| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287 | /* StarPU --- Runtime system for heterogeneous multicore architectures. * * Copyright (C) 2012,2014,2017                           Inria * Copyright (C) 2012-2017                                CNRS * Copyright (C) 2013,2014,2016                           Université de Bordeaux * Copyright (C) 2013                                     Thibaut Lambert * * 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 <starpu.h>#include <starpu_scheduler.h>#include "../helper.h"#include <core/perfmodel/perfmodel.h>/* * Schedulers that are aware of the expected task length provided by the * perfmodels must make sure that : * 	- cpu_task is cheduled on a CPU. * 	- gpu_task is scheduled on a GPU. * * Applies to : dmda and to what other schedulers ? */void dummy(void *buffers[], void *args){	(void) buffers;	(void) args;}/* * Fake cost functions. */static doublecpu_task_cpu(struct starpu_task *task,	     struct starpu_perfmodel_arch* arch,	     unsigned nimpl){	(void) task;	(void) arch;	(void) nimpl;	return 1.0;}static doublecpu_task_gpu(struct starpu_task *task,	     struct starpu_perfmodel_arch* arch,	     unsigned nimpl){	(void) task;	(void) arch;	(void) nimpl;	return 10000000.0;}static doublegpu_task_cpu(struct starpu_task *task,	     struct starpu_perfmodel_arch* arch,	     unsigned nimpl){	(void) task;	(void) arch;	(void) nimpl;	return 10000000.0;}static doublegpu_task_gpu(struct starpu_task *task,	     struct starpu_perfmodel_arch* arch,	     unsigned nimpl){	(void) task;	(void) arch;	(void) nimpl;	return 1.0;}static struct starpu_perfmodel model_cpu_task ={	.type = STARPU_PER_ARCH,	.symbol = "model_cpu_task"};static struct starpu_perfmodel model_gpu_task ={	.type = STARPU_PER_ARCH,	.symbol = "model_gpu_task"};static voidinit_perfmodels_gpu(int gpu_type){	int nb_worker_gpu = starpu_worker_get_count_by_type(gpu_type);	int *worker_gpu_ids = malloc(nb_worker_gpu * sizeof(int));	int worker_gpu;	starpu_worker_get_ids_by_type(gpu_type, worker_gpu_ids, nb_worker_gpu);	for(worker_gpu = 0 ; worker_gpu < nb_worker_gpu ; worker_gpu ++)	{		starpu_perfmodel_set_per_devices_cost_function(&model_cpu_task, 0, cpu_task_gpu,							       gpu_type, starpu_worker_get_devid(worker_gpu_ids[worker_gpu]), 1,							       -1);		starpu_perfmodel_set_per_devices_cost_function(&model_gpu_task, 0, gpu_task_gpu,							       gpu_type, starpu_worker_get_devid(worker_gpu_ids[worker_gpu]), 1,							       -1);	}	free(worker_gpu_ids);}static voidinit_perfmodels(void){	starpu_perfmodel_init(&model_cpu_task);	starpu_perfmodel_init(&model_gpu_task);	starpu_perfmodel_set_per_devices_cost_function(&model_cpu_task, 0, cpu_task_cpu, STARPU_CPU_WORKER, 0, 1, -1);	starpu_perfmodel_set_per_devices_cost_function(&model_gpu_task, 0, gpu_task_cpu, STARPU_CPU_WORKER, 0, 1, -1);	// We need to set the cost function for each combination with a CUDA or a OpenCL worker	init_perfmodels_gpu(STARPU_CUDA_WORKER);	init_perfmodels_gpu(STARPU_OPENCL_WORKER);}/* * Dummy codelets. */static struct starpu_codelet cpu_cl ={	.cpu_funcs    = { dummy },	.cuda_funcs   = { dummy },	.opencl_funcs = { dummy },	.nbuffers     = 0,	.model        = &model_cpu_task};static struct starpu_codelet gpu_cl ={	.cpu_funcs    = { dummy },	.cuda_funcs   = { dummy },	.opencl_funcs = { dummy },	.nbuffers     = 0,	.model        = &model_gpu_task};static intrun(struct starpu_sched_policy *policy){	struct starpu_conf conf;	starpu_conf_init(&conf);	conf.sched_policy = policy;	int ret = starpu_init(&conf);	if (ret == -ENODEV)		exit(STARPU_TEST_SKIPPED);	/* At least 1 CPU and 1 GPU are needed. */	if (starpu_cpu_worker_get_count() == 0)	{		starpu_shutdown();		exit(STARPU_TEST_SKIPPED);	}	if (starpu_cuda_worker_get_count() == 0 && starpu_opencl_worker_get_count() == 0)	{		starpu_shutdown();		exit(STARPU_TEST_SKIPPED);	}	starpu_profiling_status_set(1);	init_perfmodels();	struct starpu_task *cpu_task = starpu_task_create();	cpu_task->cl = &cpu_cl;	cpu_task->destroy = 0;	struct starpu_task *gpu_task = starpu_task_create();	gpu_task->cl = &gpu_cl;	gpu_task->destroy = 0;	ret = starpu_task_submit(cpu_task);	STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	ret = starpu_task_submit(gpu_task);	STARPU_CHECK_RETURN_VALUE(ret, "starpu_task_submit");	starpu_task_wait_for_all();	enum starpu_worker_archtype cpu_task_worker, gpu_task_worker;	cpu_task_worker = starpu_worker_get_type(cpu_task->profiling_info->workerid);	gpu_task_worker = starpu_worker_get_type(gpu_task->profiling_info->workerid);	if (cpu_task_worker != STARPU_CPU_WORKER || (gpu_task_worker != STARPU_CUDA_WORKER && gpu_task_worker != STARPU_OPENCL_WORKER))	{		FPRINTF(stderr, "Tasks did not execute on expected worker\n");		if (cpu_task_worker != STARPU_CPU_WORKER)		{			FPRINTF(stderr, "The CPU task did not run on a CPU worker\n");		}		if (gpu_task_worker != STARPU_CUDA_WORKER && gpu_task_worker != STARPU_OPENCL_WORKER)		{			FPRINTF(stderr, "The GPU task did not run on a Cuda or OpenCL worker\n");		}		ret = 1;	}	else	{		FPRINTF(stderr, "Tasks DID execute on expected worker\n");		ret = 0;	}	starpu_task_destroy(cpu_task);	starpu_task_destroy(gpu_task);	starpu_shutdown();	return ret;}/*extern struct starpu_sched_policy _starpu_sched_ws_policy;extern struct starpu_sched_policy _starpu_sched_prio_policy;extern struct starpu_sched_policy _starpu_sched_random_policy;extern struct starpu_sched_policy _starpu_sched_dm_policy;extern struct starpu_sched_policy _starpu_sched_dmda_ready_policy;extern struct starpu_sched_policy _starpu_sched_dmda_sorted_policy;extern struct starpu_sched_policy _starpu_sched_eager_policy;extern struct starpu_sched_policy _starpu_sched_parallel_heft_policy;extern struct starpu_sched_policy _starpu_sched_peager_policy;*/extern struct starpu_sched_policy _starpu_sched_dmda_policy;/* XXX: what policies are we interested in ? */static struct starpu_sched_policy *policies[] ={	//&_starpu_sched_ws_policy,	//&_starpu_sched_prio_policy,	//&_starpu_sched_dm_policy,	&_starpu_sched_dmda_policy,	//&_starpu_sched_dmda_ready_policy,	//&_starpu_sched_dmda_sorted_policy,	//&_starpu_sched_random_policy,	//&_starpu_sched_eager_policy,	//&_starpu_sched_parallel_heft_policy,	//&_starpu_sched_peager_policy};int main(void){#ifndef STARPU_HAVE_SETENV/* XXX: is this macro used by all the schedulers we are interested in ? */#warning "setenv() is not available, skipping this test"	return STARPU_TEST_SKIPPED;#else	setenv("STARPU_SCHED_BETA", "0", 1);#ifdef STARPU_HAVE_UNSETENV	unsetenv("STARPU_SCHED");#endif	if (starpu_get_env_number_default("STARPU_NWORKER_PER_CUDA", 1) != 1)		return STARPU_TEST_SKIPPED;	int i;	int n_policies = sizeof(policies)/sizeof(policies[0]);	for (i = 0; i < n_policies; ++i)	{		struct starpu_sched_policy *policy = policies[i];		FPRINTF(stdout, "Running with policy %s.\n",			policy->policy_name);		int ret;		ret = run(policy);		if (ret == 1)			return EXIT_FAILURE;	}	return EXIT_SUCCESS;#endif}
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