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hpc-2022-g3/cuda/lab3/.solutions/gemm-v2.cu

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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 gemm.cu
* @author Alessandro Capotondi
* @date 12 May 2020
* @brief GEMM Kernel
*
* @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 TILE_W
#define TILE_W 128
#endif
#ifndef BLOCK_SIZE
#define BLOCK_SIZE 32
#endif
#define SM 64
static void reorder(float *__restrict__ a, float *__restrict__ b, int n)
{
for (int i = 0; i < SM; i++)
for (int j = 0; j < SM; j++)
b[i * SM + j] = a[i * n + j];
}
static void mm(float *__restrict__ a, float *__restrict__ b, float *__restrict__ c, int n)
{
for (int i = 0; i < SM; i++)
{
for (int k = 0; k < SM; k++)
{
for (int j = 0; j < SM; j++)
{
c[i * n + j] += a[i * n + k] * b[k * SM + j];
}
}
}
}
void gemm_host(float *a, float *b, float *c, int n)
{
int bk = n / SM;
#pragma omp parallel for collapse(3)
for (int i = 0; i < bk; i++)
{
for (int j = 0; j < bk; j++)
{
for (int k = 0; k < bk; k++)
{
float b2[SM * SM];
reorder(&b[SM * (k * n + j)], b2, n);
mm(&a[SM * (i * n + k)], b2, &c[SM * (i * n + j)], n);
}
}
}
}
__global__ void gemm(float *__restrict__ a, float *__restrict__ b, float *__restrict__ c, int n)
{
__shared__ float As[BLOCK_SIZE][BLOCK_SIZE];
__shared__ float Bs[BLOCK_SIZE][BLOCK_SIZE];
int ib = blockIdx.y;
int jb = blockIdx.x;
int it = threadIdx.y;
int jt = threadIdx.x;
int a_offset, b_offset, c_offset;
float Cvalue = 0.0f;
for (int kb = 0; kb < (n / BLOCK_SIZE); ++kb)
{
a_offset = ib * n * BLOCK_SIZE + kb * BLOCK_SIZE;
b_offset = kb * n * BLOCK_SIZE + jb * BLOCK_SIZE;
As[it][jt] = a[a_offset + it * n + jt];
Bs[it][jt] = b[b_offset + it * n + jt];
__syncthreads();
for (int k = 0; k < BLOCK_SIZE; ++k)
Cvalue += As[it][k] * Bs[k][jt];
__syncthreads();
}
c_offset = ib * n * BLOCK_SIZE + jb * BLOCK_SIZE;
c[c_offset + it * n + jt] = Cvalue;
}
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]);
//TODO Update malloc to cudaMallocManaged
gpuErrchk(cudaMallocManaged((void **)&a, sizeof(float) * n *n));
gpuErrchk(cudaMallocManaged((void **)&b, sizeof(float) * n *n));
gpuErrchk(cudaMallocManaged((void **)&c, sizeof(float) * n *n));
if (NULL == (g = (float *)malloc(sizeof(*g) * n * n)))
{
printf("error: memory allocation for 'z'\n");
iret = -1;
}
if (0 != iret)
{
gpuErrchk(cudaFree(a));
gpuErrchk(cudaFree(b));
gpuErrchk(cudaFree(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_host(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));
clock_gettime(CLOCK_REALTIME, rt + 0);
dim3 dimBlock(BLOCK_SIZE, BLOCK_SIZE);
dim3 dimGrid((n + (BLOCK_SIZE)-1) / (BLOCK_SIZE), (n + (BLOCK_SIZE)-1) / (BLOCK_SIZE));
gemm<<<dimGrid, dimBlock>>>(a, b, c, n);
gpuErrchk(cudaPeekAtLastError());
cudaDeviceSynchronize();
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-v1 (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);
}
gpuErrchk(cudaFree(a));
gpuErrchk(cudaFree(b));
gpuErrchk(cudaFree(c));
free(g);
return 0;
}