105 lines
2.8 KiB
C++
105 lines
2.8 KiB
C++
|
#include "convolution.h"
|
||
|
|
#include <mpi.h>
|
||
|
|
#include <stdio.h>
|
||
|
|
#include "util.h"
|
||
|
|
|
||
|
|
extern void cuda_mem_init(int _N, int _C, int _H, int _W, int _K, int _R, int _S, int _pad, int _dilation, int _stride);
|
||
|
|
extern void cuda_conv_init(float *input, float *filter, float *output);
|
||
|
|
extern void cuda_conv_final(float *output);
|
||
|
|
extern void cuda_conv();
|
||
|
|
|
||
|
|
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;
|
||
|
|
|
||
|
|
|
||
|
|
#define MAX_NODE 2
|
||
|
|
|
||
|
|
static int size[MAX_NODE], offset[MAX_NODE];
|
||
|
|
|
||
|
|
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) {
|
||
|
|
MPI_Request request;
|
||
|
|
MPI_Status status;
|
||
|
|
|
||
|
|
if(mpi_rank == 0) {
|
||
|
|
input = _input;
|
||
|
|
output = _output;
|
||
|
|
filter = _filter;
|
||
|
|
|
||
|
|
for (int node=1; node < mpi_world_size; node++) {
|
||
|
|
MPI_Isend(&input[offset[node]*C*H*W], size[node]*C*H*W, MPI_FLOAT, node, 0, MPI_COMM_WORLD, &request);
|
||
|
|
MPI_Isend(filter, K*C*R*S, MPI_FLOAT, node, 0, MPI_COMM_WORLD, &request);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
MPI_Recv(input, size[mpi_rank]*C*H*W, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &status);
|
||
|
|
MPI_Recv(filter, K*C*R*S, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &status);
|
||
|
|
}
|
||
|
|
|
||
|
|
cuda_conv_init(input, filter, output);
|
||
|
|
|
||
|
|
cuda_conv();
|
||
|
|
|
||
|
|
cuda_conv_final(output);
|
||
|
|
|
||
|
|
if(mpi_rank == 0) {
|
||
|
|
for (int node=1; node < mpi_world_size; node++) {
|
||
|
|
MPI_Recv(&output[offset[node]*K*OH*OW], size[node]*K*OH*OW, MPI_FLOAT, node, 0, MPI_COMM_WORLD, &status);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
MPI_Isend(output, size[mpi_rank]*K*OH*OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &request);
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
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;
|
||
|
|
|
||
|
|
OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1;
|
||
|
|
OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1;
|
||
|
|
|
||
|
|
MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
|
||
|
|
MPI_Comm_size(MPI_COMM_WORLD, &mpi_world_size);
|
||
|
|
|
||
|
|
//Calc partitioned size
|
||
|
|
for (int i=0; i < mpi_world_size; i++) {
|
||
|
|
int st = i * (N/mpi_world_size);
|
||
|
|
int ed = i == mpi_world_size-1 ? N : (i+1)*(N/mpi_world_size);
|
||
|
|
|
||
|
|
size[i] = ed - st;
|
||
|
|
offset[i] = st;
|
||
|
|
}
|
||
|
|
|
||
|
|
if(mpi_rank != 0) {
|
||
|
|
alloc_tensor(&input, size[mpi_rank], C, H, W);
|
||
|
|
alloc_tensor(&output, size[mpi_rank], K, OH, OW);
|
||
|
|
alloc_tensor(&filter, K, C, R, S);
|
||
|
|
}
|
||
|
|
|
||
|
|
cuda_mem_init(size[mpi_rank], C, H, W, K, R, S, pad, dilation, stride);
|
||
|
|
}
|
||
|
|
|
||
|
|
void convolution_final(
|
||
|
|
int _N, int _C, int _H, int _W,
|
||
|
|
int _K, int _R, int _S,
|
||
|
|
int _pad, int _dilation, int _stride) {
|
||
|
|
|
||
|
|
}
|