mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-11-24 19:49:19 +08:00
154 lines
5.5 KiB
C++
154 lines
5.5 KiB
C++
/* Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/**
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* Vector addition: C = A + B.
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*
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* This sample is a very basic sample that implements element by element
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* vector addition. It is the same as the sample illustrating Chapter 2
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* of the programming guide with some additions like error checking.
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*/
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#include <stdio.h>
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#include <cmath>
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// For the CUDA runtime routines (prefixed with "cuda_")
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#include <cuda.h>
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#include <cuda_runtime.h>
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// helper functions and utilities to work with CUDA
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#include <helper_functions.h>
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#include <nvrtc_helper.h>
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/**
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* Host main routine
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*/
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int main(int argc, char **argv) {
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char *cubin, *kernel_file;
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size_t cubinSize;
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kernel_file = sdkFindFilePath("vectorAdd_kernel.cu", argv[0]);
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compileFileToCUBIN(kernel_file, argc, argv, &cubin, &cubinSize, 0);
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CUmodule module = loadCUBIN(cubin, argc, argv);
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CUfunction kernel_addr;
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checkCudaErrors(cuModuleGetFunction(&kernel_addr, module, "vectorAdd"));
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// Print the vector length to be used, and compute its size
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int numElements = 50000;
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size_t size = numElements * sizeof(float);
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printf("[Vector addition of %d elements]\n", numElements);
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// Allocate the host input vector A
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float *h_A = reinterpret_cast<float *>(malloc(size));
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// Allocate the host input vector B
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float *h_B = reinterpret_cast<float *>(malloc(size));
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// Allocate the host output vector C
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float *h_C = reinterpret_cast<float *>(malloc(size));
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// Verify that allocations succeeded
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if (h_A == NULL || h_B == NULL || h_C == NULL) {
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fprintf(stderr, "Failed to allocate host vectors!\n");
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exit(EXIT_FAILURE);
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}
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// Initialize the host input vectors
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for (int i = 0; i < numElements; ++i) {
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h_A[i] = rand() / static_cast<float>(RAND_MAX);
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h_B[i] = rand() / static_cast<float>(RAND_MAX);
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}
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// Allocate the device input vector A
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CUdeviceptr d_A;
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checkCudaErrors(cuMemAlloc(&d_A, size));
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// Allocate the device input vector B
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CUdeviceptr d_B;
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checkCudaErrors(cuMemAlloc(&d_B, size));
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// Allocate the device output vector C
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CUdeviceptr d_C;
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checkCudaErrors(cuMemAlloc(&d_C, size));
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// Copy the host input vectors A and B in host memory to the device input
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// vectors in device memory
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printf("Copy input data from the host memory to the CUDA device\n");
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checkCudaErrors(cuMemcpyHtoD(d_A, h_A, size));
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checkCudaErrors(cuMemcpyHtoD(d_B, h_B, size));
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// Launch the Vector Add CUDA Kernel
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int threadsPerBlock = 256;
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int blocksPerGrid = (numElements + threadsPerBlock - 1) / threadsPerBlock;
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printf("CUDA kernel launch with %d blocks of %d threads\n", blocksPerGrid,
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threadsPerBlock);
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dim3 cudaBlockSize(threadsPerBlock, 1, 1);
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dim3 cudaGridSize(blocksPerGrid, 1, 1);
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void *arr[] = {reinterpret_cast<void *>(&d_A), reinterpret_cast<void *>(&d_B),
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reinterpret_cast<void *>(&d_C),
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reinterpret_cast<void *>(&numElements)};
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checkCudaErrors(cuLaunchKernel(kernel_addr, cudaGridSize.x, cudaGridSize.y,
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cudaGridSize.z, /* grid dim */
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cudaBlockSize.x, cudaBlockSize.y,
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cudaBlockSize.z, /* block dim */
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0, 0, /* shared mem, stream */
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&arr[0], /* arguments */
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0));
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checkCudaErrors(cuCtxSynchronize());
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// Copy the device result vector in device memory to the host result vector
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// in host memory.
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printf("Copy output data from the CUDA device to the host memory\n");
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checkCudaErrors(cuMemcpyDtoH(h_C, d_C, size));
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// Verify that the result vector is correct
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for (int i = 0; i < numElements; ++i) {
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if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {
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fprintf(stderr, "Result verification failed at element %d!\n", i);
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exit(EXIT_FAILURE);
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}
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}
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printf("Test PASSED\n");
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// Free device global memory
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checkCudaErrors(cuMemFree(d_A));
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checkCudaErrors(cuMemFree(d_B));
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checkCudaErrors(cuMemFree(d_C));
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// Free host memory
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free(h_A);
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free(h_B);
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free(h_C);
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printf("Done\n");
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return 0;
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}
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