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hpc-2022-g3/cuda/lab1/.solutions/exercise3-v2.cu
Alessandro Capotondi 0d0b0f04cf HPC CUDA Lab 1
2021-04-28 11:09:08 +02:00

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/*
* 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 exercise3.cu
* @author Alessandro Capotondi
* @date 27 Mar 2020
* @brief Exercise 3 - CUDA MATMUL
*
* @see https://dolly.fim.unimore.it/2019/course/view.php?id=152
*/
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#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 << 10)
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 32
#endif
void gemm(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
#pragma omp parallel for collapse(2)
for (int i = 0; i < n; ++i)
{
for (int j = 0; j < n; ++j)
{
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[i * n + k] * b[k *n + j];
}
c[i * n + j] = sum;
}
}
}
/**
* @brief EX 3 - Complete Matrix Multiplication
*/
__global__ void gemm_kernel(float * __restrict__ a, float * __restrict__ b, float * __restrict__ c, int n)
{
int row = threadIdx.x + blockIdx.x * blockDim.x;
int col = threadIdx.y + blockIdx.y * blockDim.y;
float sum = 0.0;
for (int k = 0; k < n; ++k)
{
sum += a[row * n + k] * b[k * n + col];
}
c[row * n + col] = sum;
}
int main(int argc, char *argv[])
{
int n = N, iret = 0;
float *a, *b, *c, *g;
struct timespec rt[2];
double wt; // walltime
if (argc > 1)
n = atoi(argv[1]);
if (NULL == (a = (float *)malloc(sizeof(*a) * n * n)))
{
printf("error: memory allocation for 'x'\n");
iret = -1;
}
if (NULL == (b = (float *)malloc(sizeof(*b) * n * n)))
{
printf("error: memory allocation for 'y'\n");
iret = -1;
}
if (NULL == (c = (float *)malloc(sizeof(*c) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
free(a);
free(b);
free(c);
free(g);
exit(EXIT_FAILURE);
}
//Init Data
int _b = rand() % TWO04;
int _c = rand() % TWO08;
#pragma omp parallel for
for (int i = 0; i < n * n; i++)
{
a[i] = _b / (float)TWO02;
b[i] = _c / (float)TWO04;
c[i] = g[i] = 0.0;
}
clock_gettime(CLOCK_REALTIME, rt + 0);
gemm(a, b, g, n);
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (Host) : %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
//CUDA Buffer Allocation
float *d_a, *d_b, *d_c;
gpuErrchk(cudaMalloc((void **)&d_a, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_b, sizeof(float) * n * n));
gpuErrchk(cudaMalloc((void **)&d_c, sizeof(float) * n * n));
clock_gettime(CLOCK_REALTIME, rt + 0);
gpuErrchk(cudaMemcpy(d_a, a, sizeof(float) * n * n, cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(d_b, b, sizeof(float) * n * n, cudaMemcpyHostToDevice));
dim3 dimBlock(BLOCK_SIZE,BLOCK_SIZE);
dim3 dimGrid((n+BLOCK_SIZE-1)/BLOCK_SIZE,(n+BLOCK_SIZE-1)/BLOCK_SIZE);
gemm_kernel<<<dimGrid, dimBlock>>> (d_a, d_b, d_c, n);
gpuErrchk(cudaPeekAtLastError());
gpuErrchk(cudaMemcpy(c, d_c, sizeof(float) * n * n, cudaMemcpyDeviceToHost));
clock_gettime(CLOCK_REALTIME, rt + 1);
wt = (rt[1].tv_sec - rt[0].tv_sec) + 1.0e-9 * (rt[1].tv_nsec - rt[0].tv_nsec);
printf("GEMM (GPU): %9.3f sec %9.1f GFLOPS\n", wt, 2.0 * n * n * n / (1.0e9 * wt));
for (int i = 0; i < n * n; i++)
{
iret = *(int *)(g + i) ^ *(int *)(c + i);
assert(iret == 0);
}
free(a);
free(b);
free(c);
free(g);
gpuErrchk(cudaFree(d_a));
gpuErrchk(cudaFree(d_b));
gpuErrchk(cudaFree(d_c));
return 0;
}