/* StarPU --- Runtime system for heterogeneous multicore architectures. * * Copyright (C) 2011-2021 Université de Bordeaux, CNRS (LaBRI UMR 5800), Inria * * StarPU is free software; you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as published by * the Free Software Foundation; either version 2.1 of the License, or (at * your option) any later version. * * StarPU is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * * See the GNU Lesser General Public License in COPYING.LGPL for more details. */ #include #include "../test_interfaces.h" #include "../../../helper.h" #define NX 4 #define NY NX #define NZ NX #define NT NX /* Prototypes */ static void register_data(void); static void unregister_data(void); void test_tensor_cpu_func(void *buffers[], void *args); #ifdef STARPU_USE_CUDA extern void test_tensor_cuda_func(void *buffers[], void *_args); #endif #ifdef STARPU_USE_OPENCL extern void test_tensor_opencl_func(void *buffers[], void *args); #endif static starpu_data_handle_t _tensor_handle; static starpu_data_handle_t _tensor2_handle; struct test_config tensor_config = { .cpu_func = test_tensor_cpu_func, #ifdef STARPU_USE_CUDA .cuda_func = test_tensor_cuda_func, #endif #ifdef STARPU_USE_OPENCL .opencl_func = test_tensor_opencl_func, #endif #ifdef STARPU_USE_MIC .cpu_func_name = "test_tensor_cpu_func", #endif .handle = &_tensor_handle, .dummy_handle = &_tensor2_handle, .copy_failed = SUCCESS, .name = "tensor_interface" }; static int _tensor[NX*NY*NZ*NT]; static int _tensor2[NX*NY*NZ*NT]; static void register_data(void) { /* Initializing data */ int val = 0; int i, j, k, l; for (l = 0; l < NT; l++) for (k = 0; k < NZ; k++) for (j = 0; j < NY; j++) for (i = 0; i < NX; i++) _tensor[(l*NX*NY*NZ)+(k*NX*NY)+(j*NX)+i] = val++; /* Registering data */ starpu_tensor_data_register(&_tensor_handle, STARPU_MAIN_RAM, (uintptr_t)_tensor, NX, NX * NY, NX * NY * NZ, NX, NY, NZ, NT, sizeof(_tensor[0])); starpu_tensor_data_register(&_tensor2_handle, STARPU_MAIN_RAM, (uintptr_t)_tensor2, NX, NX * NY, NX * NY * NZ, NX, NY, NZ, NT, sizeof(_tensor2[0])); } static void unregister_data(void) { starpu_data_unregister(_tensor_handle); starpu_data_unregister(_tensor2_handle); } void test_tensor_cpu_func(void *buffers[], void *args) { STARPU_SKIP_IF_VALGRIND; int factor = *(int*)args; int nx = STARPU_TENSOR_GET_NX(buffers[0]); int ny = STARPU_TENSOR_GET_NY(buffers[0]); int nz = STARPU_TENSOR_GET_NZ(buffers[0]); int nt = STARPU_TENSOR_GET_NT(buffers[0]); unsigned ldy = STARPU_TENSOR_GET_LDY(buffers[0]); unsigned ldz = STARPU_TENSOR_GET_LDZ(buffers[0]); unsigned ldt = STARPU_TENSOR_GET_LDT(buffers[0]); int *tensor = (int *) STARPU_TENSOR_GET_PTR(buffers[0]); int i, j, k, l; int val = 0; tensor_config.copy_failed = SUCCESS; for (l = 0; l < nt; l++) { for (k = 0; k < nz; k++) { for (j = 0; j < ny; j++) { for (i = 0; i < nx; i++) { if (tensor[(l*ldt)+(k*ldz)+(j*ldy)+i] != factor * val) { tensor_config.copy_failed = FAILURE; return; } else { tensor[(l*ldt)+(k*ldz)+(j*ldy)+i] *= -1; val++; } } } } } } int main(int argc, char **argv) { struct data_interface_test_summary summary; struct starpu_conf conf; starpu_conf_init(&conf); conf.ncuda = 2; conf.nopencl = 1; conf.nmic = -1; if (starpu_initialize(&conf, &argc, &argv) == -ENODEV || starpu_cpu_worker_get_count() == 0) goto enodev; register_data(); run_tests(&tensor_config, &summary); unregister_data(); starpu_shutdown(); data_interface_test_summary_print(stderr, &summary); return data_interface_test_summary_success(&summary); enodev: return STARPU_TEST_SKIPPED; }