chundoong-lab-ta/SamsungDS22/submissions/HW5/jj15.kim/mat_mul.cpp

243 lines
7.5 KiB
C++

#include "mat_mul.h"
#include "util.h"
#include <stdio.h>
#include <CL/cl.h>
#define CHECK_ERROR(err) \
if (err != CL_SUCCESS) { \
printf("[%s:%d] OpenCL error %d\n", __FILE__, __LINE__, err); \
exit(EXIT_FAILURE); \
}
#define MAX_DEV 4
#define WPT 8
#define sizeA (M * K * sizeof(float))
#define sizeB (K * N * sizeof(float))
#define sizeC (M * N * sizeof(float))
#define sizeEA (extra * K * sizeof(float))
#define sizeEC (extra * N * sizeof(float))
static cl_int err;
static cl_platform_id platform;
static cl_device_id device[MAX_DEV];
static cl_context context;
static cl_command_queue queue[MAX_DEV];
static cl_program program;
static cl_kernel kernel[MAX_DEV];
static int ndev;
static cl_mem a_d[MAX_DEV], b_d[MAX_DEV], c_d[MAX_DEV];
static float *A, *B, *C;
static int M, N, K;
static int extra;
void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K) {
A = _A, B = _B, C = _C;
M = _M, N = _N, K = _K;
// Setup kernel arguments
for (int i = 0; i < ndev; i++) {
M = (i == ndev - 1 && extra)? M/ndev + extra : M/ndev;
err = clSetKernelArg(kernel[i], 0, sizeof(cl_mem), &a_d[i]);
CHECK_ERROR(err);
err = clSetKernelArg(kernel[i], 1, sizeof(cl_mem), &b_d[i]);
CHECK_ERROR(err);
err = clSetKernelArg(kernel[i], 2, sizeof(cl_mem), &c_d[i]);
CHECK_ERROR(err);
err = clSetKernelArg(kernel[i], 3, sizeof(int), &M);
CHECK_ERROR(err);
err = clSetKernelArg(kernel[i], 4, sizeof(int), &N);
CHECK_ERROR(err);
err = clSetKernelArg(kernel[i], 5, sizeof(int), &K);
CHECK_ERROR(err);
// Setup global work size and local work size
size_t gws[2] = {(size_t)(M + WPT - 1)/WPT, (size_t)N}, lws[2] = {32/WPT, 32};
for (int i = 0; i < 2; ++i) {
// By OpenCL spec, global work size should be MULTIPLE of local work size
// Formula below achieve it
// e.g., gws = 25, lws = 16, then (25 + 16 - 1) / 16 * 16 = 40 / 16 * 16 = 2 * 16 = 32
gws[i] = (gws[i] + lws[i] - 1) / lws[i] * lws[i];
}
//printf("GPU(%d), M(%d), gws(%d, %d)\n", i + 1, M, (int)gws[0], (int)gws[1]);
// Run kernel
err = clEnqueueNDRangeKernel(queue[i], kernel[i], 2, NULL, gws, lws, 0, NULL, NULL);
CHECK_ERROR(err);
M = _M;
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < ndev; i++) {
err = clFinish(queue[i]);
CHECK_ERROR(err);
}
}
static void print_platform_info(cl_platform_id platform) {
size_t sz;
char *buf;
CHECK_ERROR(clGetPlatformInfo(platform, CL_PLATFORM_NAME, 0, NULL, &sz));
buf = (char*)malloc(sz);
CHECK_ERROR(clGetPlatformInfo(platform, CL_PLATFORM_NAME, sz, buf, NULL));
printf("Detected OpenCL platform: %s\n", buf);
free(buf);
}
static void print_device_info(cl_device_id *device) {
size_t sz;
char *buf;
for (int i = 0; i < ndev; i++) {
CHECK_ERROR(clGetDeviceInfo(device[i], CL_DEVICE_NAME, 0, NULL, &sz));
buf = (char*)malloc(sz);
CHECK_ERROR(clGetDeviceInfo(device[i], CL_DEVICE_NAME, sz, buf, NULL));
printf("Detected OpenCL device: %s\n", buf);
free(buf);
}
}
static cl_program create_and_build_program_with_source(cl_context context, cl_device_id *device, const char *file_name) {
FILE *file = fopen(file_name, "rb");
if (file == NULL) {
printf("Failed to open %s\n", file_name);
exit(EXIT_FAILURE);
}
fseek(file, 0, SEEK_END);
size_t source_size = ftell(file);
rewind(file);
char *source_code = (char*)malloc(source_size + 1);
size_t ntotal = 0;
while (ntotal < source_size) {
int nread = fread(source_code, sizeof(char), source_size, file);
ntotal += nread;
}
source_code[source_size] = '\0';
fclose(file);
cl_program program = clCreateProgramWithSource(context, 1, (const char **)&source_code, &source_size, &err);
CHECK_ERROR(err);
free(source_code);
err = clBuildProgram(program, ndev, device, "", NULL, NULL);
if (err == CL_BUILD_PROGRAM_FAILURE) {
size_t log_size;
CHECK_ERROR(clGetProgramBuildInfo(program, device[0], CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size));
char *log = (char*)malloc(log_size + 1);
CHECK_ERROR(clGetProgramBuildInfo(program, device[0], CL_PROGRAM_BUILD_LOG, log_size, log, NULL));
log[log_size] = 0;
printf("Compile error:\n%s\n", log);
free(log);
}
CHECK_ERROR(err);
return program;
}
void mat_mul_init(float *A, float *B, float *C, int M, int N, int K) {
// Get OpenCL platform
err = clGetPlatformIDs(1, &platform, NULL);
CHECK_ERROR(err);
print_platform_info(platform);
// Get OpenCL device
err = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, MAX_DEV, device, (unsigned int*)&ndev);
CHECK_ERROR(err);
print_device_info(device);
// Use one GPU only if M is smaller than MAX_DEV
if (M < MAX_DEV) ndev = 1;
//int tempM = M;
extra = M % ndev;
M /= ndev;
// Create OpenCL context
context = clCreateContext(NULL, ndev, device, NULL, NULL, &err);
CHECK_ERROR(err);
// Create OpenCL command queue
for (int i = 0; i < ndev; i++) {
queue[i] = clCreateCommandQueue(context, device[i], 0, &err);
CHECK_ERROR(err);
}
// Compile program from "kernel.cl"
program = create_and_build_program_with_source(context, device, "kernel.cl");
// Extract kernel from compiled program
for (int i = 0; i < ndev; i++) {
kernel[i] = clCreateKernel(program, "sgemm", &err);
CHECK_ERROR(err);
}
// Create GPU buffers
for (int i = 0; i < ndev; i++) {
if (i == ndev - 1 && extra) {
//printf("%d extra rows are allocated to (%d)th GPU\n", extra, i + 1);
a_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeA + sizeEA, NULL, &err);
CHECK_ERROR(err);
c_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeC + sizeEC, NULL, &err);
CHECK_ERROR(err);
}
else {
a_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeA, NULL, &err);
CHECK_ERROR(err);
c_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeC, NULL, &err);
CHECK_ERROR(err);
}
b_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, sizeB, NULL, &err);
CHECK_ERROR(err);
}
// Write to GPU; A (cpu) -> a_d (gpu), B (cpu) -> b_d (gpu)
for (int i = 0; i < ndev; i++) {
int size = (i == ndev - 1 && extra)? sizeA + sizeEA : sizeA;
err = clEnqueueWriteBuffer(queue[i], a_d[i], CL_TRUE, 0, size, (void*)((size_t)A + sizeA * i), 0, NULL, NULL);
CHECK_ERROR(err);
err = clEnqueueWriteBuffer(queue[i], b_d[i], CL_TRUE, 0, sizeB, B, 0, NULL, NULL);
CHECK_ERROR(err);
//float * dA[4];
//alloc_mat(&dA[i], size / (K*sizeof(float)), K);
//err = clEnqueueReadBuffer(queue[i], a_d[i], CL_TRUE, 0, size, (void*)dA[i], 0, NULL, NULL);
//CHECK_ERROR(err);
//printf("A matrix of (%d) GPU, size(%d), M(%d), N(%d), sizeA(%d), sizeEA(%d), extra(%d)\n", i+1, (int)size, M, N, (int)sizeA, (int)sizeEA, extra);
//print_mat(dA[i], size / (K*sizeof(float)), K);
}
//printf("Original A matrix\n");
//print_mat(A, tempM, K);
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < ndev; i++) {
err = clFinish(queue[i]);
CHECK_ERROR(err);
}
}
void mat_mul_final(float *A, float *B, float *C, int M, int N, int K) {
M /= ndev;
// Read from GPU; c_d (gpu) -> C (cpu)
for (int i = 0; i < ndev; i++) {
if (i == ndev - 1 && extra) {
err = clEnqueueReadBuffer(queue[i], c_d[i], CL_TRUE, 0, sizeC + sizeEC, (void*)((size_t)C + sizeC * i), 0, NULL, NULL);
}
else {
err = clEnqueueReadBuffer(queue[i], c_d[i], CL_TRUE, 0, sizeC, (void*)((size_t)C + sizeC * i), 0, NULL, NULL);
}
//printf("M(%d), N(%d), sizeC(%d), sizeEC(%d)\n", M, N, (int)sizeC, (int)sizeEC);
CHECK_ERROR(err);
}
// DO NOT REMOVE; NEEDED FOR TIME MEASURE
for (int i = 0; i < ndev; i++) {
err = clFinish(queue[i]);
CHECK_ERROR(err);
}
}