/* * BSD 2-Clause License * * Copyright (c) 2020, Alessandro Capotondi * 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. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "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 HOLDER 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. */ /** * @file exercise2.cu * @author Alessandro Capotondi * @date 27 Mar 2020 * @brief Exercise 2 * * @see https://dolly.fim.unimore.it/2019/course/view.php?id=152 */ #include #include #include #include #include #include #include #define gpuErrchk(ans) \ { \ gpuAssert((ans), __FILE__, __LINE__); \ } static inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort = true) { if (code != cudaSuccess) { fprintf(stderr, "GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line); if (abort) exit(code); } } extern "C" { #include "utils.h" } #define TWO02 (1 << 2) #define TWO04 (1 << 4) #define TWO08 (1 << 8) #ifndef N #define N (1 << 27) #endif #ifndef BLOCK_SIZE #define BLOCK_SIZE (1024) #endif /* *SAXPY (host implementation) * y := a * x + y */ void host_saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n) { #pragma omp parallel for simd schedule(simd: static) for (int i = 0; i < n; i++) { y[i] = a * x[i] + y[i]; } } __global__ void saxpy(float * __restrict__ y, float a, float * __restrict__ x, int n) { //TODO: Add saxpy kernel body } int main(int argc, const char **argv) { int iret = 0; int n = N; float *h_x, *d_x; float *h_y, *d_y; float *h_z; float a = 101.0f / TWO02, b, c; if (argc > 1) n = atoi(argv[1]); if (NULL == (h_x = (float *)malloc(sizeof(float) * n))) { printf("error: memory allocation for 'x'\n"); iret = -1; } if (NULL == (h_y = (float *)malloc(sizeof(float) * n))) { printf("error: memory allocation for 'y'\n"); iret = -1; } if (NULL == (h_z = (float *)malloc(sizeof(float) * n))) { printf("error: memory allocation for 'z'\n"); iret = -1; } if (0 != iret) { free(h_x); free(h_y); free(h_z); exit(EXIT_FAILURE); } //Init Data b = rand() % TWO04; c = rand() % TWO08; for (int i = 0; i < n; i++) { h_x[i] = b / (float)TWO02; h_y[i] = h_z[i] = c / (float)TWO04; } //CUDA Buffer Allocation gpuErrchk(cudaMalloc((void **)&d_x, sizeof(float) * n)); gpuErrchk(cudaMalloc((void **)&d_y, sizeof(float) * n)); //TODO: ADD CUDA Data Move start_timer(); cudaMemcpy(d_x, h_x, sizeof(float) * n, cudaMemcpyHostToDevice); //TODO: Add kernel call here gpuErrchk(cudaPeekAtLastError()); //TODO: ADD CUDA Data Move stop_timer(); printf("saxpy (GPU): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns())); //Check Matematical Consistency start_timer(); host_saxpy(h_z, a, h_x, n); stop_timer(); printf("saxpy (Host): %9.3f sec %9.1f MFLOPS\n", elapsed_ns() / 1.0e9, 2 * n / ((1.0e6 / 1e9) * elapsed_ns())); for (int i = 0; i < n; ++i) { iret = *(int *)(h_y + i) ^ *(int *)(h_z + i); assert(iret == 0); } //CUDA Buffer Allocation free(h_x); gpuErrchk(cudaFree(d_x)); free(h_y); gpuErrchk(cudaFree(d_y)); free(h_z); return 0; }