1 #ifndef lint 2 static char vcid[] = "$Id: mpiaij.c,v 1.27 1995/04/15 03:28:13 bsmith Exp curfman $"; 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 MatBeginAssembly_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 MatEndAssembly_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 = MatBeginAssembly(aij->A,mode); CHKERR(ierr); 281 ierr = MatEndAssembly(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 = MatBeginAssembly(aij->B,mode); CHKERR(ierr); 288 ierr = MatEndAssembly(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 } 540 541 static int MatView_MPIAIJ(PetscObject obj,Viewer viewer) 542 { 543 Mat mat = (Mat) obj; 544 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data; 545 int ierr; 546 PetscObject vobj = (PetscObject) viewer; 547 548 if (!viewer) { /* so that viewers may be used from debuggers */ 549 viewer = STDOUT_VIEWER; vobj = (PetscObject) viewer; 550 } 551 if (!aij->assembled) SETERR(1,"MatView_MPIAIJ: must assemble matrix first"); 552 if (vobj->cookie == VIEWER_COOKIE) { 553 FILE *fd = ViewerFileGetPointer(viewer); 554 if (vobj->type == FILE_VIEWER) { 555 MPE_Seq_begin(mat->comm,1); 556 fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n", 557 aij->mytid,aij->m,aij->rstart,aij->rend,aij->n,aij->cstart, 558 aij->cend); 559 ierr = MatView(aij->A,viewer); CHKERR(ierr); 560 ierr = MatView(aij->B,viewer); CHKERR(ierr); 561 fflush(fd); 562 MPE_Seq_end(mat->comm,1); 563 } 564 else if (vobj->type == FILES_VIEWER) { 565 int numtids = aij->numtids, mytid = aij->mytid; 566 if (numtids == 1) { 567 ierr = MatView(aij->A,viewer); CHKERR(ierr); 568 } 569 else { 570 /* assemble the entire matrix onto first processor. */ 571 Mat A; 572 Mat_AIJ *Aloc; 573 int M = aij->M, N = aij->N,m,*ai,*aj,row,*cols,i,*ct; 574 Scalar *a; 575 576 if (!mytid) { 577 ierr = MatCreateMPIAIJ(mat->comm,M,N,M,N,0,0,0,0,&A); 578 } 579 else { 580 ierr = MatCreateMPIAIJ(mat->comm,0,0,M,N,0,0,0,0,&A); 581 } 582 CHKERR(ierr); 583 584 /* copy over the A part */ 585 Aloc = (Mat_AIJ*) aij->A->data; 586 m = Aloc->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 587 row = aij->rstart; 588 for ( i=0; i<ai[m]; i++ ) {aj[i] += aij->cstart - 1;} 589 for ( i=0; i<m; i++ ) { 590 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,InsertValues); 591 CHKERR(ierr); 592 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 593 } 594 aj = Aloc->j; 595 for ( i=0; i<ai[m]; i++ ) {aj[i] -= aij->cstart - 1;} 596 597 /* copy over the B part */ 598 Aloc = (Mat_AIJ*) aij->B->data; 599 m = Aloc->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 600 row = aij->rstart; 601 ct = cols = (int *) MALLOC( (ai[m]+1)*sizeof(int) ); CHKPTR(cols); 602 for ( i=0; i<ai[m]; i++ ) {cols[i] = aij->garray[aj[i]-1];} 603 for ( i=0; i<m; i++ ) { 604 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,InsertValues); 605 CHKERR(ierr); 606 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 607 } 608 FREE(ct); 609 ierr = MatBeginAssembly(A,FINAL_ASSEMBLY); CHKERR(ierr); 610 ierr = MatEndAssembly(A,FINAL_ASSEMBLY); CHKERR(ierr); 611 if (!mytid) { 612 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,viewer); CHKERR(ierr); 613 } 614 ierr = MatDestroy(A); CHKERR(ierr); 615 } 616 } 617 } 618 return 0; 619 } 620 621 extern int MatMarkDiag_AIJ(Mat_AIJ *); 622 /* 623 This has to provide several versions. 624 625 1) per sequential 626 2) a) use only local smoothing updating outer values only once. 627 b) local smoothing updating outer values each inner iteration 628 3) color updating out values betwen colors. 629 */ 630 static int MatRelax_MPIAIJ(Mat matin,Vec bb,double omega,int flag,double shift, 631 int its,Vec xx) 632 { 633 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 634 Mat AA = mat->A, BB = mat->B; 635 Mat_AIJ *A = (Mat_AIJ *) AA->data, *B = (Mat_AIJ *)BB->data; 636 Scalar zero = 0.0,*b,*x,*xs,*ls,d,*v,sum,scale,*t,*ts; 637 int ierr,*idx, *diag; 638 int n = mat->n, m = mat->m, i; 639 Vec tt; 640 641 if (!mat->assembled) SETERR(1,"MatRelax_MPIAIJ: must assemble matrix first"); 642 643 VecGetArray(xx,&x); VecGetArray(bb,&b); VecGetArray(mat->lvec,&ls); 644 xs = x -1; /* shift by one for index start of 1 */ 645 ls--; 646 if (!A->diag) {if ((ierr = MatMarkDiag_AIJ(A))) return ierr;} 647 diag = A->diag; 648 if (flag == SOR_APPLY_UPPER || flag == SOR_APPLY_LOWER) { 649 SETERR(1,"That option not yet support for parallel AIJ matrices"); 650 } 651 if (flag & SOR_EISENSTAT) { 652 /* Let A = L + U + D; where L is lower trianglar, 653 U is upper triangular, E is diagonal; This routine applies 654 655 (L + E)^{-1} A (U + E)^{-1} 656 657 to a vector efficiently using Eisenstat's trick. This is for 658 the case of SSOR preconditioner, so E is D/omega where omega 659 is the relaxation factor. 660 */ 661 ierr = VecCreate(xx,&tt); CHKERR(ierr); 662 VecGetArray(tt,&t); 663 scale = (2.0/omega) - 1.0; 664 /* x = (E + U)^{-1} b */ 665 VecSet(&zero,mat->lvec); 666 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 667 mat->Mvctx); CHKERR(ierr); 668 for ( i=m-1; i>-1; i-- ) { 669 n = A->i[i+1] - diag[i] - 1; 670 idx = A->j + diag[i]; 671 v = A->a + diag[i]; 672 sum = b[i]; 673 SPARSEDENSEMDOT(sum,xs,v,idx,n); 674 d = shift + A->a[diag[i]-1]; 675 n = B->i[i+1] - B->i[i]; 676 idx = B->j + B->i[i] - 1; 677 v = B->a + B->i[i] - 1; 678 SPARSEDENSEMDOT(sum,ls,v,idx,n); 679 x[i] = omega*(sum/d); 680 } 681 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 682 mat->Mvctx); CHKERR(ierr); 683 684 /* t = b - (2*E - D)x */ 685 v = A->a; 686 for ( i=0; i<m; i++ ) { t[i] = b[i] - scale*(v[*diag++ - 1])*x[i]; } 687 688 /* t = (E + L)^{-1}t */ 689 ts = t - 1; /* shifted by one for index start of a or mat->j*/ 690 diag = A->diag; 691 VecSet(&zero,mat->lvec); 692 ierr = VecPipelineBegin(tt,0,mat->lvec,0,InsertValues,PipelineDown, 693 mat->Mvctx); CHKERR(ierr); 694 for ( i=0; i<m; i++ ) { 695 n = diag[i] - A->i[i]; 696 idx = A->j + A->i[i] - 1; 697 v = A->a + A->i[i] - 1; 698 sum = t[i]; 699 SPARSEDENSEMDOT(sum,ts,v,idx,n); 700 d = shift + A->a[diag[i]-1]; 701 n = B->i[i+1] - B->i[i]; 702 idx = B->j + B->i[i] - 1; 703 v = B->a + B->i[i] - 1; 704 SPARSEDENSEMDOT(sum,ls,v,idx,n); 705 t[i] = omega*(sum/d); 706 } 707 ierr = VecPipelineEnd(tt,0,mat->lvec,0,InsertValues,PipelineDown, 708 mat->Mvctx); CHKERR(ierr); 709 /* x = x + t */ 710 for ( i=0; i<m; i++ ) { x[i] += t[i]; } 711 VecDestroy(tt); 712 return 0; 713 } 714 715 716 if ((flag & SOR_SYMMETRIC_SWEEP) == SOR_SYMMETRIC_SWEEP){ 717 if (flag & SOR_ZERO_INITIAL_GUESS) { 718 VecSet(&zero,mat->lvec); VecSet(&zero,xx); 719 } 720 else { 721 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 722 CHKERR(ierr); 723 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 724 CHKERR(ierr); 725 } 726 while (its--) { 727 /* go down through the rows */ 728 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 729 mat->Mvctx); CHKERR(ierr); 730 for ( i=0; i<m; i++ ) { 731 n = A->i[i+1] - A->i[i]; 732 idx = A->j + A->i[i] - 1; 733 v = A->a + A->i[i] - 1; 734 sum = b[i]; 735 SPARSEDENSEMDOT(sum,xs,v,idx,n); 736 d = shift + A->a[diag[i]-1]; 737 n = B->i[i+1] - B->i[i]; 738 idx = B->j + B->i[i] - 1; 739 v = B->a + B->i[i] - 1; 740 SPARSEDENSEMDOT(sum,ls,v,idx,n); 741 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 742 } 743 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 744 mat->Mvctx); CHKERR(ierr); 745 /* come up through the rows */ 746 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 747 mat->Mvctx); CHKERR(ierr); 748 for ( i=m-1; i>-1; i-- ) { 749 n = A->i[i+1] - A->i[i]; 750 idx = A->j + A->i[i] - 1; 751 v = A->a + A->i[i] - 1; 752 sum = b[i]; 753 SPARSEDENSEMDOT(sum,xs,v,idx,n); 754 d = shift + A->a[diag[i]-1]; 755 n = B->i[i+1] - B->i[i]; 756 idx = B->j + B->i[i] - 1; 757 v = B->a + B->i[i] - 1; 758 SPARSEDENSEMDOT(sum,ls,v,idx,n); 759 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 760 } 761 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 762 mat->Mvctx); CHKERR(ierr); 763 } 764 } 765 else if (flag & SOR_FORWARD_SWEEP){ 766 if (flag & SOR_ZERO_INITIAL_GUESS) { 767 VecSet(&zero,mat->lvec); 768 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 769 mat->Mvctx); CHKERR(ierr); 770 for ( i=0; i<m; i++ ) { 771 n = diag[i] - A->i[i]; 772 idx = A->j + A->i[i] - 1; 773 v = A->a + A->i[i] - 1; 774 sum = b[i]; 775 SPARSEDENSEMDOT(sum,xs,v,idx,n); 776 d = shift + A->a[diag[i]-1]; 777 n = B->i[i+1] - B->i[i]; 778 idx = B->j + B->i[i] - 1; 779 v = B->a + B->i[i] - 1; 780 SPARSEDENSEMDOT(sum,ls,v,idx,n); 781 x[i] = omega*(sum/d); 782 } 783 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 784 mat->Mvctx); CHKERR(ierr); 785 its--; 786 } 787 while (its--) { 788 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 789 CHKERR(ierr); 790 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx); 791 CHKERR(ierr); 792 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown, 793 mat->Mvctx); CHKERR(ierr); 794 for ( i=0; i<m; i++ ) { 795 n = A->i[i+1] - A->i[i]; 796 idx = A->j + A->i[i] - 1; 797 v = A->a + A->i[i] - 1; 798 sum = b[i]; 799 SPARSEDENSEMDOT(sum,xs,v,idx,n); 800 d = shift + A->a[diag[i]-1]; 801 n = B->i[i+1] - B->i[i]; 802 idx = B->j + B->i[i] - 1; 803 v = B->a + B->i[i] - 1; 804 SPARSEDENSEMDOT(sum,ls,v,idx,n); 805 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 806 } 807 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown, 808 mat->Mvctx); CHKERR(ierr); 809 } 810 } 811 else if (flag & SOR_BACKWARD_SWEEP){ 812 if (flag & SOR_ZERO_INITIAL_GUESS) { 813 VecSet(&zero,mat->lvec); 814 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 815 mat->Mvctx); CHKERR(ierr); 816 for ( i=m-1; i>-1; i-- ) { 817 n = A->i[i+1] - diag[i] - 1; 818 idx = A->j + diag[i]; 819 v = A->a + diag[i]; 820 sum = b[i]; 821 SPARSEDENSEMDOT(sum,xs,v,idx,n); 822 d = shift + A->a[diag[i]-1]; 823 n = B->i[i+1] - B->i[i]; 824 idx = B->j + B->i[i] - 1; 825 v = B->a + B->i[i] - 1; 826 SPARSEDENSEMDOT(sum,ls,v,idx,n); 827 x[i] = omega*(sum/d); 828 } 829 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 830 mat->Mvctx); CHKERR(ierr); 831 its--; 832 } 833 while (its--) { 834 ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterDown, 835 mat->Mvctx); CHKERR(ierr); 836 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterDown, 837 mat->Mvctx); CHKERR(ierr); 838 ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp, 839 mat->Mvctx); CHKERR(ierr); 840 for ( i=m-1; i>-1; i-- ) { 841 n = A->i[i+1] - A->i[i]; 842 idx = A->j + A->i[i] - 1; 843 v = A->a + A->i[i] - 1; 844 sum = b[i]; 845 SPARSEDENSEMDOT(sum,xs,v,idx,n); 846 d = shift + A->a[diag[i]-1]; 847 n = B->i[i+1] - B->i[i]; 848 idx = B->j + B->i[i] - 1; 849 v = B->a + B->i[i] - 1; 850 SPARSEDENSEMDOT(sum,ls,v,idx,n); 851 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 852 } 853 ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp, 854 mat->Mvctx); CHKERR(ierr); 855 } 856 } 857 else if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 858 if (flag & SOR_ZERO_INITIAL_GUESS) { 859 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 860 } 861 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 862 CHKERR(ierr); 863 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 864 CHKERR(ierr); 865 while (its--) { 866 /* go down through the rows */ 867 for ( i=0; i<m; i++ ) { 868 n = A->i[i+1] - A->i[i]; 869 idx = A->j + A->i[i] - 1; 870 v = A->a + A->i[i] - 1; 871 sum = b[i]; 872 SPARSEDENSEMDOT(sum,xs,v,idx,n); 873 d = shift + A->a[diag[i]-1]; 874 n = B->i[i+1] - B->i[i]; 875 idx = B->j + B->i[i] - 1; 876 v = B->a + B->i[i] - 1; 877 SPARSEDENSEMDOT(sum,ls,v,idx,n); 878 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 879 } 880 /* come up through the rows */ 881 for ( i=m-1; i>-1; i-- ) { 882 n = A->i[i+1] - A->i[i]; 883 idx = A->j + A->i[i] - 1; 884 v = A->a + A->i[i] - 1; 885 sum = b[i]; 886 SPARSEDENSEMDOT(sum,xs,v,idx,n); 887 d = shift + A->a[diag[i]-1]; 888 n = B->i[i+1] - B->i[i]; 889 idx = B->j + B->i[i] - 1; 890 v = B->a + B->i[i] - 1; 891 SPARSEDENSEMDOT(sum,ls,v,idx,n); 892 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 893 } 894 } 895 } 896 else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 897 if (flag & SOR_ZERO_INITIAL_GUESS) { 898 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 899 } 900 ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 901 CHKERR(ierr); 902 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx); 903 CHKERR(ierr); 904 while (its--) { 905 for ( i=0; i<m; i++ ) { 906 n = A->i[i+1] - A->i[i]; 907 idx = A->j + A->i[i] - 1; 908 v = A->a + A->i[i] - 1; 909 sum = b[i]; 910 SPARSEDENSEMDOT(sum,xs,v,idx,n); 911 d = shift + A->a[diag[i]-1]; 912 n = B->i[i+1] - B->i[i]; 913 idx = B->j + B->i[i] - 1; 914 v = B->a + B->i[i] - 1; 915 SPARSEDENSEMDOT(sum,ls,v,idx,n); 916 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 917 } 918 } 919 } 920 else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 921 if (flag & SOR_ZERO_INITIAL_GUESS) { 922 return MatRelax(mat->A,bb,omega,flag,shift,its,xx); 923 } 924 ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll, 925 mat->Mvctx); CHKERR(ierr); 926 ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll, 927 mat->Mvctx); CHKERR(ierr); 928 while (its--) { 929 for ( i=m-1; i>-1; i-- ) { 930 n = A->i[i+1] - A->i[i]; 931 idx = A->j + A->i[i] - 1; 932 v = A->a + A->i[i] - 1; 933 sum = b[i]; 934 SPARSEDENSEMDOT(sum,xs,v,idx,n); 935 d = shift + A->a[diag[i]-1]; 936 n = B->i[i+1] - B->i[i]; 937 idx = B->j + B->i[i] - 1; 938 v = B->a + B->i[i] - 1; 939 SPARSEDENSEMDOT(sum,ls,v,idx,n); 940 x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]); 941 } 942 } 943 } 944 return 0; 945 } 946 947 static int MatGetInfo_MPIAIJ(Mat matin,int flag,int *nz,int *nzalloc,int *mem) 948 { 949 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 950 Mat A = mat->A, B = mat->B; 951 int ierr, isend[3], irecv[3], nzA, nzallocA, memA; 952 953 ierr = MatGetInfo(A,MAT_LOCAL,&nzA,&nzallocA,&memA); CHKERR(ierr); 954 ierr = MatGetInfo(B,MAT_LOCAL,&isend[0],&isend[1],&isend[2]); CHKERR(ierr); 955 isend[0] += nzA; isend[1] += nzallocA; isend[2] += memA; 956 if (flag == MAT_LOCAL) { 957 *nz = isend[0]; *nzalloc = isend[1]; *mem = isend[2]; 958 } else if (flag == MAT_GLOBAL_MAX) { 959 MPI_Allreduce((void *) isend,(void *) irecv,3,MPI_INT,MPI_MAX,matin->comm); 960 *nz = irecv[0]; *nzalloc = irecv[1]; *mem = irecv[2]; 961 } else if (flag == MAT_GLOBAL_SUM) { 962 MPI_Allreduce((void *) isend,(void *) irecv,3,MPI_INT,MPI_SUM,matin->comm); 963 *nz = irecv[0]; *nzalloc = irecv[1]; *mem = irecv[2]; 964 } 965 return 0; 966 } 967 968 static int MatSetOption_MPIAIJ(Mat aijin,int op) 969 { 970 Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data; 971 972 if (op == NO_NEW_NONZERO_LOCATIONS) { 973 MatSetOption(aij->A,op); 974 MatSetOption(aij->B,op); 975 } 976 else if (op == YES_NEW_NONZERO_LOCATIONS) { 977 MatSetOption(aij->A,op); 978 MatSetOption(aij->B,op); 979 } 980 else if (op == COLUMN_ORIENTED) SETERR(1,"Column oriented not supported"); 981 return 0; 982 } 983 984 static int MatGetSize_MPIAIJ(Mat matin,int *m,int *n) 985 { 986 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 987 *m = mat->M; *n = mat->N; 988 return 0; 989 } 990 991 static int MatGetLocalSize_MPIAIJ(Mat matin,int *m,int *n) 992 { 993 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 994 *m = mat->m; *n = mat->n; 995 return 0; 996 } 997 998 static int MatGetOwnershipRange_MPIAIJ(Mat matin,int *m,int *n) 999 { 1000 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 1001 *m = mat->rstart; *n = mat->rend; 1002 return 0; 1003 } 1004 1005 static int MatGetRow_MPIAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1006 { 1007 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data; 1008 Scalar *vworkA, *vworkB, **pvA, **pvB; 1009 int i, ierr, *cworkA, *cworkB, **pcA, **pcB, cstart = mat->cstart; 1010 int nztot, nzA, nzB, lrow, rstart = mat->rstart, rend = mat->rend; 1011 1012 if (!mat->assembled) 1013 SETERR(1,"MatGetRow_MPIAIJ: Must assemble matrix first."); 1014 if (row < rstart || row >= rend) 1015 SETERR(1,"MatGetRow_MPIAIJ: Currently you can get only local rows.") 1016 lrow = row - rstart; 1017 1018 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1019 if (!v) {pvA = 0; pvB = 0;} 1020 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1021 ierr = MatGetRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr); 1022 ierr = MatGetRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr); 1023 nztot = nzA + nzB; 1024 1025 if (v || idx) { 1026 if (nztot) { 1027 /* Sort by increasing column numbers, assuming A and B already sorted */ 1028 int imark, imark2; 1029 for (i=0; i<nzB; i++) cworkB[i] = mat->garray[cworkB[i]]; 1030 if (v) { 1031 *v = (Scalar *) MALLOC( (nztot)*sizeof(Scalar) ); CHKPTR(*v); 1032 for ( i=0; i<nzB; i++ ) { 1033 if (cworkB[i] < cstart) (*v)[i] = vworkB[i]; 1034 else break; 1035 } 1036 imark = i; 1037 for ( i=0; i<nzA; i++ ) (*v)[imark+i] = vworkA[i]; 1038 imark2 = imark+nzA; 1039 for ( i=imark; i<nzB; i++ ) (*v)[imark2+i] = vworkB[i]; 1040 } 1041 if (idx) { 1042 *idx = (int *) MALLOC( (nztot)*sizeof(int) ); CHKPTR(*idx); 1043 for (i=0; i<nzA; i++) cworkA[i] += cstart; 1044 for ( i=0; i<nzB; i++ ) { 1045 if (cworkB[i] < cstart) (*idx)[i] = cworkB[i]; 1046 else break; 1047 } 1048 imark = i; 1049 for ( i=0; i<nzA; i++ ) (*idx)[imark+i] = cworkA[i]; 1050 imark2 = imark+nzA; 1051 for ( i=imark; i<nzB; i++ ) (*idx)[imark2+i] = cworkB[i]; 1052 } 1053 } 1054 else {*idx = 0; *v=0;} 1055 } 1056 *nz = nztot; 1057 ierr = MatRestoreRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr); 1058 ierr = MatRestoreRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr); 1059 return 0; 1060 } 1061 1062 static int MatRestoreRow_MPIAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1063 { 1064 if (idx) FREE(*idx); 1065 if (v) FREE(*v); 1066 return 0; 1067 } 1068 1069 static int MatCopy_MPIAIJ(Mat,Mat *); 1070 extern int MatConvert_MPIAIJ(Mat,MATTYPE,Mat *); 1071 1072 /* -------------------------------------------------------------------*/ 1073 static struct _MatOps MatOps = {MatSetValues_MPIAIJ, 1074 MatGetRow_MPIAIJ,MatRestoreRow_MPIAIJ, 1075 MatMult_MPIAIJ,MatMultAdd_MPIAIJ, 1076 MatMultTrans_MPIAIJ,MatMultTransAdd_MPIAIJ, 1077 0,0,0,0, 1078 0,0, 1079 MatRelax_MPIAIJ, 1080 0, 1081 MatGetInfo_MPIAIJ,0, 1082 MatCopy_MPIAIJ, 1083 MatGetDiagonal_MPIAIJ,0,0, 1084 MatBeginAssembly_MPIAIJ,MatEndAssembly_MPIAIJ, 1085 0, 1086 MatSetOption_MPIAIJ,MatZeroEntries_MPIAIJ,MatZeroRows_MPIAIJ,0, 1087 0,0,0,0, 1088 MatGetSize_MPIAIJ,MatGetLocalSize_MPIAIJ,MatGetOwnershipRange_MPIAIJ, 1089 0,0, 1090 0,MatConvert_MPIAIJ }; 1091 1092 /*@ 1093 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 1094 (the default parallel PETSc format). 1095 1096 Input Parameters: 1097 . comm - MPI communicator 1098 . m - number of local rows (or PETSC_DECIDE to have calculated) 1099 . n - number of local columns (or PETSC_DECIDE to have calculated) 1100 . M - number of global rows (or PETSC_DECIDE to have calculated) 1101 . N - number of global columns (or PETSC_DECIDE to have calculated) 1102 . d_nz - number of nonzeros per row in diagonal portion of matrix 1103 (same for all local rows) 1104 . d_nzz - number of nonzeros per row in diagonal portion of matrix or null 1105 (possibly different for each row). You must leave room for the 1106 diagonal entry even if it is zero. 1107 . o_nz - number of nonzeros per row in off-diagonal portion of matrix 1108 (same for all local rows) 1109 . o_nzz - number of nonzeros per row in off-diagonal portion of matrix 1110 or null (possibly different for each row). 1111 1112 Output Parameter: 1113 . newmat - the matrix 1114 1115 Notes: 1116 The AIJ format (also called the Yale sparse matrix format or 1117 compressed row storage), is fully compatible with standard Fortran 77 1118 storage. That is, the stored row and column indices begin at 1119 one, not zero. 1120 1121 The user MUST specify either the local or global matrix dimensions 1122 (possibly both). 1123 1124 The user can set d_nz, d_nnz, o_nz, and o_nnz to zero for PETSc to 1125 control dynamic memory allocation. 1126 1127 .keywords: Mat, matrix, aij, compressed row, sparse, parallel 1128 1129 .seealso: MatCreateSequentialAIJ(), MatSetValues() 1130 @*/ 1131 int MatCreateMPIAIJ(MPI_Comm comm,int m,int n,int M,int N, 1132 int d_nz,int *d_nnz, int o_nz,int *o_nnz,Mat *newmat) 1133 { 1134 Mat mat; 1135 Mat_MPIAIJ *aij; 1136 int ierr, i,sum[2],work[2]; 1137 *newmat = 0; 1138 PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,comm); 1139 PLogObjectCreate(mat); 1140 mat->data = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij); 1141 mat->ops = &MatOps; 1142 mat->destroy = MatDestroy_MPIAIJ; 1143 mat->view = MatView_MPIAIJ; 1144 mat->factor = 0; 1145 mat->row = 0; 1146 mat->col = 0; 1147 1148 mat->comm = comm; 1149 aij->insertmode = NotSetValues; 1150 MPI_Comm_rank(comm,&aij->mytid); 1151 MPI_Comm_size(comm,&aij->numtids); 1152 1153 if (M == -1 || N == -1) { 1154 work[0] = m; work[1] = n; 1155 MPI_Allreduce((void *) work,(void *) sum,2,MPI_INT,MPI_SUM,comm ); 1156 if (M == -1) M = sum[0]; 1157 if (N == -1) N = sum[1]; 1158 } 1159 if (m == -1) {m = M/aij->numtids + ((M % aij->numtids) > aij->mytid);} 1160 if (n == -1) {n = N/aij->numtids + ((N % aij->numtids) > aij->mytid);} 1161 aij->m = m; 1162 aij->n = n; 1163 aij->N = N; 1164 aij->M = M; 1165 1166 /* build local table of row and column ownerships */ 1167 aij->rowners = (int *) MALLOC(2*(aij->numtids+2)*sizeof(int)); 1168 CHKPTR(aij->rowners); 1169 aij->cowners = aij->rowners + aij->numtids + 1; 1170 MPI_Allgather(&m,1,MPI_INT,aij->rowners+1,1,MPI_INT,comm); 1171 aij->rowners[0] = 0; 1172 for ( i=2; i<=aij->numtids; i++ ) { 1173 aij->rowners[i] += aij->rowners[i-1]; 1174 } 1175 aij->rstart = aij->rowners[aij->mytid]; 1176 aij->rend = aij->rowners[aij->mytid+1]; 1177 MPI_Allgather(&n,1,MPI_INT,aij->cowners+1,1,MPI_INT,comm); 1178 aij->cowners[0] = 0; 1179 for ( i=2; i<=aij->numtids; i++ ) { 1180 aij->cowners[i] += aij->cowners[i-1]; 1181 } 1182 aij->cstart = aij->cowners[aij->mytid]; 1183 aij->cend = aij->cowners[aij->mytid+1]; 1184 1185 1186 ierr = MatCreateSequentialAIJ(MPI_COMM_SELF,m,n,d_nz,d_nnz,&aij->A); 1187 CHKERR(ierr); 1188 PLogObjectParent(mat,aij->A); 1189 ierr = MatCreateSequentialAIJ(MPI_COMM_SELF,m,N,o_nz,o_nnz,&aij->B); 1190 CHKERR(ierr); 1191 PLogObjectParent(mat,aij->B); 1192 1193 /* build cache for off array entries formed */ 1194 aij->stash.nmax = CHUNCKSIZE; /* completely arbratray number */ 1195 aij->stash.n = 0; 1196 aij->stash.array = (Scalar *) MALLOC( aij->stash.nmax*(2*sizeof(int) + 1197 sizeof(Scalar))); CHKPTR(aij->stash.array); 1198 aij->stash.idx = (int *) (aij->stash.array + aij->stash.nmax); 1199 aij->stash.idy = (int *) (aij->stash.idx + aij->stash.nmax); 1200 aij->colmap = 0; 1201 aij->garray = 0; 1202 1203 /* stuff used for matrix vector multiply */ 1204 aij->lvec = 0; 1205 aij->Mvctx = 0; 1206 aij->assembled = 0; 1207 1208 *newmat = mat; 1209 return 0; 1210 } 1211 1212 static int MatCopy_MPIAIJ(Mat matin,Mat *newmat) 1213 { 1214 Mat mat; 1215 Mat_MPIAIJ *aij,*oldmat = (Mat_MPIAIJ *) matin->data; 1216 int ierr, len; 1217 *newmat = 0; 1218 1219 if (!oldmat->assembled) SETERR(1,"Cannot copy unassembled matrix"); 1220 PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,matin->comm); 1221 PLogObjectCreate(mat); 1222 mat->data = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij); 1223 mat->ops = &MatOps; 1224 mat->destroy = MatDestroy_MPIAIJ; 1225 mat->view = MatView_MPIAIJ; 1226 mat->factor = matin->factor; 1227 mat->row = 0; 1228 mat->col = 0; 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