143 lines
4.1 KiB
Plaintext
143 lines
4.1 KiB
Plaintext
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#include "mat_mul.h"
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#include <cstdio>
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#include <cuda_runtime.h>
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#define CUDA_CALL(f) \
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{ \
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cudaError_t err = (f); \
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if (err != cudaSuccess) { \
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fprintf(stderr, "CUDA error at [%s:%d] %d %s\n", __FILE__, __LINE__, \
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err, cudaGetErrorString(err)); \
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exit(1); \
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} \
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}
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#define MAX_NUM_GPU 4
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int num_devices = 0;
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#define TILE_SIZE 16
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__global__ void sgemm(float *A, float *B, float *C, int M, int N, int K) {
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int bx = blockIdx.x, by = blockIdx.y;
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int tx = threadIdx.x, ty = threadIdx.y;
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__shared__ float As[TILE_SIZE][TILE_SIZE];
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__shared__ float Bs[TILE_SIZE][TILE_SIZE];
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int aBegin = K * TILE_SIZE * by;
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int aEnd = aBegin + K - 1;
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int aStep = TILE_SIZE;
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int bBegin = TILE_SIZE * bx;
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int bStep = TILE_SIZE * N;
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float Csub = 0;
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for (int i = aBegin, j = bBegin; i <= aEnd; i += aStep, j += bStep) {
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As[ty][tx] = A[i + K * ty + tx];
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Bs[tx][ty] = B[j + N * tx + ty];
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__syncthreads();
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for (int k = 0; k < TILE_SIZE; ++k) {
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Csub += As[ty][k]*Bs[k][tx];
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}
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__syncthreads();
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}
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int cIdx = N * TILE_SIZE * by + TILE_SIZE * bx;
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C[cIdx + N * ty + tx] = Csub;
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}
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// Array of device (GPU) pointers
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static float *a_d[MAX_NUM_GPU];
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static float *b_d[MAX_NUM_GPU];
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static float *c_d[MAX_NUM_GPU];
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static int M, N, K;
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static int Mbegin[MAX_NUM_GPU], Mend[MAX_NUM_GPU];
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void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K) {
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// Launch kernel on every GPU
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// FIXME: Every GPU redundantly calculate all elements of C
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for (int i = 0; i < num_devices; i++) {
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dim3 blockDim(TILE_SIZE, TILE_SIZE, 1);
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dim3 gridDim(N / TILE_SIZE, (Mend[i] - Mbegin[i]) / TILE_SIZE, 1);
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cudaSetDevice(i);
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sgemm<<<gridDim, blockDim>>>(a_d[i], b_d[i], c_d[i], Mend[i] - Mbegin[i], N, K);
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL( cudaDeviceSynchronize() );
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}
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}
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void mat_mul_init(float *A, float *B, float *C, int _M, int _N, int _K) {
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M = _M, N = _N, K = _K;
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cudaGetDeviceCount(&num_devices);
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printf("Using %d devices\n", num_devices);
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for (int i = 0; i < num_devices; i++) {
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cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, i);
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// Try printing more detailed information here
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printf("[GPU %d] %s\n", i, prop.name);
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}
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if (num_devices <= 0) {
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printf("No CUDA device found. Aborting\n");
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exit(1);
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}
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// Setup problem size for each GPU
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for (int i = 0; i < num_devices; i++) {
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Mbegin[i] = (M / num_devices) * i;
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Mend[i] = (M / num_devices) * (i + 1);
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}
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Mend[num_devices - 1] = M;
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// Allocate device memory for each GPU
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for (int i = 0; i < num_devices; i++) {
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cudaSetDevice(i);
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cudaMalloc(&a_d[i], (Mend[i] - Mbegin[i]) * K * sizeof(float));
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cudaMalloc(&b_d[i], K * N * sizeof(float));
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cudaMalloc(&c_d[i], (Mend[i] - Mbegin[i]) * N * sizeof(float));
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}
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// Upload A and B matrix to every GPU
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for (int i = 0; i < num_devices; i++) {
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cudaMemcpy(a_d[i], A + Mbegin[i] * K,
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(Mend[i] - Mbegin[i]) * K * sizeof(float),
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cudaMemcpyHostToDevice);
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cudaMemcpy(b_d[i], B, K * N * sizeof(float), cudaMemcpyHostToDevice);
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < num_devices; i++) {
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cudaDeviceSynchronize();
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}
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}
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void mat_mul_final(float *A, float *B, float *C, int M, int N, int K) {
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// Do any post-matmul cleanup work here.
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// Download C matrix from GPU 0
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// FIXME: Result from the other GPUs are ignored
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for (int i = 0; i < num_devices; i++) {
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cudaMemcpy(C + Mbegin[i] * N, c_d[i],
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(Mend[i] - Mbegin[i]) * N * sizeof(float),
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cudaMemcpyDeviceToHost);
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < num_devices; i++) {
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cudaDeviceSynchronize();
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}
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}
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