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- /* StarPU --- Runtime system for heterogeneous multicore architectures.
- *
- * Copyright (C) 2010, 2015 Université de Bordeaux
- * Copyright (C) 2010, 2011, 2012, 2013 CNRS
- *
- * 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.
- */
- /*
- * This examples demonstrates how to use multiple linear regression models.
- The duration of the task test_mlr will
- be computed using the following equation:
- T = a + b * (M^2*N) + c * (N^3*K)
- where M, N, K are the parameters of the task,
- exponents are coming from cl.model->combinations[..][..]
- and finally a, b, c are coefficients
- which mostly depend on the machine speed.
-
- These coefficients are going to be automatically computed
- using least square method.
- */
- #include <stdio.h>
- #include <stdlib.h>
- #include <stdint.h>
- #include <starpu.h>
- int sum;
- /* Performance function of the task, which is in this case very simple, as the parameter values just need to be written in the array "parameters" */
- void cl_perf_func(struct starpu_task *task, double *parameters)
- {
- starpu_codelet_unpack_args(task->cl_arg,
- ¶meters[0],
- ¶meters[1],
- ¶meters[2]);
- }
- /* Function of the task that will be executed. In this case running dummy cycles, just to make sure task duration is significant */
- void cpu_func(void *buffers[], void *cl_arg)
- {
- double m,n,k;
- starpu_codelet_unpack_args(cl_arg,
- &m,
- &n,
- &k);
-
- for(int i=0; i < (int) (m*m*n); i++)
- sum+=i;
- for(int i=0; i < (int) (n*n*n*k); i++)
- sum+=i;
- }
- int main(int argc, char **argv)
- {
- struct starpu_codelet cl;
- starpu_init(NULL);
- /* Allocating and naming codelet, similar to any other StarPU program */
- memset(&cl, 0, sizeof(cl));
- cl.cpu_funcs[0] = cpu_func;
- cl.cpu_funcs_name[0] = "mlr_codelet";
- cl.nbuffers = 0;
- cl.name="test_mlr";
- /* ############################################ */
- /* Start of the part specific to multiple linear regression perfmodels */
-
- /* Defining perfmodel, number of parameters and their names */
- struct starpu_perfmodel *model = calloc(1,sizeof(struct starpu_perfmodel));
- cl.model = model;
- cl.model->type = STARPU_MULTIPLE_REGRESSION_BASED;
- cl.model->symbol = cl.name;
- cl.model->parameters = cl_perf_func;
- cl.model->nparameters = 3;
- cl.model->parameters_names = (const char **) calloc(1, cl.model->nparameters*sizeof(char *));
- cl.model->parameters_names[0] = "M";
- cl.model->parameters_names[1] = "N";
- cl.model->parameters_names[2] = "K";
- /* Defining the equation for modeling duration of the task */
- /* Refer to the explanation and equation on the top of this file
- to get more detailed explanation */
- cl.model->ncombinations = 2;
- cl.model->combinations = (unsigned **) malloc(cl.model->ncombinations*sizeof(unsigned *));
- if (cl.model->combinations)
- {
- for (unsigned i = 0; i < cl.model->ncombinations; i++)
- {
- cl.model->combinations[i] = (unsigned *) malloc(cl.model->nparameters*sizeof(unsigned));
- }
- }
- cl.model->combinations[0][0] = 2;
- cl.model->combinations[0][1] = 1;
- cl.model->combinations[0][2] = 0;
- cl.model->combinations[1][0] = 0;
- cl.model->combinations[1][1] = 3;
- cl.model->combinations[1][2] = 1;
- /* End of the part specific to multiple linear regression perfmodels */
- /* ############################################ */
-
- sum=0;
- double m,n,k;
- /* Giving pseudo-random values to the M,N,K parameters and inserting tasks */
- for(int i=0; i < 42; i++)
- {
- m = (double) ((rand() % 10)+1);
- n = (double) ((rand() % 10)+1);
- k = (double) ((rand() % 10)+1);
-
- for(int j=0; j < 42; j++)
- starpu_insert_task(&cl,
- STARPU_VALUE, &m, sizeof(double),
- STARPU_VALUE, &n, sizeof(double),
- STARPU_VALUE, &k, sizeof(double),
- 0);
- }
-
- starpu_shutdown();
- return 0;
- }
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