starpu-max/examples/cholesky/cholesky_implicit.c

/* StarPU --- Runtime system for heterogeneous multicore architectures.
 *
 * Copyright (C) 2009, 2010, 2011  Université de Bordeaux 1
 * Copyright (C) 2010  Mehdi Juhoor <mjuhoor@gmail.com>
 * Copyright (C) 2010, 2011  Centre National de la Recherche Scientifique
 *
 * 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 "cholesky.h"

/*
 *	Create the codelets
 */

static struct starpu_codelet cl11 =
{
	.where = STARPU_CPU|STARPU_CUDA,
	.type = STARPU_SEQ,
	.cpu_funcs = {chol_cpu_codelet_update_u11, NULL},
#ifdef STARPU_USE_CUDA
	.cuda_funcs = {chol_cublas_codelet_update_u11, NULL},
#endif
	.nbuffers = 1,
	.model = &chol_model_11
};

static struct starpu_codelet cl21 =
{
	.where = STARPU_CPU|STARPU_CUDA,
	.type = STARPU_SEQ,
	.cpu_funcs = {chol_cpu_codelet_update_u21, NULL},
#ifdef STARPU_USE_CUDA
	.cuda_funcs = {chol_cublas_codelet_update_u21, NULL},
#endif
	.nbuffers = 2,
	.model = &chol_model_21
};

static struct starpu_codelet cl22 =
{
	.where = STARPU_CPU|STARPU_CUDA,
	.type = STARPU_SEQ,
	.max_parallelism = INT_MAX,
	.cpu_funcs = {chol_cpu_codelet_update_u22, NULL},
#ifdef STARPU_USE_CUDA
	.cuda_funcs = {chol_cublas_codelet_update_u22, NULL},
#endif
	.nbuffers = 3,
	.model = &chol_model_22
};

/*
 *	code to bootstrap the factorization
 *	and construct the DAG
 */

static void callback_turn_spmd_on(void *arg __attribute__ ((unused)))
{
	cl22.type = STARPU_SPMD;
}

static void _cholesky(starpu_data_handle_t dataA, unsigned nblocks)
{
	struct timeval start;
	struct timeval end;

	unsigned i,j,k;

	int prio_level = noprio?STARPU_DEFAULT_PRIO:STARPU_MAX_PRIO;

	gettimeofday(&start, NULL);

	if (bound)
		starpu_bound_start(0, 0);
	/* create all the DAG nodes */
	for (k = 0; k < nblocks; k++)
	{
                starpu_data_handle_t sdatakk = starpu_data_get_sub_data(dataA, 2, k, k);

                starpu_insert_task(&cl11,
                                   STARPU_PRIORITY, prio_level,
                                   STARPU_RW, sdatakk,
				   STARPU_CALLBACK, (k == 3*nblocks/4)?callback_turn_spmd_on:NULL,
                                   0);

		for (j = k+1; j<nblocks; j++)
		{
                        starpu_data_handle_t sdatakj = starpu_data_get_sub_data(dataA, 2, k, j);

                        starpu_insert_task(&cl21,
                                           STARPU_PRIORITY, (j == k+1)?prio_level:STARPU_DEFAULT_PRIO,
                                           STARPU_R, sdatakk,
                                           STARPU_RW, sdatakj,
                                           0);

			for (i = k+1; i<nblocks; i++)
			{
				if (i <= j)
                                {
					starpu_data_handle_t sdataki = starpu_data_get_sub_data(dataA, 2, k, i);
					starpu_data_handle_t sdataij = starpu_data_get_sub_data(dataA, 2, i, j);
					
					starpu_insert_task(&cl22,
                                                           STARPU_PRIORITY, ((i == k+1) && (j == k+1))?prio_level:STARPU_DEFAULT_PRIO,
                                                           STARPU_R, sdataki,
                                                           STARPU_R, sdatakj,
                                                           STARPU_RW, sdataij,
                                                           0);
                                }
			}
		}
	}

	starpu_task_wait_for_all();
	if (bound)
		starpu_bound_stop();

	starpu_data_unpartition(dataA, 0);

	gettimeofday(&end, NULL);

	double timing = (double)((end.tv_sec - start.tv_sec)*1000000 + (end.tv_usec - start.tv_usec));
	FPRINTF(stderr, "Computation took (in ms)\n");
	FPRINTF(stdout, "%2.2f\n", timing/1000);

	unsigned long n = starpu_matrix_get_nx(dataA);

	double flop = (1.0f*n*n*n)/3.0f;
	FPRINTF(stderr, "Synthetic GFlops : %2.2f\n", (flop/timing/1000.0f));
	if (bound) {
		double res;
		starpu_bound_compute(&res, NULL, 0);
		FPRINTF(stderr, "Theoretical GFlops: %2.2f\n", (flop/res/1000000.0f));
	}
}

static void cholesky(float *matA, unsigned size, unsigned ld, unsigned nblocks)
{
	starpu_data_handle_t dataA;

	/* monitor and partition the A matrix into blocks :
	 * one block is now determined by 2 unsigned (i,j) */
	starpu_matrix_data_register(&dataA, 0, (uintptr_t)matA, ld, size, size, sizeof(float));

	struct starpu_data_filter f = {
		.filter_func = starpu_vertical_block_filter_func,
		.nchildren = nblocks
	};

	struct starpu_data_filter f2 = {
		.filter_func = starpu_block_filter_func,
		.nchildren = nblocks
	};

	starpu_data_map_filters(dataA, 2, &f, &f2);

	_cholesky(dataA, nblocks);

	starpu_data_unregister(dataA);
}

int main(int argc, char **argv)
{
	/* create a simple definite positive symetric matrix example
	 *
	 *	Hilbert matrix : h(i,j) = 1/(i+j+1)
	 * */

	parse_args(argc, argv);

	starpu_init(NULL);

	starpu_helper_cublas_init();

	float *mat;
	starpu_malloc((void **)&mat, (size_t)size*size*sizeof(float));

	unsigned i,j;
	for (i = 0; i < size; i++)
	{
		for (j = 0; j < size; j++)
		{
			mat[j +i*size] = (1.0f/(1.0f+i+j)) + ((i == j)?1.0f*size:0.0f);
			/* mat[j +i*size] = ((i == j)?1.0f*size:0.0f); */
		}
	}

/* #define PRINT_OUTPUT */
#ifdef PRINT_OUTPUT
	FPRINTF(stdout, "Input :\n");

	for (j = 0; j < size; j++)
	{
		for (i = 0; i < size; i++)
		{
			if (i <= j) {
				FPRINTF(stdout, "%2.2f\t", mat[j +i*size]);
			}
			else {
				FPRINTF(stdout, ".\t");
			}
		}
		FPRINTF(stdout, "\n");
	}
#endif

	cholesky(mat, size, size, nblocks);

#ifdef PRINT_OUTPUT
	FPRINTF(stdout, "Results :\n");
	for (j = 0; j < size; j++)
	{
		for (i = 0; i < size; i++)
		{
			if (i <= j) {
				FPRINTF(stdout, "%2.2f\t", mat[j +i*size]);
			}
			else {
				FPRINTF(stdout, ".\t");
				mat[j+i*size] = 0.0f; /* debug */
			}
		}
		FPRINTF(stdout, "\n");
	}
#endif

	if (check)
	{
		FPRINTF(stderr, "compute explicit LLt ...\n");
		for (j = 0; j < size; j++)
		{
			for (i = 0; i < size; i++)
			{
				if (i > j) {
					mat[j+i*size] = 0.0f; /* debug */
				}
			}
		}
		float *test_mat = malloc(size*size*sizeof(float));
		STARPU_ASSERT(test_mat);
	
		SSYRK("L", "N", size, size, 1.0f,
					mat, size, 0.0f, test_mat, size);
	
		FPRINTF(stderr, "comparing results ...\n");
#ifdef PRINT_OUTPUT
		for (j = 0; j < size; j++)
		{
			for (i = 0; i < size; i++)
			{
				if (i <= j) {
					FPRINTF(stdout, "%2.2f\t", test_mat[j +i*size]);
				}
				else {
					FPRINTF(stdout, ".\t");
				}
			}
			FPRINTF(stdout, "\n");
		}
#endif
	
		for (j = 0; j < size; j++)
		{
			for (i = 0; i < size; i++)
			{
				if (i <= j) {
	                                float orig = (1.0f/(1.0f+i+j)) + ((i == j)?1.0f*size:0.0f);
	                                float err = abs(test_mat[j +i*size] - orig);
	                                if (err > 0.00001) {
	                                        FPRINTF(stderr, "Error[%u, %u] --> %2.2f != %2.2f (err %2.2f)\n", i, j, test_mat[j +i*size], orig, err);
	                                        assert(0);
	                                }
	                        }
			}
	        }
	}

	starpu_helper_cublas_shutdown();
	starpu_shutdown();

	return 0;
}