1 #ifndef lint 2 static char vcid[] = "$Id: mpiaij.c,v 1.34 1995/04/28 05:14:26 curfman Exp bsmith $"; 3 #endif 4 5 #include "mpiaij.h" 6 #include "vec/vecimpl.h" 7 #include "inline/spops.h" 8 9 #define CHUNCKSIZE 100 10 /* 11 This is a simple minded stash. Do a linear search to determine if 12 in stash, if not add to end. 13 */ 14 static int StashValues(Stash *stash,int row,int n, int *idxn, 15 Scalar *values,InsertMode addv) 16 { 17 int i,j,N = stash->n,found,*n_idx, *n_idy; 18 Scalar val,*n_array; 19 20 for ( i=0; i<n; i++ ) { 21 found = 0; 22 val = *values++; 23 for ( j=0; j<N; j++ ) { 24 if ( stash->idx[j] == row && stash->idy[j] == idxn[i]) { 25 /* found a match */ 26 if (addv == AddValues) stash->array[j] += val; 27 else stash->array[j] = val; 28 found = 1; 29 break; 30 } 31 } 32 if (!found) { /* not found so add to end */ 33 if ( stash->n == stash->nmax ) { 34 /* allocate a larger stash */ 35 n_array = (Scalar *) MALLOC( (stash->nmax + CHUNCKSIZE)*( 36 2*sizeof(int) + sizeof(Scalar))); 37 CHKPTR(n_array); 38 n_idx = (int *) (n_array + stash->nmax + CHUNCKSIZE); 39 n_idy = (int *) (n_idx + stash->nmax + CHUNCKSIZE); 40 MEMCPY(n_array,stash->array,stash->nmax*sizeof(Scalar)); 41 MEMCPY(n_idx,stash->idx,stash->nmax*sizeof(int)); 42 MEMCPY(n_idy,stash->idy,stash->nmax*sizeof(int)); 43 if (stash->array) FREE(stash->array); 44 stash->array = n_array; stash->idx = n_idx; stash->idy = n_idy; 45 stash->nmax += CHUNCKSIZE; 46 } 47 stash->array[stash->n] = val; 48 stash->idx[stash->n] = row; 49 stash->idy[stash->n++] = idxn[i]; 50 } 51 } 52 return 0; 53 } 54 55 /* local utility routine that creates a mapping from the global column 56 number to the local number in the off-diagonal part of the local 57 storage of the matrix. This is done in a non scable way since the 58 length of colmap equals the global matrix length. 59 */ 60 static int CreateColmap(Mat mat) 61 { 62 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 63 Mat_AIJ *B = (Mat_AIJ*) aij->B->data; 64 int n = B->n,i; 65 aij->colmap = (int *) MALLOC( aij->N*sizeof(int) ); CHKPTR(aij->colmap); 66 MEMSET(aij->colmap,0,aij->N*sizeof(int)); 67 for ( i=0; i<n; i++ ) aij->colmap[aij->garray[i]] = i+1; 68 return 0; 69 } 70 71 static int MatSetValues_MPIAIJ(Mat mat,int m,int *idxm,int n, 72 int *idxn,Scalar *v,InsertMode addv) 73 { 74 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 75 int ierr,i,j, rstart = aij->rstart, rend = aij->rend; 76 int cstart = aij->cstart, cend = aij->cend,row,col; 77 78 if (aij->insertmode != NotSetValues && aij->insertmode != addv) { 79 SETERR(1,"You cannot mix inserts and adds"); 80 } 81 aij->insertmode = addv; 82 for ( i=0; i<m; i++ ) { 83 if (idxm[i] < 0) SETERR(1,"Negative row index"); 84 if (idxm[i] >= aij->M) SETERR(1,"Row index too large"); 85 if (idxm[i] >= rstart && idxm[i] < rend) { 86 row = idxm[i] - rstart; 87 for ( j=0; j<n; j++ ) { 88 if (idxn[j] < 0) SETERR(1,"Negative column index"); 89 if (idxn[j] >= aij->N) SETERR(1,"Column index too large"); 90 if (idxn[j] >= cstart && idxn[j] < cend){ 91 col = idxn[j] - cstart; 92 ierr = MatSetValues(aij->A,1,&row,1,&col,v+i*n+j,addv);CHKERR(ierr); 93 } 94 else { 95 if (aij->assembled) { 96 if (!aij->colmap) {ierr = CreateColmap(mat); CHKERR(ierr);} 97 col = aij->colmap[idxn[j]] - 1; 98 if (col < 0) { 99 SETERR(1,"Cannot insert new off diagonal block nonzero in\ 100 already\ 101 assembled matrix. Contact petsc-maint@mcs.anl.gov\ 102 if your need this feature"); 103 } 104 } 105 else col = idxn[j]; 106 ierr = MatSetValues(aij->B,1,&row,1,&col,v+i*n+j,addv);CHKERR(ierr); 107 } 108 } 109 } 110 else { 111 ierr = StashValues(&aij->stash,idxm[i],n,idxn,v+i*n,addv);CHKERR(ierr); 112 } 113 } 114 return 0; 115 } 116 117 /* 118 the assembly code is alot like the code for vectors, we should 119 sometime derive a single assembly code that can be used for 120 either case. 121 */ 122 123 static int MatAssemblyBegin_MPIAIJ(Mat mat,int mode) 124 { 125 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 126 MPI_Comm comm = mat->comm; 127 int numtids = aij->numtids, *owners = aij->rowners; 128 int mytid = aij->mytid; 129 MPI_Request *send_waits,*recv_waits; 130 int *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work; 131 int tag = 50, *owner,*starts,count; 132 InsertMode addv; 133 Scalar *rvalues,*svalues; 134 135 /* make sure all processors are either in INSERTMODE or ADDMODE */ 136 MPI_Allreduce((void *) &aij->insertmode,(void *) &addv,1,MPI_INT, 137 MPI_BOR,comm); 138 if (addv == (AddValues|InsertValues)) { 139 SETERR(1,"Some processors have inserted while others have added"); 140 } 141 aij->insertmode = addv; /* in case this processor had no cache */ 142 143 /* first count number of contributors to each processor */ 144 nprocs = (int *) MALLOC( 2*numtids*sizeof(int) ); CHKPTR(nprocs); 145 MEMSET(nprocs,0,2*numtids*sizeof(int)); procs = nprocs + numtids; 146 owner = (int *) MALLOC( (aij->stash.n+1)*sizeof(int) ); CHKPTR(owner); 147 for ( i=0; i<aij->stash.n; i++ ) { 148 idx = aij->stash.idx[i]; 149 for ( j=0; j<numtids; j++ ) { 150 if (idx >= owners[j] && idx < owners[j+1]) { 151 nprocs[j]++; procs[j] = 1; owner[i] = j; break; 152 } 153 } 154 } 155 nsends = 0; for ( i=0; i<numtids; i++ ) { nsends += procs[i];} 156 157 /* inform other processors of number of messages and max length*/ 158 work = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(work); 159 MPI_Allreduce((void *) procs,(void *) work,numtids,MPI_INT,MPI_SUM,comm); 160 nreceives = work[mytid]; 161 MPI_Allreduce((void *) nprocs,(void *) work,numtids,MPI_INT,MPI_MAX,comm); 162 nmax = work[mytid]; 163 FREE(work); 164 165 /* post receives: 166 1) each message will consist of ordered pairs 167 (global index,value) we store the global index as a double 168 to simplify the message passing. 169 2) since we don't know how long each individual message is we 170 allocate the largest needed buffer for each receive. Potentially 171 this is a lot of wasted space. 172 173 174 This could be done better. 175 */ 176 rvalues = (Scalar *) MALLOC(3*(nreceives+1)*(nmax+1)*sizeof(Scalar)); 177 CHKPTR(rvalues); 178 recv_waits = (MPI_Request *) MALLOC((nreceives+1)*sizeof(MPI_Request)); 179 CHKPTR(recv_waits); 180 for ( i=0; i<nreceives; i++ ) { 181 MPI_Irecv((void *)(rvalues+3*nmax*i),3*nmax,MPI_SCALAR,MPI_ANY_SOURCE,tag, 182 comm,recv_waits+i); 183 } 184 185 /* do sends: 186 1) starts[i] gives the starting index in svalues for stuff going to 187 the ith processor 188 */ 189 svalues = (Scalar *) MALLOC( 3*(aij->stash.n+1)*sizeof(Scalar) ); 190 CHKPTR(svalues); 191 send_waits = (MPI_Request *) MALLOC( (nsends+1)*sizeof(MPI_Request)); 192 CHKPTR(send_waits); 193 starts = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(starts); 194 starts[0] = 0; 195 for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 196 for ( i=0; i<aij->stash.n; i++ ) { 197 svalues[3*starts[owner[i]]] = (Scalar) aij->stash.idx[i]; 198 svalues[3*starts[owner[i]]+1] = (Scalar) aij->stash.idy[i]; 199 svalues[3*(starts[owner[i]]++)+2] = aij->stash.array[i]; 200 } 201 FREE(owner); 202 starts[0] = 0; 203 for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 204 count = 0; 205 for ( i=0; i<numtids; i++ ) { 206 if (procs[i]) { 207 MPI_Isend((void*)(svalues+3*starts[i]),3*nprocs[i],MPI_SCALAR,i,tag, 208 comm,send_waits+count++); 209 } 210 } 211 FREE(starts); FREE(nprocs); 212 213 /* Free cache space */ 214 aij->stash.nmax = aij->stash.n = 0; 215 if (aij->stash.array){ FREE(aij->stash.array); aij->stash.array = 0;} 216 217 aij->svalues = svalues; aij->rvalues = rvalues; 218 aij->nsends = nsends; aij->nrecvs = nreceives; 219 aij->send_waits = send_waits; aij->recv_waits = recv_waits; 220 aij->rmax = nmax; 221 222 return 0; 223 } 224 extern int MatSetUpMultiply_MPIAIJ(Mat); 225 226 static int MatAssemblyEnd_MPIAIJ(Mat mat,int mode) 227 { 228 int ierr; 229 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 230 231 MPI_Status *send_status,recv_status; 232 int imdex,nrecvs = aij->nrecvs, count = nrecvs, i, n; 233 int row,col; 234 Scalar *values,val; 235 InsertMode addv = aij->insertmode; 236 237 /* wait on receives */ 238 while (count) { 239 MPI_Waitany(nrecvs,aij->recv_waits,&imdex,&recv_status); 240 /* unpack receives into our local space */ 241 values = aij->rvalues + 3*imdex*aij->rmax; 242 MPI_Get_count(&recv_status,MPI_SCALAR,&n); 243 n = n/3; 244 for ( i=0; i<n; i++ ) { 245 row = (int) PETSCREAL(values[3*i]) - aij->rstart; 246 col = (int) PETSCREAL(values[3*i+1]); 247 val = values[3*i+2]; 248 if (col >= aij->cstart && col < aij->cend) { 249 col -= aij->cstart; 250 MatSetValues(aij->A,1,&row,1,&col,&val,addv); 251 } 252 else { 253 if (aij->assembled) { 254 if (!aij->colmap) {ierr = CreateColmap(mat); CHKERR(ierr);} 255 col = aij->colmap[col] - 1; 256 if (col < 0) { 257 SETERR(1,"Cannot insert new off diagonal block nonzero in\ 258 already\ 259 assembled matrix. Contact petsc-maint@mcs.anl.gov\ 260 if your need this feature"); 261 } 262 } 263 MatSetValues(aij->B,1,&row,1,&col,&val,addv); 264 } 265 } 266 count--; 267 } 268 FREE(aij->recv_waits); FREE(aij->rvalues); 269 270 /* wait on sends */ 271 if (aij->nsends) { 272 send_status = (MPI_Status *) MALLOC( aij->nsends*sizeof(MPI_Status) ); 273 CHKPTR(send_status); 274 MPI_Waitall(aij->nsends,aij->send_waits,send_status); 275 FREE(send_status); 276 } 277 FREE(aij->send_waits); FREE(aij->svalues); 278 279 aij->insertmode = NotSetValues; 280 ierr = MatAssemblyBegin(aij->A,mode); CHKERR(ierr); 281 ierr = MatAssemblyEnd(aij->A,mode); CHKERR(ierr); 282 283 if (!aij->assembled && mode == FINAL_ASSEMBLY) { 284 ierr = MatSetUpMultiply_MPIAIJ(mat); CHKERR(ierr); 285 aij->assembled = 1; 286 } 287 ierr = MatAssemblyBegin(aij->B,mode); CHKERR(ierr); 288 ierr = MatAssemblyEnd(aij->B,mode); CHKERR(ierr); 289 290 return 0; 291 } 292 293 static int MatZeroEntries_MPIAIJ(Mat A) 294 { 295 Mat_MPIAIJ *l = (Mat_MPIAIJ *) A->data; 296 297 MatZeroEntries(l->A); MatZeroEntries(l->B); 298 return 0; 299 } 300 301 /* again this uses the same basic stratagy as in the assembly and 302 scatter create routines, we should try to do it systemamatically 303 if we can figure out the proper level of generality. */ 304 305 /* the code does not do the diagonal entries correctly unless the 306 matrix is square and the column and row owerships are identical. 307 This is a BUG. The only way to fix it seems to be to access 308 aij->A and aij->B directly and not through the MatZeroRows() 309 routine. 310 */ 311 static int MatZeroRows_MPIAIJ(Mat A,IS is,Scalar *diag) 312 { 313 Mat_MPIAIJ *l = (Mat_MPIAIJ *) A->data; 314 int i,ierr,N, *rows,*owners = l->rowners,numtids = l->numtids; 315 int *procs,*nprocs,j,found,idx,nsends,*work; 316 int nmax,*svalues,*starts,*owner,nrecvs,mytid = l->mytid; 317 int *rvalues,tag = 67,count,base,slen,n,*source; 318 int *lens,imdex,*lrows,*values; 319 MPI_Comm comm = A->comm; 320 MPI_Request *send_waits,*recv_waits; 321 MPI_Status recv_status,*send_status; 322 IS istmp; 323 324 if (!l->assembled) SETERR(1,"MatZeroRows_MPIAIJ: must assemble matrix first"); 325 ierr = ISGetLocalSize(is,&N); CHKERR(ierr); 326 ierr = ISGetIndices(is,&rows); CHKERR(ierr); 327 328 /* first count number of contributors to each processor */ 329 nprocs = (int *) MALLOC( 2*numtids*sizeof(int) ); CHKPTR(nprocs); 330 MEMSET(nprocs,0,2*numtids*sizeof(int)); procs = nprocs + numtids; 331 owner = (int *) MALLOC((N+1)*sizeof(int)); CHKPTR(owner); /* see note*/ 332 for ( i=0; i<N; i++ ) { 333 idx = rows[i]; 334 found = 0; 335 for ( j=0; j<numtids; j++ ) { 336 if (idx >= owners[j] && idx < owners[j+1]) { 337 nprocs[j]++; procs[j] = 1; owner[i] = j; found = 1; break; 338 } 339 } 340 if (!found) SETERR(1,"Imdex out of range"); 341 } 342 nsends = 0; for ( i=0; i<numtids; i++ ) { nsends += procs[i];} 343 344 /* inform other processors of number of messages and max length*/ 345 work = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(work); 346 MPI_Allreduce((void *) procs,(void *) work,numtids,MPI_INT,MPI_SUM,comm); 347 nrecvs = work[mytid]; 348 MPI_Allreduce((void *) nprocs,(void *) work,numtids,MPI_INT,MPI_MAX,comm); 349 nmax = work[mytid]; 350 FREE(work); 351 352 /* post receives: */ 353 rvalues = (int *) MALLOC((nrecvs+1)*(nmax+1)*sizeof(int)); /*see note */ 354 CHKPTR(rvalues); 355 recv_waits = (MPI_Request *) MALLOC((nrecvs+1)*sizeof(MPI_Request)); 356 CHKPTR(recv_waits); 357 for ( i=0; i<nrecvs; i++ ) { 358 MPI_Irecv((void *)(rvalues+nmax*i),nmax,MPI_INT,MPI_ANY_SOURCE,tag, 359 comm,recv_waits+i); 360 } 361 362 /* do sends: 363 1) starts[i] gives the starting index in svalues for stuff going to 364 the ith processor 365 */ 366 svalues = (int *) MALLOC( (N+1)*sizeof(int) ); CHKPTR(svalues); 367 send_waits = (MPI_Request *) MALLOC( (nsends+1)*sizeof(MPI_Request)); 368 CHKPTR(send_waits); 369 starts = (int *) MALLOC( (numtids+1)*sizeof(int) ); CHKPTR(starts); 370 starts[0] = 0; 371 for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 372 for ( i=0; i<N; i++ ) { 373 svalues[starts[owner[i]]++] = rows[i]; 374 } 375 ISRestoreIndices(is,&rows); 376 377 starts[0] = 0; 378 for ( i=1; i<numtids+1; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 379 count = 0; 380 for ( i=0; i<numtids; i++ ) { 381 if (procs[i]) { 382 MPI_Isend((void*)(svalues+starts[i]),nprocs[i],MPI_INT,i,tag, 383 comm,send_waits+count++); 384 } 385 } 386 FREE(starts); 387 388 base = owners[mytid]; 389 390 /* wait on receives */ 391 lens = (int *) MALLOC( 2*(nrecvs+1)*sizeof(int) ); CHKPTR(lens); 392 source = lens + nrecvs; 393 count = nrecvs; slen = 0; 394 while (count) { 395 MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status); 396 /* unpack receives into our local space */ 397 MPI_Get_count(&recv_status,MPI_INT,&n); 398 source[imdex] = recv_status.MPI_SOURCE; 399 lens[imdex] = n; 400 slen += n; 401 count--; 402 } 403 FREE(recv_waits); 404 405 /* move the data into the send scatter */ 406 lrows = (int *) MALLOC( slen*sizeof(int) ); CHKPTR(lrows); 407 count = 0; 408 for ( i=0; i<nrecvs; i++ ) { 409 values = rvalues + i*nmax; 410 for ( j=0; j<lens[i]; j++ ) { 411 lrows[count++] = values[j] - base; 412 } 413 } 414 FREE(rvalues); FREE(lens); 415 FREE(owner); FREE(nprocs); 416 417 /* actually zap the local rows */ 418 ierr = ISCreateSequential(MPI_COMM_SELF,slen,lrows,&istmp); 419 CHKERR(ierr); FREE(lrows); 420 ierr = MatZeroRows(l->A,istmp,diag); CHKERR(ierr); 421 ierr = MatZeroRows(l->B,istmp,0); CHKERR(ierr); 422 ierr = ISDestroy(istmp); CHKERR(ierr); 423 424 /* wait on sends */ 425 if (nsends) { 426 send_status = (MPI_Status *) MALLOC( nsends*sizeof(MPI_Status) ); 427 CHKPTR(send_status); 428 MPI_Waitall(nsends,send_waits,send_status); 429 FREE(send_status); 430 } 431 FREE(send_waits); FREE(svalues); 432 433 434 return 0; 435 } 436 437 static int MatMult_MPIAIJ(Mat aijin,Vec xx,Vec yy) 438 { 439 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 440 int ierr; 441 if (!aij->assembled) SETERR(1,"MatMult_MPIAIJ: must assemble matrix first"); 442 ierr = VecScatterBegin(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx); 443 CHKERR(ierr); 444 ierr = MatMult(aij->A,xx,yy); CHKERR(ierr); 445 ierr = VecScatterEnd(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx); 446 CHKERR(ierr); 447 ierr = MatMultAdd(aij->B,aij->lvec,yy,yy); CHKERR(ierr); 448 return 0; 449 } 450 451 static int MatMultAdd_MPIAIJ(Mat aijin,Vec xx,Vec yy,Vec zz) 452 { 453 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 454 int ierr; 455 if (!aij->assembled) SETERR(1,"MatMult_MPIAIJ: must assemble matrix first"); 456 ierr = VecScatterBegin(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx); 457 CHKERR(ierr); 458 ierr = MatMultAdd(aij->A,xx,yy,zz); CHKERR(ierr); 459 ierr = VecScatterEnd(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx); 460 CHKERR(ierr); 461 ierr = MatMultAdd(aij->B,aij->lvec,zz,zz); CHKERR(ierr); 462 return 0; 463 } 464 465 static int MatMultTrans_MPIAIJ(Mat aijin,Vec xx,Vec yy) 466 { 467 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 468 int ierr; 469 470 if (!aij->assembled) 471 SETERR(1,"MatMulTrans_MPIAIJ: must assemble matrix first"); 472 /* do nondiagonal part */ 473 ierr = MatMultTrans(aij->B,xx,aij->lvec); CHKERR(ierr); 474 /* send it on its way */ 475 ierr = VecScatterBegin(aij->lvec,0,yy,0,AddValues, 476 ScatterAll|ScatterReverse,aij->Mvctx); CHKERR(ierr); 477 /* do local part */ 478 ierr = MatMultTrans(aij->A,xx,yy); CHKERR(ierr); 479 /* receive remote parts: note this assumes the values are not actually */ 480 /* inserted in yy until the next line, which is true for my implementation*/ 481 /* but is not perhaps always true. */ 482 ierr = VecScatterEnd(aij->lvec,0,yy,0,AddValues,ScatterAll|ScatterReverse, 483 aij->Mvctx); CHKERR(ierr); 484 return 0; 485 } 486 487 static int MatMultTransAdd_MPIAIJ(Mat aijin,Vec xx,Vec yy,Vec zz) 488 { 489 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 490 int ierr; 491 492 if (!aij->assembled) 493 SETERR(1,"MatMulTransAdd_MPIAIJ: must assemble matrix first"); 494 /* do nondiagonal part */ 495 ierr = MatMultTrans(aij->B,xx,aij->lvec); CHKERR(ierr); 496 /* send it on its way */ 497 ierr = VecScatterBegin(aij->lvec,0,zz,0,AddValues, 498 ScatterAll|ScatterReverse,aij->Mvctx); CHKERR(ierr); 499 /* do local part */ 500 ierr = MatMultTransAdd(aij->A,xx,yy,zz); CHKERR(ierr); 501 /* receive remote parts: note this assumes the values are not actually */ 502 /* inserted in yy until the next line, which is true for my implementation*/ 503 /* but is not perhaps always true. */ 504 ierr = VecScatterEnd(aij->lvec,0,zz,0,AddValues,ScatterAll|ScatterReverse, 505 aij->Mvctx); CHKERR(ierr); 506 return 0; 507 } 508 509 /* 510 This only works correctly for square matrices where the subblock A->A is the 511 diagonal block 512 */ 513 static int MatGetDiagonal_MPIAIJ(Mat Ain,Vec v) 514 { 515 Mat_MPIAIJ *A = (Mat_MPIAIJ *) Ain->data; 516 if (!A->assembled) SETERR(1,"MatGetDiag_MPIAIJ: must assemble matrix first"); 517 return MatGetDiagonal(A->A,v); 518 } 519 520 static int MatDestroy_MPIAIJ(PetscObject obj) 521 { 522 Mat mat = (Mat) obj; 523 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 524 int ierr; 525 #if defined(PETSC_LOG) 526 PLogObjectState(obj,"Rows %d Cols %d",aij->M,aij->N); 527 #endif 528 FREE(aij->rowners); 529 ierr = MatDestroy(aij->A); CHKERR(ierr); 530 ierr = MatDestroy(aij->B); CHKERR(ierr); 531 if (aij->colmap) FREE(aij->colmap); 532 if (aij->garray) FREE(aij->garray); 533 if (aij->lvec) VecDestroy(aij->lvec); 534 if (aij->Mvctx) VecScatterCtxDestroy(aij->Mvctx); 535 FREE(aij); 536 PLogObjectDestroy(mat); 537 PETSCHEADERDESTROY(mat); 538 return 0; 539 } 540 #include "draw.h" 541 #include "pviewer.h" 542 543 static int MatView_MPIAIJ(PetscObject obj,Viewer viewer) 544 { 545 Mat mat = (Mat) obj; 546 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 547 int ierr; 548 PetscObject vobj = (PetscObject) viewer; 549 550 if (!aij->assembled) SETERR(1,"MatView_MPIAIJ: must assemble matrix first"); 551 if (!viewer) { /* so that viewers may be used from debuggers */ 552 viewer = STDOUT_VIEWER; vobj = (PetscObject) viewer; 553 } 554 if (vobj->cookie == DRAW_COOKIE && vobj->type == NULLWINDOW) return 0; 555 if (vobj->cookie == VIEWER_COOKIE && vobj->type == FILE_VIEWER) { 556 FILE *fd = ViewerFileGetPointer_Private(viewer); 557 MPE_Seq_begin(mat->comm,1); 558 fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n", 559 aij->mytid,aij->m,aij->rstart,aij->rend,aij->n,aij->cstart, 560 aij->cend); 561 ierr = MatView(aij->A,viewer); CHKERR(ierr); 562 ierr = MatView(aij->B,viewer); CHKERR(ierr); 563 fflush(fd); 564 MPE_Seq_end(mat->comm,1); 565 } 566 else if ((vobj->cookie == VIEWER_COOKIE && vobj->type == FILES_VIEWER) || 567 vobj->cookie == DRAW_COOKIE) { 568 int numtids = aij->numtids, mytid = aij->mytid; 569 if (numtids == 1) { 570 ierr = MatView(aij->A,viewer); CHKERR(ierr); 571 } 572 else { 573 /* assemble the entire matrix onto first processor. */ 574 Mat A; 575 Mat_AIJ *Aloc; 576 int M = aij->M, N = aij->N,m,*ai,*aj,row,*cols,i,*ct; 577 Scalar *a; 578 579 if (!mytid) { 580 ierr = MatCreateMPIAIJ(mat->comm,M,N,M,N,0,0,0,0,&A); 581 } 582 else { 583 ierr = MatCreateMPIAIJ(mat->comm,0,0,M,N,0,0,0,0,&A); 584 } 585 CHKERR(ierr); 586 587 /* copy over the A part */ 588 Aloc = (Mat_AIJ*) aij->A->data; 589 m = Aloc->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 590 row = aij->rstart; 591 for ( i=0; i<ai[m]; i++ ) {aj[i] += aij->cstart - 1;} 592 for ( i=0; i<m; i++ ) { 593 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,InsertValues); 594 CHKERR(ierr); 595 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 596 } 597 aj = Aloc->j; 598 for ( i=0; i<ai[m]; i++ ) {aj[i] -= aij->cstart - 1;} 599 600 /* copy over the B part */ 601 Aloc = (Mat_AIJ*) aij->B->data; 602 m = Aloc->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 603 row = aij->rstart; 604 ct = cols = (int *) MALLOC( (ai[m]+1)*sizeof(int) ); CHKPTR(cols); 605 for ( i=0; i<ai[m]; i++ ) {cols[i] = aij->garray[aj[i]-1];} 606 for ( i=0; i<m; i++ ) { 607 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,InsertValues); 608 CHKERR(ierr); 609 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 610 } 611 FREE(ct); 612 ierr = MatAssemblyBegin(A,FINAL_ASSEMBLY); CHKERR(ierr); 613 ierr = MatAssemblyEnd(A,FINAL_ASSEMBLY); CHKERR(ierr); 614 if (!mytid) { 615 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,viewer); CHKERR(ierr); 616 } 617 ierr = MatDestroy(A); CHKERR(ierr); 618 } 619 } 620 return 0; 621 } 622 623 extern int MatMarkDiag_AIJ(Mat_AIJ *); 624 /* 625 This has to provide several versions. 626 627 1) per sequential 628 2) a) use only local smoothing updating outer values only once. 629 b) local smoothing updating outer values each inner iteration 630 3) color updating out values betwen colors. 631 */ 632 static int MatRelax_MPIAIJ(Mat matin,Vec bb,double omega,int flag,double shift, 633 int its,Vec xx) 634 { 635 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 636 Mat AA = mat->A, BB = mat->B; 637 Mat_AIJ *A = (Mat_AIJ *) AA->data, *B = (Mat_AIJ *)BB->data; 638 Scalar zero = 0.0,*b,*x,*xs,*ls,d,*v,sum,scale,*t,*ts; 639 int ierr,*idx, *diag; 640 int n = mat->n, m = mat->m, i; 641 Vec tt; 642 643 if (!mat->assembled) SETERR(1,"MatRelax_MPIAIJ: must assemble matrix first"); 644 645 VecGetArray(xx,&x); VecGetArray(bb,&b); VecGetArray(mat->lvec,&ls); 646 xs = x -1; /* shift by one for index start of 1 */ 647 ls--; 648 if (!A->diag) {if ((ierr = MatMarkDiag_AIJ(A))) return ierr;} 649 diag = A->diag; 650 if (flag == SOR_APPLY_UPPER || flag == SOR_APPLY_LOWER) { 651 SETERR(1,"That option not yet support for parallel AIJ matrices"); 652 } 653 if (flag & SOR_EISENSTAT) { 654 /* Let A = L + U + D; where L is lower trianglar, 655 U is upper triangular, E is diagonal; This routine applies 656 657 (L + E)^{-1} A (U + E)^{-1} 658 659 to a vector efficiently using Eisenstat's trick. This is for 660 the case of SSOR preconditioner, so E is D/omega where omega 661 is the relaxation factor. 662 */ 663 ierr = VecCreate(xx,&tt); CHKERR(ierr); 664 VecGetArray(tt,&t); 665 scale = (2.0/omega) - 1.0; 666 /* x = (E + U)^{-1} b */ 667 VecSet(&zero,mat->lvec); 668 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 669 mat->Mvctx); CHKERR(ierr); 670 for ( i=m-1; i>-1; i-- ) { 671 n = A->i[i+1] - diag[i] - 1; 672 idx = A->j + diag[i]; 673 v = A->a + diag[i]; 674 sum = b[i]; 675 SPARSEDENSEMDOT(sum,xs,v,idx,n); 676 d = shift + A->a[diag[i]-1]; 677 n = B->i[i+1] - B->i[i]; 678 idx = B->j + B->i[i] - 1; 679 v = B->a + B->i[i] - 1; 680 SPARSEDENSEMDOT(sum,ls,v,idx,n); 681 x[i] = omega*(sum/d); 682 } 683 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 684 mat->Mvctx); CHKERR(ierr); 685 686 /* t = b - (2*E - D)x */ 687 v = A->a; 688 for ( i=0; i<m; i++ ) { t[i] = b[i] - scale*(v[*diag++ - 1])*x[i]; } 689 690 /* t = (E + L)^{-1}t */ 691 ts = t - 1; /* shifted by one for index start of a or mat->j*/ 692 diag = A->diag; 693 VecSet(&zero,mat->lvec); 694 ierr = VecPipelineBegin(tt,0,mat->lvec,0,InsertValues,PipelineDown, 695 mat->Mvctx); CHKERR(ierr); 696 for ( i=0; i<m; i++ ) { 697 n = diag[i] - A->i[i]; 698 idx = A->j + A->i[i] - 1; 699 v = A->a + A->i[i] - 1; 700 sum = t[i]; 701 SPARSEDENSEMDOT(sum,ts,v,idx,n); 702 d = shift + A->a[diag[i]-1]; 703 n = B->i[i+1] - B->i[i]; 704 idx = B->j + B->i[i] - 1; 705 v = B->a + B->i[i] - 1; 706 SPARSEDENSEMDOT(sum,ls,v,idx,n); 707 t[i] = omega*(sum/d); 708 } 709 ierr = VecPipelineEnd(tt,0,mat->lvec,0,InsertValues,PipelineDown, 710 mat->Mvctx); CHKERR(ierr); 711 /* x = x + t */ 712 for ( i=0; i<m; i++ ) { x[i] += t[i]; } 713 VecDestroy(tt); 714 return 0; 715 } 716 717 718 if ((flag & SOR_SYMMETRIC_SWEEP) == SOR_SYMMETRIC_SWEEP){ 719 if (flag & SOR_ZERO_INITIAL_GUESS) { 720 VecSet(&zero,mat->lvec); VecSet(&zero,xx); 721 } 722 else { 723 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 724 CHKERR(ierr); 725 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 726 CHKERR(ierr); 727 } 728 while (its--) { 729 /* go down through the rows */ 730 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 731 mat->Mvctx); CHKERR(ierr); 732 for ( i=0; i<m; i++ ) { 733 n = A->i[i+1] - A->i[i]; 734 idx = A->j + A->i[i] - 1; 735 v = A->a + A->i[i] - 1; 736 sum = b[i]; 737 SPARSEDENSEMDOT(sum,xs,v,idx,n); 738 d = shift + A->a[diag[i]-1]; 739 n = B->i[i+1] - B->i[i]; 740 idx = B->j + B->i[i] - 1; 741 v = B->a + B->i[i] - 1; 742 SPARSEDENSEMDOT(sum,ls,v,idx,n); 743 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 744 } 745 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 746 mat->Mvctx); CHKERR(ierr); 747 /* come up through the rows */ 748 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 749 mat->Mvctx); CHKERR(ierr); 750 for ( i=m-1; i>-1; i-- ) { 751 n = A->i[i+1] - A->i[i]; 752 idx = A->j + A->i[i] - 1; 753 v = A->a + A->i[i] - 1; 754 sum = b[i]; 755 SPARSEDENSEMDOT(sum,xs,v,idx,n); 756 d = shift + A->a[diag[i]-1]; 757 n = B->i[i+1] - B->i[i]; 758 idx = B->j + B->i[i] - 1; 759 v = B->a + B->i[i] - 1; 760 SPARSEDENSEMDOT(sum,ls,v,idx,n); 761 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 762 } 763 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 764 mat->Mvctx); CHKERR(ierr); 765 } 766 } 767 else if (flag & SOR_FORWARD_SWEEP){ 768 if (flag & SOR_ZERO_INITIAL_GUESS) { 769 VecSet(&zero,mat->lvec); 770 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 771 mat->Mvctx); CHKERR(ierr); 772 for ( i=0; i<m; i++ ) { 773 n = diag[i] - A->i[i]; 774 idx = A->j + A->i[i] - 1; 775 v = A->a + A->i[i] - 1; 776 sum = b[i]; 777 SPARSEDENSEMDOT(sum,xs,v,idx,n); 778 d = shift + A->a[diag[i]-1]; 779 n = B->i[i+1] - B->i[i]; 780 idx = B->j + B->i[i] - 1; 781 v = B->a + B->i[i] - 1; 782 SPARSEDENSEMDOT(sum,ls,v,idx,n); 783 x[i] = omega*(sum/d); 784 } 785 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 786 mat->Mvctx); CHKERR(ierr); 787 its--; 788 } 789 while (its--) { 790 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 791 CHKERR(ierr); 792 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 793 CHKERR(ierr); 794 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 795 mat->Mvctx); CHKERR(ierr); 796 for ( i=0; i<m; i++ ) { 797 n = A->i[i+1] - A->i[i]; 798 idx = A->j + A->i[i] - 1; 799 v = A->a + A->i[i] - 1; 800 sum = b[i]; 801 SPARSEDENSEMDOT(sum,xs,v,idx,n); 802 d = shift + A->a[diag[i]-1]; 803 n = B->i[i+1] - B->i[i]; 804 idx = B->j + B->i[i] - 1; 805 v = B->a + B->i[i] - 1; 806 SPARSEDENSEMDOT(sum,ls,v,idx,n); 807 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 808 } 809 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 810 mat->Mvctx); CHKERR(ierr); 811 } 812 } 813 else if (flag & SOR_BACKWARD_SWEEP){ 814 if (flag & SOR_ZERO_INITIAL_GUESS) { 815 VecSet(&zero,mat->lvec); 816 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 817 mat->Mvctx); CHKERR(ierr); 818 for ( i=m-1; i>-1; i-- ) { 819 n = A->i[i+1] - diag[i] - 1; 820 idx = A->j + diag[i]; 821 v = A->a + diag[i]; 822 sum = b[i]; 823 SPARSEDENSEMDOT(sum,xs,v,idx,n); 824 d = shift + A->a[diag[i]-1]; 825 n = B->i[i+1] - B->i[i]; 826 idx = B->j + B->i[i] - 1; 827 v = B->a + B->i[i] - 1; 828 SPARSEDENSEMDOT(sum,ls,v,idx,n); 829 x[i] = omega*(sum/d); 830 } 831 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 832 mat->Mvctx); CHKERR(ierr); 833 its--; 834 } 835 while (its--) { 836 ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterDown, 837 mat->Mvctx); CHKERR(ierr); 838 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterDown, 839 mat->Mvctx); CHKERR(ierr); 840 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 841 mat->Mvctx); CHKERR(ierr); 842 for ( i=m-1; i>-1; i-- ) { 843 n = A->i[i+1] - A->i[i]; 844 idx = A->j + A->i[i] - 1; 845 v = A->a + A->i[i] - 1; 846 sum = b[i]; 847 SPARSEDENSEMDOT(sum,xs,v,idx,n); 848 d = shift + A->a[diag[i]-1]; 849 n = B->i[i+1] - B->i[i]; 850 idx = B->j + B->i[i] - 1; 851 v = B->a + B->i[i] - 1; 852 SPARSEDENSEMDOT(sum,ls,v,idx,n); 853 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 854 } 855 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 856 mat->Mvctx); CHKERR(ierr); 857 } 858 } 859 else if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 860 if (flag & SOR_ZERO_INITIAL_GUESS) { 861 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 862 } 863 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 864 CHKERR(ierr); 865 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 866 CHKERR(ierr); 867 while (its--) { 868 /* go down through the rows */ 869 for ( i=0; i<m; i++ ) { 870 n = A->i[i+1] - A->i[i]; 871 idx = A->j + A->i[i] - 1; 872 v = A->a + A->i[i] - 1; 873 sum = b[i]; 874 SPARSEDENSEMDOT(sum,xs,v,idx,n); 875 d = shift + A->a[diag[i]-1]; 876 n = B->i[i+1] - B->i[i]; 877 idx = B->j + B->i[i] - 1; 878 v = B->a + B->i[i] - 1; 879 SPARSEDENSEMDOT(sum,ls,v,idx,n); 880 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 881 } 882 /* come up through the rows */ 883 for ( i=m-1; i>-1; i-- ) { 884 n = A->i[i+1] - A->i[i]; 885 idx = A->j + A->i[i] - 1; 886 v = A->a + A->i[i] - 1; 887 sum = b[i]; 888 SPARSEDENSEMDOT(sum,xs,v,idx,n); 889 d = shift + A->a[diag[i]-1]; 890 n = B->i[i+1] - B->i[i]; 891 idx = B->j + B->i[i] - 1; 892 v = B->a + B->i[i] - 1; 893 SPARSEDENSEMDOT(sum,ls,v,idx,n); 894 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 895 } 896 } 897 } 898 else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 899 if (flag & SOR_ZERO_INITIAL_GUESS) { 900 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 901 } 902 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 903 CHKERR(ierr); 904 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 905 CHKERR(ierr); 906 while (its--) { 907 for ( i=0; i<m; i++ ) { 908 n = A->i[i+1] - A->i[i]; 909 idx = A->j + A->i[i] - 1; 910 v = A->a + A->i[i] - 1; 911 sum = b[i]; 912 SPARSEDENSEMDOT(sum,xs,v,idx,n); 913 d = shift + A->a[diag[i]-1]; 914 n = B->i[i+1] - B->i[i]; 915 idx = B->j + B->i[i] - 1; 916 v = B->a + B->i[i] - 1; 917 SPARSEDENSEMDOT(sum,ls,v,idx,n); 918 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 919 } 920 } 921 } 922 else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 923 if (flag & SOR_ZERO_INITIAL_GUESS) { 924 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 925 } 926 ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll, 927 mat->Mvctx); CHKERR(ierr); 928 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll, 929 mat->Mvctx); CHKERR(ierr); 930 while (its--) { 931 for ( i=m-1; i>-1; i-- ) { 932 n = A->i[i+1] - A->i[i]; 933 idx = A->j + A->i[i] - 1; 934 v = A->a + A->i[i] - 1; 935 sum = b[i]; 936 SPARSEDENSEMDOT(sum,xs,v,idx,n); 937 d = shift + A->a[diag[i]-1]; 938 n = B->i[i+1] - B->i[i]; 939 idx = B->j + B->i[i] - 1; 940 v = B->a + B->i[i] - 1; 941 SPARSEDENSEMDOT(sum,ls,v,idx,n); 942 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 943 } 944 } 945 } 946 return 0; 947 } 948 949 static int MatGetInfo_MPIAIJ(Mat matin,int flag,int *nz,int *nzalloc,int *mem) 950 { 951 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 952 Mat A = mat->A, B = mat->B; 953 int ierr, isend[3], irecv[3], nzA, nzallocA, memA; 954 955 ierr = MatGetInfo(A,MAT_LOCAL,&nzA,&nzallocA,&memA); CHKERR(ierr); 956 ierr = MatGetInfo(B,MAT_LOCAL,&isend[0],&isend[1],&isend[2]); CHKERR(ierr); 957 isend[0] += nzA; isend[1] += nzallocA; isend[2] += memA; 958 if (flag == MAT_LOCAL) { 959 *nz = isend[0]; *nzalloc = isend[1]; *mem = isend[2]; 960 } else if (flag == MAT_GLOBAL_MAX) { 961 MPI_Allreduce((void *) isend,(void *) irecv,3,MPI_INT,MPI_MAX,matin->comm); 962 *nz = irecv[0]; *nzalloc = irecv[1]; *mem = irecv[2]; 963 } else if (flag == MAT_GLOBAL_SUM) { 964 MPI_Allreduce((void *) isend,(void *) irecv,3,MPI_INT,MPI_SUM,matin->comm); 965 *nz = irecv[0]; *nzalloc = irecv[1]; *mem = irecv[2]; 966 } 967 return 0; 968 } 969 970 static int MatSetOption_MPIAIJ(Mat aijin,int op) 971 { 972 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 973 974 if (op == NO_NEW_NONZERO_LOCATIONS) { 975 MatSetOption(aij->A,op); 976 MatSetOption(aij->B,op); 977 } 978 else if (op == YES_NEW_NONZERO_LOCATIONS) { 979 MatSetOption(aij->A,op); 980 MatSetOption(aij->B,op); 981 } 982 else if (op == COLUMN_ORIENTED) SETERR(1,"Column oriented not supported"); 983 return 0; 984 } 985 986 static int MatGetSize_MPIAIJ(Mat matin,int *m,int *n) 987 { 988 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 989 *m = mat->M; *n = mat->N; 990 return 0; 991 } 992 993 static int MatGetLocalSize_MPIAIJ(Mat matin,int *m,int *n) 994 { 995 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 996 *m = mat->m; *n = mat->n; 997 return 0; 998 } 999 1000 static int MatGetOwnershipRange_MPIAIJ(Mat matin,int *m,int *n) 1001 { 1002 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 1003 *m = mat->rstart; *n = mat->rend; 1004 return 0; 1005 } 1006 1007 static int MatGetRow_MPIAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1008 { 1009 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 1010 Scalar *vworkA, *vworkB, **pvA, **pvB; 1011 int i, ierr, *cworkA, *cworkB, **pcA, **pcB, cstart = mat->cstart; 1012 int nztot, nzA, nzB, lrow, rstart = mat->rstart, rend = mat->rend; 1013 1014 if (!mat->assembled) 1015 SETERR(1,"MatGetRow_MPIAIJ: Must assemble matrix first."); 1016 if (row < rstart || row >= rend) 1017 SETERR(1,"MatGetRow_MPIAIJ: Currently you can get only local rows.") 1018 lrow = row - rstart; 1019 1020 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1021 if (!v) {pvA = 0; pvB = 0;} 1022 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1023 ierr = MatGetRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr); 1024 ierr = MatGetRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr); 1025 nztot = nzA + nzB; 1026 1027 if (v || idx) { 1028 if (nztot) { 1029 /* Sort by increasing column numbers, assuming A and B already sorted */ 1030 int imark, imark2; 1031 for (i=0; i<nzB; i++) cworkB[i] = mat->garray[cworkB[i]]; 1032 if (v) { 1033 *v = (Scalar *) MALLOC( (nztot)*sizeof(Scalar) ); CHKPTR(*v); 1034 for ( i=0; i<nzB; i++ ) { 1035 if (cworkB[i] < cstart) (*v)[i] = vworkB[i]; 1036 else break; 1037 } 1038 imark = i; 1039 for ( i=0; i<nzA; i++ ) (*v)[imark+i] = vworkA[i]; 1040 imark2 = imark+nzA; 1041 for ( i=imark; i<nzB; i++ ) (*v)[imark2+i] = vworkB[i]; 1042 } 1043 if (idx) { 1044 *idx = (int *) MALLOC( (nztot)*sizeof(int) ); CHKPTR(*idx); 1045 for (i=0; i<nzA; i++) cworkA[i] += cstart; 1046 for ( i=0; i<nzB; i++ ) { 1047 if (cworkB[i] < cstart) (*idx)[i] = cworkB[i]; 1048 else break; 1049 } 1050 imark = i; 1051 for ( i=0; i<nzA; i++ ) (*idx)[imark+i] = cworkA[i]; 1052 imark2 = imark+nzA; 1053 for ( i=imark; i<nzB; i++ ) (*idx)[imark2+i] = cworkB[i]; 1054 } 1055 } 1056 else {*idx = 0; *v=0;} 1057 } 1058 *nz = nztot; 1059 ierr = MatRestoreRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr); 1060 ierr = MatRestoreRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr); 1061 return 0; 1062 } 1063 1064 static int MatRestoreRow_MPIAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1065 { 1066 if (idx) FREE(*idx); 1067 if (v) FREE(*v); 1068 return 0; 1069 } 1070 1071 static int MatCopy_MPIAIJ(Mat,Mat *); 1072 extern int MatConvert_MPIAIJ(Mat,MATTYPE,Mat *); 1073 1074 /* -------------------------------------------------------------------*/ 1075 static struct _MatOps MatOps = {MatSetValues_MPIAIJ, 1076 MatGetRow_MPIAIJ,MatRestoreRow_MPIAIJ, 1077 MatMult_MPIAIJ,MatMultAdd_MPIAIJ, 1078 MatMultTrans_MPIAIJ,MatMultTransAdd_MPIAIJ, 1079 0,0,0,0, 1080 0,0, 1081 MatRelax_MPIAIJ, 1082 0, 1083 MatGetInfo_MPIAIJ,0, 1084 MatCopy_MPIAIJ, 1085 MatGetDiagonal_MPIAIJ,0,0, 1086 MatAssemblyBegin_MPIAIJ,MatAssemblyEnd_MPIAIJ, 1087 0, 1088 MatSetOption_MPIAIJ,MatZeroEntries_MPIAIJ,MatZeroRows_MPIAIJ,0, 1089 0,0,0,0, 1090 MatGetSize_MPIAIJ,MatGetLocalSize_MPIAIJ,MatGetOwnershipRange_MPIAIJ, 1091 0,0, 1092 0,MatConvert_MPIAIJ }; 1093 1094 /*@ 1095 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 1096 (the default parallel PETSc format). 1097 1098 Input Parameters: 1099 . comm - MPI communicator 1100 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1101 . n - number of local columns (or PETSC_DECIDE to have calculated 1102 if N is given) 1103 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1104 . N - number of global columns (or PETSC_DECIDE to have calculated 1105 if n is given) 1106 . d_nz - number of nonzeros per row in diagonal portion of matrix 1107 (same for all local rows) 1108 . d_nzz - number of nonzeros per row in diagonal portion of matrix or null 1109 (possibly different for each row). You must leave room for the 1110 diagonal entry even if it is zero. 1111 . o_nz - number of nonzeros per row in off-diagonal portion of matrix 1112 (same for all local rows) 1113 . o_nzz - number of nonzeros per row in off-diagonal portion of matrix 1114 or null (possibly different for each row). 1115 1116 Output Parameter: 1117 . newmat - the matrix 1118 1119 Notes: 1120 The AIJ format (also called the Yale sparse matrix format or 1121 compressed row storage), is fully compatible with standard Fortran 77 1122 storage. That is, the stored row and column indices begin at 1123 one, not zero. 1124 1125 The user MUST specify either the local or global matrix dimensions 1126 (possibly both). 1127 1128 The user can set d_nz, d_nnz, o_nz, and o_nnz to zero for PETSc to 1129 control dynamic memory allocation. 1130 1131 .keywords: Mat, matrix, aij, compressed row, sparse, parallel 1132 1133 .seealso: MatCreateSequentialAIJ(), MatSetValues() 1134 @*/ 1135 int MatCreateMPIAIJ(MPI_Comm comm,int m,int n,int M,int N, 1136 int d_nz,int *d_nnz, int o_nz,int *o_nnz,Mat *newmat) 1137 { 1138 Mat mat; 1139 Mat_MPIAIJ *aij; 1140 int ierr, i,sum[2],work[2]; 1141 *newmat = 0; 1142 PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,comm); 1143 PLogObjectCreate(mat); 1144 mat->data = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij); 1145 mat->ops = &MatOps; 1146 mat->destroy = MatDestroy_MPIAIJ; 1147 mat->view = MatView_MPIAIJ; 1148 mat->factor = 0; 1149 1150 mat->comm = comm; 1151 aij->insertmode = NotSetValues; 1152 MPI_Comm_rank(comm,&aij->mytid); 1153 MPI_Comm_size(comm,&aij->numtids); 1154 1155 if (M == -1 || N == -1) { 1156 work[0] = m; work[1] = n; 1157 MPI_Allreduce((void *) work,(void *) sum,2,MPI_INT,MPI_SUM,comm ); 1158 if (M == -1) M = sum[0]; 1159 if (N == -1) N = sum[1]; 1160 } 1161 if (m == -1) {m = M/aij->numtids + ((M % aij->numtids) > aij->mytid);} 1162 if (n == -1) {n = N/aij->numtids + ((N % aij->numtids) > aij->mytid);} 1163 aij->m = m; 1164 aij->n = n; 1165 aij->N = N; 1166 aij->M = M; 1167 1168 /* build local table of row and column ownerships */ 1169 aij->rowners = (int *) MALLOC(2*(aij->numtids+2)*sizeof(int)); 1170 CHKPTR(aij->rowners); 1171 aij->cowners = aij->rowners + aij->numtids + 1; 1172 MPI_Allgather(&m,1,MPI_INT,aij->rowners+1,1,MPI_INT,comm); 1173 aij->rowners[0] = 0; 1174 for ( i=2; i<=aij->numtids; i++ ) { 1175 aij->rowners[i] += aij->rowners[i-1]; 1176 } 1177 aij->rstart = aij->rowners[aij->mytid]; 1178 aij->rend = aij->rowners[aij->mytid+1]; 1179 MPI_Allgather(&n,1,MPI_INT,aij->cowners+1,1,MPI_INT,comm); 1180 aij->cowners[0] = 0; 1181 for ( i=2; i<=aij->numtids; i++ ) { 1182 aij->cowners[i] += aij->cowners[i-1]; 1183 } 1184 aij->cstart = aij->cowners[aij->mytid]; 1185 aij->cend = aij->cowners[aij->mytid+1]; 1186 1187 1188 ierr = MatCreateSequentialAIJ(MPI_COMM_SELF,m,n,d_nz,d_nnz,&aij->A); 1189 CHKERR(ierr); 1190 PLogObjectParent(mat,aij->A); 1191 ierr = MatCreateSequentialAIJ(MPI_COMM_SELF,m,N,o_nz,o_nnz,&aij->B); 1192 CHKERR(ierr); 1193 PLogObjectParent(mat,aij->B); 1194 1195 /* build cache for off array entries formed */ 1196 aij->stash.nmax = CHUNCKSIZE; /* completely arbratray number */ 1197 aij->stash.n = 0; 1198 aij->stash.array = (Scalar *) MALLOC( aij->stash.nmax*(2*sizeof(int) + 1199 sizeof(Scalar))); CHKPTR(aij->stash.array); 1200 aij->stash.idx = (int *) (aij->stash.array + aij->stash.nmax); 1201 aij->stash.idy = (int *) (aij->stash.idx + aij->stash.nmax); 1202 aij->colmap = 0; 1203 aij->garray = 0; 1204 1205 /* stuff used for matrix vector multiply */ 1206 aij->lvec = 0; 1207 aij->Mvctx = 0; 1208 aij->assembled = 0; 1209 1210 *newmat = mat; 1211 return 0; 1212 } 1213 1214 static int MatCopy_MPIAIJ(Mat matin,Mat *newmat) 1215 { 1216 Mat mat; 1217 Mat_MPIAIJ *aij,*oldmat = (Mat_MPIAIJ *) matin->data; 1218 int ierr, len; 1219 *newmat = 0; 1220 1221 if (!oldmat->assembled) SETERR(1,"Cannot copy unassembled matrix"); 1222 PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,matin->comm); 1223 PLogObjectCreate(mat); 1224 mat->data = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij); 1225 mat->ops = &MatOps; 1226 mat->destroy = MatDestroy_MPIAIJ; 1227 mat->view = MatView_MPIAIJ; 1228 mat->factor = matin->factor; 1229 1230 aij->m = oldmat->m; 1231 aij->n = oldmat->n; 1232 aij->M = oldmat->M; 1233 aij->N = oldmat->N; 1234 1235 aij->assembled = 1; 1236 aij->rstart = oldmat->rstart; 1237 aij->rend = oldmat->rend; 1238 aij->cstart = oldmat->cstart; 1239 aij->cend = oldmat->cend; 1240 aij->numtids = oldmat->numtids; 1241 aij->mytid = oldmat->mytid; 1242 aij->insertmode = NotSetValues; 1243 1244 aij->rowners = (int *) MALLOC( (aij->numtids+1)*sizeof(int) ); 1245 CHKPTR(aij->rowners); 1246 MEMCPY(aij->rowners,oldmat->rowners,(aij->numtids+1)*sizeof(int)); 1247 aij->stash.nmax = 0; 1248 aij->stash.n = 0; 1249 aij->stash.array = 0; 1250 if (oldmat->colmap) { 1251 aij->colmap = (int *) MALLOC( (aij->N)*sizeof(int) ); 1252 CHKPTR(aij->colmap); 1253 MEMCPY(aij->colmap,oldmat->colmap,(aij->N)*sizeof(int)); 1254 } else aij->colmap = 0; 1255 if (oldmat->garray && (len = ((Mat_AIJ *) (oldmat->B->data))->n)) { 1256 aij->garray = (int *) MALLOC(len*sizeof(int) ); CHKPTR(aij->garray); 1257 MEMCPY(aij->garray,oldmat->garray,len*sizeof(int)); 1258 } else aij->garray = 0; 1259 mat->comm = matin->comm; 1260 1261 ierr = VecCreate(oldmat->lvec,&aij->lvec); CHKERR(ierr); 1262 PLogObjectParent(mat,aij->lvec); 1263 ierr = VecScatterCtxCopy(oldmat->Mvctx,&aij->Mvctx); CHKERR(ierr); 1264 PLogObjectParent(mat,aij->Mvctx); 1265 ierr = MatCopy(oldmat->A,&aij->A); CHKERR(ierr); 1266 PLogObjectParent(mat,aij->A); 1267 ierr = MatCopy(oldmat->B,&aij->B); CHKERR(ierr); 1268 PLogObjectParent(mat,aij->B); 1269 *newmat = mat; 1270 return 0; 1271 } 1272