ConjugateGradient.c 29.5 KB
Newer Older
iker_martin's avatar
iker_martin committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <mkl_blas.h>
#include <mkl_spblas.h>
#include "ScalarVectors.h"
#include "SparseMatrices.h"
#include <mpi.h>
#include <string.h>
#include "../malleability/malleabilityManager.h"

//#define ONLY_SYM 0
#define ROOT 0
//#define DEBUG 0
#define MAX_PROCS_SET 16

typedef struct {
  double umbral, tol;
  int iter, maxiter, n;

  double beta, rho, alpha;
  double *res, *z, *d, *vec;
  SparseMatrix subm;
  double *d_full;

  int *dist_elem, *displs_elem;
  int *dist_rows, *displs_rows;
  int *vlen;
} Compute_data;

struct Dist_data {
  int ini;
  int fin;

  int tamBl; // Numero de filas
  int tot_r; // Total de filas en la matriz

  int myId;
  int numP;

  int numP_parents;

  MPI_Comm comm, comm_children, comm_parents;
  MPI_Datatype scalars, arrays;
};

void init_app(Compute_data *computeData, struct Dist_data *dist_data, char* argv[]);
void get_mat_dist(Compute_data *computeData, struct Dist_data dist_data, SparseMatrix mat);
void get_rows_dist(Compute_data *computeData, int numP, int n);
void mat_alloc(Compute_data *computeData, SparseMatrix mat, struct Dist_data dist_data);
void computeSolution(Compute_data computeData, double **subsol, SparseMatrix mat, int myId, double **full_vec);
void pre_compute(Compute_data *computeData, struct Dist_data dist_data, double *subsol, double *full_vec);
53
int compute(Compute_data *computeData, struct Dist_data *dist_data);
iker_martin's avatar
iker_martin committed
54
55
56
57
58
59
void free_computeData(Compute_data *computeData);

//===================================MALLEABILITY FUNCTIONS====================================================

int n_check = 30;

60
int dist_old(struct Dist_data *dist_data, Compute_data *computeData, int num_children, int sm, int ss, int rm, int rs);
iker_martin's avatar
iker_martin committed
61
62
63
64
65
66
67
68
69
70
71
72
73
74
void send_matrix(struct Dist_data dist_data, Compute_data computeData, int rootBcast, int numP_child, int idI, int idE,
                 int *sendcounts, int *recvcounts,int *sdispls, int *rdispls);

void dist_new(struct Dist_data *dist_data, Compute_data *computeData);
void recv_matrix(struct Dist_data *dist_data, Compute_data *computeData, int idI, int idE,
                 int *sendcounts, int *recvcounts,int *sdispls, int *rdispls);
//----------------------------------------------------------------------------------------------------
void get_dist(int total_r, int id, int numP, struct Dist_data *dist_data);
void set_counts(int id, int numP, struct Dist_data data_dist, int *sendcounts);
void getIds_intercomm(struct Dist_data dist_data, int numP_other, int **idS);
//----------------------------------------------------------------------------------------------------

int main (int argc, char *argv[]) {
	int terminate;
75
	int req, num_nodes, num_cpus = 20;
iker_martin's avatar
iker_martin committed
76
77
78
        char *nodelist = NULL;
        Compute_data computeData;

79
        computeData.z = NULL; computeData.d_full = NULL, computeData.d = NULL;
iker_martin's avatar
iker_martin committed
80
81
82
        computeData.vec = NULL; computeData.res = NULL;
        computeData.dist_elem = NULL; computeData.displs_elem = NULL;
        computeData.dist_rows = NULL; computeData.displs_rows = NULL;
83
84
	computeData.subm.vptr = NULL;
	computeData.vlen = NULL;
iker_martin's avatar
iker_martin committed
85
86
87
88
89
90
91
92
93
94

        int numP, myId, num_children = 0;
        struct Dist_data dist_data;
        if (argc >= 5) {
          num_children = atoi(argv[2]);
          nodelist = argv[3];
          num_nodes = atoi(argv[4]);
          num_cpus = num_nodes * num_cpus;
        }

95
        MPI_Init_thread(&argc, &argv, MPI_THREAD_MULTIPLE, &req);
iker_martin's avatar
iker_martin committed
96
97
98
        MPI_Comm_size(MPI_COMM_WORLD, &numP);
        MPI_Comm_rank(MPI_COMM_WORLD, &myId);

99
	printf("Nuevo set %d/%d\n", myId, numP);
iker_martin's avatar
iker_martin committed
100
101
102
103
104
105
106
107
        dist_data.myId = myId;
        dist_data.numP = numP;
	dist_data.comm = MPI_COMM_WORLD;

        int new_group = init_malleability(myId, numP, ROOT, dist_data.comm, argv[0], nodelist, num_cpus, num_nodes);

	if( !new_group ) { //First set of processes
	  init_app(&computeData, &dist_data, argv);
108
          dist_old(&dist_data, &computeData, num_children, 0, 1, 0, 1);
iker_martin's avatar
iker_martin committed
109
110
111
112
113
        } else {
          dist_new(&dist_data, &computeData);
	}


114
115
116
	if ( computeData.iter == 0 ) {
        terminate = compute(&computeData, &dist_data);
	}
117
	terminate = 1;
iker_martin's avatar
iker_martin committed
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
        if(myId == ROOT && terminate) {
	  printf ("End(%d) --> (%d,%20.10e)\n", computeData.n, computeData.iter, computeData.tol);
        }

	// End of CG
        free_malleability();
        free_computeData(&computeData);
        MPI_Finalize();
}

/*
 * Init application data before
 * starting iterative computation
 */
void init_app(Compute_data *computeData, struct Dist_data *dist_data, char* argv[]) {
	SparseMatrix mat, sym;
        double *full_vec = NULL;
	double *subsol = NULL;

        if(dist_data->myId == ROOT) {
#ifdef ONLY_SYM
  	  printf ("Working with symmetric format\n");
	  CreateSparseMatrixHB (argv[1], &mat, 1);
#else
	  printf ("Working with general format\n");
	  CreateSparseMatrixHB (argv[1], &sym, 1);
	  DesymmetrizeSparseMatrices (sym, &mat);
	  RemoveSparseMatrix (&sym);
#endif
          computeData->n = mat.dim1;
        }

        // Communicate number of rows to distribute and number of elements in the matrix
        MPI_Bcast(&computeData->n, 1, MPI_INT, ROOT, MPI_COMM_WORLD);

	// Each process calcules their own distribution
        get_dist(computeData->n, dist_data->myId, dist_data->numP, dist_data);
        
        if(dist_data->myId == ROOT) { // ROOT gets rows and vpos/vval distribution
	  get_mat_dist(computeData, *dist_data, mat);
          TransformHeadertoLength(mat.vptr, computeData->n); // From vptr to vlen
        } else { // Non ROOT proceses gets row distribution
          get_rows_dist(computeData, dist_data->numP, computeData->n);
          CreateInts (&computeData->dist_elem, dist_data->numP*2);
	  InitInts (computeData->dist_elem, dist_data->numP * 2, 0.0, 0); 
          computeData->displs_elem = computeData->dist_elem + dist_data->numP;
        }
        // Allocate for each process their submatrix and get their distribution from ROOT
	mat_alloc(computeData, mat, *dist_data);

	computeSolution(*computeData, &subsol, mat, dist_data->myId, &full_vec);
	pre_compute(computeData, *dist_data, subsol, full_vec);

        //Free Initial data
	RemoveDoubles(&subsol);
	RemoveDoubles(&full_vec);
        if(dist_data->myId == ROOT) {
	  RemoveSparseMatrix(&mat);
        }
}

/*
 * MPI Dist
 * Broadcast the vptr array and each process gets the data that corresponds to itself.
 *
 * mat.vptr must be in vlen format to work correctly
 */
void get_mat_dist(Compute_data *computeData, struct Dist_data dist_data, SparseMatrix mat) {
	int i, j;
        struct Dist_data dist_data_aux;

#ifdef DEBUG
        if(dist_data.myId == ROOT) printf("Distribuyendo vptr\n");
#endif
        CreateInts (&computeData->dist_rows, dist_data.numP);
        CreateInts (&computeData->displs_rows, dist_data.numP);
        CreateInts (&computeData->dist_elem, dist_data.numP*2);
        computeData->displs_elem = computeData->dist_elem + dist_data.numP;

        InitInts (computeData->dist_rows, dist_data.numP, 0, 0);
        InitInts (computeData->displs_rows, dist_data.numP, 0, 0);
        InitInts (computeData->dist_elem, dist_data.numP*2, 0, 0);

	// Fill dist_rows and dist_elem so each process can make ScatterV or GatherV calls
        for(i=0; i<dist_data.numP; i++) {
          get_dist(computeData->n, i, dist_data.numP, &dist_data_aux);

          computeData->dist_rows[i] = dist_data_aux.tamBl;
          computeData->dist_elem[i] = mat.vptr[dist_data_aux.fin] - mat.vptr[dist_data_aux.ini];

          // Fill displacements
          if(i!=0) { 
            computeData->displs_elem[i] = computeData->displs_elem[i-1] + computeData->dist_elem[i-1];
            computeData->displs_rows[i] = computeData->displs_rows[i-1] + computeData->dist_rows[i-1];
          }
        }

#ifdef DEBUG
        printf("Proc %d almacena %d filas con %d elementos\n", dist_data.myId, computeData->dist_rows[dist_data.myId], computeData->dist_elem[dist_data.myId]);
        fflush(stdout);
#endif
}

/*
 * MPI Dist
 * Get the rows distribution of n rows in a given number of processes
 */
void get_rows_dist(Compute_data *computeData, int numP, int n) {
	int i, j;
        struct Dist_data dist_data;

        CreateInts (&(computeData->dist_rows), numP);
        CreateInts (&(computeData->displs_rows), numP);

        InitInts (computeData->dist_rows, numP, 0, 0);
        InitInts (computeData->displs_rows, numP, 0, 0);

	// Fill dist_rows and dist_elem so each process can make ScatterV or GatherV calls
        for(i=0; i<numP; i++) {
          get_dist(n, i, numP, &dist_data);

          computeData->dist_rows[i] = dist_data.tamBl;

          // Fill displacements
          if(i!=0) { 
            computeData->displs_rows[i] = computeData->displs_rows[i-1] + computeData->dist_rows[i-1];
          }
        }
}

/*
 * Matrix allocation
 *
 * The matrix that each process will use is allocated and
 * their vptr array initialised.
 *
 * MPI Dist
 * Distribute vpos and vvalues data among processes
 * Both arrays have the same distribution
 */
void mat_alloc(Compute_data *computeData, SparseMatrix mat, struct Dist_data dist_data) {
	int i;
	int elems; // Number of elements this process has
#ifdef DEBUG
        if(dist_data.myId == ROOT) printf("Distribuyendo vpos y vvalue\n");
#endif

	// dist_rows[myId] is the number of rows, n the number of columns, and dist_elem[myId] is the number of elements this process will have in the matrix
        CreateSparseMatrixVptr(&(computeData->subm), dist_data.tamBl, computeData->n, 0);
        computeData->subm.vptr[0] = 0;

        MPI_Scatterv((mat.vptr)+1, computeData->dist_rows, computeData->displs_rows, MPI_INT, (computeData->subm.vptr)+1, dist_data.tamBl, MPI_INT, ROOT, MPI_COMM_WORLD);

271
272
273
274
        CreateInts(&(computeData->vlen), dist_data.tamBl+1);
        for(i=0; i<dist_data.tamBl+1; i++) {
          computeData->vlen[i] = computeData->subm.vptr[i];
        }
iker_martin's avatar
iker_martin committed
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
        TransformLengthtoHeader(computeData->subm.vptr, computeData->subm.dim1); // The array is converted from vlen to vptr
        elems = computeData->subm.vptr[dist_data.tamBl];
        CreateSparseMatrixValues(&(computeData->subm), dist_data.tamBl, computeData->n, elems, 0);

        MPI_Scatterv(mat.vpos, computeData->dist_elem, computeData->displs_elem, MPI_INT,    computeData->subm.vpos, elems, MPI_INT,    ROOT, MPI_COMM_WORLD);
        MPI_Scatterv(mat.vval, computeData->dist_elem, computeData->displs_elem, MPI_DOUBLE, computeData->subm.vval, elems, MPI_DOUBLE, ROOT, MPI_COMM_WORLD);

	// Free elem arrays, as they are not going to be used again
        RemoveInts (&computeData->dist_elem);
}

/*
 * Compute solution
 */
void computeSolution(Compute_data computeData, double **subsol, SparseMatrix mat, int myId, double **full_vec) {
        
	CreateDoubles (subsol, computeData.dist_rows[myId]);
	InitDoubles (*subsol, computeData.dist_rows[myId], 0.0, 0.0);
	CreateDoubles(full_vec, computeData.n);
	InitDoubles (*full_vec, computeData.n, 1.0, 0.0);

//Compute SOLUTION
#ifdef ONLY_SYM
	ProdSymSparseMatrixVector (computeData.subm, *full_vec, *subsol);                  // sol += A * x
#else
	ProdSparseMatrixVector (computeData.subm, *full_vec, *subsol);                    	// sol += A * x
#endif
/*
#ifdef DEBUG
	int aux, i;
	double *solD = NULL, *sol = NULL;
	if(myId == ROOT) {
          printf("Computing solution\n");
	  CreateDoubles (&sol, computeData.n);
	  CreateDoubles (&solD, computeData.n);
	  InitDoubles (sol, computeData.n, 0.0, 0.0);
	  InitDoubles (solD, computeData.n, 0.0, 0.0);

          TransformLengthtoHeader(mat.vptr, mat.dim1); // vlen to vptr (At mat_alloc was needed as vlen)
        }

	MPI_Gatherv(*subsol, computeData.dist_rows[myId], MPI_DOUBLE, sol, computeData.dist_rows, computeData.displs_rows, MPI_DOUBLE, ROOT, MPI_COMM_WORLD);

        if(myId == ROOT) {

#ifdef ONLY_SYM
	  ProdSymSparseMatrixVector (mat, *full_vec, solD);                   // solD += A * x
#else
	  ProdSparseMatrixVector (mat, *full_vec, solD);                      // solD += A * x
#endif // ONLY_SIM
          aux = 1;
          printf("Checking sol array is ok\n");
          for(i=0; i<mat.dim1; i++) {
            if(sol[i] != solD[i]) {
              printf("[%d]Expected %lf - Result %lf\n", i, solD[i],sol[i]);
              aux = 0;
            }
          }
          if(aux) printf("sol array is correct\n");
          
        }
	RemoveDoubles (&sol);
	RemoveDoubles (&solD);
#endif // DEBUG
*/
}

/*
 * Realiza los preparativos para pasar al bucle de computo principal
 * inicializando los datos y realizando una primera iteración
 */
void pre_compute(Compute_data *computeData, struct Dist_data dist_data, double *subsol, double *full_vec) {

	int IZERO = 0, IONE = 1; 
	double DONE = 1.0, DMONE = -1.0, DZERO = 0.0;

        if(dist_data.myId == ROOT) {
	  printf("Start CG\n");
        }

        computeData->res = NULL; computeData->z = NULL; computeData->d = NULL;
	computeData->umbral = 1.0e-8;

	CreateDoubles(&computeData->res, dist_data.tamBl); 
	CreateDoubles(&computeData->z, dist_data.tamBl); 
	CreateDoubles(&computeData->d, dist_data.tamBl);
	CreateDoubles (&computeData->vec, dist_data.tamBl);
	CreateDoubles (&computeData->d_full, computeData->n);

	InitDoubles (computeData->vec, dist_data.tamBl, DZERO, DZERO); // x = 0
	InitDoubles (full_vec, computeData->n, DZERO, DZERO); // full_x = 0
	
	computeData->iter = 0;

#ifdef ONLY_SYM
	ProdSymSparseMatrixVector (computeData->subm, full_vec, computeData->z);                     				// z += A * full_x
//	mkl_dcsrsymv ("U", &n, mat.vval, mat.vptr, mat.vpos, vec, z); 			   // z = A * full_x
#else
	ProdSparseMatrixVector (computeData->subm, full_vec, computeData->z);                       				// z += A * full_x
#endif
	dcopy (&(dist_data.tamBl), subsol, &IONE, computeData->res, &IONE);             					// res = b
	daxpy (&(dist_data.tamBl), &DMONE, computeData->z, &IONE, computeData->res, &IONE);           				// res -= z
	//dcopy (&(computeData.subm.dim1), computeData.res, &IONE, &(computeData.d+computeData.displs_rows[myId]), &IONE);      // d_full = res
        MPI_Allgatherv(computeData->res, dist_data.tamBl, MPI_DOUBLE, computeData->d_full, computeData->dist_rows, computeData->displs_rows, MPI_DOUBLE, MPI_COMM_WORLD);
	dcopy (&(dist_data.tamBl), &(computeData->d_full[dist_data.ini]), &IONE, computeData->d, &IONE);             		// d = d_full[ini] to d_full[ini+tamBl]
	computeData->beta = ddot (&(dist_data.tamBl), computeData->res, &IONE, computeData->res, &IONE);      			// beta = res' * res
        MPI_Allreduce(MPI_IN_PLACE, &computeData->beta, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);
	computeData->tol = sqrt (computeData->beta);                                          			   		// tol = sqrt(beta) = norm (res)
}

/*
 * Bucle de computo principal
 */
388
int compute(Compute_data *computeData, struct Dist_data *dist_data) {
iker_martin's avatar
iker_martin committed
389
390
391
392
	int IZERO = 0, IONE = 1; 
	double DONE = 1.0, DMONE = -1.0, DZERO = 0.0;

        int ended_loop = 1;
393
        int cnt = 0;
iker_martin's avatar
iker_martin committed
394
395
396
397
398

        computeData->maxiter = 1000;

	while ((computeData->iter < computeData->maxiter) && (computeData->tol > computeData->umbral)) {
	//while (computeData->tol > computeData->umbral) {
399
                if (computeData->iter == 3) { malleability_checkpoint(); }
iker_martin's avatar
iker_martin committed
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434

//		if(dist_data->myId == ROOT) printf ("(%d,%20.10e)\n", computeData->iter, computeData->tol);

//      	COMPUTATION
#ifdef ONLY_SYM
		ProdSymSparseMatrixVector (computeData->subm, computeData->d_full, computeData->z);                     // z += A * d_full
#else
		ProdSparseMatrixVector (computeData->subm, computeData->d_full, computeData->z);                    	// z += A * d_full
#endif
        	computeData->rho = ddot (&(dist_data->tamBl), computeData->d, &IONE, computeData->z, &IONE);		// rho = (d * z)
	        MPI_Allreduce(MPI_IN_PLACE, &computeData->rho, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);			// Reduce(rho, SUM)
		computeData->rho = computeData->beta / computeData->rho;                 		                // rho = beta / aux
		daxpy (&(dist_data->tamBl), &computeData->rho, computeData->d, &IONE, computeData->vec, &IONE);		// x += rho * d
		computeData->rho = -computeData->rho;
		daxpy (&(dist_data->tamBl), &computeData->rho, computeData->z, &IONE, computeData->res, &IONE);         // res -= rho * z
		computeData->alpha = computeData->beta;                                               		        // alpha = beta
		computeData->beta = ddot (&(dist_data->tamBl), computeData->res, &IONE, computeData->res, &IONE);       // beta = res' * res
	        MPI_Allreduce(MPI_IN_PLACE, &computeData->beta, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);		// Reduce(beta, SUM)
		computeData->alpha = computeData->beta / computeData->alpha;                                       	// alpha = beta / alpha
		dscal (&(dist_data->tamBl), &computeData->alpha, computeData->d, &IONE);                   		// d = alpha * d
		daxpy (&(dist_data->tamBl), &DONE, computeData->res, &IONE, computeData->d, &IONE);        		// d += res
	        MPI_Allgatherv(computeData->d, dist_data->tamBl, MPI_DOUBLE, computeData->d_full, 
				computeData->dist_rows, computeData->displs_rows, MPI_DOUBLE, MPI_COMM_WORLD);		// d_full = Gather(d)
		computeData->tol = sqrt (computeData->beta);                                          			// tol = sqrt(beta) = norm (res)
		computeData->iter++;

	}
#ifdef DEBUG
	if(dist_data->myId == ROOT) printf ("Ended loop\n");
#endif
	return ended_loop;
}


void free_computeData(Compute_data *computeData) {
435
	if(computeData->res != NULL) {
iker_martin's avatar
iker_martin committed
436
	RemoveDoubles (&computeData->res); 
437
438
	}
	if(computeData->z != NULL) {
iker_martin's avatar
iker_martin committed
439
        RemoveDoubles (&computeData->z); 
440
441
	}
	if(computeData->d != NULL) {
iker_martin's avatar
iker_martin committed
442
        RemoveDoubles (&computeData->d);
443
444
	}
	if(computeData->vec != NULL) {
iker_martin's avatar
iker_martin committed
445
	RemoveDoubles (&computeData->vec);
446
	}
iker_martin's avatar
iker_martin committed
447
448


449
450
451
452
	if(computeData->d_full != NULL) {
        RemoveDoubles (&computeData->d_full);
	}
	if(computeData->subm.vptr != NULL) {
iker_martin's avatar
iker_martin committed
453
	RemoveSparseMatrix2 (&computeData->subm);
454
455
456
	}

	if(computeData->dist_rows != NULL) {
iker_martin's avatar
iker_martin committed
457
        RemoveInts (&computeData->dist_rows);
458
459
	}
	if(computeData->displs_rows != NULL) {
iker_martin's avatar
iker_martin committed
460
        RemoveInts (&computeData->displs_rows);
461
462
	}
	if(computeData->vlen != NULL) {
iker_martin's avatar
iker_martin committed
463
        RemoveInts (&computeData->vlen);
464
	}
iker_martin's avatar
iker_martin committed
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
}

/*
 *  _____________________________________________________________________________________
 * ||                                                                                   ||
 * ||                                                                                   ||
 * ||                            DISTRIBUTION FUNCTIONS                                 ||
 * ||                                                                                   ||
 * ||                                                                                   ||
 * \_____________________________________________________________________________________/
*/

/*
 * Las siguientes funciones están todas relacionadas con la distribución de los datos
 * o procesos.
 */

/*
 * ========================================================================================
 * ========================================================================================
 * ========================PARENTS COMMUNICATION FUNCTIONS=================================
 * ========================================================================================
 * ========================================================================================
*/

/*
 */
492
493
494
495
496
int dist_old(struct Dist_data *dist_data, Compute_data *computeData, int num_children, int sm, int ss, int rm, int rs) {
    int phy_dist = 2;
    set_malleability_configuration(sm, ss, phy_dist, rm, rs);
    set_children_number(num_children);
    
iker_martin's avatar
iker_martin committed
497
    malleability_add_data(&(computeData->iter), 1, MAL_INT, 1, 1);
498
499
500
501
    //malleability_add_data(&(computeData->tol), 1, MAL_DOUBLE, 1, 1);
    //malleability_add_data(&(computeData->beta), 1, MAL_DOUBLE, 1, 1);
    //malleability_add_data(&(computeData->umbral), 1, MAL_DOUBLE, 1, 1);
/*
iker_martin's avatar
iker_martin committed
502
503
504
505
506
507
508
509
    malleability_add_data(&(computeData->vec), computeData->n, MAL_DOUBLE, 0, 1);
    malleability_add_data(&(computeData->res), computeData->n, MAL_DOUBLE, 0, 1);
    malleability_add_data(&(computeData->z), computeData->n, MAL_DOUBLE, 0, 1);
    malleability_add_data(&(computeData->d_full), computeData->n, MAL_DOUBLE, 1, 1);

    malleability_add_data(&(computeData->vlen), computeData->n, MAL_INT, 1, 1); //FIXME Ultimo valor puede sere asinc
    malleability_add_data(&(computeData->subm.vpos), computeData->n, MAL_INT, 1, 1);
    malleability_add_data(&(computeData->subm.vval), computeData->n, MAL_DOUBLE, 1, 1);
510
    */
iker_martin's avatar
iker_martin committed
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
}

/*
    MPI_Bcast(computeData->d_full, computeData->n, MPI_DOUBLE, rootBcast, dist_data.comm_children);
    MPI_Alltoallv(computeData->res, sendcounts, sdispls, dist_data.arrays, NULL, recvcounts, rdispls, MPI_INT, dist_data.comm_children);
    */

void send_matrix(struct Dist_data dist_data, Compute_data computeData, int rootBcast, int numP_child, int idI, int idE,
                 int *sendcounts, int *recvcounts,int *sdispls, int *rdispls) {
    int i;

    TransformHeadertoLength(computeData.subm.vptr, computeData.subm.dim1); // De vptr a vlen
    // Distribuir vlen con los hijos
    MPI_Alltoallv(computeData.subm.vptr+1, sendcounts, sdispls, MPI_INT, NULL, recvcounts, rdispls, MPI_INT, dist_data.comm_children);
    TransformLengthtoHeader(computeData.subm.vptr, computeData.subm.dim1); // De vlen a vptr

    // Calcular cuantos elementos se van a enviar a cada proceso hijo
    if(idI == 0 && sendcounts[0] > 0) {    
      sendcounts[0] = computeData.subm.vptr[sdispls[0] + sendcounts[0]] - computeData.subm.vptr[sdispls[0]];
      idI++;
    }
    for(i=idI; i<idE; i++) {
      if(sendcounts[i] > 0) {    
        sendcounts[i] = computeData.subm.vptr[sdispls[i] + sendcounts[i]] - computeData.subm.vptr[sdispls[i]];
      }
      sdispls[i] = sdispls[i-1] + sendcounts[i-1];
    }
    //print_counts(dist_data, sendcounts, sdispls, numP_child, "Send");

    /* COMUNICACION DE DATOS */
    MPI_Alltoallv(computeData.subm.vpos, sendcounts, sdispls, MPI_INT, NULL, recvcounts, rdispls, MPI_INT, dist_data.comm_children);
    MPI_Alltoallv(computeData.subm.vval, sendcounts, sdispls, MPI_DOUBLE, NULL, recvcounts, rdispls, MPI_DOUBLE, dist_data.comm_children);
}

/*
 * ========================================================================================
 * ========================================================================================
 * ========================CHILDREN COMMUNICATION FUNCTIONS================================
 * ========================================================================================
 * ========================================================================================
*/

/*
 * Función llamada por un set de procesos hijos.
 *
 * Primero los hijos obtienen de los padres una información iniciar 
 * con la que conocer el tamaño de sus vectores y matriz, como asi 
 * tambien cuantos datos van a recibir de cada padre.
 *
 * Tras esto se preparan para recibir los datos de los padres.
 *
 */
void dist_new(struct Dist_data *dist_data, Compute_data *computeData) {
    void *value = NULL;
    malleability_get_data(&value, 0, 1, 1);
    computeData->iter = *((int *)value);
567
   /* malleability_get_data(&value, 1, 1, 1);
iker_martin's avatar
iker_martin committed
568
569
570
571
572
    computeData->tol = *((double *)value);
    malleability_get_data(&value, 2, 1, 1);
    computeData->beta = *((double *)value);
    malleability_get_data(&value, 3, 1, 1);
    computeData->umbral = *((double *)value);
573
574
*/
    /*
iker_martin's avatar
iker_martin committed
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
    malleability_get_data(&value, 0, 0, 1);
    computeData->vec = ((double *)value);
    malleability_get_data(&value, 1, 0, 1);
    computeData->res = ((double *)value);
    malleability_get_data(&value, 2, 0, 1);
    computeData->z = ((double *)value);
    malleability_get_data(&value, 4, 1, 1);
    computeData->d_full = ((double *)value);

    malleability_get_data(&value, 5, 1, 1);
    computeData->subm.vptr = ((int *)value);
    malleability_get_data(&value, 6, 1, 1);
    computeData->subm.vpos = ((int *)value);
    malleability_get_data(&value, 7, 1, 1);
    computeData->subm.vval = ((double *)value);
    TransformLengthtoHeader(computeData->subm.vptr, computeData->subm.dim1); // De vlen a vptr
591
    */
iker_martin's avatar
iker_martin committed
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
}

/*
    MPI_Bcast(computeData->d_full, computeData->n, MPI_DOUBLE, ROOT, dist_data->comm_parents); // Recibir vectores RES y D_FULL
    MPI_Alltoallv(aux, sendcounts, sdispls, MPI_INT, computeData->res, recvcounts, rdispls, dist_data->arrays, dist_data->comm_parents);
    dcopy (&(dist_data->tamBl), &(computeData->d_full[dist_data->ini]), &IONE, computeData->d, &IONE); // Copia parcial de D_FULL a D
*/

void recv_matrix(struct Dist_data *dist_data, Compute_data *computeData, int idI, int idE,
                 int *sendcounts, int *recvcounts,int *sdispls, int *rdispls) {
    int i;
    double *aux;
    int *aux_int, elems;
    Compute_data dist_parents;

    /* PREPARAR DATOS DE RECEPCION SOBRE MATRIZ */
    get_rows_dist(&dist_parents, dist_data->numP_parents, computeData->n);

    get_rows_dist(computeData, dist_data->numP, computeData->n);
    CreateSparseMatrixVptr(&(computeData->subm), dist_data->tamBl, computeData->n, 0);

    MPI_Alltoallv(aux_int, sendcounts, sdispls, MPI_INT, (computeData->subm.vptr)+1, recvcounts, rdispls, MPI_INT, dist_data->comm_parents);

    TransformLengthtoHeader(computeData->subm.vptr, computeData->subm.dim1); // De vlen a vptr
    elems = computeData->subm.vptr[dist_data->tamBl];
    CreateSparseMatrixValues(&(computeData->subm), dist_data->tamBl, computeData->n, elems, 0);

    // Calcular cuantos elementos se van a recibir de cada proceso padre
    if(idI == 0 && recvcounts[0] > 0) {    
      recvcounts[0] = computeData->subm.vptr[rdispls[0] + recvcounts[0]] - computeData->subm.vptr[rdispls[0]];
      idI++;
    }
    for(i=idI; i<idE; i++) {
      if(recvcounts[i] > 0) {    
        recvcounts[i] = computeData->subm.vptr[rdispls[i] + recvcounts[i]] - computeData->subm.vptr[rdispls[i]];
      }
      rdispls[i] = rdispls[i-1] + recvcounts[i-1];
    }
    //print_counts(*dist_data, recvcounts, rdispls, numP_parents, "Recv");

    /* COMUNICACION DE DATOS */
    MPI_Alltoallv(aux_int, sendcounts, sdispls, MPI_INT, computeData->subm.vpos, recvcounts, rdispls, MPI_INT, dist_data->comm_parents);
    MPI_Alltoallv(aux, sendcounts, sdispls, MPI_DOUBLE, computeData->subm.vval, recvcounts, rdispls, MPI_DOUBLE, dist_data->comm_parents);

    free(dist_parents.dist_rows);
    free(dist_parents.displs_rows);
}

/*
 * ========================================================================================
 * ========================================================================================
 * ================================DISTRIBUTION FUNCTIONS==================================
 * ========================================================================================
 * ========================================================================================
*/

/*
 * Obtiene para el Id que se pasa junto a su
 * numero de procesos total, con cuantas filas (tamBl),
 * elementos por fila, y total de filas (fin - ini)
 * con las que va a trabajar el proceso
 */
void get_dist(int total_r, int id, int numP, struct Dist_data *dist_data) {
  int rem;

  dist_data->tot_r = total_r;
  dist_data->tamBl = total_r / numP;
  rem = total_r % numP;

  if(id < rem) { // First subgroup
    dist_data->ini = id * dist_data->tamBl + id;
    dist_data->fin = (id+1) * dist_data->tamBl + (id+1);
  } else { // Second subgroup
    dist_data->ini = id * dist_data->tamBl + rem;
    dist_data->fin = (id+1) * dist_data->tamBl + rem;
  }
  
  if(dist_data->fin > total_r) {
    dist_data->fin = total_r;
  }
  if(dist_data->ini > dist_data->fin) {
    dist_data->ini = dist_data->fin;
  }

  dist_data->tamBl = dist_data->fin - dist_data->ini;
}

/*
 * Obtiene para un Id de proceso, cuantos elementos va 
 * a enviar/recibir el proceso myId
 */
void set_counts(int id, int numP, struct Dist_data data_dist, int *sendcounts) {
  struct Dist_data other;
  int biggest_ini, smallest_end, tot_rows;

  get_dist(data_dist.tot_r, id, numP, &other);

  // Si el rango de valores no coincide, se pasa al siguiente proceso
  if(data_dist.ini >= other.fin || data_dist.fin <= other.ini) {
    return;
  }

  // Obtiene el proceso con mayor ini entre los dos procesos
  if(data_dist.ini > other.ini) { 
    biggest_ini = data_dist.ini;
  } else {
    biggest_ini = other.ini;
  }

  // Obtiene el proceso con menor fin entre los dos procesos
  if(data_dist.fin < other.fin) {
    smallest_end = data_dist.fin;
  } else {
    smallest_end = other.fin;
  }
  sendcounts[id] = smallest_end - biggest_ini; // Numero de elementos a enviar/recibir del proceso Id
}

/*
 * Obtiene para un proceso de un grupo a que rango procesos de 
 * otro grupo tiene que enviar o recibir datos.
 *
 * Devuelve el primer identificador y el último (Excluido) con el que
 * comunicarse.
 */
void getIds_intercomm(struct Dist_data dist_data, int numP_other, int **idS) {
    int idI, idE;
    int tamOther = dist_data.tot_r / numP_other;
    int remOther = dist_data.tot_r % numP_other;
    int middle = (tamOther + 1) * remOther;

    if(middle > dist_data.ini) { // First subgroup
      idI = dist_data.ini / (tamOther + 1);
    } else { // Second subgroup
      idI = ((dist_data.ini - middle) / tamOther) + remOther;
    }

    if(middle >= dist_data.fin) { // First subgroup
      idE = dist_data.fin / (tamOther + 1);
      idE = (dist_data.fin % (tamOther + 1) > 0 && idE+1 <= numP_other) ? idE+1 : idE;
    } else { // Second subgroup
      idE = ((dist_data.fin - middle) / tamOther) + remOther;
      idE = ((dist_data.fin - middle) % tamOther > 0 && idE+1 <= numP_other) ? idE+1 : idE;
    }

    //free(*idS);
    CreateInts(idS, 2);
    (*idS)[0] = idI;
    (*idS)[1] = idE;
}

/*
 
	  double starttime, endtime, total, res;
          MPI_Barrier(MPI_COMM_WORLD);
	  starttime = MPI_Wtime();
	  endtime = MPI_Wtime();
          total = endtime - starttime;
          MPI_Reduce(&total, &res, 1, MPI_DOUBLE, MPI_MAX, ROOT, MPI_COMM_WORLD);
          if(dist_data.myId == ROOT) {printf("Tiempo BCAST PADRE %f\n", total); fflush(stdout);}
 */