chundoong-lab-ta/SamsungDS22/submissions/final/junha96.jeon/B/convolution.cu

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2022-09-29 18:01:45 +09:00
#include "convolution.h"
#include "util.h"
#include <mpi.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_GPU 8
#define TS 32
int num_devices = 0;
static int mpi_world_size, mpi_rank;
static float *input, *output, *filter;
//static int OH, OW;
__global__ void sgemm(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 n = blockIdx.x;
int k = blockIdx.y;
int oh = blockIdx.z;
int ow = threadIdx.x;
const int OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1;
const int OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1;
float o = 0.f;
for(int c = 0; c < C; ++c){
for (int r = 0; r < R; ++r) {
for (int s = 0; s < S; ++s) {
int h = oh * stride - pad + r * dilation;
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];
o += i*f;
}
}
}
output[n*K*OH*OW + k*OH*OW + oh*OW + ow] = o;
}
// Array of device (GPU) pointers
static float *input_d[MAX_NUM_GPU];
static float *filter_d[MAX_NUM_GPU];
static float *output_d[MAX_NUM_GPU];
static int N, C, H, W, K, R, S, pad, dilation, stride, OH, OW;
static int Nbegin[MAX_NUM_GPU], Nend[MAX_NUM_GPU];
static int is[2], ie[2];
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_world_size > 1) {
for (int i = 0; i < mpi_world_size; i++) {
is[i] = N / mpi_world_size * i;
ie[i] = N / mpi_world_size * (i + 1);
}
ie[mpi_world_size - 1] = N;
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_rank == 0) {
for (int i = 1; i < mpi_world_size; i++) {
MPI_Send(input+is[i]*C*H*W, (ie[i]-is[i])*C*H*W, MPI_FLOAT, i, 0, MPI_COMM_WORLD);
}
}
else {
MPI_Recv(input+is[mpi_rank]*C*H*W, (ie[mpi_rank]-is[mpi_rank])*C*H*W, MPI_FLOAT, 0, 0, MPI_COMM_WORLD, nullptr);
}
// Broadcast B
MPI_Bcast(filter, K*C*R*S, MPI_FLOAT, 0, MPI_COMM_WORLD);
}
//if(mpi_rank == 0){
/* CUDA_CALL( cudaGetDeviceCount(&num_devices) );
printf("Using %d devices\n", num_devices);
for (int i = 0; i < num_devices; i++) {
cudaDeviceProp prop;
CUDA_CALL( cudaGetDeviceProperties(&prop, i) );
// Try printing more detailed information here
printf("[GPU %d] %s\n", i, prop.name);
}
if (num_devices <= 0) {
printf("No CUDA device found. Aborting\n");
exit(1);
}
if(mpi_world_size > 1){
// Setup problem size for each GPU
if(mpi_rank == 0){
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = (N/mpi_world_size) / num_devices * i;
Nend[i] = (N/mpi_world_size) / num_devices * (i + 1);
}
Nend[num_devices - 1] = N/mpi_world_size;
}
else {
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = N/mpi_world_size + (N/mpi_world_size + N%mpi_world_size) / num_devices * i;
Nend[i] = N/mpi_world_size + (N/mpi_world_size + N%mpi_world_size) / num_devices * (i+1);
}
Nend[num_devices - 1] = N;
}
}
else {
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = N / num_devices * i;
Nend[i] = N / num_devices * (i + 1);
}
Nend[num_devices - 1] = N;
}
// Allocate device memory for each GPU
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaSetDevice(i) );
CUDA_CALL( cudaMalloc(&input_d[i], (Nend[i] - Nbegin[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[i] - Nbegin[i])*K*OH*OW*sizeof(float)) );
}*/
// Upload A and B matrix to every GPU
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaMemcpy(input_d[i], input + Nbegin[i]*C*H*W, (Nend[i] - Nbegin[i])*C*H*W*sizeof(float), cudaMemcpyHostToDevice) );
CUDA_CALL( cudaMemcpy(filter_d[i], filter, K*C*R*S*sizeof(float), cudaMemcpyHostToDevice) );
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaDeviceSynchronize() );
}
// Launch kernel on every GPU
for (int i = 0; i < num_devices; i++) {
dim3 blockDim(OW, 1, 1);
dim3 gridDim(Nend[i]-Nbegin[i], K, OH);
CUDA_CALL( cudaSetDevice(i) );
sgemm<<<gridDim, blockDim>>>(input_d[i], output_d[i], filter_d[i], Nend[i]-Nbegin[i],C,H,W,K,R,S,pad,dilation,stride);
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaDeviceSynchronize() );
}
//}
/* // Gather C
if (mpi_rank == 0) {
for (int i = 1; i < mpi_world_size; i++) {
MPI_Recv(output+is[i]*K*OH*OW, (ie[i]-is[i])*K*OH*OW, MPI_FLOAT, i, 0, MPI_COMM_WORLD, nullptr);
}
}
else {
MPI_Send(output+is[mpi_rank]*K*OH*OW, (ie[mpi_rank]-is[mpi_rank])*K*OH*OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD);
}*/
// }
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaMemcpy(output + Nbegin[i]*K*OH*OW, output_d[i], (Nend[i] - Nbegin[i])*K*OH*OW*sizeof(float), cudaMemcpyDeviceToHost) );
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaDeviceSynchronize() );
}
if(mpi_world_size > 1){
// Gather C
if (mpi_rank == 0) {
for (int i = 1; i < mpi_world_size; i++) {
MPI_Recv(output+is[i]*K*OH*OW, (ie[i]-is[i])*K*OH*OW, MPI_FLOAT, i, 0, MPI_COMM_WORLD, nullptr);
}
}
else {
MPI_Send(output+is[mpi_rank]*K*OH*OW, (ie[mpi_rank]-is[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);
CUDA_CALL( cudaGetDeviceCount(&num_devices) );
printf("Using %d devices\n", num_devices);
for (int i = 0; i < num_devices; i++) {
cudaDeviceProp prop;
CUDA_CALL( cudaGetDeviceProperties(&prop, i) );
// Try printing more detailed information here
printf("[GPU %d] %s\n", i, prop.name);
}
if (num_devices <= 0) {
printf("No CUDA device found. Aborting\n");
exit(1);
}
if(mpi_world_size > 1){
// Setup problem size for each GPU
if(mpi_rank == 0){
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = (N/mpi_world_size) / num_devices * i;
Nend[i] = (N/mpi_world_size) / num_devices * (i + 1);
}
Nend[num_devices - 1] = N/mpi_world_size;
}
else {
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = N/mpi_world_size + (N/mpi_world_size + N%mpi_world_size) / num_devices * i;
Nend[i] = N/mpi_world_size + (N/mpi_world_size + N%mpi_world_size) / num_devices * (i+1);
}
Nend[num_devices - 1] = N;
}
}
else {
for (int i = 0; i < num_devices; i++) {
Nbegin[i] = N / num_devices * i;
Nend[i] = N / num_devices * (i + 1);
}
Nend[num_devices - 1] = N;
}
OH = (H + 2 * pad - dilation * (R - 1) -1) / stride + 1;
OW = (W + 2 * pad - dilation * (S - 1) -1) / stride + 1;
// Allocate device memory for each GPU
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaSetDevice(i) );
CUDA_CALL( cudaMalloc(&input_d[i], (Nend[i] - Nbegin[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[i] - Nbegin[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) {
// Do any post-matmul cleanup work here.
//int OH = (H + 2 * pad - dilation * (R - 1) - 1) / stride + 1;
//int OW = (W + 2 * pad - dilation * (S - 1) - 1) / stride + 1;
//float *input, *output, *filter;
//if(mpi_rank == 0) {
// Download C matrix from GPUs
//if(mpi_rank == 0){
/* for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaMemcpy(output + Nbegin[i]*K*OH*OW, output_d[i], (Nend[i] - Nbegin[i])*K*OH*OW*sizeof(float), cudaMemcpyDeviceToHost) );
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < num_devices; i++) {
CUDA_CALL( cudaDeviceSynchronize() );
}
if(mpi_world_size > 1){
// Gather C
if (mpi_rank == 0) {
for (int i = 1; i < mpi_world_size; i++) {
MPI_Recv(output+is[i]*K*OH*OW, (ie[i]-is[i])*K*OH*OW, MPI_FLOAT, i, 0, MPI_COMM_WORLD, nullptr);
}
}
else {
MPI_Send(output+is[mpi_rank]*K*OH*OW, (ie[mpi_rank]-is[mpi_rank])*K*OH*OW, MPI_FLOAT, 0, 0, MPI_COMM_WORLD);
}
} */
//}
}