252 lines
8.3 KiB
Plaintext
252 lines
8.3 KiB
Plaintext
|
#include "convolution.h"
|
||
|
#include "util.h"
|
||
|
#include <mpi.h>
|
||
|
#include <stdio.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_CPU 2
|
||
|
#define MAX_NUM_GPU 4
|
||
|
#define TS 8
|
||
|
|
||
|
static float *input, *output, *filter;
|
||
|
static int N, C, H, W;
|
||
|
static int K, R, S;
|
||
|
static int OH, OW;
|
||
|
static int pad;
|
||
|
static int dilation;
|
||
|
static int stride;
|
||
|
static int mpi_rank, mpi_world_size;
|
||
|
static int ns[MAX_NUM_CPU], ne[MAX_NUM_CPU];
|
||
|
|
||
|
static float *input_d[MAX_NUM_GPU];
|
||
|
static float *filter_d[MAX_NUM_GPU];
|
||
|
static float *output_d[MAX_NUM_GPU];
|
||
|
static int Nbegin[MAX_NUM_CPU][MAX_NUM_GPU], Nend[MAX_NUM_CPU][MAX_NUM_GPU];
|
||
|
|
||
|
int num_devices = 0;
|
||
|
|
||
|
__global__ void convolution_thread(
|
||
|
float *input, float *output, float *filter,
|
||
|
int N, int C, int H, int W,
|
||
|
int K, int R, int S,
|
||
|
int pad, int dilation, int stride,
|
||
|
int OH, int OW) {
|
||
|
//printf("blockIdx.x:%d\n", blockIdx.x);
|
||
|
//printf("blockDim.x:%d\n", blockDim.x);
|
||
|
//printf("threadIdx.x:%d\n", threadIdx.x);
|
||
|
//printf("blockIdx.y:%d\n", blockIdx.y);
|
||
|
#if 0
|
||
|
int oh = (blockIdx.x * blockDim.x + threadIdx.x);
|
||
|
int ow = (blockIdx.y * blockDim.y + threadIdx.y);
|
||
|
//int k = (blockIdx.z * blockDim.z + threadIdx.z) % K;
|
||
|
//int n = (blockIdx.z * blockDim.z + threadIdx.z) / K;
|
||
|
int k = (blockIdx.z) % K;
|
||
|
int n = (blockIdx.z) / K;
|
||
|
|
||
|
#else
|
||
|
int ow = threadIdx.x;
|
||
|
int oh = blockIdx.x;
|
||
|
int k = blockIdx.y;
|
||
|
int n = blockIdx.z;
|
||
|
//int ow = threadIdx.x;
|
||
|
//int oh = blockIdx.z;
|
||
|
//int k = blockIdx.y;
|
||
|
//int n = blockIdx.x;
|
||
|
#endif
|
||
|
if (oh >= OH || ow >= OW || k >= K || n >= N) return;
|
||
|
|
||
|
//__shared__ int *filter_d;
|
||
|
|
||
|
//__syncthreads();
|
||
|
//
|
||
|
|
||
|
float o = 0.f;
|
||
|
for (int c = 0; c < C; ++c) {
|
||
|
for (int r = 0; r < R; ++r) {
|
||
|
int h = oh * stride - pad + r * dilation;
|
||
|
for (int s = 0; s < S; ++s) {
|
||
|
int w = ow * stride - pad + s * dilation;
|
||
|
if (h < 0 || h >= H || w < 0 || w >= W) continue;
|
||
|
float i = input[n * C * H * W + c * H * W + h * W + w];
|
||
|
float f = filter[k * C * R * S + c * R * S + r * S + s];
|
||
|
//printf("input[n * C * H * W + c * H * W + h * W + w] = %f\n", i);
|
||
|
//printf("filter[k * C * R * S + c * R * S + r * S + s] = %f\n", f);
|
||
|
o += i * f;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
output[n * K * OH * OW + k * OH * OW + oh * OW + ow] = o;
|
||
|
//printf("output[n * K * OH * OW + k * OH * OW + oh * OW + ow]= %f\n", o);
|
||
|
}
|
||
|
|
||
|
|
||
|
void convolution (
|
||
|
float *_input, float *_output, float *_filter,
|
||
|
int _N, int _C, int _H, int _W,
|
||
|
int _K, int _R, int _S,
|
||
|
int _pad, int _dilation, int _stride) {
|
||
|
input = _input;
|
||
|
output = _output;
|
||
|
filter = _filter;
|
||
|
|
||
|
if (mpi_rank != 0) {
|
||
|
alloc_tensor(&input, N, C, H, W);
|
||
|
alloc_tensor(&output, N, K, OH, OW);
|
||
|
alloc_tensor(&filter, K, C, R, S);
|
||
|
}
|
||
|
|
||
|
|
||
|
if (mpi_world_size > 1) {
|
||
|
if (mpi_rank == 0) {
|
||
|
for (int i = 1; i < mpi_world_size; i++) {
|
||
|
MPI_Send(input + ns[i] * C * H * W, (ne[i] - ns[i]) * C * H * W, MPI_FLOAT, i, 0,
|
||
|
MPI_COMM_WORLD);
|
||
|
MPI_Send(filter, K * C * R * S, MPI_FLOAT, i, 0, MPI_COMM_WORLD);
|
||
|
}
|
||
|
} else {
|
||
|
MPI_Recv(input + ns[mpi_rank] * C * H * W, (ne[mpi_rank] - ns[mpi_rank]) * C * H * W, MPI_FLOAT,
|
||
|
0, 0, MPI_COMM_WORLD, nullptr);
|
||
|
MPI_Recv(filter, K * C * R * S, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, nullptr);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
//printf("ns[%d] : %d\n", mpi_rank, ns[mpi_rank]);
|
||
|
//printf("ne[%d] : %d\n", mpi_rank, ne[mpi_rank]);
|
||
|
//for(int i = 0; i < num_devices; i++)
|
||
|
//{
|
||
|
// printf("Nbegin[%d][%d] : %d\n", mpi_rank,i,Nbegin[mpi_rank][i]);
|
||
|
// printf("Nend[%d][%d] : %d\n", mpi_rank,i,Nend[mpi_rank][i]);
|
||
|
//}
|
||
|
|
||
|
// Cuda start
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
if(Nend[mpi_rank][i] - Nbegin[mpi_rank][i] != 0)
|
||
|
{
|
||
|
//printf("Nend[mpi_rank][%d]:%d\n", i, Nend[mpi_rank][i]);
|
||
|
//printf("Nbegin[mpi_rank][%d]:%d\n", i, Nbegin[mpi_rank][i]);
|
||
|
//printf("%d, %d\n",ns[mpi_rank], Nbegin[mpi_rank][i]);
|
||
|
CUDA_CALL( cudaMemcpy(input_d[i], input + (ns[mpi_rank] + Nbegin[mpi_rank][i]) * C * H * W,
|
||
|
(Nend[mpi_rank][i] - Nbegin[mpi_rank][i]) * C * H * W * sizeof(float), cudaMemcpyHostToDevice) );
|
||
|
CUDA_CALL( cudaMemcpy(filter_d[i], filter, K * C * R * S * sizeof(float), cudaMemcpyHostToDevice) );
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
CUDA_CALL( cudaDeviceSynchronize() );
|
||
|
}
|
||
|
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
//dim3 blockDim(OH, OW);
|
||
|
//dim3 gridDim(Nend[mpi_rank][i] - Nbegin[mpi_rank][i], K);
|
||
|
//printf("test[%d]\n", mpi_rank);
|
||
|
if(Nend[mpi_rank][i] - Nbegin[mpi_rank][i] != 0)
|
||
|
{
|
||
|
#if 0
|
||
|
dim3 blockDim(TS, TS);
|
||
|
dim3 gridDim((OH + TS - 1) / TS, (OW + TS - 1)/ TS, ((Nend[mpi_rank][i] - Nbegin[mpi_rank][i]) * K));
|
||
|
//printf("Nend[mpi_rank][%d]:%d\n", i, Nend[mpi_rank][i]);
|
||
|
//printf("Nbegin[mpi_rank][%d]:%d\n", i, Nbegin[mpi_rank][i]);
|
||
|
#else
|
||
|
dim3 blockDim(OW);
|
||
|
dim3 gridDim(OH, K, Nend[mpi_rank][i] - Nbegin[mpi_rank][i]);
|
||
|
//dim3 gridDim(Nend[mpi_rank][i] - Nbegin[mpi_rank][i], K, OH);
|
||
|
#endif
|
||
|
CUDA_CALL( cudaSetDevice(i) );
|
||
|
convolution_thread<<<gridDim, blockDim>>>(input_d[i], output_d[i], filter_d[i], (Nend[mpi_rank][i] - Nbegin[mpi_rank][i]),
|
||
|
_C, _H, _W, _K, _R, _S, _pad, _dilation, _stride, OH, OW);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
CUDA_CALL( cudaDeviceSynchronize() );
|
||
|
}
|
||
|
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
if(Nend[mpi_rank][i] - Nbegin[mpi_rank][i] != 0)
|
||
|
{
|
||
|
CUDA_CALL( cudaMemcpy(output + (ns[mpi_rank] + Nbegin[mpi_rank][i]) * K * OH * OW, output_d[i],
|
||
|
(Nend[mpi_rank][i] - Nbegin[mpi_rank][i]) * K * OH * OW * sizeof(float),
|
||
|
cudaMemcpyDeviceToHost) );
|
||
|
}
|
||
|
}
|
||
|
// Cuda end
|
||
|
|
||
|
if (mpi_world_size > 1) {
|
||
|
if (mpi_rank == 0) {
|
||
|
for (int i = 1; i <mpi_world_size; i++) {
|
||
|
MPI_Recv(output + ns[i] * K * OH * OW, (ne[i] - ns[i]) * K * OH * OW, MPI_FLOAT, i, 0,
|
||
|
MPI_COMM_WORLD, nullptr);
|
||
|
}
|
||
|
} else {
|
||
|
MPI_Send(output + ns[mpi_rank] * K * OH * OW, (ne[mpi_rank] - ns[mpi_rank]) * K * OH * OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void convolution_init(
|
||
|
int _N, int _C, int _H, int _W,
|
||
|
int _K, int _R, int _S,
|
||
|
int _pad, int _dilation, int _stride) {
|
||
|
N = _N; C = _C; H = _H; W = _W;
|
||
|
K = _K; R = _R; S = _S;
|
||
|
pad = _pad;
|
||
|
dilation = _dilation;
|
||
|
stride = _stride;
|
||
|
|
||
|
MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
|
||
|
MPI_Comm_size(MPI_COMM_WORLD, &mpi_world_size);
|
||
|
|
||
|
OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1;
|
||
|
OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1;
|
||
|
|
||
|
CUDA_CALL( cudaGetDeviceCount(&num_devices) );
|
||
|
|
||
|
for (int i = 0; i < mpi_world_size; i++) {
|
||
|
ns[i] = N / mpi_world_size * i;
|
||
|
ne[i] = N / mpi_world_size * (i + 1);
|
||
|
for (int j = 0; j < num_devices; j++) {
|
||
|
Nbegin[i][j] = ((ne[i] - ns[i]) / num_devices) * j;
|
||
|
Nend[i][j] = ((ne[i] - ns[i]) / num_devices) * (j + 1);
|
||
|
}
|
||
|
}
|
||
|
ne[mpi_world_size - 1] = N;
|
||
|
for(int i = 0; i < mpi_world_size; i++) {
|
||
|
Nend[i][num_devices - 1] = ne[i] - ns[i];
|
||
|
}
|
||
|
|
||
|
//for (int i = 0; i< num_devices; i++) {
|
||
|
// printf("%d: Nbegin[%d]: %d\n",mpi_rank, i, Nbegin[mpi_rank][i]);
|
||
|
// printf("%d: Nend[%d]: %d\n",mpi_rank, i, Nend[mpi_rank][i]);
|
||
|
//}
|
||
|
|
||
|
for (int i = 0; i < num_devices; i++) {
|
||
|
if(Nend[mpi_rank][i] - Nbegin[mpi_rank][i] != 0)
|
||
|
{
|
||
|
CUDA_CALL( cudaSetDevice(i) );
|
||
|
CUDA_CALL( cudaMalloc(&input_d[i], (Nend[mpi_rank][i] - Nbegin[mpi_rank][i]) * C * H * W * sizeof(float)) );
|
||
|
CUDA_CALL( cudaMalloc(&filter_d[i], K * C * R * S* sizeof(float)) );
|
||
|
CUDA_CALL( cudaMalloc(&output_d[i], (Nend[mpi_rank][i] - Nbegin[mpi_rank][i]) * K * OH * OW * sizeof(float)) );
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
void convolution_final(
|
||
|
int _N, int _C, int _H, int _W,
|
||
|
int _K, int _R, int _S,
|
||
|
int _pad, int _dilation, int _stride) {
|
||
|
}
|