1 #ifndef lint 2 static char vcid[] = "$Id: mpibaij.c,v 1.11 1996/07/08 12:45:27 curfman Exp bsmith $"; 3 #endif 4 5 #include "mpibaij.h" 6 7 8 #include "draw.h" 9 #include "pinclude/pviewer.h" 10 11 extern int MatSetUpMultiply_MPIBAIJ(Mat); 12 extern int DisAssemble_MPIBAIJ(Mat); 13 extern int MatIncreaseOverlap_MPIBAIJ(Mat,int,IS *,int); 14 extern int MatGetSubMatrices_MPIBAIJ(Mat,int,IS *,IS *,MatGetSubMatrixCall,Mat **); 15 16 /* local utility routine that creates a mapping from the global column 17 number to the local number in the off-diagonal part of the local 18 storage of the matrix. This is done in a non scable way since the 19 length of colmap equals the global matrix length. 20 */ 21 static int CreateColmap_MPIBAIJ_Private(Mat mat) 22 { 23 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 24 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*) baij->B->data; 25 int nbs = B->nbs,i; 26 27 baij->colmap = (int *) PetscMalloc(baij->Nbs*sizeof(int));CHKPTRQ(baij->colmap); 28 PLogObjectMemory(mat,baij->Nbs*sizeof(int)); 29 PetscMemzero(baij->colmap,baij->Nbs*sizeof(int)); 30 for ( i=0; i<nbs; i++ ) baij->colmap[baij->garray[i]] = i; 31 return 0; 32 } 33 34 35 static int MatGetReordering_MPIBAIJ(Mat mat,MatReordering type,IS *rperm,IS *cperm) 36 { 37 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 38 int ierr; 39 if (baij->size == 1) { 40 ierr = MatGetReordering(baij->A,type,rperm,cperm); CHKERRQ(ierr); 41 } else SETERRQ(1,"MatGetReordering_MPIBAIJ:not supported in parallel"); 42 return 0; 43 } 44 45 static int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 46 { 47 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 48 Scalar value; 49 int ierr,i,j, rstart = baij->rstart, rend = baij->rend; 50 int cstart = baij->cstart, cend = baij->cend,row,col; 51 int roworiented = baij->roworiented,rstart_orig,rend_orig; 52 int cstart_orig,cend_orig,bs=baij->bs; 53 54 if (baij->insertmode != NOT_SET_VALUES && baij->insertmode != addv) { 55 SETERRQ(1,"MatSetValues_MPIBAIJ:Cannot mix inserts and adds"); 56 } 57 baij->insertmode = addv; 58 rstart_orig = rstart*bs; 59 rend_orig = rend*bs; 60 cstart_orig = cstart*bs; 61 cend_orig = cend*bs; 62 for ( i=0; i<m; i++ ) { 63 if (im[i] < 0) SETERRQ(1,"MatSetValues_MPIBAIJ:Negative row"); 64 if (im[i] >= baij->M) SETERRQ(1,"MatSetValues_MPIBAIJ:Row too large"); 65 if (im[i] >= rstart_orig && im[i] < rend_orig) { 66 row = im[i] - rstart_orig; 67 for ( j=0; j<n; j++ ) { 68 if (in[j] < 0) SETERRQ(1,"MatSetValues_MPIBAIJ:Negative column"); 69 if (in[j] >= baij->N) SETERRQ(1,"MatSetValues_MPIBAIJ:Col too large"); 70 if (in[j] >= cstart_orig && in[j] < cend_orig){ 71 col = in[j] - cstart_orig; 72 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 73 ierr = MatSetValues(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); 74 } 75 else { 76 if (mat->was_assembled) { 77 if (!baij->colmap) {ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);} 78 col = baij->colmap[in[j]]; 79 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 80 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 81 col = in[j]; 82 } 83 } 84 else col = in[j]; 85 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 86 ierr = MatSetValues(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); 87 } 88 } 89 } 90 else { 91 if (roworiented) { 92 ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr); 93 } 94 else { 95 row = im[i]; 96 for ( j=0; j<n; j++ ) { 97 ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr); 98 } 99 } 100 } 101 } 102 return 0; 103 } 104 105 static int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 106 { 107 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 108 int bs=baij->bs,ierr,i,j, bsrstart = baij->rstart*bs, bsrend = baij->rend*bs; 109 int bscstart = baij->cstart*bs, bscend = baij->cend*bs,row,col; 110 111 for ( i=0; i<m; i++ ) { 112 if (idxm[i] < 0) SETERRQ(1,"MatGetValues_MPIBAIJ:Negative row"); 113 if (idxm[i] >= baij->M) SETERRQ(1,"MatGetValues_MPIBAIJ:Row too large"); 114 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 115 row = idxm[i] - bsrstart; 116 for ( j=0; j<n; j++ ) { 117 if (idxn[j] < 0) SETERRQ(1,"MatGetValues_MPIBAIJ:Negative column"); 118 if (idxn[j] >= baij->N) SETERRQ(1,"MatGetValues_MPIBAIJ:Col too large"); 119 if (idxn[j] >= bscstart && idxn[j] < bscend){ 120 col = idxn[j] - bscstart; 121 ierr = MatGetValues(baij->A,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 122 } 123 else { 124 if (!baij->colmap) {ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);} 125 if ( baij->garray[baij->colmap[idxn[j]/bs]] != idxn[j]/bs ) *(v+i*n+j) = 0.0; 126 else { 127 col = baij->colmap[idxn[j]/bs]*bs + idxn[j]%bs; 128 ierr = MatGetValues(baij->B,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 129 } 130 } 131 } 132 } 133 else { 134 SETERRQ(1,"MatGetValues_MPIBAIJ:Only local values currently supported"); 135 } 136 } 137 return 0; 138 } 139 140 static int MatNorm_MPIBAIJ(Mat mat,NormType type,double *norm) 141 { 142 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 143 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*) baij->A->data, *bmat = (Mat_SeqBAIJ*) baij->B->data; 144 int ierr, i,bs2=baij->bs2; 145 double sum = 0.0; 146 Scalar *v; 147 148 if (baij->size == 1) { 149 ierr = MatNorm(baij->A,type,norm); CHKERRQ(ierr); 150 } else { 151 if (type == NORM_FROBENIUS) { 152 v = amat->a; 153 for (i=0; i<amat->nz*bs2; i++ ) { 154 #if defined(PETSC_COMPLEX) 155 sum += real(conj(*v)*(*v)); v++; 156 #else 157 sum += (*v)*(*v); v++; 158 #endif 159 } 160 v = bmat->a; 161 for (i=0; i<bmat->nz*bs2; i++ ) { 162 #if defined(PETSC_COMPLEX) 163 sum += real(conj(*v)*(*v)); v++; 164 #else 165 sum += (*v)*(*v); v++; 166 #endif 167 } 168 MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm); 169 *norm = sqrt(*norm); 170 } 171 else 172 SETERRQ(1,"MatNorm_SeqBAIJ:No support for this norm yet"); 173 } 174 return 0; 175 } 176 177 static int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 178 { 179 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 180 MPI_Comm comm = mat->comm; 181 int size = baij->size, *owners = baij->rowners,bs=baij->bs; 182 int rank = baij->rank,tag = mat->tag, *owner,*starts,count,ierr; 183 MPI_Request *send_waits,*recv_waits; 184 int *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work; 185 InsertMode addv; 186 Scalar *rvalues,*svalues; 187 188 /* make sure all processors are either in INSERTMODE or ADDMODE */ 189 MPI_Allreduce(&baij->insertmode,&addv,1,MPI_INT,MPI_BOR,comm); 190 if (addv == (ADD_VALUES|INSERT_VALUES)) { 191 SETERRQ(1,"MatAssemblyBegin_MPIBAIJ:Some processors inserted others added"); 192 } 193 baij->insertmode = addv; /* in case this processor had no cache */ 194 195 /* first count number of contributors to each processor */ 196 nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs); 197 PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size; 198 owner = (int *) PetscMalloc( (baij->stash.n+1)*sizeof(int) ); CHKPTRQ(owner); 199 for ( i=0; i<baij->stash.n; i++ ) { 200 idx = baij->stash.idx[i]; 201 for ( j=0; j<size; j++ ) { 202 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 203 nprocs[j]++; procs[j] = 1; owner[i] = j; break; 204 } 205 } 206 } 207 nsends = 0; for ( i=0; i<size; i++ ) { nsends += procs[i];} 208 209 /* inform other processors of number of messages and max length*/ 210 work = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work); 211 MPI_Allreduce(procs, work,size,MPI_INT,MPI_SUM,comm); 212 nreceives = work[rank]; 213 MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm); 214 nmax = work[rank]; 215 PetscFree(work); 216 217 /* post receives: 218 1) each message will consist of ordered pairs 219 (global index,value) we store the global index as a double 220 to simplify the message passing. 221 2) since we don't know how long each individual message is we 222 allocate the largest needed buffer for each receive. Potentially 223 this is a lot of wasted space. 224 225 226 This could be done better. 227 */ 228 rvalues = (Scalar *) PetscMalloc(3*(nreceives+1)*(nmax+1)*sizeof(Scalar)); 229 CHKPTRQ(rvalues); 230 recv_waits = (MPI_Request *) PetscMalloc((nreceives+1)*sizeof(MPI_Request)); 231 CHKPTRQ(recv_waits); 232 for ( i=0; i<nreceives; i++ ) { 233 MPI_Irecv(rvalues+3*nmax*i,3*nmax,MPIU_SCALAR,MPI_ANY_SOURCE,tag, 234 comm,recv_waits+i); 235 } 236 237 /* do sends: 238 1) starts[i] gives the starting index in svalues for stuff going to 239 the ith processor 240 */ 241 svalues = (Scalar *) PetscMalloc(3*(baij->stash.n+1)*sizeof(Scalar));CHKPTRQ(svalues); 242 send_waits = (MPI_Request *) PetscMalloc( (nsends+1)*sizeof(MPI_Request)); 243 CHKPTRQ(send_waits); 244 starts = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(starts); 245 starts[0] = 0; 246 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 247 for ( i=0; i<baij->stash.n; i++ ) { 248 svalues[3*starts[owner[i]]] = (Scalar) baij->stash.idx[i]; 249 svalues[3*starts[owner[i]]+1] = (Scalar) baij->stash.idy[i]; 250 svalues[3*(starts[owner[i]]++)+2] = baij->stash.array[i]; 251 } 252 PetscFree(owner); 253 starts[0] = 0; 254 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 255 count = 0; 256 for ( i=0; i<size; i++ ) { 257 if (procs[i]) { 258 MPI_Isend(svalues+3*starts[i],3*nprocs[i],MPIU_SCALAR,i,tag, 259 comm,send_waits+count++); 260 } 261 } 262 PetscFree(starts); PetscFree(nprocs); 263 264 /* Free cache space */ 265 PLogInfo(0,"[%d]MatAssemblyBegin_MPIBAIJ:Number of off processor values %d\n",rank,baij->stash.n); 266 ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr); 267 268 baij->svalues = svalues; baij->rvalues = rvalues; 269 baij->nsends = nsends; baij->nrecvs = nreceives; 270 baij->send_waits = send_waits; baij->recv_waits = recv_waits; 271 baij->rmax = nmax; 272 273 return 0; 274 } 275 276 277 static int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 278 { 279 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 280 MPI_Status *send_status,recv_status; 281 int imdex,nrecvs = baij->nrecvs, count = nrecvs, i, n, ierr; 282 int bs=baij->bs,row,col,other_disassembled; 283 Scalar *values,val; 284 InsertMode addv = baij->insertmode; 285 286 /* wait on receives */ 287 while (count) { 288 MPI_Waitany(nrecvs,baij->recv_waits,&imdex,&recv_status); 289 /* unpack receives into our local space */ 290 values = baij->rvalues + 3*imdex*baij->rmax; 291 MPI_Get_count(&recv_status,MPIU_SCALAR,&n); 292 n = n/3; 293 for ( i=0; i<n; i++ ) { 294 row = (int) PetscReal(values[3*i]) - baij->rstart*bs; 295 col = (int) PetscReal(values[3*i+1]); 296 val = values[3*i+2]; 297 if (col >= baij->cstart*bs && col < baij->cend*bs) { 298 col -= baij->cstart*bs; 299 MatSetValues(baij->A,1,&row,1,&col,&val,addv); 300 } 301 else { 302 if (mat->was_assembled) { 303 if (!baij->colmap) {ierr = CreateColmap_MPIBAIJ_Private(mat); CHKERRQ(ierr);} 304 col = baij->colmap[col/bs]*bs + col%bs; 305 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 306 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 307 col = (int) PetscReal(values[3*i+1]); 308 } 309 } 310 MatSetValues(baij->B,1,&row,1,&col,&val,addv); 311 } 312 } 313 count--; 314 } 315 PetscFree(baij->recv_waits); PetscFree(baij->rvalues); 316 317 /* wait on sends */ 318 if (baij->nsends) { 319 send_status = (MPI_Status *) PetscMalloc(baij->nsends*sizeof(MPI_Status)); 320 CHKPTRQ(send_status); 321 MPI_Waitall(baij->nsends,baij->send_waits,send_status); 322 PetscFree(send_status); 323 } 324 PetscFree(baij->send_waits); PetscFree(baij->svalues); 325 326 baij->insertmode = NOT_SET_VALUES; 327 ierr = MatAssemblyBegin(baij->A,mode); CHKERRQ(ierr); 328 ierr = MatAssemblyEnd(baij->A,mode); CHKERRQ(ierr); 329 330 /* determine if any processor has disassembled, if so we must 331 also disassemble ourselfs, in order that we may reassemble. */ 332 MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm); 333 if (mat->was_assembled && !other_disassembled) { 334 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 335 } 336 337 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 338 ierr = MatSetUpMultiply_MPIBAIJ(mat); CHKERRQ(ierr); 339 } 340 ierr = MatAssemblyBegin(baij->B,mode); CHKERRQ(ierr); 341 ierr = MatAssemblyEnd(baij->B,mode); CHKERRQ(ierr); 342 343 if (baij->rowvalues) {PetscFree(baij->rowvalues); baij->rowvalues = 0;} 344 return 0; 345 } 346 347 static int MatView_MPIBAIJ_Binary(Mat mat,Viewer viewer) 348 { 349 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 350 int ierr; 351 352 if (baij->size == 1) { 353 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 354 } 355 else SETERRQ(1,"MatView_MPIBAIJ_Binary:Only uniprocessor output supported"); 356 return 0; 357 } 358 359 static int MatView_MPIBAIJ_ASCIIorDraworMatlab(Mat mat,Viewer viewer) 360 { 361 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 362 int ierr, format,rank,bs=baij->bs; 363 FILE *fd; 364 ViewerType vtype; 365 366 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 367 if (vtype == ASCII_FILES_VIEWER || vtype == ASCII_FILE_VIEWER) { 368 ierr = ViewerGetFormat(viewer,&format); 369 if (format == ASCII_FORMAT_INFO_DETAILED) { 370 int nz, nzalloc, mem; 371 MPI_Comm_rank(mat->comm,&rank); 372 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 373 ierr = MatGetInfo(mat,MAT_LOCAL,&nz,&nzalloc,&mem); 374 PetscSequentialPhaseBegin(mat->comm,1); 375 fprintf(fd,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 376 rank,baij->m,nz*bs,nzalloc*bs,baij->bs,mem); 377 ierr = MatGetInfo(baij->A,MAT_LOCAL,&nz,&nzalloc,&mem); 378 fprintf(fd,"[%d] on-diagonal part: nz %d \n",rank,nz*bs); 379 ierr = MatGetInfo(baij->B,MAT_LOCAL,&nz,&nzalloc,&mem); 380 fprintf(fd,"[%d] off-diagonal part: nz %d \n",rank,nz*bs); 381 fflush(fd); 382 PetscSequentialPhaseEnd(mat->comm,1); 383 ierr = VecScatterView(baij->Mvctx,viewer); CHKERRQ(ierr); 384 return 0; 385 } 386 else if (format == ASCII_FORMAT_INFO) { 387 return 0; 388 } 389 } 390 391 if (vtype == DRAW_VIEWER) { 392 Draw draw; 393 PetscTruth isnull; 394 ierr = ViewerDrawGetDraw(viewer,&draw); CHKERRQ(ierr); 395 ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); if (isnull) return 0; 396 } 397 398 if (vtype == ASCII_FILE_VIEWER) { 399 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 400 PetscSequentialPhaseBegin(mat->comm,1); 401 fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n", 402 baij->rank,baij->m,baij->rstart*bs,baij->rend*bs,baij->n, 403 baij->cstart*bs,baij->cend*bs); 404 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 405 ierr = MatView(baij->B,viewer); CHKERRQ(ierr); 406 fflush(fd); 407 PetscSequentialPhaseEnd(mat->comm,1); 408 } 409 else { 410 int size = baij->size; 411 rank = baij->rank; 412 if (size == 1) { 413 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 414 } 415 else { 416 /* assemble the entire matrix onto first processor. */ 417 Mat A; 418 Mat_SeqBAIJ *Aloc; 419 int M = baij->M, N = baij->N,*ai,*aj,row,col,i,j,k,*rvals; 420 int mbs=baij->mbs; 421 Scalar *a; 422 423 if (!rank) { 424 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A); 425 CHKERRQ(ierr); 426 } 427 else { 428 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A); 429 CHKERRQ(ierr); 430 } 431 PLogObjectParent(mat,A); 432 433 /* copy over the A part */ 434 Aloc = (Mat_SeqBAIJ*) baij->A->data; 435 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 436 row = baij->rstart; 437 rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals); 438 439 for ( i=0; i<mbs; i++ ) { 440 rvals[0] = bs*(baij->rstart + i); 441 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 442 for ( j=ai[i]; j<ai[i+1]; j++ ) { 443 col = (baij->cstart+aj[j])*bs; 444 for (k=0; k<bs; k++ ) { 445 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 446 col++; a += bs; 447 } 448 } 449 } 450 /* copy over the B part */ 451 Aloc = (Mat_SeqBAIJ*) baij->B->data; 452 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 453 row = baij->rstart*bs; 454 for ( i=0; i<mbs; i++ ) { 455 rvals[0] = bs*(baij->rstart + i); 456 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 457 for ( j=ai[i]; j<ai[i+1]; j++ ) { 458 col = baij->garray[aj[j]]*bs; 459 for (k=0; k<bs; k++ ) { 460 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 461 col++; a += bs; 462 } 463 } 464 } 465 PetscFree(rvals); 466 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 467 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 468 if (!rank) { 469 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,viewer); CHKERRQ(ierr); 470 } 471 ierr = MatDestroy(A); CHKERRQ(ierr); 472 } 473 } 474 return 0; 475 } 476 477 478 479 static int MatView_MPIBAIJ(PetscObject obj,Viewer viewer) 480 { 481 Mat mat = (Mat) obj; 482 int ierr; 483 ViewerType vtype; 484 485 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 486 if (vtype == ASCII_FILE_VIEWER || vtype == ASCII_FILES_VIEWER || 487 vtype == DRAW_VIEWER || vtype == MATLAB_VIEWER) { 488 ierr = MatView_MPIBAIJ_ASCIIorDraworMatlab(mat,viewer); CHKERRQ(ierr); 489 } 490 else if (vtype == BINARY_FILE_VIEWER) { 491 return MatView_MPIBAIJ_Binary(mat,viewer); 492 } 493 return 0; 494 } 495 496 static int MatDestroy_MPIBAIJ(PetscObject obj) 497 { 498 Mat mat = (Mat) obj; 499 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 500 int ierr; 501 502 #if defined(PETSC_LOG) 503 PLogObjectState(obj,"Rows=%d, Cols=%d",baij->M,baij->N); 504 #endif 505 506 PetscFree(baij->rowners); 507 ierr = MatDestroy(baij->A); CHKERRQ(ierr); 508 ierr = MatDestroy(baij->B); CHKERRQ(ierr); 509 if (baij->colmap) PetscFree(baij->colmap); 510 if (baij->garray) PetscFree(baij->garray); 511 if (baij->lvec) VecDestroy(baij->lvec); 512 if (baij->Mvctx) VecScatterDestroy(baij->Mvctx); 513 if (baij->rowvalues) PetscFree(baij->rowvalues); 514 PetscFree(baij); 515 PLogObjectDestroy(mat); 516 PetscHeaderDestroy(mat); 517 return 0; 518 } 519 520 static int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 521 { 522 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 523 int ierr, nt; 524 525 ierr = VecGetLocalSize(xx,&nt); CHKERRQ(ierr); 526 if (nt != a->n) { 527 SETERRQ(1,"MatMult_MPIAIJ:Incompatible parition of A and xx"); 528 } 529 ierr = VecGetLocalSize(yy,&nt); CHKERRQ(ierr); 530 if (nt != a->m) { 531 SETERRQ(1,"MatMult_MPIAIJ:Incompatible parition of A and yy"); 532 } 533 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_ALL,a->Mvctx); CHKERRQ(ierr); 534 ierr = (*a->A->ops.mult)(a->A,xx,yy); CHKERRQ(ierr); 535 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_ALL,a->Mvctx); CHKERRQ(ierr); 536 ierr = (*a->B->ops.multadd)(a->B,a->lvec,yy,yy); CHKERRQ(ierr); 537 return 0; 538 } 539 540 static int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 541 { 542 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 543 int ierr; 544 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_ALL,a->Mvctx);CHKERRQ(ierr); 545 ierr = (*a->A->ops.multadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 546 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_ALL,a->Mvctx);CHKERRQ(ierr); 547 ierr = (*a->B->ops.multadd)(a->B,a->lvec,zz,zz); CHKERRQ(ierr); 548 return 0; 549 } 550 551 static int MatMultTrans_MPIBAIJ(Mat A,Vec xx,Vec yy) 552 { 553 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 554 int ierr; 555 556 /* do nondiagonal part */ 557 ierr = (*a->B->ops.multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 558 /* send it on its way */ 559 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES, 560 (ScatterMode)(SCATTER_ALL|SCATTER_REVERSE),a->Mvctx); CHKERRQ(ierr); 561 /* do local part */ 562 ierr = (*a->A->ops.multtrans)(a->A,xx,yy); CHKERRQ(ierr); 563 /* receive remote parts: note this assumes the values are not actually */ 564 /* inserted in yy until the next line, which is true for my implementation*/ 565 /* but is not perhaps always true. */ 566 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES, 567 (ScatterMode)(SCATTER_ALL|SCATTER_REVERSE),a->Mvctx); CHKERRQ(ierr); 568 return 0; 569 } 570 571 static int MatMultTransAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 572 { 573 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 574 int ierr; 575 576 /* do nondiagonal part */ 577 ierr = (*a->B->ops.multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 578 /* send it on its way */ 579 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES, 580 (ScatterMode)(SCATTER_ALL|SCATTER_REVERSE),a->Mvctx); CHKERRQ(ierr); 581 /* do local part */ 582 ierr = (*a->A->ops.multtransadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 583 /* receive remote parts: note this assumes the values are not actually */ 584 /* inserted in yy until the next line, which is true for my implementation*/ 585 /* but is not perhaps always true. */ 586 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES, 587 (ScatterMode)(SCATTER_ALL|SCATTER_REVERSE),a->Mvctx); CHKERRQ(ierr); 588 return 0; 589 } 590 591 /* 592 This only works correctly for square matrices where the subblock A->A is the 593 diagonal block 594 */ 595 static int MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 596 { 597 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 598 if (a->M != a->N) 599 SETERRQ(1,"MatGetDiagonal_MPIBAIJ:Supports only square matrix where A->A is diag block"); 600 return MatGetDiagonal(a->A,v); 601 } 602 603 static int MatScale_MPIBAIJ(Scalar *aa,Mat A) 604 { 605 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 606 int ierr; 607 ierr = MatScale(aa,a->A); CHKERRQ(ierr); 608 ierr = MatScale(aa,a->B); CHKERRQ(ierr); 609 return 0; 610 } 611 static int MatGetSize_MPIBAIJ(Mat matin,int *m,int *n) 612 { 613 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 614 *m = mat->M; *n = mat->N; 615 return 0; 616 } 617 618 static int MatGetLocalSize_MPIBAIJ(Mat matin,int *m,int *n) 619 { 620 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 621 *m = mat->m; *n = mat->N; 622 return 0; 623 } 624 625 static int MatGetOwnershipRange_MPIBAIJ(Mat matin,int *m,int *n) 626 { 627 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 628 *m = mat->rstart*mat->bs; *n = mat->rend*mat->bs; 629 return 0; 630 } 631 632 extern int MatGetRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 633 extern int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 634 635 int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 636 { 637 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 638 Scalar *vworkA, *vworkB, **pvA, **pvB,*v_p; 639 int bs = mat->bs, bs2 = mat->bs2, i, ierr, *cworkA, *cworkB, **pcA, **pcB; 640 int nztot, nzA, nzB, lrow, brstart = mat->rstart*bs, brend = mat->rend*bs; 641 int *cmap, *idx_p,cstart = mat->cstart; 642 643 if (mat->getrowactive == PETSC_TRUE) SETERRQ(1,"MatGetRow_MPIBAIJ:Already active"); 644 mat->getrowactive = PETSC_TRUE; 645 646 if (!mat->rowvalues && (idx || v)) { 647 /* 648 allocate enough space to hold information from the longest row. 649 */ 650 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ *) mat->A->data,*Ba = (Mat_SeqBAIJ *) mat->B->data; 651 int max = 1,mbs = mat->mbs,tmp; 652 for ( i=0; i<mbs; i++ ) { 653 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 654 if (max < tmp) { max = tmp; } 655 } 656 mat->rowvalues = (Scalar *) PetscMalloc( max*bs2*(sizeof(int)+sizeof(Scalar))); 657 CHKPTRQ(mat->rowvalues); 658 mat->rowindices = (int *) (mat->rowvalues + max*bs2); 659 } 660 661 662 if (row < brstart || row >= brend) SETERRQ(1,"MatGetRow_MPIBAIJ:Only local rows") 663 lrow = row - brstart; 664 665 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 666 if (!v) {pvA = 0; pvB = 0;} 667 if (!idx) {pcA = 0; if (!v) pcB = 0;} 668 ierr = (*mat->A->ops.getrow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 669 ierr = (*mat->B->ops.getrow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 670 nztot = nzA + nzB; 671 672 cmap = mat->garray; 673 if (v || idx) { 674 if (nztot) { 675 /* Sort by increasing column numbers, assuming A and B already sorted */ 676 int imark = -1; 677 if (v) { 678 *v = v_p = mat->rowvalues; 679 for ( i=0; i<nzB; i++ ) { 680 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 681 else break; 682 } 683 imark = i; 684 for ( i=0; i<nzA; i++ ) v_p[imark+i] = vworkA[i]; 685 for ( i=imark; i<nzB; i++ ) v_p[nzA+i] = vworkB[i]; 686 } 687 if (idx) { 688 *idx = idx_p = mat->rowindices; 689 if (imark > -1) { 690 for ( i=0; i<imark; i++ ) { 691 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 692 } 693 } else { 694 for ( i=0; i<nzB; i++ ) { 695 if (cmap[cworkB[i]/bs] < cstart) 696 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 697 else break; 698 } 699 imark = i; 700 } 701 for ( i=0; i<nzA; i++ ) idx_p[imark+i] = cstart*bs + cworkA[i]; 702 for ( i=imark; i<nzB; i++ ) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 703 } 704 } 705 else { 706 if (idx) *idx = 0; 707 if (v) *v = 0; 708 } 709 } 710 *nz = nztot; 711 ierr = (*mat->A->ops.restorerow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 712 ierr = (*mat->B->ops.restorerow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 713 return 0; 714 } 715 716 int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 717 { 718 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 719 if (baij->getrowactive == PETSC_FALSE) { 720 SETERRQ(1,"MatRestoreRow_MPIBAIJ:MatGetRow not called"); 721 } 722 baij->getrowactive = PETSC_FALSE; 723 return 0; 724 } 725 726 /* -------------------------------------------------------------------*/ 727 static struct _MatOps MatOps = { 728 MatSetValues_MPIBAIJ,MatGetRow_MPIBAIJ,MatRestoreRow_MPIBAIJ,MatMult_MPIBAIJ, 729 MatMultAdd_MPIBAIJ,MatMultTrans_MPIBAIJ,MatMultTransAdd_MPIBAIJ,0, 730 0,0,0,0, 731 0,0,0,0, 732 0,MatGetDiagonal_MPIBAIJ,0,MatNorm_MPIBAIJ, 733 MatAssemblyBegin_MPIBAIJ,MatAssemblyEnd_MPIBAIJ,0,0, 734 0,0,MatGetReordering_MPIBAIJ,0, 735 0,0,0,MatGetSize_MPIBAIJ, 736 MatGetLocalSize_MPIBAIJ,MatGetOwnershipRange_MPIBAIJ,0,0, 737 0,0,0,0, 738 0,0,0,0, 739 0,0,0,MatGetSubMatrices_MPIBAIJ, 740 MatIncreaseOverlap_MPIBAIJ,MatGetValues_MPIBAIJ,0,0, 741 MatScale_MPIBAIJ,0,0}; 742 743 744 /*@C 745 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 746 (block compressed row). For good matrix assembly performance 747 the user should preallocate the matrix storage by setting the parameters 748 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 749 performance can be increased by more than a factor of 50. 750 751 Input Parameters: 752 . comm - MPI communicator 753 . bs - size of blockk 754 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 755 This value should be the same as the local size used in creating the 756 y vector for the matrix-vector product y = Ax. 757 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 758 This value should be the same as the local size used in creating the 759 x vector for the matrix-vector product y = Ax. 760 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 761 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 762 . d_nz - number of block nonzeros per block row in diagonal portion of local 763 submatrix (same for all local rows) 764 . d_nzz - array containing the number of block nonzeros in the various block rows 765 of the in diagonal portion of the local (possibly different for each block 766 row) or PETSC_NULL. You must leave room for the diagonal entry even if 767 it is zero. 768 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 769 submatrix (same for all local rows). 770 . o_nzz - array containing the number of nonzeros in the various block rows of the 771 off-diagonal portion of the local submatrix (possibly different for 772 each block row) or PETSC_NULL. 773 774 Output Parameter: 775 . A - the matrix 776 777 Notes: 778 The user MUST specify either the local or global matrix dimensions 779 (possibly both). 780 781 Storage Information: 782 For a square global matrix we define each processor's diagonal portion 783 to be its local rows and the corresponding columns (a square submatrix); 784 each processor's off-diagonal portion encompasses the remainder of the 785 local matrix (a rectangular submatrix). 786 787 The user can specify preallocated storage for the diagonal part of 788 the local submatrix with either d_nz or d_nnz (not both). Set 789 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 790 memory allocation. Likewise, specify preallocated storage for the 791 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 792 793 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 794 the figure below we depict these three local rows and all columns (0-11). 795 796 $ 0 1 2 3 4 5 6 7 8 9 10 11 797 $ ------------------- 798 $ row 3 | o o o d d d o o o o o o 799 $ row 4 | o o o d d d o o o o o o 800 $ row 5 | o o o d d d o o o o o o 801 $ ------------------- 802 $ 803 804 Thus, any entries in the d locations are stored in the d (diagonal) 805 submatrix, and any entries in the o locations are stored in the 806 o (off-diagonal) submatrix. Note that the d and the o submatrices are 807 stored simply in the MATSEQBAIJ format for compressed row storage. 808 809 Now d_nz should indicate the number of nonzeros per row in the d matrix, 810 and o_nz should indicate the number of nonzeros per row in the o matrix. 811 In general, for PDE problems in which most nonzeros are near the diagonal, 812 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 813 or you will get TERRIBLE performance; see the users' manual chapter on 814 matrices and the file $(PETSC_DIR)/Performance. 815 816 .keywords: matrix, block, aij, compressed row, sparse, parallel 817 818 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues() 819 @*/ 820 int MatCreateMPIBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N, 821 int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 822 { 823 Mat B; 824 Mat_MPIBAIJ *b; 825 int ierr, i,sum[2],work[2],mbs,nbs,Mbs=PETSC_DECIDE,Nbs=PETSC_DECIDE; 826 827 if (bs < 1) SETERRQ(1,"MatCreateMPIBAIJ: invalid block size specified"); 828 *A = 0; 829 PetscHeaderCreate(B,_Mat,MAT_COOKIE,MATMPIBAIJ,comm); 830 PLogObjectCreate(B); 831 B->data = (void *) (b = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(b); 832 PetscMemzero(b,sizeof(Mat_MPIBAIJ)); 833 PetscMemcpy(&B->ops,&MatOps,sizeof(struct _MatOps)); 834 B->destroy = MatDestroy_MPIBAIJ; 835 B->view = MatView_MPIBAIJ; 836 837 B->factor = 0; 838 B->assembled = PETSC_FALSE; 839 840 b->insertmode = NOT_SET_VALUES; 841 MPI_Comm_rank(comm,&b->rank); 842 MPI_Comm_size(comm,&b->size); 843 844 if ( m == PETSC_DECIDE && (d_nnz != PETSC_NULL || o_nnz != PETSC_NULL)) 845 SETERRQ(1,"MatCreateMPIBAIJ:Cannot have PETSC_DECIDE rows but set d_nnz or o_nnz"); 846 if ( M == PETSC_DECIDE && m == PETSC_DECIDE) SETERRQ(1,"MatCreateMPIBAIJ: either M or m should be specified"); 847 if ( M == PETSC_DECIDE && n == PETSC_DECIDE)SETERRQ(1,"MatCreateMPIBAIJ: either N or n should be specified"); 848 if ( M != PETSC_DECIDE && m != PETSC_DECIDE) M = PETSC_DECIDE; 849 if ( N != PETSC_DECIDE && n != PETSC_DECIDE) N = PETSC_DECIDE; 850 851 if (M == PETSC_DECIDE || N == PETSC_DECIDE) { 852 work[0] = m; work[1] = n; 853 mbs = m/bs; nbs = n/bs; 854 MPI_Allreduce( work, sum,2,MPI_INT,MPI_SUM,comm ); 855 if (M == PETSC_DECIDE) {M = sum[0]; Mbs = M/bs;} 856 if (N == PETSC_DECIDE) {N = sum[1]; Nbs = N/bs;} 857 } 858 if (m == PETSC_DECIDE) { 859 Mbs = M/bs; 860 if (Mbs*bs != M) SETERRQ(1,"MatCreateMPIBAIJ: No of global rows must be divisible by blocksize"); 861 mbs = Mbs/b->size + ((Mbs % b->size) > b->rank); 862 m = mbs*bs; 863 } 864 if (n == PETSC_DECIDE) { 865 Nbs = N/bs; 866 if (Nbs*bs != N) SETERRQ(1,"MatCreateMPIBAIJ: No of global cols must be divisible by blocksize"); 867 nbs = Nbs/b->size + ((Nbs % b->size) > b->rank); 868 n = nbs*bs; 869 } 870 if (mbs*bs != m || nbs*bs != n) SETERRQ(1,"MatCreateMPIBAIJ: No of local rows, cols must be divisible by blocksize"); 871 872 b->m = m; B->m = m; 873 b->n = n; B->n = n; 874 b->N = N; B->N = N; 875 b->M = M; B->M = M; 876 b->bs = bs; 877 b->bs2 = bs*bs; 878 b->mbs = mbs; 879 b->nbs = nbs; 880 b->Mbs = Mbs; 881 b->Nbs = Nbs; 882 883 /* build local table of row and column ownerships */ 884 b->rowners = (int *) PetscMalloc(2*(b->size+2)*sizeof(int)); CHKPTRQ(b->rowners); 885 PLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _Mat)+sizeof(Mat_MPIBAIJ)); 886 b->cowners = b->rowners + b->size + 1; 887 MPI_Allgather(&mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,comm); 888 b->rowners[0] = 0; 889 for ( i=2; i<=b->size; i++ ) { 890 b->rowners[i] += b->rowners[i-1]; 891 } 892 b->rstart = b->rowners[b->rank]; 893 b->rend = b->rowners[b->rank+1]; 894 MPI_Allgather(&nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,comm); 895 b->cowners[0] = 0; 896 for ( i=2; i<=b->size; i++ ) { 897 b->cowners[i] += b->cowners[i-1]; 898 } 899 b->cstart = b->cowners[b->rank]; 900 b->cend = b->cowners[b->rank+1]; 901 902 if (d_nz == PETSC_DEFAULT) d_nz = 5; 903 ierr = MatCreateSeqBAIJ(MPI_COMM_SELF,bs,m,n,d_nz,d_nnz,&b->A); CHKERRQ(ierr); 904 PLogObjectParent(B,b->A); 905 if (o_nz == PETSC_DEFAULT) o_nz = 0; 906 ierr = MatCreateSeqBAIJ(MPI_COMM_SELF,bs,m,N,o_nz,o_nnz,&b->B); CHKERRQ(ierr); 907 PLogObjectParent(B,b->B); 908 909 /* build cache for off array entries formed */ 910 ierr = StashBuild_Private(&b->stash); CHKERRQ(ierr); 911 b->colmap = 0; 912 b->garray = 0; 913 b->roworiented = 1; 914 915 /* stuff used for matrix vector multiply */ 916 b->lvec = 0; 917 b->Mvctx = 0; 918 919 /* stuff for MatGetRow() */ 920 b->rowindices = 0; 921 b->rowvalues = 0; 922 b->getrowactive = PETSC_FALSE; 923 924 *A = B; 925 return 0; 926 } 927 928 #include "sys.h" 929 930 int MatLoad_MPIBAIJ(Viewer viewer,MatType type,Mat *newmat) 931 { 932 Mat A; 933 int i, nz, ierr, j,rstart, rend, fd; 934 Scalar *vals,*buf; 935 MPI_Comm comm = ((PetscObject)viewer)->comm; 936 MPI_Status status; 937 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 938 int *locrowlens,*sndcounts = 0,*procsnz = 0, jj,*mycols,*ibuf; 939 int flg,tag = ((PetscObject)viewer)->tag,bs=1,bs2,Mbs,mbs,extra_rows; 940 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 941 int dcount,kmax,k,nzcount,tmp; 942 943 944 ierr = OptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,&flg);CHKERRQ(ierr); 945 bs2 = bs*bs; 946 947 MPI_Comm_size(comm,&size); MPI_Comm_rank(comm,&rank); 948 if (!rank) { 949 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 950 ierr = PetscBinaryRead(fd,(char *)header,4,BINARY_INT); CHKERRQ(ierr); 951 if (header[0] != MAT_COOKIE) SETERRQ(1,"MatLoad_MPIBAIJ:not matrix object"); 952 } 953 954 MPI_Bcast(header+1,3,MPI_INT,0,comm); 955 M = header[1]; N = header[2]; 956 957 958 if (M != N) SETERRQ(1,"MatLoad_SeqBAIJ:Can only do square matrices"); 959 960 /* 961 This code adds extra rows to make sure the number of rows is 962 divisible by the blocksize 963 */ 964 Mbs = M/bs; 965 extra_rows = bs - M + bs*(Mbs); 966 if (extra_rows == bs) extra_rows = 0; 967 else Mbs++; 968 if (extra_rows &&!rank) { 969 PLogInfo(0,"MatLoad_SeqBAIJ:Padding loaded matrix to match blocksize"); 970 } 971 /* determine ownership of all rows */ 972 mbs = Mbs/size + ((Mbs % size) > rank); 973 m = mbs * bs; 974 rowners = (int *) PetscMalloc(2*(size+2)*sizeof(int)); CHKPTRQ(rowners); 975 browners = rowners + size + 1; 976 MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm); 977 rowners[0] = 0; 978 for ( i=2; i<=size; i++ ) rowners[i] += rowners[i-1]; 979 for ( i=0; i<=size; i++ ) browners[i] = rowners[i]*bs; 980 rstart = rowners[rank]; 981 rend = rowners[rank+1]; 982 983 /* distribute row lengths to all processors */ 984 locrowlens = (int*) PetscMalloc( (rend-rstart)*bs*sizeof(int) ); CHKPTRQ(locrowlens); 985 if (!rank) { 986 rowlengths = (int*) PetscMalloc( (M+extra_rows)*sizeof(int) ); CHKPTRQ(rowlengths); 987 ierr = PetscBinaryRead(fd,rowlengths,M,BINARY_INT); CHKERRQ(ierr); 988 for ( i=0; i<extra_rows; i++ ) rowlengths[M+i] = 1; 989 sndcounts = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(sndcounts); 990 for ( i=0; i<size; i++ ) sndcounts[i] = browners[i+1] - browners[i]; 991 MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm); 992 PetscFree(sndcounts); 993 } 994 else { 995 MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT, 0,comm); 996 } 997 998 if (!rank) { 999 /* calculate the number of nonzeros on each processor */ 1000 procsnz = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(procsnz); 1001 PetscMemzero(procsnz,size*sizeof(int)); 1002 for ( i=0; i<size; i++ ) { 1003 for ( j=rowners[i]*bs; j< rowners[i+1]*bs; j++ ) { 1004 procsnz[i] += rowlengths[j]; 1005 } 1006 } 1007 PetscFree(rowlengths); 1008 1009 /* determine max buffer needed and allocate it */ 1010 maxnz = 0; 1011 for ( i=0; i<size; i++ ) { 1012 maxnz = PetscMax(maxnz,procsnz[i]); 1013 } 1014 cols = (int *) PetscMalloc( maxnz*sizeof(int) ); CHKPTRQ(cols); 1015 1016 /* read in my part of the matrix column indices */ 1017 nz = procsnz[0]; 1018 ibuf = (int *) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 1019 mycols = ibuf; 1020 if (size == 1) nz -= extra_rows; 1021 ierr = PetscBinaryRead(fd,mycols,nz,BINARY_INT); CHKERRQ(ierr); 1022 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 1023 1024 /* read in every ones (except the last) and ship off */ 1025 for ( i=1; i<size-1; i++ ) { 1026 nz = procsnz[i]; 1027 ierr = PetscBinaryRead(fd,cols,nz,BINARY_INT); CHKERRQ(ierr); 1028 MPI_Send(cols,nz,MPI_INT,i,tag,comm); 1029 } 1030 /* read in the stuff for the last proc */ 1031 if ( size != 1 ) { 1032 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 1033 ierr = PetscBinaryRead(fd,cols,nz,BINARY_INT); CHKERRQ(ierr); 1034 for ( i=0; i<extra_rows; i++ ) cols[nz+i] = M+i; 1035 MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm); 1036 } 1037 PetscFree(cols); 1038 } 1039 else { 1040 /* determine buffer space needed for message */ 1041 nz = 0; 1042 for ( i=0; i<m; i++ ) { 1043 nz += locrowlens[i]; 1044 } 1045 ibuf = (int*) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 1046 mycols = ibuf; 1047 /* receive message of column indices*/ 1048 MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status); 1049 MPI_Get_count(&status,MPI_INT,&maxnz); 1050 if (maxnz != nz) SETERRQ(1,"MatLoad_MPIBAIJ:something is wrong with file"); 1051 } 1052 1053 /* loop over local rows, determining number of off diagonal entries */ 1054 dlens = (int *) PetscMalloc( 2*(rend-rstart+1)*sizeof(int) ); CHKPTRQ(dlens); 1055 odlens = dlens + (rend-rstart); 1056 mask = (int *) PetscMalloc( 3*Mbs*sizeof(int) ); CHKPTRQ(mask); 1057 PetscMemzero(mask,3*Mbs*sizeof(int)); 1058 masked1 = mask + Mbs; 1059 masked2 = masked1 + Mbs; 1060 rowcount = 0; nzcount = 0; 1061 for ( i=0; i<mbs; i++ ) { 1062 dcount = 0; 1063 odcount = 0; 1064 for ( j=0; j<bs; j++ ) { 1065 kmax = locrowlens[rowcount]; 1066 for ( k=0; k<kmax; k++ ) { 1067 tmp = mycols[nzcount++]/bs; 1068 if (!mask[tmp]) { 1069 mask[tmp] = 1; 1070 if (tmp < rstart || tmp >= rend ) masked2[odcount++] = tmp; 1071 else masked1[dcount++] = tmp; 1072 } 1073 } 1074 rowcount++; 1075 } 1076 1077 dlens[i] = dcount; 1078 odlens[i] = odcount; 1079 1080 /* zero out the mask elements we set */ 1081 for ( j=0; j<dcount; j++ ) mask[masked1[j]] = 0; 1082 for ( j=0; j<odcount; j++ ) mask[masked2[j]] = 0; 1083 } 1084 1085 /* create our matrix */ 1086 ierr = MatCreateMPIBAIJ(comm,bs,m,PETSC_DECIDE,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat);CHKERRQ(ierr); 1087 A = *newmat; 1088 MatSetOption(A,MAT_COLUMNS_SORTED); 1089 1090 if (!rank) { 1091 buf = (Scalar *) PetscMalloc( maxnz*sizeof(Scalar) ); CHKPTRQ(buf); 1092 /* read in my part of the matrix numerical values */ 1093 nz = procsnz[0]; 1094 vals = buf; 1095 mycols = ibuf; 1096 if (size == 1) nz -= extra_rows; 1097 ierr = PetscBinaryRead(fd,vals,nz,BINARY_SCALAR); CHKERRQ(ierr); 1098 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 1099 /* insert into matrix */ 1100 jj = rstart*bs; 1101 for ( i=0; i<m; i++ ) { 1102 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 1103 mycols += locrowlens[i]; 1104 vals += locrowlens[i]; 1105 jj++; 1106 } 1107 /* read in other processors( except the last one) and ship out */ 1108 for ( i=1; i<size-1; i++ ) { 1109 nz = procsnz[i]; 1110 vals = buf; 1111 ierr = PetscBinaryRead(fd,vals,nz,BINARY_SCALAR); CHKERRQ(ierr); 1112 MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm); 1113 } 1114 /* the last proc */ 1115 if ( size != 1 ){ 1116 nz = procsnz[i] - extra_rows; 1117 vals = buf; 1118 ierr = PetscBinaryRead(fd,vals,nz,BINARY_SCALAR); CHKERRQ(ierr); 1119 for ( i=0; i<extra_rows; i++ ) vals[nz+i] = 1.0; 1120 MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm); 1121 } 1122 PetscFree(procsnz); 1123 } 1124 else { 1125 /* receive numeric values */ 1126 buf = (Scalar*) PetscMalloc( nz*sizeof(Scalar) ); CHKPTRQ(buf); 1127 1128 /* receive message of values*/ 1129 vals = buf; 1130 mycols = ibuf; 1131 MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status); 1132 MPI_Get_count(&status,MPIU_SCALAR,&maxnz); 1133 if (maxnz != nz) SETERRQ(1,"MatLoad_MPIBAIJ:something is wrong with file"); 1134 1135 /* insert into matrix */ 1136 jj = rstart*bs; 1137 for ( i=0; i<m; i++ ) { 1138 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 1139 mycols += locrowlens[i]; 1140 vals += locrowlens[i]; 1141 jj++; 1142 } 1143 } 1144 PetscFree(locrowlens); 1145 PetscFree(buf); 1146 PetscFree(ibuf); 1147 PetscFree(rowners); 1148 PetscFree(dlens); 1149 PetscFree(mask); 1150 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1151 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1152 return 0; 1153 } 1154 1155 1156