259 lines
8.9 KiB
C++
259 lines
8.9 KiB
C++
#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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#include <immintrin.h>
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#include <omp.h>
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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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#define min(a,b) (a>b?b:a)
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#define HSLICE OH
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#define WSLICE 128
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int num_threads = 100;
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void convolution_omp_slc()
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{
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if((dilation == 1) && (stride == 1) && (pad == 0) && (W%16 == 0) && (S%16 == 0))
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{
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//printf("AVX\n");
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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 < N; ++n) {
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for (int k = 0; k < K; ++k) {
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//#pragma omp parallel for num_threads(num_threads) 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) schedule(dynamic)
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for (int ow = 0; ow < OW; ++ow) {
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//float o = 0.f;
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__m512 vo = {0.0f};
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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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for (int s = 0; s < S; s+=16) {
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int h = oh * stride - pad + r;
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int w = ow * stride - pad + s;
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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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__m512 vi = _mm512_loadu_ps(&input[n * C * H * W + c * H * W + h * W + w]);
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__m512 vf = _mm512_loadu_ps(&filter[k * C * R * S + c * R * S + r * S + s]);
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//o += i * f;
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vo = _mm512_fmadd_ps(vi, vf, vo);
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}
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}
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}
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//_mm512_storeu_ps(&output[n * K * OH * OW + k * OH * OW + oh * OW + ow], vo);
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float o = _mm512_reduce_add_ps(vo);
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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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else
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{
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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 < N; ++n) {
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for (int k = 0; k < K; ++k) {
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for (int ohs = 0; ohs<OH; ohs += HSLICE) {
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for (int ows = 0; ows<OW; ows += WSLICE) {
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//#pragma omp parallel for num_threads(num_threads) schedule(dynamic)
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for (int oh = ohs; oh < min(ohs + HSLICE, OH); ++oh) {
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//#pragma omp parallel for num_threads(num_threads) schedule(dynamic)
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for (int ow = ows; ow < min(ows + WSLICE, 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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//Slice
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}}
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}
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}
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}
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}
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void convolution_omp()
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{
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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 < N; ++n) {
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for (int k = 0; k < K; ++k) {
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//#pragma omp parallel for num_threads(num_threads) 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) schedule(dynamic)
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for (int ow = 0; ow < 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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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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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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int default_div_size = N/mpi_world_size;
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MPI_Status status;
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//MPI_Request request;
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if (mpi_rank == 0) {
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// 1. Distribute batch to the other nodes
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//timer_start(1);
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MPI_Request arrA_req[4];
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MPI_Status arrA_status[4];
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for(int target_rank = 1; target_rank < mpi_world_size; target_rank++){
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int div_start, div_size;
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div_start = target_rank * default_div_size;
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div_size = default_div_size;
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if(target_rank == (mpi_world_size - 1))
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div_size += N - (default_div_size * mpi_world_size);
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//printf("send. target_rank=%d, div_start=%d, div_size=%d, tot_size=%d\n", target_rank, div_start, div_size, div_size * C*H*W);
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MPI_Isend(input + (div_start * C*H*W), div_size * C*H*W, MPI_FLOAT, target_rank, 0, MPI_COMM_WORLD, &arrA_req[target_rank-1]);
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//MPI_Isend(B, K * N, MPI_FLOAT, target_rank, 0, MPI_COMM_WORLD, &request);
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}
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// 2. Broadcase all Filters
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MPI_Bcast(filter, K*C*R*S, MPI_FLOAT, 0, MPI_COMM_WORLD);
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//double elapsed_time = timer_stop(1);
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//printf("[rank %d] scatter time: %f sec\n", mpi_rank, elapsed_time);
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int original_N = N;
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N = default_div_size;
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// 3. Do Convolution
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//timer_start(1);
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convolution_omp_slc();
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//elapsed_time = timer_stop(1);
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//printf("[rank %d] time: %f sec\n", mpi_rank, elapsed_time);
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N = original_N;
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//timer_start(1);
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// 4. Receive result from the other node
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MPI_Request arrC_req[4];
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MPI_Status arrC_status[4];
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for(int target_rank = 1; target_rank < mpi_world_size; target_rank++){
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int div_start, div_size;
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div_start = target_rank * default_div_size;
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div_size = default_div_size;
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if(target_rank == (mpi_world_size - 1))
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div_size += N - (default_div_size * mpi_world_size);
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//printf("wait div_size=%d\n", div_size);
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MPI_Irecv(output + (div_start * K*OH*OW), div_size * K*OH*OW, MPI_FLOAT, target_rank, 0, MPI_COMM_WORLD, &arrC_req[target_rank-1]);
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//MPI_Recv(output + (div_start * K*OH*OW), div_size * K*OH*OW, MPI_FLOAT, target_rank, 0, MPI_COMM_WORLD, &arrC_status[target_rank-1]);
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}
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//MPI_Waitall(mpi_world_size-1, arrA_req, arrA_status);
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MPI_Waitall(mpi_world_size-1, arrC_req, arrC_status);
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//elapsed_time = timer_stop(1);
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//printf("[rank %d] collect time: %f sec\n", mpi_rank, elapsed_time);
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}else{
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//0. alloc local memory
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int div_size;
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div_size = default_div_size;
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if(mpi_rank == (mpi_world_size - 1))
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div_size += N - (default_div_size * mpi_world_size);
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int original_N = N;
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N = div_size; // Adjust N size
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//printf("defulat div size=%d\n", default_div_size);
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alloc_tensor(&input, N, C, H, W);
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alloc_tensor(&filter, K, C, R, S);
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alloc_tensor(&output, N, K, OH, OW);
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// 1. Recv part of A
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//printf("sub. rank=%d, div_size=%d, Recv start, tot_size=%d\n", mpi_rank, div_size, N*C*H*W);
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MPI_Recv(input, N*C*H*W, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &status);
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//printf("sub. rank=%d, div_size=%d, Recv end\n", mpi_rank, div_size);
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// 2. Recv full Filter
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MPI_Bcast(filter, K*C*R*S, MPI_FLOAT, 0, MPI_COMM_WORLD);
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// 3. Do Convolution
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//timer_start(1);
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convolution_omp();
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//double elapsed_time = timer_stop(1);
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//printf("[rank %d] time: %f sec\n", mpi_rank, elapsed_time);
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// 4. Send C to rank 0 node.
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//printf("sub. end. my rank=%d, div_size=%d\n", mpi_rank, div_size);
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MPI_Send(output, N*K*OH*OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD);
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N = original_N;
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//free
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free(input);
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free(filter);
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free(output);
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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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