCoreGemm)** |
**[UnifiedMemoryPerf](./Samples/UnifiedMemoryPerf)** | **[vectorAddMMAP](./Samples/vectorAddMMAP)** | **[vectorAdd_nvrtc](./Samples/vectorAdd_nvrtc)** | **[vulkanImageCUDA](./Samples/vulkanImageCUDA)** |
**[warpAggregatedAtomicsCG](./Samples/warpAggregatedAtomicsCG)** | **[watershedSegmentationNPP](./Samples/watershedSegmentationNPP)** |
#### Windows
**[warpAggregatedAtomicsCG](./Samples/warpAggregatedAtomicsCG)** | **[boxFilterNPP](./Samples/boxFilterNPP)** | **[streamOrderedAllocationP2P](./Samples/streamOrderedAllocationP2P)** | **[binaryPartitionCG](./Samples/binaryPartitionCG)** |
**[bandwidthTest](./Samples/bandwidthTest)** | **[batchedLabelMarkersAndLabelCompressionNPP](./Samples/batchedLabelMarkersAndLabelCompressionNPP)** | **[bf16TensorCoreGemm](./Samples/bf16TensorCoreGemm)** | **[binaryPartitionCG](./Samples/binaryPartitionCG)** |
---|---|---|---|
**[dmmaTensorCoreGemm](./Samples/dmmaTensorCoreGemm)** | **[conjugateGradientMultiBlockCG](./Samples/conjugateGradientMultiBlockCG)** | **[simpleIPC](./Samples/simpleIPC)** | **[memMapIPCDrv](./Samples/memMapIPCDrv)** |
**[vectorAddMMAP](./Samples/vectorAddMMAP)** | **[shfl_scan](./Samples/shfl_scan)** | **[simpleZeroCopy](./Samples/simpleZeroCopy)** | **[conjugateGradientCudaGraphs](./Samples/conjugateGradientCudaGraphs)** |
**[globalToShmemAsyncCopy](./Samples/globalToShmemAsyncCopy)** | **[nvJPEG](./Samples/nvJPEG)** | **[batchedLabelMarkersAndLabelCompressionNPP](./Samples/batchedLabelMarkersAndLabelCompressionNPP)** | **[simpleD3D12](./Samples/simpleD3D12)** |
**[watershedSegmentationNPP](./Samples/watershedSegmentationNPP)** | **[simpleCudaGraphs](./Samples/simpleCudaGraphs)** | **[streamOrderedAllocation](./Samples/streamOrderedAllocation)** | **[deviceQuery](./Samples/deviceQuery)** |
**[simpleVoteIntrinsics](./Samples/simpleVoteIntrinsics)** | **[simpleCUBLASXT](./Samples/simpleCUBLASXT)** | **[simpleAttributes](./Samples/simpleAttributes)** | **[tf32TensorCoreGemm](./Samples/tf32TensorCoreGemm)** |
**[UnifiedMemoryPerf](./Samples/UnifiedMemoryPerf)** | **[cudaCompressibleMemory](./Samples/cudaCompressibleMemory)** | **[bf16TensorCoreGemm](./Samples/bf16TensorCoreGemm)** | **[cuSolverDn_LinearSolver](./Samples/cuSolverDn_LinearSolver)** |
**[vulkanImageCUDA](./Samples/vulkanImageCUDA)** | **[conjugateGradientMultiDeviceCG](./Samples/conjugateGradientMultiDeviceCG)** | **[matrixMulDrv](./Samples/matrixMulDrv)** | **[cuSolverSp_LinearSolver](./Samples/cuSolverSp_LinearSolver)** |
**[simpleCUFFT](./Samples/simpleCUFFT)** | **[reduction](./Samples/reduction)** | **[nvJPEG_encoder](./Samples/nvJPEG_encoder)** | **[simpleDrvRuntime](./Samples/simpleDrvRuntime)** |
**[simpleD3D11](./Samples/simpleD3D11)** | **[MersenneTwisterGP11213](./Samples/MersenneTwisterGP11213)** | **[simpleAWBarrier](./Samples/simpleAWBarrier)** | **[immaTensorCoreGemm](./Samples/immaTensorCoreGemm)** |
**[bandwidthTest](./Samples/bandwidthTest)** | **[concurrentKernels](./Samples/concurrentKernels)** | **[simpleCUBLAS](./Samples/simpleCUBLAS)** | **[NV12toBGRandResize](./Samples/NV12toBGRandResize)** |
**[simpleGL](./Samples/simpleGL)** | **[cudaTensorCoreGemm](./Samples/cudaTensorCoreGemm)** | **[jacobiCudaGraphs](./Samples/jacobiCudaGraphs)** | **[simpleVulkan](./Samples/simpleVulkan)** |
**[vectorAdd_nvrtc](./Samples/vectorAdd_nvrtc)** | **[cannyEdgeDetectorNPP](./Samples/cannyEdgeDetectorNPP)** | **[p2pBandwidthLatencyTest](./Samples/p2pBandwidthLatencyTest)** | **[simpleVulkanMMAP](./Samples/simpleVulkanMMAP)** |
**[cudaOpenMP](./Samples/cudaOpenMP)** | **[matrixMul](./Samples/matrixMul)** |
**[boxFilterNPP](./Samples/boxFilterNPP)** | **[cannyEdgeDetectorNPP](./Samples/cannyEdgeDetectorNPP)** | **[concurrentKernels](./Samples/concurrentKernels)** | **[conjugateGradientCudaGraphs](./Samples/conjugateGradientCudaGraphs)** |
**[conjugateGradientMultiBlockCG](./Samples/conjugateGradientMultiBlockCG)** | **[conjugateGradientMultiDeviceCG](./Samples/conjugateGradientMultiDeviceCG)** | **[cudaCompressibleMemory](./Samples/cudaCompressibleMemory)** | **[cudaOpenMP](./Samples/cudaOpenMP)** |
**[cudaTensorCoreGemm](./Samples/cudaTensorCoreGemm)** | **[cuSolverDn_LinearSolver](./Samples/cuSolverDn_LinearSolver)** | **[cuSolverSp_LinearSolver](./Samples/cuSolverSp_LinearSolver)** | **[deviceQuery](./Samples/deviceQuery)** |
**[dmmaTensorCoreGemm](./Samples/dmmaTensorCoreGemm)** | **[globalToShmemAsyncCopy](./Samples/globalToShmemAsyncCopy)** | **[immaTensorCoreGemm](./Samples/immaTensorCoreGemm)** | **[jacobiCudaGraphs](./Samples/jacobiCudaGraphs)** |
**[matrixMul](./Samples/matrixMul)** | **[matrixMulDrv](./Samples/matrixMulDrv)** | **[memMapIPCDrv](./Samples/memMapIPCDrv)** | **[MersenneTwisterGP11213](./Samples/MersenneTwisterGP11213)** |
**[NV12toBGRandResize](./Samples/NV12toBGRandResize)** | **[nvJPEG](./Samples/nvJPEG)** | **[nvJPEG_encoder](./Samples/nvJPEG_encoder)** | **[p2pBandwidthLatencyTest](./Samples/p2pBandwidthLatencyTest)** |
**[reduction](./Samples/reduction)** | **[shfl_scan](./Samples/shfl_scan)** | **[simpleAttributes](./Samples/simpleAttributes)** | **[simpleAWBarrier](./Samples/simpleAWBarrier)** |
**[simpleCUBLAS](./Samples/simpleCUBLAS)** | **[simpleCUBLASXT](./Samples/simpleCUBLASXT)** | **[simpleCUBLAS_LU](./Samples/simpleCUBLAS_LU)** | **[simpleCudaGraphs](./Samples/simpleCudaGraphs)** |
**[simpleCUFFT](./Samples/simpleCUFFT)** | **[simpleD3D11](./Samples/simpleD3D11)** | **[simpleD3D12](./Samples/simpleD3D12)** | **[simpleDrvRuntime](./Samples/simpleDrvRuntime)** |
**[simpleGL](./Samples/simpleGL)** | **[simpleIPC](./Samples/simpleIPC)** | **[simpleVoteIntrinsics](./Samples/simpleVoteIntrinsics)** | **[simpleVulkan](./Samples/simpleVulkan)** |
**[simpleVulkanMMAP](./Samples/simpleVulkanMMAP)** | **[simpleZeroCopy](./Samples/simpleZeroCopy)** | **[streamOrderedAllocation](./Samples/streamOrderedAllocation)** | **[streamOrderedAllocationP2P](./Samples/streamOrderedAllocationP2P)** |
**[tf32TensorCoreGemm](./Samples/tf32TensorCoreGemm)** | **[UnifiedMemoryPerf](./Samples/UnifiedMemoryPerf)** | **[vectorAddMMAP](./Samples/vectorAddMMAP)** | **[vectorAdd_nvrtc](./Samples/vectorAdd_nvrtc)** |
**[vulkanImageCUDA](./Samples/vulkanImageCUDA)** | **[warpAggregatedAtomicsCG](./Samples/warpAggregatedAtomicsCG)** | **[watershedSegmentationNPP](./Samples/watershedSegmentationNPP)** |
## Dependencies

6
Samples/EGLStream_CUDA_Interop/Makefile
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@ -285,6 +285,12 @@ ifeq ($(TARGET_OS),android)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - EGLStream_CUDA_Interop is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))

2
Samples/EGLStream_CUDA_Interop/README.md
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@ -30,7 +30,7 @@ cuDeviceGet, cuDeviceGetAttribute, cuDeviceComputeCapability, cuDeviceGetCount,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

29
Samples/MersenneTwisterGP11213/Makefile
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@ -263,6 +263,14 @@ ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - MersenneTwisterGP11213 is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
@ -297,6 +305,10 @@ ALL_CCFLAGS += --threads 0
LIBRARIES += -lcurand_static -lculibos
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
@ -304,16 +316,23 @@ all: build
build: MersenneTwisterGP11213
check.deps:
ifeq ($(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
MersenneTwister.o:MersenneTwister.cpp
$(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
$(EXEC) $(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)
$(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
./MersenneTwisterGP11213
$(EXEC) ./MersenneTwisterGP11213
clean:
rm -f MersenneTwisterGP11213 MersenneTwister.o

188
Samples/MersenneTwisterGP11213/MersenneTwister.cpp
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@ -47,138 +47,134 @@
float compareResults(int rand_n, float *h_RandGPU, float *h_RandCPU);
const int DEFAULT_RAND_N = 2400000;
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]);
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);
// 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;
// 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");
}
if (checkCmdLineFlag(argc, (const char **)argv, "count")) {
rand_n = getCmdLineArgumentInt(argc, (const char **)argv, "count");
}
printf("Allocating data for %i samples...\n", rand_n);
printf("Allocating data for %i samples...\n", rand_n);
// parsing the seed
int seed = DEFAULT_SEED;
// parsing the seed
int seed = DEFAULT_SEED;
if (checkCmdLineFlag(argc, (const char **) argv, "seed"))
{
seed = getCmdLineArgumentInt(argc, (const char **) argv, "seed");
}
if (checkCmdLineFlag(argc, (const char **)argv, "seed")) {
seed = getCmdLineArgumentInt(argc, (const char **)argv, "seed");
}
printf("Seeding with %i ...\n", seed);
printf("Seeding with %i ...\n", seed);
cudaStream_t stream;
checkCudaErrors(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
cudaStream_t stream;
checkCudaErrors(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
float *d_Rand;
checkCudaErrors(cudaMalloc((void **)&d_Rand, rand_n * sizeof(float)));
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 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));
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));
//
// Example 1: Compare random numbers generated on GPU and CPU
float *h_RandGPU;
checkCudaErrors(cudaMallocHost(&h_RandGPU, rand_n * sizeof(float)));
printf("Generating random numbers on GPU...\n\n");
checkCudaErrors(curandGenerateUniform(prngGPU, (float *) d_Rand, rand_n));
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));
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));
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));
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);
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;
//
// Example 2: Timing of random number generation on GPU
const int numIterations = 10;
int i;
StopWatchInterface *hTimer;
sdkCreateTimer(&hTimer);
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
sdkCreateTimer(&hTimer);
sdkResetTimer(&hTimer);
sdkStartTimer(&hTimer);
for (i = 0; i < numIterations; i++) {
checkCudaErrors(curandGenerateUniform(prngGPU, (float *)d_Rand, rand_n));
}
for (i = 0; i < numIterations; i++)
{
checkCudaErrors(curandGenerateUniform(prngGPU, (float *) d_Rand, rand_n));
}
checkCudaErrors(cudaStreamSynchronize(stream));
sdkStopTimer(&hTimer);
checkCudaErrors(cudaStreamSynchronize(stream));
sdkStopTimer(&hTimer);
double gpuTime = 1.0e-3 * sdkGetTimerValue(&hTimer) / (double)numIterations;
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("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");
printf("Shutting down...\n");
checkCudaErrors(curandDestroyGenerator(prngGPU));
checkCudaErrors(curandDestroyGenerator(prngCPU));
checkCudaErrors(cudaStreamDestroy(stream));
checkCudaErrors(cudaFree(d_Rand));
sdkDeleteTimer(&hTimer);
checkCudaErrors(cudaFreeHost(h_RandGPU));
free(h_RandCPU);
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);
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.;
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);
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;
}
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);
float L1norm = (float)(sum_delta / sum_ref);
printf("Max absolute error: %E\n", max_delta);
printf("L1 norm: %E\n\n", L1norm);
return L1norm;
return L1norm;
}

4
Samples/MersenneTwisterGP11213/MersenneTwisterGP11213_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/MersenneTwisterGP11213/MersenneTwisterGP11213_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/MersenneTwisterGP11213/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/NV12toBGRandResize/NV12toBGRandResize_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/NV12toBGRandResize/NV12toBGRandResize_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/NV12toBGRandResize/README.md
View File

@ -27,7 +27,7 @@ cudaMemcpy2D, cudaMallocManaged
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

2
Samples/UnifiedMemoryPerf/README.md
View File

@ -28,7 +28,7 @@ cudaMallocManaged, cudaStreamAttachMemAsync, cudaMemcpyAsync, cudaMallocHost, cu
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/UnifiedMemoryPerf/UnifiedMemoryPerf_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -111,6 +111,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/UnifiedMemoryPerf/UnifiedMemoryPerf_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/bandwidthTest/README.md
View File

@ -27,7 +27,7 @@ cudaSetDevice, cudaHostAlloc, cudaFree, cudaMallocHost, cudaFreeHost, cudaMemcpy
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/bandwidthTest/bandwidthTest_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/bandwidthTest/bandwidthTest_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

6
Samples/batchedLabelMarkersAndLabelCompressionNPP/Makefile
View File

@ -271,6 +271,12 @@ ifeq ($(TARGET_OS),darwin)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - batchedLabelMarkersAndLabelCompressionNPP is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))

2
Samples/batchedLabelMarkersAndLabelCompressionNPP/README.md
View File

@ -28,7 +28,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

93
Samples/batchedLabelMarkersAndLabelCompressionNPP/batchedLabelMarkersAndLabelCompressionNPP.cpp
View File

@ -36,11 +36,13 @@
#include <string.h>
#include <fstream>
#include <cuda_runtime.h>
#include <helper_cuda.h>
#include <helper_string.h>
#include <npp.h>
// Note: If you want to view these images we HIGHLY recommend using imagej
// which is free on the internet and works on most platforms
// which is free on the internet and works on most platforms
// because it is one of the few image viewing apps that can display 32
// bit integer image data. While it normalizes the data to floating
// point values for viewing it still provides a good representation of
@ -102,11 +104,12 @@ void tearDown() // Clean up and tear down
if (pUFBatchSrcDstImageListDev != 0) cudaFree(pUFBatchSrcDstImageListDev);
if (pUFBatchSrcImageListDev != 0) cudaFree(pUFBatchSrcImageListDev);
if (pUFBatchPerImageCompressedCountListHost != 0)
free(pUFBatchPerImageCompressedCountListHost);
cudaFreeHost(pUFBatchPerImageCompressedCountListHost);
if (pUFBatchSrcDstScratchBufferListHost != 0)
free(pUFBatchSrcDstScratchBufferListHost);
if (pUFBatchSrcDstImageListHost != 0) free(pUFBatchSrcDstImageListHost);
if (pUFBatchSrcImageListHost != 0) free(pUFBatchSrcImageListHost);
cudaFreeHost(pUFBatchSrcDstScratchBufferListHost);
if (pUFBatchSrcDstImageListHost != 0)
cudaFreeHost(pUFBatchSrcDstImageListHost);
if (pUFBatchSrcImageListHost != 0) cudaFreeHost(pUFBatchSrcImageListHost);
for (int j = 0; j < NUMBER_OF_IMAGES; j++) {
if (pUFCompressedLabelsScratchBufferDev[j] != 0)
@ -115,8 +118,8 @@ void tearDown() // Clean up and tear down
cudaFree(pUFGenerateLabelsScratchBufferDev[j]);
if (pUFLabelDev[j] != 0) cudaFree(pUFLabelDev[j]);
if (pInputImageDev[j] != 0) cudaFree(pInputImageDev[j]);
if (pUFLabelHost[j] != 0) free(pUFLabelHost[j]);
if (pInputImageHost[j] != 0) free(pInputImageHost[j]);
if (pUFLabelHost[j] != 0) cudaFreeHost(pUFLabelHost[j]);
if (pInputImageHost[j] != 0) cudaFreeHost(pInputImageHost[j]);
}
}
@ -177,7 +180,7 @@ int loadRaw8BitImage(Npp8u *pImage, int nWidth, int nHeight, int nImage) {
exit(EXIT_WAIVED);
}
bmpFile = fopen(InputFile, "rb");
FOPEN(bmpFile, InputFile, "rb");
} else if (nImage == 1) {
if (nWidth != 512 || nHeight != 512) return -1;
const char *fileName = "CT_skull_512x512_8u.raw";
@ -187,7 +190,7 @@ int loadRaw8BitImage(Npp8u *pImage, int nWidth, int nHeight, int nImage) {
exit(EXIT_WAIVED);
}
bmpFile = fopen(InputFile, "rb");
FOPEN(bmpFile, InputFile, "rb");
} else if (nImage == 2) {
if (nWidth != 509 || nHeight != 335) return -1;
const char *fileName = "PCB_METAL_509x335_8u.raw";
@ -197,7 +200,7 @@ int loadRaw8BitImage(Npp8u *pImage, int nWidth, int nHeight, int nImage) {
exit(EXIT_WAIVED);
}
bmpFile = fopen(InputFile, "rb");
FOPEN(bmpFile, InputFile, "rb");
} else if (nImage == 3) {
if (nWidth != 1024 || nHeight != 683) return -1;
const char *fileName = "PCB2_1024x683_8u.raw";
@ -207,7 +210,7 @@ int loadRaw8BitImage(Npp8u *pImage, int nWidth, int nHeight, int nImage) {
exit(EXIT_WAIVED);
}
bmpFile = fopen(InputFile, "rb");
FOPEN(bmpFile, InputFile, "rb");
} else if (nImage == 4) {
if (nWidth != 1280 || nHeight != 720) return -1;
const char *fileName = "PCB_1280x720_8u.raw";
@ -217,7 +220,7 @@ int loadRaw8BitImage(Npp8u *pImage, int nWidth, int nHeight, int nImage) {
exit(EXIT_WAIVED);
}
bmpFile = fopen(InputFile, "rb");
FOPEN(bmpFile, InputFile, "rb");
} else {
printf("Input file load failed.\n");
return -1;
@ -347,9 +350,11 @@ int main(int argc, char **argv) {
oSizeROI[nImage].width * sizeof(Npp32u) * oSizeROI[nImage].height);
if (cudaError != cudaSuccess) return NPP_MEMORY_ALLOCATION_ERR;
pInputImageHost[nImage] = reinterpret_cast<Npp8u *>(malloc(
checkCudaErrors(cudaMallocHost(
&(pInputImageHost[nImage]),
oSizeROI[nImage].width * sizeof(Npp8u) * oSizeROI[nImage].height));
pUFLabelHost[nImage] = reinterpret_cast<Npp32u *>(malloc(
checkCudaErrors(cudaMallocHost(
&(pUFLabelHost[nImage]),
oSizeROI[nImage].width * sizeof(Npp32u) * oSizeROI[nImage].height));
// Use UF functions throughout this sample.
@ -409,15 +414,15 @@ int main(int argc, char **argv) {
}
if (nImage == 0)
bmpFile = fopen(LabelMarkersOutputFile0.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersOutputFile0.c_str(), "wb");
else if (nImage == 1)
bmpFile = fopen(LabelMarkersOutputFile1.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersOutputFile1.c_str(), "wb");
else if (nImage == 2)
bmpFile = fopen(LabelMarkersOutputFile2.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersOutputFile2.c_str(), "wb");
else if (nImage == 3)
bmpFile = fopen(LabelMarkersOutputFile3.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersOutputFile3.c_str(), "wb");
else if (nImage == 4)
bmpFile = fopen(LabelMarkersOutputFile4.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersOutputFile4.c_str(), "wb");
if (bmpFile == NULL) return -1;
size_t nSize = 0;
@ -478,15 +483,15 @@ int main(int argc, char **argv) {
}
if (nImage == 0)
bmpFile = fopen(CompressedMarkerLabelsOutputFile0.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsOutputFile0.c_str(), "wb");
else if (nImage == 1)
bmpFile = fopen(CompressedMarkerLabelsOutputFile1.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsOutputFile1.c_str(), "wb");
else if (nImage == 2)
bmpFile = fopen(CompressedMarkerLabelsOutputFile2.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsOutputFile2.c_str(), "wb");
else if (nImage == 3)
bmpFile = fopen(CompressedMarkerLabelsOutputFile3.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsOutputFile3.c_str(), "wb");
else if (nImage == 4)
bmpFile = fopen(CompressedMarkerLabelsOutputFile4.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsOutputFile4.c_str(), "wb");
if (bmpFile == NULL) return -1;
nSize = 0;
@ -554,10 +559,11 @@ int main(int argc, char **argv) {
cudaMalloc((void **)&pUFBatchSrcDstImageListDev, nBatchImageListBytes);
if (cudaError != cudaSuccess) return NPP_MEMORY_ALLOCATION_ERR;
pUFBatchSrcImageListHost =
reinterpret_cast<NppiImageDescriptor *>(malloc(nBatchImageListBytes));
pUFBatchSrcDstImageListHost =
reinterpret_cast<NppiImageDescriptor *>(malloc(nBatchImageListBytes));
checkCudaErrors(
cudaMallocHost((void **)&pUFBatchSrcImageListHost, nBatchImageListBytes));
checkCudaErrors(cudaMallocHost((void **)&pUFBatchSrcDstImageListHost,
nBatchImageListBytes));
NppiSize oMaxROISize = {0, 0};
@ -620,15 +626,15 @@ int main(int argc, char **argv) {
// Save output to files
for (int nImage = 0; nImage < NUMBER_OF_IMAGES; nImage++) {
if (nImage == 0)
bmpFile = fopen(LabelMarkersBatchOutputFile0.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersBatchOutputFile0.c_str(), "wb");
else if (nImage == 1)
bmpFile = fopen(LabelMarkersBatchOutputFile1.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersBatchOutputFile1.c_str(), "wb");
else if (nImage == 2)
bmpFile = fopen(LabelMarkersBatchOutputFile2.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersBatchOutputFile2.c_str(), "wb");
else if (nImage == 3)
bmpFile = fopen(LabelMarkersBatchOutputFile3.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersBatchOutputFile3.c_str(), "wb");
else if (nImage == 4)
bmpFile = fopen(LabelMarkersBatchOutputFile4.c_str(), "wb");
FOPEN(bmpFile, LabelMarkersBatchOutputFile4.c_str(), "wb");
if (bmpFile == NULL) return -1;
size_t nSize = 0;
@ -652,12 +658,13 @@ int main(int argc, char **argv) {
// Allocate host side scratch buffer point and size list and initialize with
// device scratch buffer pointers
pUFBatchSrcDstScratchBufferListHost =
reinterpret_cast<NppiBufferDescriptor *>(
malloc(NUMBER_OF_IMAGES * sizeof(NppiBufferDescriptor)));
checkCudaErrors(
cudaMallocHost((void **)&pUFBatchSrcDstScratchBufferListHost,
NUMBER_OF_IMAGES * sizeof(NppiBufferDescriptor)));
pUFBatchPerImageCompressedCountListHost =
reinterpret_cast<Npp32u *>(malloc(NUMBER_OF_IMAGES * sizeof(Npp32u)));
checkCudaErrors(
cudaMallocHost((void **)&pUFBatchPerImageCompressedCountListHost,
+NUMBER_OF_IMAGES * sizeof(Npp32u)));
// Start buffer pointer at beginning of full per image buffer list sized
// pUFCompressedLabelsScratchBufferDev[0]
@ -728,15 +735,15 @@ int main(int argc, char **argv) {
// Save compressed label images into files
for (int nImage = 0; nImage < NUMBER_OF_IMAGES; nImage++) {
if (nImage == 0)
bmpFile = fopen(CompressedMarkerLabelsBatchOutputFile0.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsBatchOutputFile0.c_str(), "wb");
else if (nImage == 1)
bmpFile = fopen(CompressedMarkerLabelsBatchOutputFile1.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsBatchOutputFile1.c_str(), "wb");
else if (nImage == 2)
bmpFile = fopen(CompressedMarkerLabelsBatchOutputFile2.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsBatchOutputFile2.c_str(), "wb");
else if (nImage == 3)
bmpFile = fopen(CompressedMarkerLabelsBatchOutputFile3.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsBatchOutputFile3.c_str(), "wb");
else if (nImage == 4)
bmpFile = fopen(CompressedMarkerLabelsBatchOutputFile4.c_str(), "wb");
FOPEN(bmpFile, CompressedMarkerLabelsBatchOutputFile4.c_str(), "wb");
if (bmpFile == NULL) return -1;
size_t nSize = 0;

4
Samples/batchedLabelMarkersAndLabelCompressionNPP/batchedLabelMarkersAndLabelCompressionNPP_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/batchedLabelMarkersAndLabelCompressionNPP/batchedLabelMarkersAndLabelCompressionNPP_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/bf16TensorCoreGemm/README.md
View File

@ -27,7 +27,7 @@ cudaMallocManaged, cudaDeviceSynchronize, cudaFuncSetAttribute, cudaEventCreate,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/bf16TensorCoreGemm/bf16TensorCoreGemm_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/bf16TensorCoreGemm/bf16TensorCoreGemm_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/binaryPartitionCG/README.md
View File

@ -24,7 +24,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

166
Samples/binaryPartitionCG/binaryPartitionCG.cu
View File

@ -31,14 +31,16 @@
* 1.) Each thread loads a value from random array.
* 2.) then checks if it is odd or even.
* 3.) create binary partition group based on the above predicate
* 4.) we count the number of odd/even in the group based on size of the binary groups
* 4.) we count the number of odd/even in the group based on size of the binary
groups
* 5.) write it global counter of odd.
* 6.) sum the values loaded by individual threads(using reduce) and write it to global
* even & odd elements sum.
* 6.) sum the values loaded by individual threads(using reduce) and write it to
global even & odd elements sum.
*
* **NOTE** : binary_partition results in splitting warp into divergent thread groups
this is not good from performance perspective, but in cases where warp
divergence is inevitable one can use binary_partition group.
* **NOTE** :
* binary_partition results in splitting warp into divergent thread groups
* this is not good from performance perspective, but in cases where warp
* divergence is inevitable one can use binary_partition group.
*/
#include <stdio.h>
@ -48,108 +50,110 @@
namespace cg = cooperative_groups;
void initOddEvenArr(int *inputArr, unsigned int size)
{
for (int i=0; i < size; i++)
{
inputArr[i] = rand() % 50;
}
void initOddEvenArr(int *inputArr, unsigned int size) {
for (int i = 0; i < size; i++) {
inputArr[i] = rand() % 50;
}
}
/**
* CUDA kernel device code
*
* Creates cooperative groups and performs odd/even counting & summation.
*/
__global__ void oddEvenCountAndSumCG(int *inputArr, int *numOfOdds, int *sumOfOddAndEvens, unsigned int size)
{
cg::thread_block cta = cg::this_thread_block();
cg::grid_group grid = cg::this_grid();
cg::thread_block_tile<32> tile32 = cg::tiled_partition<32>(cta);
__global__ void oddEvenCountAndSumCG(int *inputArr, int *numOfOdds,
int *sumOfOddAndEvens, unsigned int size) {
cg::thread_block cta = cg::this_thread_block();
cg::grid_group grid = cg::this_grid();
cg::thread_block_tile<32> tile32 = cg::tiled_partition<32>(cta);
for (int i = grid.thread_rank(); i < size; i += grid.size())
for (int i = grid.thread_rank(); i < size; i += grid.size()) {
int elem = inputArr[i];
auto subTile = cg::binary_partition(tile32, elem & 1);
if (elem & 1) // Odd numbers group
{
int elem = inputArr[i];
auto subTile = cg::binary_partition(tile32, elem & 1);
if (elem & 1) // Odd numbers group
{
int oddGroupSum = cg::reduce(subTile, elem, cg::plus<int>());
int oddGroupSum = cg::reduce(subTile, elem, cg::plus<int>());
if (subTile.thread_rank() == 0)
{
// Add number of odds present in this group of Odds.
atomicAdd(numOfOdds, subTile.size());
if (subTile.thread_rank() == 0) {
// Add number of odds present in this group of Odds.
atomicAdd(numOfOdds, subTile.size());
// Add local reduction of odds present in this group of Odds.
atomicAdd(&sumOfOddAndEvens[0], oddGroupSum);
// Add local reduction of odds present in this group of Odds.
atomicAdd(&sumOfOddAndEvens[0], oddGroupSum);
}
} else // Even numbers group
{
int evenGroupSum = cg::reduce(subTile, elem, cg::plus<int>());
}
}
else // Even numbers group
{
int evenGroupSum = cg::reduce(subTile, elem, cg::plus<int>());
if (subTile.thread_rank() == 0)
{
// Add local reduction of even present in this group of evens.
atomicAdd(&sumOfOddAndEvens[1], evenGroupSum);
}
}
// reconverge warp so for next loop iteration we ensure convergence of
// above diverged threads to perform coalesced loads of inputArr.
cg::sync(tile32);
if (subTile.thread_rank() == 0) {
// Add local reduction of even present in this group of evens.
atomicAdd(&sumOfOddAndEvens[1], evenGroupSum);
}
}
// reconverge warp so for next loop iteration we ensure convergence of
// above diverged threads to perform coalesced loads of inputArr.
cg::sync(tile32);
}
}
/**
* Host main routine
*/
int main(int argc, const char **argv)
{
int deviceId = findCudaDevice(argc, argv);
int *h_inputArr, *d_inputArr;
int *h_numOfOdds, *d_numOfOdds;
int *h_sumOfOddEvenElems, *d_sumOfOddEvenElems;
unsigned int arrSize = 1024 * 100;
int main(int argc, const char **argv) {
int deviceId = findCudaDevice(argc, argv);
int *h_inputArr, *d_inputArr;
int *h_numOfOdds, *d_numOfOdds;
int *h_sumOfOddEvenElems, *d_sumOfOddEvenElems;
unsigned int arrSize = 1024 * 100;
h_inputArr = new int[arrSize];
h_numOfOdds = new int[1];
h_sumOfOddEvenElems = new int[2];
initOddEvenArr(h_inputArr, arrSize);
checkCudaErrors(cudaMallocHost(&h_inputArr, sizeof(int) * arrSize));
checkCudaErrors(cudaMallocHost(&h_numOfOdds, sizeof(int)));
checkCudaErrors(cudaMallocHost(&h_sumOfOddEvenElems, sizeof(int) * 2));
initOddEvenArr(h_inputArr, arrSize);
cudaStream_t stream;
checkCudaErrors(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
checkCudaErrors(cudaMalloc(&d_inputArr, sizeof(int)*arrSize));
checkCudaErrors(cudaMalloc(&d_numOfOdds, sizeof(int)));
checkCudaErrors(cudaMalloc(&d_sumOfOddEvenElems, sizeof(int)*2));
cudaStream_t stream;
checkCudaErrors(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
checkCudaErrors(cudaMalloc(&d_inputArr, sizeof(int) * arrSize));
checkCudaErrors(cudaMalloc(&d_numOfOdds, sizeof(int)));
checkCudaErrors(cudaMalloc(&d_sumOfOddEvenElems, sizeof(int) * 2));
checkCudaErrors(cudaMemcpyAsync(d_inputArr, h_inputArr, sizeof(int)*arrSize, cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemsetAsync(d_numOfOdds, 0, sizeof(int), stream));
checkCudaErrors(cudaMemsetAsync(d_sumOfOddEvenElems, 0, 2*sizeof(int), stream));
checkCudaErrors(cudaMemcpyAsync(d_inputArr, h_inputArr, sizeof(int) * arrSize,
cudaMemcpyHostToDevice, stream));
checkCudaErrors(cudaMemsetAsync(d_numOfOdds, 0, sizeof(int), stream));
checkCudaErrors(
cudaMemsetAsync(d_sumOfOddEvenElems, 0, 2 * sizeof(int), stream));
//Launch the kernel
int threadsPerBlock=1024;
int blocksPerGrid = arrSize / threadsPerBlock;
// Launch the kernel
int threadsPerBlock = 0;
int blocksPerGrid = 0;
checkCudaErrors(cudaOccupancyMaxPotentialBlockSize(
&blocksPerGrid, &threadsPerBlock, oddEvenCountAndSumCG, 0, 0));
printf("\nLaunching %d blocks with %d threads...\n\n",blocksPerGrid, threadsPerBlock);
printf("\nLaunching %d blocks with %d threads...\n\n", blocksPerGrid,
threadsPerBlock);
oddEvenCountAndSumCG<<<blocksPerGrid, threadsPerBlock, 0, stream>>>(d_inputArr, d_numOfOdds, d_sumOfOddEvenElems, arrSize);
oddEvenCountAndSumCG<<<blocksPerGrid, threadsPerBlock, 0, stream>>>(
d_inputArr, d_numOfOdds, d_sumOfOddEvenElems, arrSize);
checkCudaErrors(cudaMemcpyAsync(h_numOfOdds, d_numOfOdds, sizeof(int), cudaMemcpyDeviceToHost, stream));
checkCudaErrors(cudaMemcpyAsync(h_sumOfOddEvenElems, d_sumOfOddEvenElems, 2*sizeof(int), cudaMemcpyDeviceToHost, stream));
checkCudaErrors(cudaMemcpyAsync(h_numOfOdds, d_numOfOdds, sizeof(int),
cudaMemcpyDeviceToHost, stream));
checkCudaErrors(cudaMemcpyAsync(h_sumOfOddEvenElems, d_sumOfOddEvenElems,
2 * sizeof(int), cudaMemcpyDeviceToHost,
stream));
checkCudaErrors(cudaStreamSynchronize(stream));
printf("Array size = %d Num of Odds = %d Sum of Odds = %d Sum of Evens %d\n", arrSize, h_numOfOdds[0], h_sumOfOddEvenElems[0], h_sumOfOddEvenElems[1]);
printf("\n...Done.\n\n");
printf("Array size = %d Num of Odds = %d Sum of Odds = %d Sum of Evens %d\n",
arrSize, h_numOfOdds[0], h_sumOfOddEvenElems[0],
h_sumOfOddEvenElems[1]);
printf("\n...Done.\n\n");
delete[] h_inputArr;
delete[] h_numOfOdds;
delete[] h_sumOfOddEvenElems;
checkCudaErrors(cudaFreeHost(h_inputArr));
checkCudaErrors(cudaFreeHost(h_numOfOdds));
checkCudaErrors(cudaFreeHost(h_sumOfOddEvenElems));
checkCudaErrors(cudaFree(d_inputArr));
checkCudaErrors(cudaFree(d_numOfOdds));
checkCudaErrors(cudaFree(d_sumOfOddEvenElems));
checkCudaErrors(cudaFree(d_inputArr));
checkCudaErrors(cudaFree(d_numOfOdds));
checkCudaErrors(cudaFree(d_sumOfOddEvenElems));
return EXIT_SUCCESS;
return EXIT_SUCCESS;
}

4
Samples/binaryPartitionCG/binaryPartitionCG_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/binaryPartitionCG/binaryPartitionCG_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/boxFilterNPP/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/boxFilterNPP/boxFilterNPP_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -118,6 +118,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/boxFilterNPP/boxFilterNPP_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -114,6 +114,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/cannyEdgeDetectorNPP/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/cannyEdgeDetectorNPP/cannyEdgeDetectorNPP_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -118,6 +118,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cannyEdgeDetectorNPP/cannyEdgeDetectorNPP_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -114,6 +114,6 @@
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/concurrentKernels/README.md
View File

@ -24,7 +24,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/concurrentKernels/concurrentKernels_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/concurrentKernels/concurrentKernels_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

6
Samples/conjugateGradientCudaGraphs/Makefile
View File

@ -265,6 +265,12 @@ ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - conjugateGradientCudaGraphs is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))

2
Samples/conjugateGradientCudaGraphs/README.md
View File

@ -30,7 +30,7 @@ cudaStreamBeginCapture, cudaStreamEndCapture, cudaGraphCreate, cudaGraphLaunch,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

78
Samples/conjugateGradientCudaGraphs/conjugateGradientCudaGraphs.cu
View File

@ -25,7 +25,6 @@
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This sample implements a conjugate gradient solver on GPU
* using CUBLAS and CUSPARSE with CUDA Graphs
@ -46,7 +45,6 @@
#include <helper_cuda.h> // helper function CUDA error checking and initialization
#include <helper_functions.h> // helper for shared functions common to CUDA Samples
const char *sSDKname = "conjugateGradientCudaGraphs";
#ifndef WITH_GRAPH
@ -145,12 +143,12 @@ int main(int argc, char **argv) {
/* Generate a random tridiagonal symmetric matrix in CSR format */
N = 1048576;
nz = (N - 2) * 3 + 4;
I = (int *)malloc(sizeof(int) * (N + 1));
J = (int *)malloc(sizeof(int) * nz);
val = (float *)malloc(sizeof(float) * nz);
checkCudaErrors(cudaMallocHost(&I, sizeof(int) * (N + 1)));
checkCudaErrors(cudaMallocHost(&J, sizeof(int) * nz));
checkCudaErrors(cudaMallocHost(&val, sizeof(float) * nz));
genTridiag(I, J, val, N, nz);
x = (float *)malloc(sizeof(float) * N);
checkCudaErrors(cudaMallocHost(&x, sizeof(float) * N));
rhs = (float *)malloc(sizeof(float) * N);
for (int i = 0; i < N; i++) {
@ -192,9 +190,9 @@ int main(int argc, char **argv) {
/* Wrap raw data into cuSPARSE generic API objects */
cusparseSpMatDescr_t matA = NULL;
checkCudaErrors(cusparseCreateCsr(
&matA, N, N, nz, d_row, d_col, d_val, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F));
checkCudaErrors(cusparseCreateCsr(&matA, N, N, nz, d_row, d_col, d_val,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F));
cusparseDnVecDescr_t vecx = NULL;
checkCudaErrors(cusparseCreateDnVec(&vecx, N, d_x, CUDA_R_32F));
cusparseDnVecDescr_t vecp = NULL;
@ -206,7 +204,7 @@ int main(int argc, char **argv) {
size_t bufferSize = 0;
checkCudaErrors(cusparseSpMV_bufferSize(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecx,
&beta, vecAx, CUDA_R_32F, CUSPARSE_MV_ALG_DEFAULT, &bufferSize));
&beta, vecAx, CUDA_R_32F, CUSPARSE_SPMV_ALG_DEFAULT, &bufferSize));
void *buffer = NULL;
checkCudaErrors(cudaMalloc(&buffer, bufferSize));
@ -234,9 +232,9 @@ int main(int argc, char **argv) {
beta = 0.0;
checkCudaErrors(cusparseSetStream(cusparseHandle, stream1));
checkCudaErrors(cusparseSpMV(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecx,
&beta, vecAx, CUDA_R_32F, CUSPARSE_MV_ALG_DEFAULT, &buffer));
checkCudaErrors(cusparseSpMV(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, vecx, &beta, vecAx, CUDA_R_32F,
CUSPARSE_SPMV_ALG_DEFAULT, buffer));
checkCudaErrors(cublasSetStream(cublasHandle, stream1));
checkCudaErrors(cublasSaxpy(cublasHandle, N, &alpham1, d_Ax, 1, d_r, 1));
@ -248,9 +246,9 @@ int main(int argc, char **argv) {
k = 1;
// First Iteration when k=1 starts
checkCudaErrors(cublasScopy(cublasHandle, N, d_r, 1, d_p, 1));
checkCudaErrors(cusparseSpMV(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecp,
&beta, vecAx, CUDA_R_32F, CUSPARSE_MV_ALG_DEFAULT, &buffer));
checkCudaErrors(cusparseSpMV(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, vecp, &beta, vecAx, CUDA_R_32F,
CUSPARSE_SPMV_ALG_DEFAULT, buffer));
checkCudaErrors(cublasSdot(cublasHandle, N, d_p, 1, d_Ax, 1, d_dot));
@ -290,9 +288,9 @@ int main(int argc, char **argv) {
checkCudaErrors(
cusparseSetPointerMode(cusparseHandle, CUSPARSE_POINTER_MODE_HOST));
checkCudaErrors(cusparseSpMV(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecp,
&beta, vecAx, CUDA_R_32F, CUSPARSE_MV_ALG_DEFAULT, &buffer));
checkCudaErrors(cusparseSpMV(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, vecp, &beta, vecAx, CUDA_R_32F,
CUSPARSE_SPMV_ALG_DEFAULT, buffer));
checkCudaErrors(cudaMemsetAsync(d_dot, 0, sizeof(float), stream1));
checkCudaErrors(cublasSdot(cublasHandle, N, d_p, 1, d_Ax, 1, d_dot));
@ -335,8 +333,8 @@ int main(int argc, char **argv) {
checkCudaErrors(cublasSaxpy(cublasHandle, N, &alpha, d_r, 1, d_p, 1));
checkCudaErrors(cusparseSpMV(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecp,
&beta, vecAx, CUDA_R_32F, CUSPARSE_MV_ALG_DEFAULT, &buffer));
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &alpha, matA, vecp,
&beta, vecAx, CUDA_R_32F, CUSPARSE_SPMV_ALG_DEFAULT, buffer));
cublasSetPointerMode(cublasHandle, CUBLAS_POINTER_MODE_DEVICE);
checkCudaErrors(cublasSdot(cublasHandle, N, d_p, 1, d_Ax, 1, d_dot));
@ -395,23 +393,31 @@ int main(int argc, char **argv) {
cusparseDestroy(cusparseHandle);
cublasDestroy(cublasHandle);
if (matA ) { checkCudaErrors(cusparseDestroySpMat(matA)); }
if (vecx ) { checkCudaErrors(cusparseDestroyDnVec(vecx)); }
if (vecAx ) { checkCudaErrors(cusparseDestroyDnVec(vecAx)); }
if (vecp ) { checkCudaErrors(cusparseDestroyDnVec(vecp)); }
if (matA) {
checkCudaErrors(cusparseDestroySpMat(matA));
}
if (vecx) {
checkCudaErrors(cusparseDestroyDnVec(vecx));
}
if (vecAx) {
checkCudaErrors(cusparseDestroyDnVec(vecAx));
}
if (vecp) {
checkCudaErrors(cusparseDestroyDnVec(vecp));
}
free(I);
free(J);
free(val);
free(x);
checkCudaErrors(cudaFreeHost(I));
checkCudaErrors(cudaFreeHost(J));
checkCudaErrors(cudaFreeHost(val));
checkCudaErrors(cudaFreeHost(x));
free(rhs);
cudaFree(d_col);
cudaFree(d_row);
cudaFree(d_val);
cudaFree(d_x);
cudaFree(d_r);
cudaFree(d_p);
cudaFree(d_Ax);
checkCudaErrors(cudaFree(d_col));
checkCudaErrors(cudaFree(d_row));
checkCudaErrors(cudaFree(d_val));
checkCudaErrors(cudaFree(d_x));
checkCudaErrors(cudaFree(d_r));
checkCudaErrors(cudaFree(d_p));
checkCudaErrors(cudaFree(d_Ax));
printf("Test Summary: Error amount = %f\n", err);
exit((k <= max_iter) ? 0 : 1);

4
Samples/conjugateGradientCudaGraphs/conjugateGradientCudaGraphs_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/conjugateGradientCudaGraphs/conjugateGradientCudaGraphs_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/conjugateGradientMultiBlockCG/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, aarch64
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/conjugateGradientMultiBlockCG/conjugateGradientMultiBlockCG_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/conjugateGradientMultiBlockCG/conjugateGradientMultiBlockCG_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/conjugateGradientMultiDeviceCG/README.md
View File

@ -30,7 +30,7 @@ cudaMemAdvise, cudaMemPrefetchAsync, cudaLaunchCooperativeKernelMultiDevice, cud
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

138
Samples/conjugateGradientMultiDeviceCG/conjugateGradientMultiDeviceCG.cu
View File

@ -223,8 +223,10 @@ __device__ void gpuDotProduct(float *vecA, float *vecB, int size,
cg::sync(cta);
if (tile32.meta_group_rank() == 0) {
temp_sum = tile32.thread_rank() < tile32.meta_group_size() ? tmp[tile32.thread_rank()] : 0.0;
temp_sum = cg::reduce(tile32, temp_sum, cg::plus<double>());
temp_sum = tile32.thread_rank() < tile32.meta_group_size()
? tmp[tile32.thread_rank()]
: 0.0;
temp_sum = cg::reduce(tile32, temp_sum, cg::plus<double>());
if (tile32.thread_rank() == 0) {
atomicAdd(&grid_dot_result, temp_sum);
@ -239,8 +241,9 @@ __device__ void gpuCopyVector(float *srcA, float *destB, int size,
}
}
__device__ void gpuScaleVectorAndSaxpy(float *x, float *y, float a, float scale, int size,
const cg::multi_grid_group &multi_grid) {
__device__ void gpuScaleVectorAndSaxpy(float *x, float *y, float a, float scale,
int size,
const cg::multi_grid_group &multi_grid) {
for (int i = multi_grid.thread_rank(); i < size; i += multi_grid.size()) {
y[i] = a * x[i] + scale * y[i];
}
@ -360,10 +363,11 @@ std::multimap<std::pair<int, int>, int> getIdenticalGPUs() {
// Filter unsupported devices
if (deviceProp.cooperativeMultiDeviceLaunch &&
deviceProp.concurrentManagedAccess) {
identicalGpus.emplace(std::make_pair(deviceProp.major, deviceProp.minor), i);
identicalGpus.emplace(std::make_pair(deviceProp.major, deviceProp.minor),
i);
}
printf("GPU Device %d: \"%s\" with compute capability %d.%d\n", i,
deviceProp.name, deviceProp.major, deviceProp.minor);
deviceProp.name, deviceProp.major, deviceProp.minor);
}
return identicalGpus;
@ -387,15 +391,17 @@ int main(int argc, char **argv) {
auto bestFit = std::make_pair(it, it);
// use std::distance to find the largest number of GPUs amongst architectures
auto distance = [](decltype(bestFit) p){return std::distance(p.first, p.second);};
auto distance = [](decltype(bestFit) p) {
return std::distance(p.first, p.second);
};
// Read each unique key/pair element in order
for (; it != end; it = gpusByArch.upper_bound(it->first)) {
// first and second are iterators bounded within the architecture group
auto testFit = gpusByArch.equal_range(it->first);
// Always use devices with highest architecture version or whichever has the most devices available
if (distance(bestFit) <= distance(testFit))
bestFit = testFit;
// Always use devices with highest architecture version or whichever has the
// most devices available
if (distance(bestFit) <= distance(testFit)) bestFit = testFit;
}
if (distance(bestFit) < kNumGpusRequired) {
@ -408,33 +414,35 @@ int main(int argc, char **argv) {
std::set<int> bestFitDeviceIds;
// check & select peer-to-peer access capable GPU devices as enabling p2p access between participating
// check & select peer-to-peer access capable GPU devices as enabling p2p
// access between participating
// GPUs gives better performance for multi_grid sync.
for (auto itr = bestFit.first; itr != bestFit.second; itr++) {
int deviceId = itr->second;
checkCudaErrors(cudaSetDevice(deviceId));
std::for_each(itr, bestFit.second, [&deviceId, &bestFitDeviceIds](decltype(*itr) mapPair) {
if (deviceId != mapPair.second)
{
std::for_each(itr, bestFit.second, [&deviceId, &bestFitDeviceIds,
&kNumGpusRequired](
decltype(*itr) mapPair) {
if (deviceId != mapPair.second) {
int access = 0;
checkCudaErrors(cudaDeviceCanAccessPeer(&access, deviceId, mapPair.second));
printf("Device=%d %s Access Peer Device=%d\n", deviceId, access ? "CAN" : "CANNOT", mapPair.second);
checkCudaErrors(
cudaDeviceCanAccessPeer(&access, deviceId, mapPair.second));
printf("Device=%d %s Access Peer Device=%d\n", deviceId,
access ? "CAN" : "CANNOT", mapPair.second);
if (access && bestFitDeviceIds.size() < kNumGpusRequired) {
bestFitDeviceIds.emplace(deviceId);
bestFitDeviceIds.emplace(mapPair.second);
}
else {
} else {
printf("Ignoring device %i (max devices exceeded)\n", mapPair.second);
}
}
});
if (bestFitDeviceIds.size() >= kNumGpusRequired)
{
if (bestFitDeviceIds.size() >= kNumGpusRequired) {
printf("Selected p2p capable devices - ");
for (auto devicesItr = bestFitDeviceIds.begin(); devicesItr != bestFitDeviceIds.end(); devicesItr++)
{
for (auto devicesItr = bestFitDeviceIds.begin();
devicesItr != bestFitDeviceIds.end(); devicesItr++) {
printf("deviceId = %d ", *devicesItr);
}
printf("\n");
@ -442,33 +450,34 @@ int main(int argc, char **argv) {
}
}
// if bestFitDeviceIds.size() == 0 it means the GPUs in system are not p2p capable,
// if bestFitDeviceIds.size() == 0 it means the GPUs in system are not p2p
// capable,
// hence we add it without p2p capability check.
if (!bestFitDeviceIds.size())
{
printf("Devices involved are not p2p capable.. selecting %zu of them\n", kNumGpusRequired);
std::for_each(bestFit.first, bestFit.second, [&bestFitDeviceIds](decltype(*bestFit.first) mapPair) {
if (bestFitDeviceIds.size() < kNumGpusRequired) {
bestFitDeviceIds.emplace(mapPair.second);
}
else {
printf("Ignoring device %i (max devices exceeded)\n", mapPair.second);
}
// Insert the sequence into the deviceIds set
});
}
else
{
// perform cudaDeviceEnablePeerAccess in both directions for all participating devices
// of a cudaLaunchCooperativeKernelMultiDevice call this gives better performance for multi_grid sync.
for (auto p1_itr = bestFitDeviceIds.begin(); p1_itr != bestFitDeviceIds.end(); p1_itr++)
{
if (!bestFitDeviceIds.size()) {
printf("Devices involved are not p2p capable.. selecting %zu of them\n",
kNumGpusRequired);
std::for_each(bestFit.first, bestFit.second,
[&bestFitDeviceIds,
&kNumGpusRequired](decltype(*bestFit.first) mapPair) {
if (bestFitDeviceIds.size() < kNumGpusRequired) {
bestFitDeviceIds.emplace(mapPair.second);
} else {
printf("Ignoring device %i (max devices exceeded)\n",
mapPair.second);
}
// Insert the sequence into the deviceIds set
});
} else {
// perform cudaDeviceEnablePeerAccess in both directions for all
// participating devices of a cudaLaunchCooperativeKernelMultiDevice call
// this gives better performance for multi_grid sync.
for (auto p1_itr = bestFitDeviceIds.begin();
p1_itr != bestFitDeviceIds.end(); p1_itr++) {
checkCudaErrors(cudaSetDevice(*p1_itr));
for (auto p2_itr = bestFitDeviceIds.begin(); p2_itr != bestFitDeviceIds.end(); p2_itr++)
{
if (*p1_itr != *p2_itr)
{
checkCudaErrors(cudaDeviceEnablePeerAccess(*p2_itr, 0 ));
for (auto p2_itr = bestFitDeviceIds.begin();
p2_itr != bestFitDeviceIds.end(); p2_itr++) {
if (*p1_itr != *p2_itr) {
checkCudaErrors(cudaDeviceEnablePeerAccess(*p2_itr, 0));
checkCudaErrors(cudaSetDevice(*p1_itr));
}
}
@ -518,7 +527,7 @@ int main(int argc, char **argv) {
std::cout << "\nRunning on GPUs = " << kNumGpusRequired << std::endl;
cudaStream_t nStreams[kNumGpusRequired];
int sMemSize = sizeof(double) * ((THREADS_PER_BLOCK/32) + 1);
int sMemSize = sizeof(double) * ((THREADS_PER_BLOCK / 32) + 1);
int numBlocksPerSm = INT_MAX;
int numThreads = THREADS_PER_BLOCK;
int numSms = INT_MAX;
@ -530,17 +539,16 @@ int main(int argc, char **argv) {
checkCudaErrors(cudaSetDevice(*deviceId));
checkCudaErrors(cudaGetDeviceProperties(&deviceProp, *deviceId));
int numBlocksPerSm_current=0;
int numBlocksPerSm_current = 0;
checkCudaErrors(cudaOccupancyMaxActiveBlocksPerMultiprocessor(
&numBlocksPerSm_current, multiGpuConjugateGradient, numThreads, sMemSize));
&numBlocksPerSm_current, multiGpuConjugateGradient, numThreads,
sMemSize));
if (numBlocksPerSm > numBlocksPerSm_current)
{
numBlocksPerSm = numBlocksPerSm_current;
if (numBlocksPerSm > numBlocksPerSm_current) {
numBlocksPerSm = numBlocksPerSm_current;
}
if (numSms > deviceProp.multiProcessorCount)
{
numSms = deviceProp.multiProcessorCount;
if (numSms > deviceProp.multiProcessorCount) {
numSms = deviceProp.multiProcessorCount;
}
deviceId++;
}
@ -554,7 +562,7 @@ int main(int argc, char **argv) {
int device_count = 0;
int totalThreadsPerGPU = numSms * numBlocksPerSm * THREADS_PER_BLOCK;
deviceId = bestFitDeviceIds.begin();;
deviceId = bestFitDeviceIds.begin();
while (deviceId != bestFitDeviceIds.end()) {
checkCudaErrors(cudaSetDevice(*deviceId));
checkCudaErrors(cudaStreamCreate(&nStreams[device_count]));
@ -621,14 +629,15 @@ int main(int argc, char **argv) {
printf("Total threads per GPU = %d numBlocksPerSm = %d\n",
numSms * numBlocksPerSm * THREADS_PER_BLOCK, numBlocksPerSm);
dim3 dimGrid(numSms * numBlocksPerSm, 1, 1), dimBlock(THREADS_PER_BLOCK, 1, 1);
dim3 dimGrid(numSms * numBlocksPerSm, 1, 1),
dimBlock(THREADS_PER_BLOCK, 1, 1);
void *kernelArgs[] = {
(void *)&I, (void *)&J, (void *)&val, (void *)&x,
(void *)&Ax, (void *)&p, (void *)&r, (void *)&dot_result,
(void *)&nz, (void *)&N, (void *)&tol,
};
cudaLaunchParams *launchParamsList = (cudaLaunchParams *)malloc(
sizeof(cudaLaunchParams) * kNumGpusRequired);
cudaLaunchParams *launchParamsList =
(cudaLaunchParams *)malloc(sizeof(cudaLaunchParams) * kNumGpusRequired);
for (int i = 0; i < kNumGpusRequired; i++) {
launchParamsList[i].func = (void *)multiGpuConjugateGradient;
launchParamsList[i].gridDim = dimGrid;
@ -645,12 +654,11 @@ int main(int argc, char **argv) {
cudaCooperativeLaunchMultiDeviceNoPreSync |
cudaCooperativeLaunchMultiDeviceNoPostSync));
checkCudaErrors(cudaMemPrefetchAsync(x, sizeof(float) * N, cudaCpuDeviceId));
checkCudaErrors(
cudaMemPrefetchAsync(x, sizeof(float) * N, cudaCpuDeviceId));
checkCudaErrors(
cudaMemPrefetchAsync(dot_result, sizeof(double), cudaCpuDeviceId));
cudaMemPrefetchAsync(dot_result, sizeof(double), cudaCpuDeviceId));
deviceId = bestFitDeviceIds.begin();;
deviceId = bestFitDeviceIds.begin();
device_count = 0;
while (deviceId != bestFitDeviceIds.end()) {
checkCudaErrors(cudaSetDevice(*deviceId));
@ -658,7 +666,7 @@ int main(int argc, char **argv) {
deviceId++;
}
r1 = *dot_result;
r1 = (float)*dot_result;
printf("GPU Final, residual = %e \n ", sqrt(r1));

4
Samples/conjugateGradientMultiDeviceCG/conjugateGradientMultiDeviceCG_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/conjugateGradientMultiDeviceCG/conjugateGradientMultiDeviceCG_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

6
Samples/cuSolverDn_LinearSolver/Makefile
View File

@ -271,6 +271,12 @@ ifeq ($(TARGET_ARCH),armv7l)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - cuSolverDn_LinearSolver is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(TARGET_OS),linux)
ALL_CCFLAGS += -Xcompiler \"-Wl,--no-as-needed\"
endif

2
Samples/cuSolverDn_LinearSolver/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, aarch64
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/cuSolverDn_LinearSolver/cuSolverDn_LinearSolver_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cuSolverDn_LinearSolver/cuSolverDn_LinearSolver_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

6
Samples/cuSolverSp_LinearSolver/Makefile
View File

@ -265,6 +265,12 @@ ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - cuSolverSp_LinearSolver is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(TARGET_OS),linux)
ALL_CCFLAGS += -Xcompiler \"-Wl,--no-as-needed\"
endif

2
Samples/cuSolverSp_LinearSolver/README.md
View File

@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

6
Samples/cuSolverSp_LinearSolver/cuSolverSp_LinearSolver.cpp
View File

@ -495,13 +495,13 @@ int main(int argc, char *argv[]) {
size_t bufferSize = 0;
checkCudaErrors(cusparseSpMV_bufferSize(
cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, &minus_one, matA, vecx,
&one, vecAx, CUDA_R_64F, CUSPARSE_MV_ALG_DEFAULT, &bufferSize));
&one, vecAx, CUDA_R_64F, CUSPARSE_SPMV_ALG_DEFAULT, &bufferSize));
void *buffer = NULL;
checkCudaErrors(cudaMalloc(&buffer, bufferSize));
checkCudaErrors(cusparseSpMV(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&minus_one, matA, vecx, &one, vecAx, CUDA_R_64F,
CUSPARSE_MV_ALG_DEFAULT, &buffer));
CUSPARSE_SPMV_ALG_DEFAULT, buffer));
checkCudaErrors(cudaMemcpyAsync(h_r, d_r, sizeof(double) * rowsA,
cudaMemcpyDeviceToHost, stream));
@ -559,7 +559,7 @@ int main(int argc, char *argv[]) {
checkCudaErrors(cusparseSpMV(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE,
&minus_one, matA, vecx, &one, vecAx, CUDA_R_64F,
CUSPARSE_MV_ALG_DEFAULT, &buffer));
CUSPARSE_SPMV_ALG_DEFAULT, buffer));
checkCudaErrors(cudaMemcpyAsync(h_x, d_x, sizeof(double) * colsA,
cudaMemcpyDeviceToHost, stream));

4
Samples/cuSolverSp_LinearSolver/cuSolverSp_LinearSolver_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cuSolverSp_LinearSolver/cuSolverSp_LinearSolver_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/cudaCompressibleMemory/README.md
View File

@ -30,7 +30,7 @@ cudaMalloc, cudaFree
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/cudaCompressibleMemory/cudaCompressibleMemory_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cudaCompressibleMemory/cudaCompressibleMemory_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

6
Samples/cudaNvSci/Makefile
View File

@ -279,6 +279,12 @@ ifeq ($(TARGET_ARCH),armv7l)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(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))

2
Samples/cudaNvSci/README.md
View File

@ -30,7 +30,7 @@ cudaImportExternalMemory, cudaExternalMemoryGetMappedBuffer, cudaExternalMemoryG
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

2
Samples/cudaNvSciNvMedia/README.md
View File

@ -30,7 +30,7 @@ cudaImportExternalMemory, cudaExternalMemoryGetMappedBuffer, cudaExternalMemoryG
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

2
Samples/cudaOpenMP/README.md
View File

@ -30,7 +30,7 @@ cudaMalloc, cudaFree, cudaMemcpy
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

4
Samples/cudaOpenMP/cudaOpenMP_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cudaOpenMP/cudaOpenMP_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/cudaTensorCoreGemm/README.md
View File

@ -31,7 +31,7 @@ cudaMallocManaged, cudaDeviceSynchronize, cudaFuncSetAttribute, cudaEventCreate,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/cudaTensorCoreGemm/cudaTensorCoreGemm_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/cudaTensorCoreGemm/cudaTensorCoreGemm_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/deviceQuery/README.md
View File

@ -27,7 +27,7 @@ cudaSetDevice, cudaGetDeviceCount, cudaGetDeviceProperties, cudaDriverGetVersion
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

21
Samples/deviceQuery/deviceQuery.cpp
View File

@ -112,10 +112,10 @@ int main(int argc, char **argv) {
char msg[256];
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(msg, sizeof(msg),
" Total amount of global memory: %.0f MBytes "
"(%llu bytes)\n",
static_cast<float>(deviceProp.totalGlobalMem / 1048576.0f),
(unsigned long long)deviceProp.totalGlobalMem);
" Total amount of global memory: %.0f MBytes "
"(%llu bytes)\n",
static_cast<float>(deviceProp.totalGlobalMem / 1048576.0f),
(unsigned long long)deviceProp.totalGlobalMem);
#else
snprintf(msg, sizeof(msg),
" Total amount of global memory: %.0f MBytes "
@ -125,7 +125,7 @@ int main(int argc, char **argv) {
#endif
printf("%s", msg);
printf(" (%2d) Multiprocessors, (%3d) CUDA Cores/MP: %d CUDA Cores\n",
printf(" (%03d) Multiprocessors, (%03d) CUDA Cores/MP: %d CUDA Cores\n",
deviceProp.multiProcessorCount,
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) *
@ -250,8 +250,7 @@ int main(int argc, char **argv) {
"device)",
"Exclusive Process (many threads in one process is able to use "
"::cudaSetDevice() with this device)",
"Unknown",
NULL};
"Unknown", NULL};
printf(" Compute Mode:\n");
printf(" < %s >\n", sComputeMode[deviceProp.computeMode]);
}
@ -272,7 +271,7 @@ int main(int argc, char **argv) {
// must be enabled to support this
&& prop[i].tccDriver
#endif
) {
) {
// This is an array of P2P capable GPUs
gpuid[gpu_p2p_count++] = i;
}
@ -307,7 +306,8 @@ int main(int argc, char **argv) {
// driver version
sProfileString += ", CUDA Driver Version = ";
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 10, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
sprintf_s(cTemp, 10, "%d.%d", driverVersion / 1000,
(driverVersion % 100) / 10);
#else
snprintf(cTemp, sizeof(cTemp), "%d.%d", driverVersion / 1000,
(driverVersion % 100) / 10);
@ -317,7 +317,8 @@ int main(int argc, char **argv) {
// Runtime version
sProfileString += ", CUDA Runtime Version = ";
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion / 1000,
(runtimeVersion % 100) / 10);
#else
snprintf(cTemp, sizeof(cTemp), "%d.%d", runtimeVersion / 1000,
(runtimeVersion % 100) / 10);

4
Samples/deviceQuery/deviceQuery_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/deviceQuery/deviceQuery_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/dmmaTensorCoreGemm/README.md
View File

@ -27,7 +27,7 @@ cudaMallocManaged, cudaDeviceSynchronize, cudaFuncSetAttribute, cudaEventCreate,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/dmmaTensorCoreGemm/dmmaTensorCoreGemm_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/dmmaTensorCoreGemm/dmmaTensorCoreGemm_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/globalToShmemAsyncCopy/README.md
View File

@ -30,7 +30,7 @@ cudaEventCreate, cudaEventRecord, cudaEventQuery, cudaEventDestroy, cudaEventEla
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

1681
Samples/globalToShmemAsyncCopy/globalToShmemAsyncCopy.cu
View File

File diff suppressed because it is too large Load Diff

4
Samples/globalToShmemAsyncCopy/globalToShmemAsyncCopy_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/globalToShmemAsyncCopy/globalToShmemAsyncCopy_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/immaTensorCoreGemm/README.md
View File

@ -27,7 +27,7 @@ cudaMallocManaged, cudaDeviceSynchronize, cudaFuncSetAttribute, cudaEventCreate,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/immaTensorCoreGemm/immaTensorCoreGemm_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/immaTensorCoreGemm/immaTensorCoreGemm_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/jacobiCudaGraphs/README.md
View File

@ -25,7 +25,7 @@ cudaStreamBeginCapture, cudaStreamEndCapture, cudaGraphCreate, cudaGraphLaunch,
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/jacobiCudaGraphs/jacobiCudaGraphs_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/jacobiCudaGraphs/jacobiCudaGraphs_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

9
Samples/jacobiCudaGraphs/main.cpp
View File

@ -100,8 +100,10 @@ int main(int argc, char **argv) {
double *b = NULL;
float *A = NULL;
b = (double *)calloc(N_ROWS, sizeof(double));
A = (float *)calloc(N_ROWS * N_ROWS, sizeof(float));
checkCudaErrors(cudaMallocHost(&b, N_ROWS * sizeof(double)));
memset(b, 0, N_ROWS * sizeof(double));
checkCudaErrors(cudaMallocHost(&A, N_ROWS * N_ROWS * sizeof(float)));
memset(A, 0, N_ROWS * N_ROWS * sizeof(float));
createLinearSystem(A, b);
double *x = NULL;
@ -170,6 +172,9 @@ int main(int argc, char **argv) {
checkCudaErrors(cudaFree(d_x));
checkCudaErrors(cudaFree(d_x_new));
checkCudaErrors(cudaFreeHost(A));
checkCudaErrors(cudaFreeHost(b));
printf("&&&& jacobiCudaGraphs %s\n",
(fabs(sum - sumGPU) < conv_threshold) ? "PASSED" : "FAILED");

2
Samples/matrixMul/README.md
View File

@ -27,7 +27,7 @@ cudaEventCreate, cudaEventRecord, cudaEventQuery, cudaEventDestroy, cudaEventEla
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/matrixMul/matrixMul_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/matrixMul/matrixMul_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

2
Samples/matrixMulDrv/README.md
View File

@ -27,7 +27,7 @@ cuModuleLoad, cuModuleLoadDataEx, cuModuleGetFunction, cuMemAlloc, cuMemFree, cu
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run

4
Samples/matrixMulDrv/matrixMulDrv_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

4
Samples/matrixMulDrv/matrixMulDrv_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(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="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

19
Samples/memMapIPCDrv/Makefile
View File

@ -302,14 +302,10 @@ LIBRARIES :=
################################################################################
FATBIN_FILE := memMapIpc_kernel${TARGET_SIZE}.fatbin
PTX_FILE := memMapIpc_kernel${TARGET_SIZE}.ptx
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64))
SMS ?= 35 37 50 52 60 61 70 72 75 80 86
else
SMS ?= 35 37 50 52 60 61 70 75 80 86
endif
SMS ?=
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
@ -395,7 +391,7 @@ endif
# Target rules
all: build
build: memMapIPCDrv $(FATBIN_FILE)
build: memMapIPCDrv $(PTX_FILE)
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@ -404,8 +400,8 @@ else
@echo "Sample is ready - all dependencies have been met"
endif
$(FATBIN_FILE): memMapIpc_kernel.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -fatbin $<
$(PTX_FILE): memMapIpc_kernel.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -ptx $<
$(EXEC) mkdir -p data
$(EXEC) cp -f $@ ./data
$(EXEC) mkdir -p ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
@ -426,9 +422,8 @@ run: build
$(EXEC) ./memMapIPCDrv
clean:
rm -f memMapIPCDrv helper_multiprocess.o memMapIpc.o data/$(FATBIN_FILE) $(FATBIN_FILE)
rm -f memMapIPCDrv helper_multiprocess.o memMapIpc.o data/$(PTX_FILE) $(PTX_FILE)
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/memMapIPCDrv
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/$(FATBIN_FILE)
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/$(PTX_FILE)
clobber: clean

2
Samples/memMapIPCDrv/README.md
View File

@ -30,7 +30,7 @@ cuModuleLoad, cuModuleLoadDataEx, cuModuleGetFunction, cuLaunchKernel, cuMemcpyD
## Prerequisites
Download and install the [CUDA Toolkit 11.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run

10
Samples/memMapIPCDrv/memMapIPCDrv_vs2017.vcxproj
View File

@ -38,7 +38,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -67,7 +67,7 @@
<OutputFile>$(OutDir)/memMapIPCDrv.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_35,compute_35;compute_35,sm_35;compute_37,sm_37;compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;</CodeGeneration>
<CodeGeneration>compute_35,compute_35;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
<Include>./;../../Common</Include>
<Defines>WIN32</Defines>
@ -105,14 +105,14 @@
<ItemGroup>
<ClCompile Include="memMapIpc.cpp" />
<CudaCompile Include="memMapIpc_kernel.cu">
<CompileOut Condition="'$(Platform)'=='x64'">data/%(Filename)64.fatbin</CompileOut>
<NvccCompilation>fatbin</NvccCompilation>
<CompileOut Condition="'$(Platform)'=='x64'">data/%(Filename)64.ptx</CompileOut>
<NvccCompilation>ptx</NvccCompilation>
</CudaCompile>
<ClCompile Include="../../Common/helper_multiprocess.cpp" />
<ClInclude Include="../../Common/helper_multiprocess.h" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

10
Samples/memMapIPCDrv/memMapIPCDrv_vs2019.vcxproj
View File

@ -34,7 +34,7 @@
</PropertyGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
<ImportGroup Label="ExtensionSettings">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.props" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.props" />
</ImportGroup>
<ImportGroup Label="PropertySheets">
<Import Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" />
@ -63,7 +63,7 @@
<OutputFile>$(OutDir)/memMapIPCDrv.exe</OutputFile>
</Link>
<CudaCompile>
<CodeGeneration>compute_35,compute_35;compute_35,sm_35;compute_37,sm_37;compute_50,sm_50;compute_52,sm_52;compute_60,sm_60;compute_61,sm_61;compute_70,sm_70;compute_75,sm_75;compute_80,sm_80;compute_86,sm_86;</CodeGeneration>
<CodeGeneration>compute_35,compute_35;</CodeGeneration>
<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
<Include>./;../../Common</Include>
<Defines>WIN32</Defines>
@ -101,14 +101,14 @@
<ItemGroup>
<ClCompile Include="memMapIpc.cpp" />
<CudaCompile Include="memMapIpc_kernel.cu">
<CompileOut Condition="'$(Platform)'=='x64'">data/%(Filename)64.fatbin</CompileOut>
<NvccCompilation>fatbin</NvccCompilation>
<CompileOut Condition="'$(Platform)'=='x64'">data/%(Filename)64.ptx</CompileOut>
<NvccCompilation>ptx</NvccCompilation>
</CudaCompile>
<ClCompile Include="../../Common/helper_multiprocess.cpp" />
<ClInclude Include="../../Common/helper_multiprocess.h" />
</ItemGroup>
<Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
<ImportGroup Label="ExtensionTargets">
<Import Project="$(CUDAPropsPath)\CUDA 11.2.targets" />
<Import Project="$(CUDAPropsPath)\CUDA 11.3.targets" />
</ImportGroup>
</Project>

87
Samples/memMapIPCDrv/memMapIpc.cpp
View File

@ -64,9 +64,13 @@ typedef struct shmStruct_st {
int sense;
} shmStruct;
// define input fatbin file
#ifndef FATBIN_FILE
#define FATBIN_FILE "memMapIpc_kernel64.fatbin"
bool findModulePath(const char *, string &, char **, string &);
// define input ptx file for different platforms
#if defined(_WIN64) || defined(__LP64__)
#define PTX_FILE "memMapIpc_kernel64.ptx"
#else
#define PTX_FILE "memMapIpc_kernel32.ptx"
#endif
// `ipcHandleTypeFlag` specifies the platform specific handle type this sample
@ -255,23 +259,44 @@ static void memMapUnmapAndFreeMemory(CUdeviceptr dptr, size_t size) {
static void memMapGetDeviceFunction(char **argv) {
// first search for the module path before we load the results
string module_path;
std::ostringstream fatbin;
if (!findFatbinPath(FATBIN_FILE, module_path, argv, fatbin)) {
exit(EXIT_FAILURE);
string module_path, ptx_source;
if (!findModulePath(PTX_FILE, module_path, argv, ptx_source)) {
if (!findModulePath("memMapIpc_kernel.cubin", module_path, argv,
ptx_source)) {
printf(
"> findModulePath could not find <simpleMemMapIpc> ptx or cubin\n");
exit(EXIT_FAILURE);
}
} else {
printf("> initCUDA loading module: <%s>\n", module_path.c_str());
}
if (!fatbin.str().size()) {
printf("fatbin file empty. exiting..\n");
exit(EXIT_FAILURE);
// Create module from binary file (PTX or CUBIN)
if (module_path.rfind("ptx") != string::npos) {
// in this branch we use compilation with parameters
const unsigned int jitNumOptions = 3;
CUjit_option *jitOptions = new CUjit_option[jitNumOptions];
void **jitOptVals = new void *[jitNumOptions];
// set up size of compilation log buffer
jitOptions[0] = CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES;
int jitLogBufferSize = 1024;
jitOptVals[0] = (void *)(size_t)jitLogBufferSize;
// set up pointer to the compilation log buffer
jitOptions[1] = CU_JIT_INFO_LOG_BUFFER;
char *jitLogBuffer = new char[jitLogBufferSize];
jitOptVals[1] = jitLogBuffer;
// set up pointer to set the Maximum # of registers for a particular kernel
jitOptions[2] = CU_JIT_MAX_REGISTERS;
int jitRegCount = 32;
jitOptVals[2] = (void *)(size_t)jitRegCount;
checkCudaErrors(cuModuleLoadDataEx(&cuModule, ptx_source.c_str(),
jitNumOptions, jitOptions,
(void **)jitOptVals));
printf("> PTX JIT log:\n%s\n", jitLogBuffer);
} else {
checkCudaErrors(cuModuleLoad(&cuModule, module_path.c_str()));
}
// Create module from binary file (FATBIN)
checkCudaErrors(cuModuleLoadData(&cuModule, fatbin.str().c_str()));
// Get function handle from module
checkCudaErrors(
cuModuleGetFunction(&_memMapIpc_kernel, cuModule, "memMapIpc_kernel"));
@ -585,3 +610,37 @@ int main(int argc, char **argv) {
return EXIT_SUCCESS;
#endif
}
bool inline findModulePath(const char *module_file, string &module_path,
char **argv, string &ptx_source) {
char *actual_path = sdkFindFilePath(module_file, argv[0]);
if (actual_path) {
module_path = actual_path;
} else {
printf("> findModulePath file not found: <%s> \n", module_file);
return false;
}
if (module_path.empty()) {
printf("> findModulePath could not find file: <%s> \n", module_file);
return false;
} else {
printf("> findModulePath found file at <%s>\n", module_path.c_str());
if (module_path.rfind(".ptx") != string::npos) {
FILE *fp = fopen(module_path.c_str(), "rb");
fseek(fp, 0, SEEK_END);
int file_size = ftell(fp);
char *buf = new char[file_size + 1];
fseek(fp, 0, SEEK_SET);
fread(buf, sizeof(char), file_size, fp);
fclose(fp);
buf[file_size] = '\0';
ptx_source = buf;
delete[] buf;
}
return true;
}
}

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