127 lines
3.7 KiB
C++
127 lines
3.7 KiB
C++
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#include "convolution.h"
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#include "util.h"
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#include <mpi.h>
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#include <stdio.h>
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#define NUM_THREADS 80
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#define T_SIZE_OH 16
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#define T_SIZE_OW 8
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static float *input, *output, *filter;
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static int N, C, H, W;
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static int K, R, S;
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static int OH, OW;
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static int pad;
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static int dilation;
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static int stride;
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static int mpi_rank, mpi_world_size;
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MPI_Request request;
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MPI_Status status;
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void convolution(
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float *_input, float *_output, float *_filter,
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int _N, int _C, int _H, int _W,
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int _K, int _R, int _S,
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int _pad, int _dilation, int _stride) {
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input = _input;
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output = _output;
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filter = _filter;
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int divided_N = N / mpi_world_size;
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int modular_N = N % mpi_world_size;
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int stride_N[4];
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int offset[4];
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OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1;
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OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1;
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offset[0] = 0;
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stride_N[0] = divided_N;
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for (int i = 1; i < mpi_world_size; i++) {
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if (i <= modular_N) stride_N[i] = divided_N + 1;
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else stride_N[i] = divided_N;
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offset[1] = divided_N;
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if (i > 1) offset[i] = offset[i-1] + stride_N[i-1];
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}
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if (mpi_rank != 0) {
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alloc_tensor(&input, stride_N[mpi_rank], C, H, W);
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alloc_tensor(&output, stride_N[mpi_rank], K, OH, OW);
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alloc_tensor(&filter, K, C, R, S);
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}
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MPI_Bcast(filter, K*C*R*S, MPI_FLOAT, 0, MPI_COMM_WORLD);
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if (mpi_rank == 0) {
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for (int i = 1; i < mpi_world_size; i++)
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MPI_Isend(&input[offset[i]*C*H*W], stride_N[i]*C*H*W, MPI_FLOAT, i, 1, MPI_COMM_WORLD, &request);
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}
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else {
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MPI_Recv(input, stride_N[mpi_rank]*C*H*W, MPI_FLOAT, 0, 1, MPI_COMM_WORLD, &status);
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}
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// if (mpi_rank == 0) {
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#pragma omp parallel for num_threads(NUM_THREADS) collapse(3) schedule(dynamic)
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for (int n = 0; n < stride_N[mpi_rank]; ++n) {
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for (int k = 0; k < K; ++k) {
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// for (int t_oh = 0; t_oh < OH; t_oh += T_SIZE_OH) {
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// #pragma omp parallel for num_threads(NUM_THREADS) shared(N, K, OH, OW, R, S, C) schedule(dynamic)
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for (int oh = 0; oh < OH; ++oh) {
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// #pragma omp parallel for num_threads(NUM_THREADS) shared(N, K, OH, OW, R, S, C) schedule(dynamic)
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for (int ow = 0; ow < OW; ++ow) {
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// for (int t_ow = 0; t_ow < OW; t_ow += T_SIZE_OW) {
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// for (int oh = t_oh; oh < t_oh+T_SIZE_OH; ++oh) {
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// for (int ow = t_ow; ow < t_ow+T_SIZE_OW; ++ow) {
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float o = 0.f;
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for (int c = 0; c < C; ++c) {
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for (int r = 0; r < R; ++r) {
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for (int s = 0; s < S; ++s) {
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int h = oh * stride - pad + r * dilation;
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int w = ow * stride - pad + s * dilation;
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if (h < 0 || h >= H || w < 0 || w >= W) continue;
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float i = input[n * C * H * W + c * H * W + h * W + w];
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float f = filter[k * C * R * S + c * R * S + r * S + s];
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o += i * f;
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}
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}
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}
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output[n * K * OH * OW + k * OH * OW + oh * OW + ow] = o;
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}
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// }
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// }
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}
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}
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}
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if (mpi_rank == 0) {
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for (int i = 1; i < mpi_world_size; i++)
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MPI_Recv(&output[offset[i]*K*OH*OW], stride_N[i]*K*OH*OW, MPI_FLOAT, i, 2, MPI_COMM_WORLD, &status);
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}
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else {
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MPI_Send(output, stride_N[mpi_rank]*K*OH*OW, MPI_FLOAT, 0, 2, MPI_COMM_WORLD);
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}
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}
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//}
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void convolution_init(
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int _N, int _C, int _H, int _W,
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int _K, int _R, int _S,
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int _pad, int _dilation, int _stride) {
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N = _N; C = _C; H = _H; W = _W;
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K = _K; R = _R; S = _S;
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pad = _pad;
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dilation = _dilation;
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stride = _stride;
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MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
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MPI_Comm_size(MPI_COMM_WORLD, &mpi_world_size);
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}
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void convolution_final(
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int _N, int _C, int _H, int _W,
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int _K, int _R, int _S,
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int _pad, int _dilation, int _stride) {
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}
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