chundoong-lab-ta/SamsungDS22/submissions/final/juhyeong.jin/A/convolution.cpp

221 lines
7.4 KiB
C++

#include "convolution.h"
#include <mpi.h>
#include <stdio.h>
#include "util.h"
#include <immintrin.h>
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;
static void perform_cal(int begin, int end)
{
#pragma omp parallel for collapse(3) num_threads(100)
for (int n = begin; n < end; ++n) {
for (int k = 0; k < K; ++k) {
for (int oh = 0; oh < OH; ++oh) {
for (int ow = 0; ow < OW; ++ow) {
__m512 o = _mm512_setzero_ps();
for (int c = 0; c < C; c++) {
float* in_p = &input[n * C * H * W + oh * W + c * H * W + ow];
float* filt_p = &filter[k * C * R * S + c * R * S];
__m512 f0 = _mm512_load_ps(&filt_p[0]);
__m512 f1 = _mm512_load_ps(&filt_p[S * 1]);
__m512 f2 = _mm512_load_ps(&filt_p[S * 2]);
__m512 f3 = _mm512_load_ps(&filt_p[S * 3]);
__m512 f4 = _mm512_load_ps(&filt_p[S * 4]);
__m512 f5 = _mm512_load_ps(&filt_p[S * 5]);
__m512 f6 = _mm512_load_ps(&filt_p[S * 6]);
__m512 f7 = _mm512_load_ps(&filt_p[S * 7]);
__m512 f8 = _mm512_load_ps(&filt_p[S * 8]);
__m512 f9 = _mm512_load_ps(&filt_p[S * 9]);
__m512 f10 = _mm512_load_ps(&filt_p[S * 10]);
__m512 f11 = _mm512_load_ps(&filt_p[S * 11]);
__m512 f12 = _mm512_load_ps(&filt_p[S * 12]);
__m512 f13 = _mm512_load_ps(&filt_p[S * 13]);
__m512 f14 = _mm512_load_ps(&filt_p[S * 14]);
__m512 f15 = _mm512_load_ps(&filt_p[S * 15]);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[0]), f0, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 1]), f1, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 2]), f2, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 3]), f3, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 4]), f4, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 5]), f5, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 6]), f6, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 7]), f7, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 8]), f8, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 9]), f9, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 10]), f10, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 11]), f11, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 12]), f12, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 13]), f13, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 14]), f14, o);
o = _mm512_fmadd_ps(_mm512_loadu_ps(&in_p[W * 15]), f15, o);
}
output[n * K * OH * OW + k * OH * OW + oh * OW + ow] = _mm512_reduce_add_ps(o);
}
}
}
}
}
static void calc(int begin, int end)
{
#pragma omp parallel for collapse(3) num_threads(100)
for (int n = begin; n < end; ++n) {
for (int k = 0; k < K; ++k) {
for (int oh = 0; oh < OH; ++oh) {
for (int ow = 0; ow < OW; ++ow) {
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;
}
}
}
}
}
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_Status MpiStatus;
MPI_Request MpiRequest[3];
if (mpi_rank == 0) {
input = _input;
output = _output;
filter = _filter;
}
if (_pad == 0
&& _dilation == 1
&& _stride == 1
&& mpi_world_size == 2
&& R == 16
&& S == 16
&& (N % 32 == 0)
&& (C % 32 == 0)
&& (H % 32 == 0)
&& (W % 32 == 0)
&& (K % 32 == 0))
{
if (mpi_rank == 0) {
MPI_Isend(input + (N / 2) * C * H * W, (N / 2) * C * H * W , MPI_FLOAT, 1, 0, MPI_COMM_WORLD, &MpiRequest[0]);
MPI_Isend(filter, K * C * R * S, MPI_FLOAT, 1, 1, MPI_COMM_WORLD, &MpiRequest[1]);
MPI_Irecv(output + (N / 2) * K * OH * OW, (N / 2) * K * OH * OW, MPI_FLOAT, 1, 2, MPI_COMM_WORLD, &MpiRequest[2]);
perform_cal(0, N / 2);
MPI_Wait(&MpiRequest[0], &MpiStatus);
MPI_Wait(&MpiRequest[1], &MpiStatus);
MPI_Wait(&MpiRequest[2], &MpiStatus);
}
else {
MPI_Irecv(input, N / 2 * C * H * W , MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &MpiRequest[0]);
MPI_Irecv(filter + K * 0 * C * R * S, K * C * R * S, MPI_FLOAT, 0, 1, MPI_COMM_WORLD, &MpiRequest[1]);
MPI_Wait(&MpiRequest[0], &MpiStatus);
MPI_Wait(&MpiRequest[1], &MpiStatus);
perform_cal(0, N / 2);
MPI_Isend(output, N / 2 * K * OH * OW, MPI_FLOAT, 0, 2, MPI_COMM_WORLD, &MpiRequest[2]);
MPI_Wait(&MpiRequest[2], &MpiStatus);
}
}
else {
int Node2Offset = mpi_world_size > 1 ? (N - (N / 2)) : N;
if (mpi_rank == 0) {
if (mpi_world_size > 1 && N / 2 > 0)
{
MPI_Isend(input + Node2Offset * C * H * W, N / 2 * C * H * W , MPI_FLOAT, 1, 0, MPI_COMM_WORLD, &MpiRequest[0]);
MPI_Isend(filter, K * C * R * S, MPI_FLOAT, 1, 1, MPI_COMM_WORLD, &MpiRequest[1]);
MPI_Irecv(output + Node2Offset * K * OH * OW, N / 2 * K * OH * OW, MPI_FLOAT, 1, 2, MPI_COMM_WORLD, &MpiRequest[2]);
}
calc(0, Node2Offset);
if (mpi_world_size > 1 && N / 2 > 0)
{
MPI_Wait(&MpiRequest[0], &MpiStatus);
MPI_Wait(&MpiRequest[1], &MpiStatus);
MPI_Wait(&MpiRequest[2], &MpiStatus);
}
}
else if (N / 2 > 0) {
MPI_Irecv(input, N / 2 * C * H * W , MPI_FLOAT, 0, 0, MPI_COMM_WORLD, &MpiRequest[0]);
MPI_Irecv(filter, K * C * R * S, MPI_FLOAT, 0, 1, MPI_COMM_WORLD, &MpiRequest[1]);
MPI_Wait(&MpiRequest[0], &MpiStatus);
MPI_Wait(&MpiRequest[1], &MpiStatus);
calc(0, N / 2);
MPI_Isend(output, N / 2 * K * OH * OW, MPI_FLOAT, 0, 2, MPI_COMM_WORLD, &MpiRequest[2]);
MPI_Wait(&MpiRequest[2], &MpiStatus);
}
}
}
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);
if (mpi_rank != 0 && N / 2 > 0)
{
alloc_tensor((float**)&input, N / 2, _C, _H, _W);
alloc_tensor((float**)&output, N / 2, _K, OH, OW);
alloc_tensor((float**)&filter, _K, _C, _R, _S);
}
}
void convolution_final(
int _N, int _C, int _H, int _W,
int _K, int _R, int _S,
int _pad, int _dilation, int _stride) {
}