216 lines
6.8 KiB
Plaintext
216 lines
6.8 KiB
Plaintext
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#include "convolution.h"
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#include <mpi.h>
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#include <stdio.h>
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#include <cuda_runtime.h>
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#define CUDA_CALL(f) { \
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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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__global__ void sgemm(float *_input, float *_filter, float *_output,
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int _N, int _C, int _H, int _W, int _K, int _R, int _S,
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int _pad, int _dilation, int _stride) {
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int n = blockIdx.x;
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int k = blockIdx.y;
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int oh = blockIdx.z;
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int ow = threadIdx.x;
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const int OH = (_H + 2 * _pad - _dilation * (_R - 1) - 1) / _stride + 1;
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const int OW = (_W + 2 * _pad - _dilation * (_S - 1) - 1) / _stride + 1;
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float o = 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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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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#define MAX_NUM_NODE 2
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#define MAX_NUM_GPU 4
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static int num_devices = 0;
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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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// Array of device (GPU) pointers
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static float *input_d[MAX_NUM_GPU];
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static float *filter_d[MAX_NUM_GPU];
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static float *output_d[MAX_NUM_GPU];
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//static int N, C, H, W, K, R, S, pad, dilation, stride;
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static int Nbegin[MAX_NUM_NODE], Nend[MAX_NUM_NODE];
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static int Gbegin[MAX_NUM_GPU], Gend[MAX_NUM_GPU];
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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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if (mpi_rank >= mpi_world_size) return;
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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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//if (mpi_rank == 0) {
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/*---------- seperating for nodes ----------*/
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if (mpi_rank != 0){
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input = (float *) aligned_alloc(32, sizeof(float) * N*C*H*W);
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filter = (float *) aligned_alloc(32, sizeof(float) * K*C*R*S);
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output = (float *) aligned_alloc(32, sizeof(float) * N*K*OH*OW);
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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_Send(&input[ Nbegin[i] * C*H*W ], (Nend[i] - Nbegin[i]) * C*H*W, MPI_FLOAT, i, 0, MPI_COMM_WORLD);
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}
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} else {
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MPI_Recv (&input[ Nbegin[mpi_rank] * C*H*W], (Nend[mpi_rank] - Nbegin[mpi_rank]) * C*H*W, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, nullptr);
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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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/*---------- calculating ----------*/
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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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CUDA_CALL( cudaMemcpy(input_d[i], input + Gbegin[i] * C*H*W, (Gend[i] - Gbegin[i]) * C*H*W * sizeof(float), cudaMemcpyHostToDevice) );
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CUDA_CALL( cudaMemcpy(filter_d[i], filter, K*C*R*S * 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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CUDA_CALL( cudaDeviceSynchronize() );
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}
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// Launch kernel on every GPU
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for (int i = 0; i < num_devices; i++) {
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dim3 blockDim( OW, 1, 1);
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dim3 gridDim(Gend[i]-Gbegin[i], K, OH);
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CUDA_CALL( cudaSetDevice(i) );
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sgemm<<<gridDim, blockDim>>>(input_d[i], filter_d[i], output_d[i], Gend[i]-Gbegin[i], C,H,W,K,R,S,pad,dilation,stride);
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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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// Download C matrix from GPUs
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL( cudaMemcpy(output + Gbegin[i] * K*OH*OW, output_d[i], (Gend[i] - Gbegin[i]) * K*OH*OW * sizeof(float), 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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CUDA_CALL( cudaDeviceSynchronize() );
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}
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/*---------- merging output ----------*/
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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[Nbegin[i] * K*OH*OW], (Nend[i] - Nbegin[i]) * K*OH*OW, MPI_FLOAT, i, 0, MPI_COMM_WORLD, nullptr);
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}
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} else {
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MPI_Send (&output[Nbegin[mpi_rank] * K*OH*OW], (Nend[mpi_rank] - Nbegin[mpi_rank]) * K*OH*OW, MPI_FLOAT, 0, 0, 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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if (mpi_rank >= mpi_world_size) return;
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//if (mpi_rank == 0) {
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CUDA_CALL( 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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CUDA_CALL( 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 size for each Node
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for (int i=0; i < mpi_world_size; ++i){
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Nbegin[i] = N / mpi_world_size * i;
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Nend[i] = N / mpi_world_size * (i+1);
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}
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Nend[mpi_world_size-1] = N;
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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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Gbegin[i] = Nbegin[mpi_rank] + (Nend[mpi_rank] - Nbegin[mpi_rank]) / num_devices * i;
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Gend[i] = Nbegin[mpi_rank] + (Nend[mpi_rank] - Nbegin[mpi_rank]) / num_devices * (i + 1);
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}
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Gend[num_devices - 1] = Nend[mpi_rank];
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// Allocate device memory for each GPU
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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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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL( cudaSetDevice(i) );
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CUDA_CALL( cudaMalloc(&input_d[i], (Gend[i] - Gbegin[i]) * C*H*W * sizeof(float)) );
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CUDA_CALL( cudaMalloc(&filter_d[i], K*C*R*S * sizeof(float)) );
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CUDA_CALL( cudaMalloc(&output_d[i], (Gend[i] - Gbegin[i]) * K*OH*OW * sizeof(float)) );
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}
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//}
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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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if (mpi_rank >= mpi_world_size) return;
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//if (mpi_rank == 0){
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//}
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}
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