277 lines
8.1 KiB
C++
277 lines
8.1 KiB
C++
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#include "mat_mul.h"
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#include <stdio.h>
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#include <CL/cl.h>
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#include "util.h"
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#define MAT_COPY (0)
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#define CHECK_ERROR(err) \
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if (err != CL_SUCCESS) { \
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printf("[%s:%d] OpenCL error %d\n", __FILE__, __LINE__, err); \
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exit(EXIT_FAILURE); \
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}
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#define ALIGN_UP(_X, _Y) (((_X) + (_Y) - 1) & ~((_Y) - 1))
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#define MAX_DEV (4)
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static cl_int err;
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static cl_platform_id platform;
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static cl_device_id device[MAX_DEV];
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static cl_context context;
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static cl_command_queue queue[MAX_DEV];
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static cl_program program[MAX_DEV];
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static cl_kernel kernel[MAX_DEV];
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static cl_mem a_d[MAX_DEV], b_d[MAX_DEV], c_d[MAX_DEV];
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static float *A, *B, *C;
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static int M, N, K;
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static int NON_OPTIMAL;
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static int nDevCnt;
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#if (MAT_COPY)
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static float *A_backup, *B_backup, *C_backup;
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static int M_backup, N_backup, K_backup;
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#endif // MAT_COPY
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#define NUM_WORK_ITEM (32)
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#define VECTOR_WIDTH (16)
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#define USING_NON_VECTOR (1)
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#if (MAT_COPY)
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static void mat_copy(float* __restrict pfDst, float* __restrict pfSrc, int nXDsize, int nYDsize, int nXSsize, int nYSsize, int nAddPadding)
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{
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if (nAddPadding)
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{
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#pragma omp parallel for
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for (int i = 0; i < nXDsize; i++)
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{
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for (int j = 0; j < nYDsize; j++)
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{
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if (i >= nXSsize || j >= nYSsize)
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{
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*(pfDst + i * nXDsize + j) = 0.0f;
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}
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else
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{
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*(pfDst + i * nXDsize + j) =*(pfSrc + i * nXSsize + j);
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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
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for (int i = 0; i < nXDsize; i++)
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{
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for (int j = 0; j < nYDsize; j++)
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{
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*(pfDst + i * nXSsize + j) =*(pfSrc + i * nXDsize + j);
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}
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}
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}
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}
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#endif // MAT_COPY
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void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K) {
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A = _A, B = _B, C = _C;
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M = _M, N = _N, K = _K;
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if (_M % (NUM_WORK_ITEM * nDevCnt) != 0
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|| _N % NUM_WORK_ITEM != 0
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|| _K % NUM_WORK_ITEM != 0)
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{
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NON_OPTIMAL = 1;
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}
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else
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{
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NON_OPTIMAL = 0;
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}
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// Setup kernel arguments
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for (int i = 0; i < nDevCnt; i++)
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{
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const int nLocalM = (i == (nDevCnt - 1)) ? M - ((M / nDevCnt) * (nDevCnt - 1)) : (M / nDevCnt);
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err = clSetKernelArg(kernel[i], 0, sizeof(cl_mem), &a_d[i]);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 1, sizeof(cl_mem), &b_d[i]);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 2, sizeof(cl_mem), &c_d[i]);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 3, sizeof(int), &nLocalM);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 4, sizeof(int), &N);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 5, sizeof(int), &K);
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CHECK_ERROR(err);
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err = clSetKernelArg(kernel[i], 6, sizeof(int), &NON_OPTIMAL);
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CHECK_ERROR(err);
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// Setup global work size and local work size
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size_t gws[2] , lws[2];
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#if (!USING_NON_VECTOR)
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if (NON_OPTIMAL == 0)
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{
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gws[0] = (size_t)nLocalM;
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gws[1] = (size_t)N / VECTOR_WIDTH;
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lws[0] = NUM_WORK_ITEM;
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lws[1] = NUM_WORK_ITEM / VECTOR_WIDTH;
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}
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else
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#endif
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{
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gws[0] = (size_t)ALIGN_UP(nLocalM, VECTOR_WIDTH) / VECTOR_WIDTH;
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gws[1] = (size_t)ALIGN_UP(N, NUM_WORK_ITEM);
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lws[0] = NUM_WORK_ITEM / VECTOR_WIDTH;
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lws[1] = NUM_WORK_ITEM;
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}
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for (int i = 0; i < 2; ++i) {
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// By OpenCL spec, global work size should be MULTIPLE of local work size
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// Formula below achieve it
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// e.g., gws = 25, lws = 16, then (25 + 16 - 1) / 16 * 16 = 40 / 16 * 16 = 2 * 16 = 32
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gws[i] = (gws[i] + lws[i] - 1) / lws[i] * lws[i];
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}
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// printf("gws : %d, %d lws : %d, %d\n",gws[0],gws[1],lws[0],lws[1]);
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// Run kernel
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err = clEnqueueNDRangeKernel(queue[i], kernel[i], 2, NULL, gws, lws, 0, NULL, NULL);
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CHECK_ERROR(err);
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < nDevCnt; i++)
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{
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err = clFinish(queue[i]);
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CHECK_ERROR(err);
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}
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}
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static void print_platform_info(cl_platform_id platform) {
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size_t sz;
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char *buf;
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CHECK_ERROR(clGetPlatformInfo(platform, CL_PLATFORM_NAME, 0, NULL, &sz));
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buf = (char*)malloc(sz);
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CHECK_ERROR(clGetPlatformInfo(platform, CL_PLATFORM_NAME, sz, buf, NULL));
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printf("Detected OpenCL platform: %s\n", buf);
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free(buf);
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}
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static void print_device_info(cl_device_id device) {
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size_t sz;
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char *buf;
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CHECK_ERROR(clGetDeviceInfo(device, CL_DEVICE_NAME, 0, NULL, &sz));
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buf = (char*)malloc(sz);
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CHECK_ERROR(clGetDeviceInfo(device, CL_DEVICE_NAME, sz, buf, NULL));
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printf("Detected OpenCL device: %s\n", buf);
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free(buf);
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}
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static cl_program create_and_build_program_with_source(cl_context context, cl_device_id device, const char *file_name) {
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FILE *file = fopen(file_name, "rb");
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if (file == NULL) {
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printf("Failed to open %s\n", file_name);
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exit(EXIT_FAILURE);
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}
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fseek(file, 0, SEEK_END);
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size_t source_size = ftell(file);
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rewind(file);
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char *source_code = (char*)malloc(source_size + 1);
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size_t ntotal = 0;
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while (ntotal < source_size) {
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int nread = fread(source_code, sizeof(char), source_size, file);
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ntotal += nread;
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}
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source_code[source_size] = '\0';
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fclose(file);
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cl_program program = clCreateProgramWithSource(context, 1, (const char **)&source_code, &source_size, &err);
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CHECK_ERROR(err);
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free(source_code);
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err = clBuildProgram(program, 1, &device, "", NULL, NULL);
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if (err == CL_BUILD_PROGRAM_FAILURE) {
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size_t log_size;
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CHECK_ERROR(clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size));
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char *log = (char*)malloc(log_size + 1);
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CHECK_ERROR(clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, log_size, log, NULL));
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log[log_size] = 0;
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printf("Compile error:\n%s\n", log);
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free(log);
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}
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CHECK_ERROR(err);
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return program;
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}
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void mat_mul_init(float *A, float *B, float *C, int M, int N, int K) {
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// Get OpenCL platform
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err = clGetPlatformIDs(1, &platform, NULL);
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CHECK_ERROR(err);
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print_platform_info(platform);
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// Get OpenCL device
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err = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 0, NULL, (cl_uint*)&nDevCnt);
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err = clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, (cl_uint)nDevCnt, device, NULL);
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CHECK_ERROR(err);
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// for (int i = 0; i < nDevCnt; i++)
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{
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print_device_info(device[0]);
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}
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// Create OpenCL context
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context = clCreateContext(NULL, (cl_uint)nDevCnt, device, NULL, NULL, &err);
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CHECK_ERROR(err);
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// Create OpenCL command queue
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for (int i = 0; i < nDevCnt; i++)
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{
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int nLocalM = (i == (nDevCnt - 1)) ? M - ((M / nDevCnt) * (nDevCnt - 1)) : (M / nDevCnt);
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queue[i] = clCreateCommandQueue(context, device[i], 0, &err);
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CHECK_ERROR(err);
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// Compile program from "kernel.cl"
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program[i] = create_and_build_program_with_source(context, device[i], "kernel.cl");
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// Extract kernel from compiled program
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kernel[i] = clCreateKernel(program[i], "sgemm", &err);
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CHECK_ERROR(err);
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// Create GPU buffers
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a_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, nLocalM * K * sizeof(float), NULL, &err);
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CHECK_ERROR(err);
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b_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, K * N * sizeof(float), NULL, &err);
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CHECK_ERROR(err);
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c_d[i] = clCreateBuffer(context, CL_MEM_READ_WRITE, nLocalM * N * sizeof(float), NULL, &err);
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CHECK_ERROR(err);
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// Write to GPU; A (cpu) -> a_d (gpu), B (cpu) -> b_d (gpu)
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err = clEnqueueWriteBuffer(queue[i], a_d[i], CL_TRUE, 0, nLocalM * K * sizeof(float), &A[i * (M / nDevCnt) * K], 0, NULL, NULL);
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CHECK_ERROR(err);
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err = clEnqueueWriteBuffer(queue[i], b_d[i], CL_TRUE, 0, K * N * sizeof(float), B, 0, NULL, NULL);
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CHECK_ERROR(err);
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < nDevCnt; i++)
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{
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err = clFinish(queue[i]);
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CHECK_ERROR(err);
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}
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}
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void mat_mul_final(float *A, float *B, float *C, int M, int N, int K) {
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// Read from GPU; c_d (gpu) -> C (cpu)
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for (int i = 0; i < nDevCnt; i++)
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{
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int nLocalM = (i == (nDevCnt - 1)) ? M - ((M / nDevCnt) * (nDevCnt - 1)) : (M / nDevCnt);
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err = clEnqueueReadBuffer(queue[i], c_d[i], CL_TRUE, 0, nLocalM * N * sizeof(float), &C[i * (M / nDevCnt) * N], 0, NULL, NULL);
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CHECK_ERROR(err);
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}
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for (int i = 0; i < nDevCnt; i++)
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{
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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err = clFinish(queue[i]);
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CHECK_ERROR(err);
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}
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}
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