119 lines
3.7 KiB
Plaintext
119 lines
3.7 KiB
Plaintext
#include "mat_mul.h"
|
|
|
|
#include <cstdio>
|
|
#include <cuda_runtime.h>
|
|
|
|
#define CUDA_CALL(f) \
|
|
{ \
|
|
cudaError_t err = (f); \
|
|
if (err != cudaSuccess) { \
|
|
fprintf(stderr, "CUDA error at [%s:%d] %d %s\n", __FILE__, __LINE__, \
|
|
err, cudaGetErrorString(err)); \
|
|
exit(1); \
|
|
} \
|
|
}
|
|
|
|
#define MAX_NUM_GPU 4
|
|
int num_devices = 0;
|
|
|
|
__global__ void sgemm(float *A, float *B, float *C, int M, int N, int K) {
|
|
int i = blockDim.x * blockIdx.x + threadIdx.x;
|
|
int j = blockDim.y * blockIdx.y + threadIdx.y;
|
|
if (i >= M || j >= N)
|
|
return;
|
|
|
|
C[i * N + j] = 0;
|
|
for (int k = 0; k < K; ++k) {
|
|
C[i * N + j] += A[i * K + k] * B[k * N + j];
|
|
}
|
|
}
|
|
|
|
// Array of device (GPU) pointers
|
|
static float *a_d[MAX_NUM_GPU];
|
|
static float *b_d[MAX_NUM_GPU];
|
|
static float *c_d[MAX_NUM_GPU];
|
|
static int M, N, K;
|
|
static int Mbegin[MAX_NUM_GPU], Mend[MAX_NUM_GPU];
|
|
|
|
void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K) {
|
|
|
|
// Launch kernel on every GPU
|
|
for (int i = 0; i < num_devices; i++) {
|
|
dim3 blockDim(1, 1, 1);
|
|
dim3 gridDim(Mend[i] - Mbegin[i], N, 1);
|
|
|
|
CUDA_CALL(cudaSetDevice(i));
|
|
sgemm<<<gridDim, blockDim>>>(a_d[i], b_d[i], c_d[i], M, N, K);
|
|
}
|
|
|
|
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaDeviceSynchronize());
|
|
}
|
|
}
|
|
|
|
void mat_mul_init(float *A, float *B, float *C, int _M, int _N, int _K) {
|
|
M = _M, N = _N, K = _K;
|
|
|
|
CUDA_CALL(cudaGetDeviceCount(&num_devices));
|
|
|
|
printf("Using %d devices\n", num_devices);
|
|
for (int i = 0; i < num_devices; i++) {
|
|
cudaDeviceProp prop;
|
|
CUDA_CALL(cudaGetDeviceProperties(&prop, i));
|
|
|
|
// Try printing more detailed information here
|
|
printf("[GPU %d] %s\n", i, prop.name);
|
|
}
|
|
|
|
if (num_devices <= 0) {
|
|
printf("No CUDA device found. Aborting\n");
|
|
exit(1);
|
|
}
|
|
|
|
// Setup problem size for each GPU
|
|
for (int i = 0; i < num_devices; i++) {
|
|
Mbegin[i] = (M / num_devices) * i;
|
|
Mend[i] = (M / num_devices) * (i + 1);
|
|
}
|
|
Mend[num_devices - 1] = M;
|
|
|
|
// Allocate device memory for each GPU
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaSetDevice(i));
|
|
CUDA_CALL(cudaMalloc(&a_d[i], (Mend[i] - Mbegin[i]) * K * sizeof(float)));
|
|
CUDA_CALL(cudaMalloc(&b_d[i], K * N * sizeof(float)));
|
|
CUDA_CALL(cudaMalloc(&c_d[i], (Mend[i] - Mbegin[i]) * N * sizeof(float)));
|
|
}
|
|
|
|
// Upload A and B matrix to every GPU
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaMemcpy(a_d[i], A + Mbegin[i] * K,
|
|
(Mend[i] - Mbegin[i]) * K * sizeof(float),
|
|
cudaMemcpyHostToDevice));
|
|
CUDA_CALL(
|
|
cudaMemcpy(b_d[i], B, K * N * sizeof(float), cudaMemcpyHostToDevice));
|
|
}
|
|
|
|
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaDeviceSynchronize());
|
|
}
|
|
}
|
|
|
|
void mat_mul_final(float *A, float *B, float *C, int M, int N, int K) {
|
|
// Do any post-matmul cleanup work here.
|
|
|
|
// Download C matrix from GPUs
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaMemcpy(C + Mbegin[i] * N, c_d[i],
|
|
(Mend[i] - Mbegin[i]) * N * sizeof(float),
|
|
cudaMemcpyDeviceToHost));
|
|
}
|
|
|
|
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
|
|
for (int i = 0; i < num_devices; i++) {
|
|
CUDA_CALL(cudaDeviceSynchronize());
|
|
}
|
|
}
|