mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-25 22:28:17 +08:00
Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks.
This commit is contained in:
Rob Armstrong
@@ -34,11 +34,11 @@
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*/
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// Includes
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#include <stdio.h>
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#include <string.h>
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#include <iostream>
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#include <cstring>
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#include <cuda.h>
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#include <iostream>
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#include <stdio.h>
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#include <string.h>
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// includes, project
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#include <helper_cuda_drvapi.h>
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@@ -50,19 +50,19 @@
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using namespace std;
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// Variables
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CUdevice cuDevice;
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CUcontext cuContext;
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CUmodule cuModule;
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CUfunction vecAdd_kernel;
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float *h_A;
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float *h_B;
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float *h_C;
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CUdevice cuDevice;
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CUcontext cuContext;
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CUmodule cuModule;
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CUfunction vecAdd_kernel;
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float *h_A;
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float *h_B;
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float *h_C;
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CUdeviceptr d_A;
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CUdeviceptr d_B;
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CUdeviceptr d_C;
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// Functions
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int CleanupNoFailure();
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int CleanupNoFailure();
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void RandomInit(float *, int);
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bool findModulePath(const char *, string &, char **, string &);
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@@ -72,150 +72,152 @@ bool findModulePath(const char *, string &, char **, string &);
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#endif
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// Host code
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int main(int argc, char **argv) {
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printf("Vector Addition (Driver API)\n");
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int N = 50000, devID = 0;
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size_t size = N * sizeof(float);
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int main(int argc, char **argv)
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{
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printf("Vector Addition (Driver API)\n");
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int N = 50000, devID = 0;
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size_t size = N * sizeof(float);
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// Initialize
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checkCudaErrors(cuInit(0));
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// Initialize
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checkCudaErrors(cuInit(0));
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cuDevice = findCudaDeviceDRV(argc, (const char **)argv);
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// Create context
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checkCudaErrors(cuCtxCreate(&cuContext, 0, cuDevice));
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cuDevice = findCudaDeviceDRV(argc, (const char **)argv);
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// Create context
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checkCudaErrors(cuCtxCreate(&cuContext, 0, cuDevice));
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// first search for the module path before we load the results
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string module_path;
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// first search for the module path before we load the results
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string module_path;
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std::ostringstream fatbin;
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std::ostringstream fatbin;
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if (!findFatbinPath(FATBIN_FILE, module_path, argv, fatbin)) {
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exit(EXIT_FAILURE);
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} else {
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printf("> initCUDA loading module: <%s>\n", module_path.c_str());
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}
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if (!findFatbinPath(FATBIN_FILE, module_path, argv, fatbin)) {
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exit(EXIT_FAILURE);
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}
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else {
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printf("> initCUDA loading module: <%s>\n", module_path.c_str());
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}
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if (!fatbin.str().size()) {
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printf("fatbin file empty. exiting..\n");
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exit(EXIT_FAILURE);
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}
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if (!fatbin.str().size()) {
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printf("fatbin file empty. exiting..\n");
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exit(EXIT_FAILURE);
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}
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// Create module from binary file (FATBIN)
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checkCudaErrors(cuModuleLoadData(&cuModule, fatbin.str().c_str()));
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// Create module from binary file (FATBIN)
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checkCudaErrors(cuModuleLoadData(&cuModule, fatbin.str().c_str()));
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// Get function handle from module
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checkCudaErrors(
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cuModuleGetFunction(&vecAdd_kernel, cuModule, "VecAdd_kernel"));
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// Get function handle from module
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checkCudaErrors(cuModuleGetFunction(&vecAdd_kernel, cuModule, "VecAdd_kernel"));
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// Allocate input vectors h_A and h_B in host memory
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h_A = (float *)malloc(size);
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h_B = (float *)malloc(size);
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h_C = (float *)malloc(size);
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// Allocate input vectors h_A and h_B in host memory
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h_A = (float *)malloc(size);
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h_B = (float *)malloc(size);
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h_C = (float *)malloc(size);
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// Initialize input vectors
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RandomInit(h_A, N);
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RandomInit(h_B, N);
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// Initialize input vectors
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RandomInit(h_A, N);
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RandomInit(h_B, N);
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// Allocate vectors in device memory
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checkCudaErrors(cuMemAlloc(&d_A, size));
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// Allocate vectors in device memory
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checkCudaErrors(cuMemAlloc(&d_A, size));
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checkCudaErrors(cuMemAlloc(&d_B, size));
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checkCudaErrors(cuMemAlloc(&d_B, size));
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checkCudaErrors(cuMemAlloc(&d_C, size));
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checkCudaErrors(cuMemAlloc(&d_C, size));
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// Copy vectors from host memory to device memory
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checkCudaErrors(cuMemcpyHtoD(d_A, h_A, size));
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// Copy vectors from host memory to device memory
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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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checkCudaErrors(cuMemcpyHtoD(d_B, h_B, size));
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if (1) {
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// This is the new CUDA 4.0 API for Kernel Parameter Passing and Kernel
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// Launch (simpler method)
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if (1) {
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// This is the new CUDA 4.0 API for Kernel Parameter Passing and Kernel
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// Launch (simpler method)
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// Grid/Block configuration
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int threadsPerBlock = 256;
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int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
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// Grid/Block configuration
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int threadsPerBlock = 256;
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int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
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void *args[] = {&d_A, &d_B, &d_C, &N};
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void *args[] = {&d_A, &d_B, &d_C, &N};
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// Launch the CUDA kernel
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checkCudaErrors(cuLaunchKernel(vecAdd_kernel, blocksPerGrid, 1, 1,
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threadsPerBlock, 1, 1, 0, NULL, args, NULL));
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} else {
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// This is the new CUDA 4.0 API for Kernel Parameter Passing and Kernel
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// Launch (advanced method)
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int offset = 0;
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void *argBuffer[16];
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*((CUdeviceptr *)&argBuffer[offset]) = d_A;
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offset += sizeof(d_A);
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*((CUdeviceptr *)&argBuffer[offset]) = d_B;
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offset += sizeof(d_B);
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*((CUdeviceptr *)&argBuffer[offset]) = d_C;
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offset += sizeof(d_C);
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*((int *)&argBuffer[offset]) = N;
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offset += sizeof(N);
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// Launch the CUDA kernel
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checkCudaErrors(cuLaunchKernel(vecAdd_kernel, blocksPerGrid, 1, 1, threadsPerBlock, 1, 1, 0, NULL, args, NULL));
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}
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else {
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// This is the new CUDA 4.0 API for Kernel Parameter Passing and Kernel
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// Launch (advanced method)
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int offset = 0;
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void *argBuffer[16];
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*((CUdeviceptr *)&argBuffer[offset]) = d_A;
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offset += sizeof(d_A);
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*((CUdeviceptr *)&argBuffer[offset]) = d_B;
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offset += sizeof(d_B);
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*((CUdeviceptr *)&argBuffer[offset]) = d_C;
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offset += sizeof(d_C);
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*((int *)&argBuffer[offset]) = N;
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offset += sizeof(N);
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// Grid/Block configuration
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int threadsPerBlock = 256;
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int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
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// Grid/Block configuration
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int threadsPerBlock = 256;
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int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
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// Launch the CUDA kernel
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checkCudaErrors(cuLaunchKernel(vecAdd_kernel, blocksPerGrid, 1, 1,
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threadsPerBlock, 1, 1, 0, NULL, NULL,
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argBuffer));
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}
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// Launch the CUDA kernel
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checkCudaErrors(
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cuLaunchKernel(vecAdd_kernel, blocksPerGrid, 1, 1, threadsPerBlock, 1, 1, 0, NULL, NULL, argBuffer));
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}
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#ifdef _DEBUG
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checkCudaErrors(cuCtxSynchronize());
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checkCudaErrors(cuCtxSynchronize());
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#endif
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// Copy result from device memory to host memory
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// h_C contains the result in host memory
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checkCudaErrors(cuMemcpyDtoH(h_C, d_C, size));
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// Copy result from device memory to host memory
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// h_C contains the result in host memory
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checkCudaErrors(cuMemcpyDtoH(h_C, d_C, size));
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// Verify result
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int i;
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// Verify result
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int i;
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for (i = 0; i < N; ++i) {
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float sum = h_A[i] + h_B[i];
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for (i = 0; i < N; ++i) {
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float sum = h_A[i] + h_B[i];
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if (fabs(h_C[i] - sum) > 1e-7f) {
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break;
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if (fabs(h_C[i] - sum) > 1e-7f) {
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break;
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}
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}
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}
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CleanupNoFailure();
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printf("%s\n", (i == N) ? "Result = PASS" : "Result = FAIL");
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CleanupNoFailure();
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printf("%s\n", (i == N) ? "Result = PASS" : "Result = FAIL");
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exit((i == N) ? EXIT_SUCCESS : EXIT_FAILURE);
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exit((i == N) ? EXIT_SUCCESS : EXIT_FAILURE);
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}
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int CleanupNoFailure() {
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// Free device 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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int CleanupNoFailure()
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{
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// Free device 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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if (h_A) {
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free(h_A);
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}
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// Free host memory
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if (h_A) {
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free(h_A);
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}
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if (h_B) {
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free(h_B);
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}
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if (h_B) {
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free(h_B);
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}
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if (h_C) {
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free(h_C);
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}
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if (h_C) {
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free(h_C);
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}
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checkCudaErrors(cuCtxDestroy(cuContext));
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checkCudaErrors(cuCtxDestroy(cuContext));
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return EXIT_SUCCESS;
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return EXIT_SUCCESS;
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}
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// Allocates an array with random float entries.
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void RandomInit(float *data, int n) {
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for (int i = 0; i < n; ++i) {
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data[i] = rand() / (float)RAND_MAX;
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}
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void RandomInit(float *data, int n)
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{
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for (int i = 0; i < n; ++i) {
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data[i] = rand() / (float)RAND_MAX;
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}
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}
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@@ -33,9 +33,10 @@
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*/
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// Device code
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extern "C" __global__ void VecAdd_kernel(const float *A, const float *B,
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float *C, int N) {
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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extern "C" __global__ void VecAdd_kernel(const float *A, const float *B, float *C, int N)
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{
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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if (i < N) C[i] = A[i] + B[i];
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if (i < N)
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C[i] = A[i] + B[i];
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}
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