/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of NVIDIA CORPORATION nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ /* * Demonstration of inline PTX (assembly language) usage in CUDA kernels */ // System includes #include #include // CUDA runtime #include #include // helper functions and utilities to work with CUDA #include void sequence_cpu(int *h_ptr, int length) { for (int elemID = 0; elemID < length; elemID++) { h_ptr[elemID] = elemID % 32; } } int main(int argc, char **argv) { printf("CUDA inline PTX assembler sample\n"); char *cubin, *kernel_file; size_t cubinSize; kernel_file = sdkFindFilePath("inlinePTX_kernel.cu", argv[0]); compileFileToCUBIN(kernel_file, argc, argv, &cubin, &cubinSize, 0); CUmodule module = loadCUBIN(cubin, argc, argv); CUfunction kernel_addr; checkCudaErrors(cuModuleGetFunction(&kernel_addr, module, "sequence_gpu")); const int N = 1000; int *h_ptr = (int *)malloc(N * sizeof(int)); dim3 cudaBlockSize(256, 1, 1); dim3 cudaGridSize((N + cudaBlockSize.x - 1) / cudaBlockSize.x, 1, 1); CUdeviceptr d_ptr; checkCudaErrors(cuMemAlloc(&d_ptr, N * sizeof(int))); void *arr[] = {(void *)&d_ptr, (void *)&N}; checkCudaErrors(cuLaunchKernel(kernel_addr, cudaGridSize.x, cudaGridSize.y, cudaGridSize.z, /* grid dim */ cudaBlockSize.x, cudaBlockSize.y, cudaBlockSize.z, /* block dim */ 0, 0, /* shared mem, stream */ &arr[0], /* arguments */ 0)); checkCudaErrors(cuCtxSynchronize()); sequence_cpu(h_ptr, N); int *h_d_ptr = (int *)malloc(N * sizeof(int)); checkCudaErrors(cuMemcpyDtoH(h_d_ptr, d_ptr, N * sizeof(int))); bool bValid = true; for (int i = 0; i < N && bValid; i++) { if (h_ptr[i] != h_d_ptr[i]) { bValid = false; } } printf("Test %s.\n", bValid ? "Successful" : "Failed"); checkCudaErrors(cuMemFree(d_ptr)); return bValid ? EXIT_SUCCESS : EXIT_FAILURE; }