1 2 3 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 4 #include <petsc/private/vecimpl.h> 5 #include <petsc/private/isimpl.h> 6 #include <petscblaslapack.h> 7 #include <petscsf.h> 8 9 /*MC 10 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 11 12 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 13 and MATMPIAIJ otherwise. As a result, for single process communicators, 14 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 15 for communicators controlling multiple processes. It is recommended that you call both of 16 the above preallocation routines for simplicity. 17 18 Options Database Keys: 19 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 20 21 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 22 enough exist. 23 24 Level: beginner 25 26 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ 27 M*/ 28 29 /*MC 30 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 31 32 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 33 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 34 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 35 for communicators controlling multiple processes. It is recommended that you call both of 36 the above preallocation routines for simplicity. 37 38 Options Database Keys: 39 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 40 41 Level: beginner 42 43 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 44 M*/ 45 46 PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 51 PetscFunctionBegin; 52 if (mat->A) { 53 ierr = MatSetBlockSizes(mat->A,rbs,cbs);CHKERRQ(ierr); 54 ierr = MatSetBlockSizes(mat->B,rbs,1);CHKERRQ(ierr); 55 } 56 PetscFunctionReturn(0); 57 } 58 59 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 60 { 61 PetscErrorCode ierr; 62 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 63 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 64 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 65 const PetscInt *ia,*ib; 66 const MatScalar *aa,*bb; 67 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 68 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 69 70 PetscFunctionBegin; 71 *keptrows = 0; 72 ia = a->i; 73 ib = b->i; 74 for (i=0; i<m; i++) { 75 na = ia[i+1] - ia[i]; 76 nb = ib[i+1] - ib[i]; 77 if (!na && !nb) { 78 cnt++; 79 goto ok1; 80 } 81 aa = a->a + ia[i]; 82 for (j=0; j<na; j++) { 83 if (aa[j] != 0.0) goto ok1; 84 } 85 bb = b->a + ib[i]; 86 for (j=0; j <nb; j++) { 87 if (bb[j] != 0.0) goto ok1; 88 } 89 cnt++; 90 ok1:; 91 } 92 ierr = MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 93 if (!n0rows) PetscFunctionReturn(0); 94 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 95 cnt = 0; 96 for (i=0; i<m; i++) { 97 na = ia[i+1] - ia[i]; 98 nb = ib[i+1] - ib[i]; 99 if (!na && !nb) continue; 100 aa = a->a + ia[i]; 101 for (j=0; j<na;j++) { 102 if (aa[j] != 0.0) { 103 rows[cnt++] = rstart + i; 104 goto ok2; 105 } 106 } 107 bb = b->a + ib[i]; 108 for (j=0; j<nb; j++) { 109 if (bb[j] != 0.0) { 110 rows[cnt++] = rstart + i; 111 goto ok2; 112 } 113 } 114 ok2:; 115 } 116 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 117 PetscFunctionReturn(0); 118 } 119 120 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 121 { 122 PetscErrorCode ierr; 123 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 124 125 PetscFunctionBegin; 126 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 127 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 128 } else { 129 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 130 } 131 PetscFunctionReturn(0); 132 } 133 134 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 135 { 136 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 137 PetscErrorCode ierr; 138 PetscInt i,rstart,nrows,*rows; 139 140 PetscFunctionBegin; 141 *zrows = NULL; 142 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 143 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 144 for (i=0; i<nrows; i++) rows[i] += rstart; 145 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 146 PetscFunctionReturn(0); 147 } 148 149 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 150 { 151 PetscErrorCode ierr; 152 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 153 PetscInt i,n,*garray = aij->garray; 154 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 155 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 156 PetscReal *work; 157 158 PetscFunctionBegin; 159 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 160 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 161 if (type == NORM_2) { 162 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 163 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 164 } 165 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 166 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 167 } 168 } else if (type == NORM_1) { 169 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 170 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 171 } 172 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 173 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 174 } 175 } else if (type == NORM_INFINITY) { 176 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 177 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 178 } 179 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 180 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 181 } 182 183 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 184 if (type == NORM_INFINITY) { 185 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 186 } else { 187 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 188 } 189 ierr = PetscFree(work);CHKERRQ(ierr); 190 if (type == NORM_2) { 191 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 192 } 193 PetscFunctionReturn(0); 194 } 195 196 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 197 { 198 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 199 IS sis,gis; 200 PetscErrorCode ierr; 201 const PetscInt *isis,*igis; 202 PetscInt n,*iis,nsis,ngis,rstart,i; 203 204 PetscFunctionBegin; 205 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 206 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 207 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 208 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 209 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 210 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 211 212 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 213 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 215 n = ngis + nsis; 216 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 217 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 218 for (i=0; i<n; i++) iis[i] += rstart; 219 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 220 221 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 222 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 223 ierr = ISDestroy(&sis);CHKERRQ(ierr); 224 ierr = ISDestroy(&gis);CHKERRQ(ierr); 225 PetscFunctionReturn(0); 226 } 227 228 /* 229 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 230 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 231 232 Only for square matrices 233 234 Used by a preconditioner, hence PETSC_EXTERN 235 */ 236 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 237 { 238 PetscMPIInt rank,size; 239 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 240 PetscErrorCode ierr; 241 Mat mat; 242 Mat_SeqAIJ *gmata; 243 PetscMPIInt tag; 244 MPI_Status status; 245 PetscBool aij; 246 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 247 248 PetscFunctionBegin; 249 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 250 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 251 if (!rank) { 252 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 253 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 254 } 255 if (reuse == MAT_INITIAL_MATRIX) { 256 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 257 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 258 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 259 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 260 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 261 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 262 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 263 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 264 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 265 266 rowners[0] = 0; 267 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 268 rstart = rowners[rank]; 269 rend = rowners[rank+1]; 270 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 271 if (!rank) { 272 gmata = (Mat_SeqAIJ*) gmat->data; 273 /* send row lengths to all processors */ 274 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 275 for (i=1; i<size; i++) { 276 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 277 } 278 /* determine number diagonal and off-diagonal counts */ 279 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 280 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 281 jj = 0; 282 for (i=0; i<m; i++) { 283 for (j=0; j<dlens[i]; j++) { 284 if (gmata->j[jj] < rstart) ld[i]++; 285 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 286 jj++; 287 } 288 } 289 /* send column indices to other processes */ 290 for (i=1; i<size; i++) { 291 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 292 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 } 295 296 /* send numerical values to other processes */ 297 for (i=1; i<size; i++) { 298 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 299 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 300 } 301 gmataa = gmata->a; 302 gmataj = gmata->j; 303 304 } else { 305 /* receive row lengths */ 306 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 307 /* receive column indices */ 308 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 309 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 310 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 311 /* determine number diagonal and off-diagonal counts */ 312 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 313 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 314 jj = 0; 315 for (i=0; i<m; i++) { 316 for (j=0; j<dlens[i]; j++) { 317 if (gmataj[jj] < rstart) ld[i]++; 318 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 319 jj++; 320 } 321 } 322 /* receive numerical values */ 323 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 324 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 325 } 326 /* set preallocation */ 327 for (i=0; i<m; i++) { 328 dlens[i] -= olens[i]; 329 } 330 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 331 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 332 333 for (i=0; i<m; i++) { 334 dlens[i] += olens[i]; 335 } 336 cnt = 0; 337 for (i=0; i<m; i++) { 338 row = rstart + i; 339 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 340 cnt += dlens[i]; 341 } 342 if (rank) { 343 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 344 } 345 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 346 ierr = PetscFree(rowners);CHKERRQ(ierr); 347 348 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 349 350 *inmat = mat; 351 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 352 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 353 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 354 mat = *inmat; 355 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 356 if (!rank) { 357 /* send numerical values to other processes */ 358 gmata = (Mat_SeqAIJ*) gmat->data; 359 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 360 gmataa = gmata->a; 361 for (i=1; i<size; i++) { 362 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 363 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 364 } 365 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 366 } else { 367 /* receive numerical values from process 0*/ 368 nz = Ad->nz + Ao->nz; 369 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 370 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 371 } 372 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 373 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 374 ad = Ad->a; 375 ao = Ao->a; 376 if (mat->rmap->n) { 377 i = 0; 378 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 379 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 380 } 381 for (i=1; i<mat->rmap->n; i++) { 382 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 383 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 384 } 385 i--; 386 if (mat->rmap->n) { 387 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 388 } 389 if (rank) { 390 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 391 } 392 } 393 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 PetscFunctionReturn(0); 396 } 397 398 /* 399 Local utility routine that creates a mapping from the global column 400 number to the local number in the off-diagonal part of the local 401 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 402 a slightly higher hash table cost; without it it is not scalable (each processor 403 has an order N integer array but is fast to acess. 404 */ 405 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 406 { 407 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 408 PetscErrorCode ierr; 409 PetscInt n = aij->B->cmap->n,i; 410 411 PetscFunctionBegin; 412 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 413 #if defined(PETSC_USE_CTABLE) 414 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 415 for (i=0; i<n; i++) { 416 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 417 } 418 #else 419 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 420 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 421 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 422 #endif 423 PetscFunctionReturn(0); 424 } 425 426 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 427 { \ 428 if (col <= lastcol1) low1 = 0; \ 429 else high1 = nrow1; \ 430 lastcol1 = col;\ 431 while (high1-low1 > 5) { \ 432 t = (low1+high1)/2; \ 433 if (rp1[t] > col) high1 = t; \ 434 else low1 = t; \ 435 } \ 436 for (_i=low1; _i<high1; _i++) { \ 437 if (rp1[_i] > col) break; \ 438 if (rp1[_i] == col) { \ 439 if (addv == ADD_VALUES) ap1[_i] += value; \ 440 else ap1[_i] = value; \ 441 goto a_noinsert; \ 442 } \ 443 } \ 444 if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 445 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 446 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 447 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 448 N = nrow1++ - 1; a->nz++; high1++; \ 449 /* shift up all the later entries in this row */ \ 450 for (ii=N; ii>=_i; ii--) { \ 451 rp1[ii+1] = rp1[ii]; \ 452 ap1[ii+1] = ap1[ii]; \ 453 } \ 454 rp1[_i] = col; \ 455 ap1[_i] = value; \ 456 A->nonzerostate++;\ 457 a_noinsert: ; \ 458 ailen[row] = nrow1; \ 459 } 460 461 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 462 { \ 463 if (col <= lastcol2) low2 = 0; \ 464 else high2 = nrow2; \ 465 lastcol2 = col; \ 466 while (high2-low2 > 5) { \ 467 t = (low2+high2)/2; \ 468 if (rp2[t] > col) high2 = t; \ 469 else low2 = t; \ 470 } \ 471 for (_i=low2; _i<high2; _i++) { \ 472 if (rp2[_i] > col) break; \ 473 if (rp2[_i] == col) { \ 474 if (addv == ADD_VALUES) ap2[_i] += value; \ 475 else ap2[_i] = value; \ 476 goto b_noinsert; \ 477 } \ 478 } \ 479 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 480 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 481 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 482 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 483 N = nrow2++ - 1; b->nz++; high2++; \ 484 /* shift up all the later entries in this row */ \ 485 for (ii=N; ii>=_i; ii--) { \ 486 rp2[ii+1] = rp2[ii]; \ 487 ap2[ii+1] = ap2[ii]; \ 488 } \ 489 rp2[_i] = col; \ 490 ap2[_i] = value; \ 491 B->nonzerostate++; \ 492 b_noinsert: ; \ 493 bilen[row] = nrow2; \ 494 } 495 496 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 497 { 498 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 499 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 500 PetscErrorCode ierr; 501 PetscInt l,*garray = mat->garray,diag; 502 503 PetscFunctionBegin; 504 /* code only works for square matrices A */ 505 506 /* find size of row to the left of the diagonal part */ 507 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 508 row = row - diag; 509 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 510 if (garray[b->j[b->i[row]+l]] > diag) break; 511 } 512 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 513 514 /* diagonal part */ 515 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 516 517 /* right of diagonal part */ 518 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 519 PetscFunctionReturn(0); 520 } 521 522 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 523 { 524 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 525 PetscScalar value; 526 PetscErrorCode ierr; 527 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 528 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 529 PetscBool roworiented = aij->roworiented; 530 531 /* Some Variables required in the macro */ 532 Mat A = aij->A; 533 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 534 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 535 MatScalar *aa = a->a; 536 PetscBool ignorezeroentries = a->ignorezeroentries; 537 Mat B = aij->B; 538 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 539 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 540 MatScalar *ba = b->a; 541 542 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 543 PetscInt nonew; 544 MatScalar *ap1,*ap2; 545 546 PetscFunctionBegin; 547 for (i=0; i<m; i++) { 548 if (im[i] < 0) continue; 549 #if defined(PETSC_USE_DEBUG) 550 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 551 #endif 552 if (im[i] >= rstart && im[i] < rend) { 553 row = im[i] - rstart; 554 lastcol1 = -1; 555 rp1 = aj + ai[row]; 556 ap1 = aa + ai[row]; 557 rmax1 = aimax[row]; 558 nrow1 = ailen[row]; 559 low1 = 0; 560 high1 = nrow1; 561 lastcol2 = -1; 562 rp2 = bj + bi[row]; 563 ap2 = ba + bi[row]; 564 rmax2 = bimax[row]; 565 nrow2 = bilen[row]; 566 low2 = 0; 567 high2 = nrow2; 568 569 for (j=0; j<n; j++) { 570 if (roworiented) value = v[i*n+j]; 571 else value = v[i+j*m]; 572 if (in[j] >= cstart && in[j] < cend) { 573 col = in[j] - cstart; 574 nonew = a->nonew; 575 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 576 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 577 } else if (in[j] < 0) continue; 578 #if defined(PETSC_USE_DEBUG) 579 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 580 #endif 581 else { 582 if (mat->was_assembled) { 583 if (!aij->colmap) { 584 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 585 } 586 #if defined(PETSC_USE_CTABLE) 587 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 588 col--; 589 #else 590 col = aij->colmap[in[j]] - 1; 591 #endif 592 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 593 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 594 col = in[j]; 595 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 596 B = aij->B; 597 b = (Mat_SeqAIJ*)B->data; 598 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 599 rp2 = bj + bi[row]; 600 ap2 = ba + bi[row]; 601 rmax2 = bimax[row]; 602 nrow2 = bilen[row]; 603 low2 = 0; 604 high2 = nrow2; 605 bm = aij->B->rmap->n; 606 ba = b->a; 607 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 608 } else col = in[j]; 609 nonew = b->nonew; 610 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 611 } 612 } 613 } else { 614 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 615 if (!aij->donotstash) { 616 mat->assembled = PETSC_FALSE; 617 if (roworiented) { 618 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 619 } else { 620 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } 622 } 623 } 624 } 625 PetscFunctionReturn(0); 626 } 627 628 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 629 { 630 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 631 PetscErrorCode ierr; 632 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 633 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 634 635 PetscFunctionBegin; 636 for (i=0; i<m; i++) { 637 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 638 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 639 if (idxm[i] >= rstart && idxm[i] < rend) { 640 row = idxm[i] - rstart; 641 for (j=0; j<n; j++) { 642 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 643 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 644 if (idxn[j] >= cstart && idxn[j] < cend) { 645 col = idxn[j] - cstart; 646 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 647 } else { 648 if (!aij->colmap) { 649 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 650 } 651 #if defined(PETSC_USE_CTABLE) 652 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 653 col--; 654 #else 655 col = aij->colmap[idxn[j]] - 1; 656 #endif 657 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 658 else { 659 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 660 } 661 } 662 } 663 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 664 } 665 PetscFunctionReturn(0); 666 } 667 668 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 669 670 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 671 { 672 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 673 PetscErrorCode ierr; 674 PetscInt nstash,reallocs; 675 676 PetscFunctionBegin; 677 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 678 679 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 680 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 681 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 682 PetscFunctionReturn(0); 683 } 684 685 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 686 { 687 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 688 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 689 PetscErrorCode ierr; 690 PetscMPIInt n; 691 PetscInt i,j,rstart,ncols,flg; 692 PetscInt *row,*col; 693 PetscBool other_disassembled; 694 PetscScalar *val; 695 696 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 697 698 PetscFunctionBegin; 699 if (!aij->donotstash && !mat->nooffprocentries) { 700 while (1) { 701 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 702 if (!flg) break; 703 704 for (i=0; i<n; ) { 705 /* Now identify the consecutive vals belonging to the same row */ 706 for (j=i,rstart=row[j]; j<n; j++) { 707 if (row[j] != rstart) break; 708 } 709 if (j < n) ncols = j-i; 710 else ncols = n-i; 711 /* Now assemble all these values with a single function call */ 712 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 713 714 i = j; 715 } 716 } 717 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 718 } 719 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 720 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 721 722 /* determine if any processor has disassembled, if so we must 723 also disassemble ourselfs, in order that we may reassemble. */ 724 /* 725 if nonzero structure of submatrix B cannot change then we know that 726 no processor disassembled thus we can skip this stuff 727 */ 728 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 729 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 730 if (mat->was_assembled && !other_disassembled) { 731 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 732 } 733 } 734 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 735 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 736 } 737 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 738 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 739 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 740 741 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 742 743 aij->rowvalues = 0; 744 745 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 746 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 747 748 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 749 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 750 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 751 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 752 } 753 PetscFunctionReturn(0); 754 } 755 756 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 757 { 758 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 759 PetscErrorCode ierr; 760 761 PetscFunctionBegin; 762 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 763 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 764 PetscFunctionReturn(0); 765 } 766 767 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 768 { 769 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 770 PetscInt *lrows; 771 PetscInt r, len; 772 PetscErrorCode ierr; 773 774 PetscFunctionBegin; 775 /* get locally owned rows */ 776 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 777 /* fix right hand side if needed */ 778 if (x && b) { 779 const PetscScalar *xx; 780 PetscScalar *bb; 781 782 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 783 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 784 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 785 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 786 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 787 } 788 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 789 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 790 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 791 PetscBool cong; 792 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 793 if (cong) A->congruentlayouts = 1; 794 else A->congruentlayouts = 0; 795 } 796 if ((diag != 0.0) && A->congruentlayouts) { 797 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 798 } else if (diag != 0.0) { 799 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 800 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 801 for (r = 0; r < len; ++r) { 802 const PetscInt row = lrows[r] + A->rmap->rstart; 803 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 804 } 805 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 806 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 807 } else { 808 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 809 } 810 ierr = PetscFree(lrows);CHKERRQ(ierr); 811 812 /* only change matrix nonzero state if pattern was allowed to be changed */ 813 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 814 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 815 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 816 } 817 PetscFunctionReturn(0); 818 } 819 820 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 821 { 822 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 823 PetscErrorCode ierr; 824 PetscMPIInt n = A->rmap->n; 825 PetscInt i,j,r,m,p = 0,len = 0; 826 PetscInt *lrows,*owners = A->rmap->range; 827 PetscSFNode *rrows; 828 PetscSF sf; 829 const PetscScalar *xx; 830 PetscScalar *bb,*mask; 831 Vec xmask,lmask; 832 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 833 const PetscInt *aj, *ii,*ridx; 834 PetscScalar *aa; 835 836 PetscFunctionBegin; 837 /* Create SF where leaves are input rows and roots are owned rows */ 838 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 839 for (r = 0; r < n; ++r) lrows[r] = -1; 840 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 841 for (r = 0; r < N; ++r) { 842 const PetscInt idx = rows[r]; 843 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 844 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 845 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 846 } 847 rrows[r].rank = p; 848 rrows[r].index = rows[r] - owners[p]; 849 } 850 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 851 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 852 /* Collect flags for rows to be zeroed */ 853 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 854 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 855 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 856 /* Compress and put in row numbers */ 857 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 858 /* zero diagonal part of matrix */ 859 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 860 /* handle off diagonal part of matrix */ 861 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 862 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 863 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 864 for (i=0; i<len; i++) bb[lrows[i]] = 1; 865 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 866 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 867 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 868 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 869 if (x) { 870 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 871 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 872 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 873 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 874 } 875 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 876 /* remove zeroed rows of off diagonal matrix */ 877 ii = aij->i; 878 for (i=0; i<len; i++) { 879 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 880 } 881 /* loop over all elements of off process part of matrix zeroing removed columns*/ 882 if (aij->compressedrow.use) { 883 m = aij->compressedrow.nrows; 884 ii = aij->compressedrow.i; 885 ridx = aij->compressedrow.rindex; 886 for (i=0; i<m; i++) { 887 n = ii[i+1] - ii[i]; 888 aj = aij->j + ii[i]; 889 aa = aij->a + ii[i]; 890 891 for (j=0; j<n; j++) { 892 if (PetscAbsScalar(mask[*aj])) { 893 if (b) bb[*ridx] -= *aa*xx[*aj]; 894 *aa = 0.0; 895 } 896 aa++; 897 aj++; 898 } 899 ridx++; 900 } 901 } else { /* do not use compressed row format */ 902 m = l->B->rmap->n; 903 for (i=0; i<m; i++) { 904 n = ii[i+1] - ii[i]; 905 aj = aij->j + ii[i]; 906 aa = aij->a + ii[i]; 907 for (j=0; j<n; j++) { 908 if (PetscAbsScalar(mask[*aj])) { 909 if (b) bb[i] -= *aa*xx[*aj]; 910 *aa = 0.0; 911 } 912 aa++; 913 aj++; 914 } 915 } 916 } 917 if (x) { 918 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 919 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 920 } 921 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 922 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 923 ierr = PetscFree(lrows);CHKERRQ(ierr); 924 925 /* only change matrix nonzero state if pattern was allowed to be changed */ 926 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 927 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 928 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 929 } 930 PetscFunctionReturn(0); 931 } 932 933 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 934 { 935 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 936 PetscErrorCode ierr; 937 PetscInt nt; 938 939 PetscFunctionBegin; 940 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 941 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 942 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 943 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 944 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 946 PetscFunctionReturn(0); 947 } 948 949 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 950 { 951 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 952 PetscErrorCode ierr; 953 954 PetscFunctionBegin; 955 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 956 PetscFunctionReturn(0); 957 } 958 959 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 960 { 961 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 962 PetscErrorCode ierr; 963 964 PetscFunctionBegin; 965 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 966 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 967 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } 971 972 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 973 { 974 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 975 PetscErrorCode ierr; 976 PetscBool merged; 977 978 PetscFunctionBegin; 979 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 980 /* do nondiagonal part */ 981 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 982 if (!merged) { 983 /* send it on its way */ 984 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 985 /* do local part */ 986 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 987 /* receive remote parts: note this assumes the values are not actually */ 988 /* added in yy until the next line, */ 989 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 990 } else { 991 /* do local part */ 992 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 993 /* send it on its way */ 994 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 995 /* values actually were received in the Begin() but we need to call this nop */ 996 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 } 998 PetscFunctionReturn(0); 999 } 1000 1001 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1002 { 1003 MPI_Comm comm; 1004 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1005 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1006 IS Me,Notme; 1007 PetscErrorCode ierr; 1008 PetscInt M,N,first,last,*notme,i; 1009 PetscMPIInt size; 1010 1011 PetscFunctionBegin; 1012 /* Easy test: symmetric diagonal block */ 1013 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1014 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1015 if (!*f) PetscFunctionReturn(0); 1016 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1017 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1018 if (size == 1) PetscFunctionReturn(0); 1019 1020 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1021 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1022 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1023 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1024 for (i=0; i<first; i++) notme[i] = i; 1025 for (i=last; i<M; i++) notme[i-last+first] = i; 1026 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1027 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1028 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1029 Aoff = Aoffs[0]; 1030 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1031 Boff = Boffs[0]; 1032 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1033 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1034 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1035 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1036 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1037 ierr = PetscFree(notme);CHKERRQ(ierr); 1038 PetscFunctionReturn(0); 1039 } 1040 1041 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1042 { 1043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1044 PetscErrorCode ierr; 1045 1046 PetscFunctionBegin; 1047 /* do nondiagonal part */ 1048 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1049 /* send it on its way */ 1050 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1051 /* do local part */ 1052 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1053 /* receive remote parts */ 1054 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 /* 1059 This only works correctly for square matrices where the subblock A->A is the 1060 diagonal block 1061 */ 1062 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1063 { 1064 PetscErrorCode ierr; 1065 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1066 1067 PetscFunctionBegin; 1068 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1069 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1070 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1071 PetscFunctionReturn(0); 1072 } 1073 1074 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1075 { 1076 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1077 PetscErrorCode ierr; 1078 1079 PetscFunctionBegin; 1080 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1081 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1082 PetscFunctionReturn(0); 1083 } 1084 1085 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1086 { 1087 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 #if defined(PETSC_USE_LOG) 1092 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1093 #endif 1094 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1095 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1096 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1097 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1098 #if defined(PETSC_USE_CTABLE) 1099 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1100 #else 1101 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1102 #endif 1103 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1104 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1105 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1106 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1107 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1108 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1109 1110 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1118 #if defined(PETSC_HAVE_ELEMENTAL) 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1120 #endif 1121 #if defined(PETSC_HAVE_HYPRE) 1122 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1123 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1124 #endif 1125 PetscFunctionReturn(0); 1126 } 1127 1128 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1129 { 1130 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1131 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1132 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1133 PetscErrorCode ierr; 1134 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1135 int fd; 1136 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1137 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1138 PetscScalar *column_values; 1139 PetscInt message_count,flowcontrolcount; 1140 FILE *file; 1141 1142 PetscFunctionBegin; 1143 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1144 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1145 nz = A->nz + B->nz; 1146 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1147 if (!rank) { 1148 header[0] = MAT_FILE_CLASSID; 1149 header[1] = mat->rmap->N; 1150 header[2] = mat->cmap->N; 1151 1152 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1153 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1154 /* get largest number of rows any processor has */ 1155 rlen = mat->rmap->n; 1156 range = mat->rmap->range; 1157 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1158 } else { 1159 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1160 rlen = mat->rmap->n; 1161 } 1162 1163 /* load up the local row counts */ 1164 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1165 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1166 1167 /* store the row lengths to the file */ 1168 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1169 if (!rank) { 1170 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1171 for (i=1; i<size; i++) { 1172 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1173 rlen = range[i+1] - range[i]; 1174 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1175 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1176 } 1177 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1178 } else { 1179 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1180 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1181 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1182 } 1183 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1184 1185 /* load up the local column indices */ 1186 nzmax = nz; /* th processor needs space a largest processor needs */ 1187 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1188 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1189 cnt = 0; 1190 for (i=0; i<mat->rmap->n; i++) { 1191 for (j=B->i[i]; j<B->i[i+1]; j++) { 1192 if ((col = garray[B->j[j]]) > cstart) break; 1193 column_indices[cnt++] = col; 1194 } 1195 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1196 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1197 } 1198 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1199 1200 /* store the column indices to the file */ 1201 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1202 if (!rank) { 1203 MPI_Status status; 1204 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1205 for (i=1; i<size; i++) { 1206 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1207 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1208 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1209 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1210 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1211 } 1212 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1213 } else { 1214 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1215 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1216 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1217 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1218 } 1219 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1220 1221 /* load up the local column values */ 1222 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1223 cnt = 0; 1224 for (i=0; i<mat->rmap->n; i++) { 1225 for (j=B->i[i]; j<B->i[i+1]; j++) { 1226 if (garray[B->j[j]] > cstart) break; 1227 column_values[cnt++] = B->a[j]; 1228 } 1229 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1230 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1231 } 1232 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1233 1234 /* store the column values to the file */ 1235 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1236 if (!rank) { 1237 MPI_Status status; 1238 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1239 for (i=1; i<size; i++) { 1240 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1241 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1242 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1243 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1244 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1245 } 1246 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1247 } else { 1248 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1249 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1250 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1251 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1252 } 1253 ierr = PetscFree(column_values);CHKERRQ(ierr); 1254 1255 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1256 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1257 PetscFunctionReturn(0); 1258 } 1259 1260 #include <petscdraw.h> 1261 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1262 { 1263 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1264 PetscErrorCode ierr; 1265 PetscMPIInt rank = aij->rank,size = aij->size; 1266 PetscBool isdraw,iascii,isbinary; 1267 PetscViewer sviewer; 1268 PetscViewerFormat format; 1269 1270 PetscFunctionBegin; 1271 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1272 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1274 if (iascii) { 1275 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1276 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1277 MatInfo info; 1278 PetscBool inodes; 1279 1280 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1281 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1282 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1283 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1284 if (!inodes) { 1285 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1286 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1287 } else { 1288 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1289 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1290 } 1291 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1292 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1293 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1297 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1298 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1299 PetscFunctionReturn(0); 1300 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1301 PetscInt inodecount,inodelimit,*inodes; 1302 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1303 if (inodes) { 1304 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1305 } else { 1306 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1307 } 1308 PetscFunctionReturn(0); 1309 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1310 PetscFunctionReturn(0); 1311 } 1312 } else if (isbinary) { 1313 if (size == 1) { 1314 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1315 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1316 } else { 1317 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1318 } 1319 PetscFunctionReturn(0); 1320 } else if (isdraw) { 1321 PetscDraw draw; 1322 PetscBool isnull; 1323 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1324 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1325 if (isnull) PetscFunctionReturn(0); 1326 } 1327 1328 { 1329 /* assemble the entire matrix onto first processor. */ 1330 Mat A; 1331 Mat_SeqAIJ *Aloc; 1332 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1333 MatScalar *a; 1334 1335 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1336 if (!rank) { 1337 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1338 } else { 1339 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1340 } 1341 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1342 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1343 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1344 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1345 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1346 1347 /* copy over the A part */ 1348 Aloc = (Mat_SeqAIJ*)aij->A->data; 1349 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1350 row = mat->rmap->rstart; 1351 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1352 for (i=0; i<m; i++) { 1353 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1354 row++; 1355 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1356 } 1357 aj = Aloc->j; 1358 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1359 1360 /* copy over the B part */ 1361 Aloc = (Mat_SeqAIJ*)aij->B->data; 1362 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1363 row = mat->rmap->rstart; 1364 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1365 ct = cols; 1366 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1367 for (i=0; i<m; i++) { 1368 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1369 row++; 1370 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1371 } 1372 ierr = PetscFree(ct);CHKERRQ(ierr); 1373 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1374 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1375 /* 1376 Everyone has to call to draw the matrix since the graphics waits are 1377 synchronized across all processors that share the PetscDraw object 1378 */ 1379 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1380 if (!rank) { 1381 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1382 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1383 } 1384 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1385 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1386 ierr = MatDestroy(&A);CHKERRQ(ierr); 1387 } 1388 PetscFunctionReturn(0); 1389 } 1390 1391 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1392 { 1393 PetscErrorCode ierr; 1394 PetscBool iascii,isdraw,issocket,isbinary; 1395 1396 PetscFunctionBegin; 1397 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1398 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1401 if (iascii || isdraw || isbinary || issocket) { 1402 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1403 } 1404 PetscFunctionReturn(0); 1405 } 1406 1407 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1408 { 1409 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1410 PetscErrorCode ierr; 1411 Vec bb1 = 0; 1412 PetscBool hasop; 1413 1414 PetscFunctionBegin; 1415 if (flag == SOR_APPLY_UPPER) { 1416 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1417 PetscFunctionReturn(0); 1418 } 1419 1420 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1421 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1422 } 1423 1424 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1425 if (flag & SOR_ZERO_INITIAL_GUESS) { 1426 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1427 its--; 1428 } 1429 1430 while (its--) { 1431 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1432 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1433 1434 /* update rhs: bb1 = bb - B*x */ 1435 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1436 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1437 1438 /* local sweep */ 1439 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1440 } 1441 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1442 if (flag & SOR_ZERO_INITIAL_GUESS) { 1443 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1444 its--; 1445 } 1446 while (its--) { 1447 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1448 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1449 1450 /* update rhs: bb1 = bb - B*x */ 1451 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1452 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1453 1454 /* local sweep */ 1455 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1456 } 1457 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1458 if (flag & SOR_ZERO_INITIAL_GUESS) { 1459 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1460 its--; 1461 } 1462 while (its--) { 1463 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1464 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1465 1466 /* update rhs: bb1 = bb - B*x */ 1467 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1468 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1469 1470 /* local sweep */ 1471 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1472 } 1473 } else if (flag & SOR_EISENSTAT) { 1474 Vec xx1; 1475 1476 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1477 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1478 1479 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1480 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1481 if (!mat->diag) { 1482 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1483 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1484 } 1485 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1486 if (hasop) { 1487 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1488 } else { 1489 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1490 } 1491 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1492 1493 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1494 1495 /* local sweep */ 1496 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1497 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1498 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1499 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1500 1501 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1502 1503 matin->factorerrortype = mat->A->factorerrortype; 1504 PetscFunctionReturn(0); 1505 } 1506 1507 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1508 { 1509 Mat aA,aB,Aperm; 1510 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1511 PetscScalar *aa,*ba; 1512 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1513 PetscSF rowsf,sf; 1514 IS parcolp = NULL; 1515 PetscBool done; 1516 PetscErrorCode ierr; 1517 1518 PetscFunctionBegin; 1519 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1520 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1521 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1522 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1523 1524 /* Invert row permutation to find out where my rows should go */ 1525 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1526 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1527 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1528 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1529 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1530 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1531 1532 /* Invert column permutation to find out where my columns should go */ 1533 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1534 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1535 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1536 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1537 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1538 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1539 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1540 1541 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1542 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1543 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1544 1545 /* Find out where my gcols should go */ 1546 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1547 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1548 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1549 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1550 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1551 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1552 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1553 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1554 1555 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1556 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1557 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1558 for (i=0; i<m; i++) { 1559 PetscInt row = rdest[i],rowner; 1560 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1561 for (j=ai[i]; j<ai[i+1]; j++) { 1562 PetscInt cowner,col = cdest[aj[j]]; 1563 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1564 if (rowner == cowner) dnnz[i]++; 1565 else onnz[i]++; 1566 } 1567 for (j=bi[i]; j<bi[i+1]; j++) { 1568 PetscInt cowner,col = gcdest[bj[j]]; 1569 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1570 if (rowner == cowner) dnnz[i]++; 1571 else onnz[i]++; 1572 } 1573 } 1574 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1575 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1578 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1579 1580 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1581 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1582 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1583 for (i=0; i<m; i++) { 1584 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1585 PetscInt j0,rowlen; 1586 rowlen = ai[i+1] - ai[i]; 1587 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1588 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1589 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1590 } 1591 rowlen = bi[i+1] - bi[i]; 1592 for (j0=j=0; j<rowlen; j0=j) { 1593 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1594 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1595 } 1596 } 1597 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1598 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1599 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1600 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1601 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1602 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1603 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1604 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1605 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1606 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1607 *B = Aperm; 1608 PetscFunctionReturn(0); 1609 } 1610 1611 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1612 { 1613 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1614 PetscErrorCode ierr; 1615 1616 PetscFunctionBegin; 1617 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1618 if (ghosts) *ghosts = aij->garray; 1619 PetscFunctionReturn(0); 1620 } 1621 1622 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1623 { 1624 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1625 Mat A = mat->A,B = mat->B; 1626 PetscErrorCode ierr; 1627 PetscReal isend[5],irecv[5]; 1628 1629 PetscFunctionBegin; 1630 info->block_size = 1.0; 1631 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1632 1633 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1634 isend[3] = info->memory; isend[4] = info->mallocs; 1635 1636 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1637 1638 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1639 isend[3] += info->memory; isend[4] += info->mallocs; 1640 if (flag == MAT_LOCAL) { 1641 info->nz_used = isend[0]; 1642 info->nz_allocated = isend[1]; 1643 info->nz_unneeded = isend[2]; 1644 info->memory = isend[3]; 1645 info->mallocs = isend[4]; 1646 } else if (flag == MAT_GLOBAL_MAX) { 1647 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1648 1649 info->nz_used = irecv[0]; 1650 info->nz_allocated = irecv[1]; 1651 info->nz_unneeded = irecv[2]; 1652 info->memory = irecv[3]; 1653 info->mallocs = irecv[4]; 1654 } else if (flag == MAT_GLOBAL_SUM) { 1655 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1656 1657 info->nz_used = irecv[0]; 1658 info->nz_allocated = irecv[1]; 1659 info->nz_unneeded = irecv[2]; 1660 info->memory = irecv[3]; 1661 info->mallocs = irecv[4]; 1662 } 1663 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1664 info->fill_ratio_needed = 0; 1665 info->factor_mallocs = 0; 1666 PetscFunctionReturn(0); 1667 } 1668 1669 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1670 { 1671 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1672 PetscErrorCode ierr; 1673 1674 PetscFunctionBegin; 1675 switch (op) { 1676 case MAT_NEW_NONZERO_LOCATIONS: 1677 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1678 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1679 case MAT_KEEP_NONZERO_PATTERN: 1680 case MAT_NEW_NONZERO_LOCATION_ERR: 1681 case MAT_USE_INODES: 1682 case MAT_IGNORE_ZERO_ENTRIES: 1683 MatCheckPreallocated(A,1); 1684 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1685 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1686 break; 1687 case MAT_ROW_ORIENTED: 1688 MatCheckPreallocated(A,1); 1689 a->roworiented = flg; 1690 1691 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1692 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1693 break; 1694 case MAT_NEW_DIAGONALS: 1695 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1696 break; 1697 case MAT_IGNORE_OFF_PROC_ENTRIES: 1698 a->donotstash = flg; 1699 break; 1700 case MAT_SPD: 1701 A->spd_set = PETSC_TRUE; 1702 A->spd = flg; 1703 if (flg) { 1704 A->symmetric = PETSC_TRUE; 1705 A->structurally_symmetric = PETSC_TRUE; 1706 A->symmetric_set = PETSC_TRUE; 1707 A->structurally_symmetric_set = PETSC_TRUE; 1708 } 1709 break; 1710 case MAT_SYMMETRIC: 1711 MatCheckPreallocated(A,1); 1712 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1713 break; 1714 case MAT_STRUCTURALLY_SYMMETRIC: 1715 MatCheckPreallocated(A,1); 1716 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1717 break; 1718 case MAT_HERMITIAN: 1719 MatCheckPreallocated(A,1); 1720 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1721 break; 1722 case MAT_SYMMETRY_ETERNAL: 1723 MatCheckPreallocated(A,1); 1724 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1725 break; 1726 case MAT_SUBMAT_SINGLEIS: 1727 A->submat_singleis = flg; 1728 break; 1729 default: 1730 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1731 } 1732 PetscFunctionReturn(0); 1733 } 1734 1735 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1736 { 1737 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1738 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1739 PetscErrorCode ierr; 1740 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1741 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1742 PetscInt *cmap,*idx_p; 1743 1744 PetscFunctionBegin; 1745 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1746 mat->getrowactive = PETSC_TRUE; 1747 1748 if (!mat->rowvalues && (idx || v)) { 1749 /* 1750 allocate enough space to hold information from the longest row. 1751 */ 1752 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1753 PetscInt max = 1,tmp; 1754 for (i=0; i<matin->rmap->n; i++) { 1755 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1756 if (max < tmp) max = tmp; 1757 } 1758 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1759 } 1760 1761 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1762 lrow = row - rstart; 1763 1764 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1765 if (!v) {pvA = 0; pvB = 0;} 1766 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1767 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1768 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1769 nztot = nzA + nzB; 1770 1771 cmap = mat->garray; 1772 if (v || idx) { 1773 if (nztot) { 1774 /* Sort by increasing column numbers, assuming A and B already sorted */ 1775 PetscInt imark = -1; 1776 if (v) { 1777 *v = v_p = mat->rowvalues; 1778 for (i=0; i<nzB; i++) { 1779 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1780 else break; 1781 } 1782 imark = i; 1783 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1784 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1785 } 1786 if (idx) { 1787 *idx = idx_p = mat->rowindices; 1788 if (imark > -1) { 1789 for (i=0; i<imark; i++) { 1790 idx_p[i] = cmap[cworkB[i]]; 1791 } 1792 } else { 1793 for (i=0; i<nzB; i++) { 1794 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1795 else break; 1796 } 1797 imark = i; 1798 } 1799 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1800 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1801 } 1802 } else { 1803 if (idx) *idx = 0; 1804 if (v) *v = 0; 1805 } 1806 } 1807 *nz = nztot; 1808 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1809 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1810 PetscFunctionReturn(0); 1811 } 1812 1813 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1814 { 1815 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1816 1817 PetscFunctionBegin; 1818 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1819 aij->getrowactive = PETSC_FALSE; 1820 PetscFunctionReturn(0); 1821 } 1822 1823 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1824 { 1825 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1826 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1827 PetscErrorCode ierr; 1828 PetscInt i,j,cstart = mat->cmap->rstart; 1829 PetscReal sum = 0.0; 1830 MatScalar *v; 1831 1832 PetscFunctionBegin; 1833 if (aij->size == 1) { 1834 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1835 } else { 1836 if (type == NORM_FROBENIUS) { 1837 v = amat->a; 1838 for (i=0; i<amat->nz; i++) { 1839 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1840 } 1841 v = bmat->a; 1842 for (i=0; i<bmat->nz; i++) { 1843 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1844 } 1845 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1846 *norm = PetscSqrtReal(*norm); 1847 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1848 } else if (type == NORM_1) { /* max column norm */ 1849 PetscReal *tmp,*tmp2; 1850 PetscInt *jj,*garray = aij->garray; 1851 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1852 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1853 *norm = 0.0; 1854 v = amat->a; jj = amat->j; 1855 for (j=0; j<amat->nz; j++) { 1856 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1857 } 1858 v = bmat->a; jj = bmat->j; 1859 for (j=0; j<bmat->nz; j++) { 1860 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1861 } 1862 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1863 for (j=0; j<mat->cmap->N; j++) { 1864 if (tmp2[j] > *norm) *norm = tmp2[j]; 1865 } 1866 ierr = PetscFree(tmp);CHKERRQ(ierr); 1867 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1868 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1869 } else if (type == NORM_INFINITY) { /* max row norm */ 1870 PetscReal ntemp = 0.0; 1871 for (j=0; j<aij->A->rmap->n; j++) { 1872 v = amat->a + amat->i[j]; 1873 sum = 0.0; 1874 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1875 sum += PetscAbsScalar(*v); v++; 1876 } 1877 v = bmat->a + bmat->i[j]; 1878 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1879 sum += PetscAbsScalar(*v); v++; 1880 } 1881 if (sum > ntemp) ntemp = sum; 1882 } 1883 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1884 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1885 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1886 } 1887 PetscFunctionReturn(0); 1888 } 1889 1890 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1891 { 1892 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1893 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1894 PetscErrorCode ierr; 1895 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1896 PetscInt cstart = A->cmap->rstart,ncol; 1897 Mat B; 1898 MatScalar *array; 1899 1900 PetscFunctionBegin; 1901 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1902 1903 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1904 ai = Aloc->i; aj = Aloc->j; 1905 bi = Bloc->i; bj = Bloc->j; 1906 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1907 PetscInt *d_nnz,*g_nnz,*o_nnz; 1908 PetscSFNode *oloc; 1909 PETSC_UNUSED PetscSF sf; 1910 1911 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1912 /* compute d_nnz for preallocation */ 1913 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1914 for (i=0; i<ai[ma]; i++) { 1915 d_nnz[aj[i]]++; 1916 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1917 } 1918 /* compute local off-diagonal contributions */ 1919 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1920 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1921 /* map those to global */ 1922 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1923 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1924 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1925 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1926 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1927 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1928 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1929 1930 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1931 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1932 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1933 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1934 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1935 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1936 } else { 1937 B = *matout; 1938 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1939 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1940 } 1941 1942 /* copy over the A part */ 1943 array = Aloc->a; 1944 row = A->rmap->rstart; 1945 for (i=0; i<ma; i++) { 1946 ncol = ai[i+1]-ai[i]; 1947 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1948 row++; 1949 array += ncol; aj += ncol; 1950 } 1951 aj = Aloc->j; 1952 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1953 1954 /* copy over the B part */ 1955 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1956 array = Bloc->a; 1957 row = A->rmap->rstart; 1958 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1959 cols_tmp = cols; 1960 for (i=0; i<mb; i++) { 1961 ncol = bi[i+1]-bi[i]; 1962 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1963 row++; 1964 array += ncol; cols_tmp += ncol; 1965 } 1966 ierr = PetscFree(cols);CHKERRQ(ierr); 1967 1968 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1969 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1970 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1971 *matout = B; 1972 } else { 1973 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1974 } 1975 PetscFunctionReturn(0); 1976 } 1977 1978 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1979 { 1980 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1981 Mat a = aij->A,b = aij->B; 1982 PetscErrorCode ierr; 1983 PetscInt s1,s2,s3; 1984 1985 PetscFunctionBegin; 1986 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1987 if (rr) { 1988 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1989 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1990 /* Overlap communication with computation. */ 1991 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1992 } 1993 if (ll) { 1994 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1995 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1996 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1997 } 1998 /* scale the diagonal block */ 1999 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2000 2001 if (rr) { 2002 /* Do a scatter end and then right scale the off-diagonal block */ 2003 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2004 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2005 } 2006 PetscFunctionReturn(0); 2007 } 2008 2009 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2010 { 2011 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2012 PetscErrorCode ierr; 2013 2014 PetscFunctionBegin; 2015 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2016 PetscFunctionReturn(0); 2017 } 2018 2019 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2020 { 2021 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2022 Mat a,b,c,d; 2023 PetscBool flg; 2024 PetscErrorCode ierr; 2025 2026 PetscFunctionBegin; 2027 a = matA->A; b = matA->B; 2028 c = matB->A; d = matB->B; 2029 2030 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2031 if (flg) { 2032 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2033 } 2034 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2035 PetscFunctionReturn(0); 2036 } 2037 2038 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2039 { 2040 PetscErrorCode ierr; 2041 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2042 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2043 2044 PetscFunctionBegin; 2045 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2046 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2047 /* because of the column compression in the off-processor part of the matrix a->B, 2048 the number of columns in a->B and b->B may be different, hence we cannot call 2049 the MatCopy() directly on the two parts. If need be, we can provide a more 2050 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2051 then copying the submatrices */ 2052 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2053 } else { 2054 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2055 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2056 } 2057 PetscFunctionReturn(0); 2058 } 2059 2060 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2061 { 2062 PetscErrorCode ierr; 2063 2064 PetscFunctionBegin; 2065 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2066 PetscFunctionReturn(0); 2067 } 2068 2069 /* 2070 Computes the number of nonzeros per row needed for preallocation when X and Y 2071 have different nonzero structure. 2072 */ 2073 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2074 { 2075 PetscInt i,j,k,nzx,nzy; 2076 2077 PetscFunctionBegin; 2078 /* Set the number of nonzeros in the new matrix */ 2079 for (i=0; i<m; i++) { 2080 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2081 nzx = xi[i+1] - xi[i]; 2082 nzy = yi[i+1] - yi[i]; 2083 nnz[i] = 0; 2084 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2085 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2086 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2087 nnz[i]++; 2088 } 2089 for (; k<nzy; k++) nnz[i]++; 2090 } 2091 PetscFunctionReturn(0); 2092 } 2093 2094 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2095 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2096 { 2097 PetscErrorCode ierr; 2098 PetscInt m = Y->rmap->N; 2099 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2100 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2101 2102 PetscFunctionBegin; 2103 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2104 PetscFunctionReturn(0); 2105 } 2106 2107 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2108 { 2109 PetscErrorCode ierr; 2110 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2111 PetscBLASInt bnz,one=1; 2112 Mat_SeqAIJ *x,*y; 2113 2114 PetscFunctionBegin; 2115 if (str == SAME_NONZERO_PATTERN) { 2116 PetscScalar alpha = a; 2117 x = (Mat_SeqAIJ*)xx->A->data; 2118 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2119 y = (Mat_SeqAIJ*)yy->A->data; 2120 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2121 x = (Mat_SeqAIJ*)xx->B->data; 2122 y = (Mat_SeqAIJ*)yy->B->data; 2123 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2124 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2125 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2126 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2127 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2128 } else { 2129 Mat B; 2130 PetscInt *nnz_d,*nnz_o; 2131 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2132 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2133 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2134 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2135 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2136 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2137 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2138 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2139 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2140 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2141 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2142 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2143 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2144 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2145 } 2146 PetscFunctionReturn(0); 2147 } 2148 2149 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2150 2151 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2152 { 2153 #if defined(PETSC_USE_COMPLEX) 2154 PetscErrorCode ierr; 2155 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2156 2157 PetscFunctionBegin; 2158 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2159 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2160 #else 2161 PetscFunctionBegin; 2162 #endif 2163 PetscFunctionReturn(0); 2164 } 2165 2166 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2167 { 2168 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2169 PetscErrorCode ierr; 2170 2171 PetscFunctionBegin; 2172 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2173 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2174 PetscFunctionReturn(0); 2175 } 2176 2177 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2178 { 2179 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2180 PetscErrorCode ierr; 2181 2182 PetscFunctionBegin; 2183 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2184 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2185 PetscFunctionReturn(0); 2186 } 2187 2188 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2189 { 2190 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2191 PetscErrorCode ierr; 2192 PetscInt i,*idxb = 0; 2193 PetscScalar *va,*vb; 2194 Vec vtmp; 2195 2196 PetscFunctionBegin; 2197 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2198 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2199 if (idx) { 2200 for (i=0; i<A->rmap->n; i++) { 2201 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2202 } 2203 } 2204 2205 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2206 if (idx) { 2207 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2208 } 2209 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2210 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2211 2212 for (i=0; i<A->rmap->n; i++) { 2213 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2214 va[i] = vb[i]; 2215 if (idx) idx[i] = a->garray[idxb[i]]; 2216 } 2217 } 2218 2219 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2220 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2221 ierr = PetscFree(idxb);CHKERRQ(ierr); 2222 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2223 PetscFunctionReturn(0); 2224 } 2225 2226 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2227 { 2228 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2229 PetscErrorCode ierr; 2230 PetscInt i,*idxb = 0; 2231 PetscScalar *va,*vb; 2232 Vec vtmp; 2233 2234 PetscFunctionBegin; 2235 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2236 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2237 if (idx) { 2238 for (i=0; i<A->cmap->n; i++) { 2239 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2240 } 2241 } 2242 2243 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2244 if (idx) { 2245 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2246 } 2247 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2248 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2249 2250 for (i=0; i<A->rmap->n; i++) { 2251 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2252 va[i] = vb[i]; 2253 if (idx) idx[i] = a->garray[idxb[i]]; 2254 } 2255 } 2256 2257 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2258 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2259 ierr = PetscFree(idxb);CHKERRQ(ierr); 2260 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2261 PetscFunctionReturn(0); 2262 } 2263 2264 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2265 { 2266 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2267 PetscInt n = A->rmap->n; 2268 PetscInt cstart = A->cmap->rstart; 2269 PetscInt *cmap = mat->garray; 2270 PetscInt *diagIdx, *offdiagIdx; 2271 Vec diagV, offdiagV; 2272 PetscScalar *a, *diagA, *offdiagA; 2273 PetscInt r; 2274 PetscErrorCode ierr; 2275 2276 PetscFunctionBegin; 2277 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2278 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2279 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2280 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2281 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2282 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2283 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2284 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2285 for (r = 0; r < n; ++r) { 2286 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2287 a[r] = diagA[r]; 2288 idx[r] = cstart + diagIdx[r]; 2289 } else { 2290 a[r] = offdiagA[r]; 2291 idx[r] = cmap[offdiagIdx[r]]; 2292 } 2293 } 2294 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2295 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2296 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2297 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2298 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2299 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2300 PetscFunctionReturn(0); 2301 } 2302 2303 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2304 { 2305 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2306 PetscInt n = A->rmap->n; 2307 PetscInt cstart = A->cmap->rstart; 2308 PetscInt *cmap = mat->garray; 2309 PetscInt *diagIdx, *offdiagIdx; 2310 Vec diagV, offdiagV; 2311 PetscScalar *a, *diagA, *offdiagA; 2312 PetscInt r; 2313 PetscErrorCode ierr; 2314 2315 PetscFunctionBegin; 2316 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2317 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2318 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2319 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2320 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2321 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2322 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2323 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2324 for (r = 0; r < n; ++r) { 2325 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2326 a[r] = diagA[r]; 2327 idx[r] = cstart + diagIdx[r]; 2328 } else { 2329 a[r] = offdiagA[r]; 2330 idx[r] = cmap[offdiagIdx[r]]; 2331 } 2332 } 2333 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2334 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2335 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2336 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2337 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2338 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2339 PetscFunctionReturn(0); 2340 } 2341 2342 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2343 { 2344 PetscErrorCode ierr; 2345 Mat *dummy; 2346 2347 PetscFunctionBegin; 2348 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2349 *newmat = *dummy; 2350 ierr = PetscFree(dummy);CHKERRQ(ierr); 2351 PetscFunctionReturn(0); 2352 } 2353 2354 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2355 { 2356 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2357 PetscErrorCode ierr; 2358 2359 PetscFunctionBegin; 2360 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2361 A->factorerrortype = a->A->factorerrortype; 2362 PetscFunctionReturn(0); 2363 } 2364 2365 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2366 { 2367 PetscErrorCode ierr; 2368 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2369 2370 PetscFunctionBegin; 2371 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2372 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2373 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2374 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2375 PetscFunctionReturn(0); 2376 } 2377 2378 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2379 { 2380 PetscFunctionBegin; 2381 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2382 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2383 PetscFunctionReturn(0); 2384 } 2385 2386 /*@ 2387 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2388 2389 Collective on Mat 2390 2391 Input Parameters: 2392 + A - the matrix 2393 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2394 2395 Level: advanced 2396 2397 @*/ 2398 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2399 { 2400 PetscErrorCode ierr; 2401 2402 PetscFunctionBegin; 2403 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2404 PetscFunctionReturn(0); 2405 } 2406 2407 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2408 { 2409 PetscErrorCode ierr; 2410 PetscBool sc = PETSC_FALSE,flg; 2411 2412 PetscFunctionBegin; 2413 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2414 ierr = PetscObjectOptionsBegin((PetscObject)A); 2415 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2416 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2417 if (flg) { 2418 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2419 } 2420 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2425 { 2426 PetscErrorCode ierr; 2427 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2428 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2429 2430 PetscFunctionBegin; 2431 if (!Y->preallocated) { 2432 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2433 } else if (!aij->nz) { 2434 PetscInt nonew = aij->nonew; 2435 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2436 aij->nonew = nonew; 2437 } 2438 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2439 PetscFunctionReturn(0); 2440 } 2441 2442 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2443 { 2444 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2445 PetscErrorCode ierr; 2446 2447 PetscFunctionBegin; 2448 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2449 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2450 if (d) { 2451 PetscInt rstart; 2452 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2453 *d += rstart; 2454 2455 } 2456 PetscFunctionReturn(0); 2457 } 2458 2459 2460 /* -------------------------------------------------------------------*/ 2461 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2462 MatGetRow_MPIAIJ, 2463 MatRestoreRow_MPIAIJ, 2464 MatMult_MPIAIJ, 2465 /* 4*/ MatMultAdd_MPIAIJ, 2466 MatMultTranspose_MPIAIJ, 2467 MatMultTransposeAdd_MPIAIJ, 2468 0, 2469 0, 2470 0, 2471 /*10*/ 0, 2472 0, 2473 0, 2474 MatSOR_MPIAIJ, 2475 MatTranspose_MPIAIJ, 2476 /*15*/ MatGetInfo_MPIAIJ, 2477 MatEqual_MPIAIJ, 2478 MatGetDiagonal_MPIAIJ, 2479 MatDiagonalScale_MPIAIJ, 2480 MatNorm_MPIAIJ, 2481 /*20*/ MatAssemblyBegin_MPIAIJ, 2482 MatAssemblyEnd_MPIAIJ, 2483 MatSetOption_MPIAIJ, 2484 MatZeroEntries_MPIAIJ, 2485 /*24*/ MatZeroRows_MPIAIJ, 2486 0, 2487 0, 2488 0, 2489 0, 2490 /*29*/ MatSetUp_MPIAIJ, 2491 0, 2492 0, 2493 MatGetDiagonalBlock_MPIAIJ, 2494 0, 2495 /*34*/ MatDuplicate_MPIAIJ, 2496 0, 2497 0, 2498 0, 2499 0, 2500 /*39*/ MatAXPY_MPIAIJ, 2501 MatCreateSubMatrices_MPIAIJ, 2502 MatIncreaseOverlap_MPIAIJ, 2503 MatGetValues_MPIAIJ, 2504 MatCopy_MPIAIJ, 2505 /*44*/ MatGetRowMax_MPIAIJ, 2506 MatScale_MPIAIJ, 2507 MatShift_MPIAIJ, 2508 MatDiagonalSet_MPIAIJ, 2509 MatZeroRowsColumns_MPIAIJ, 2510 /*49*/ MatSetRandom_MPIAIJ, 2511 0, 2512 0, 2513 0, 2514 0, 2515 /*54*/ MatFDColoringCreate_MPIXAIJ, 2516 0, 2517 MatSetUnfactored_MPIAIJ, 2518 MatPermute_MPIAIJ, 2519 0, 2520 /*59*/ MatCreateSubMatrix_MPIAIJ, 2521 MatDestroy_MPIAIJ, 2522 MatView_MPIAIJ, 2523 0, 2524 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2525 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2526 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2527 0, 2528 0, 2529 0, 2530 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2531 MatGetRowMinAbs_MPIAIJ, 2532 0, 2533 0, 2534 0, 2535 0, 2536 /*75*/ MatFDColoringApply_AIJ, 2537 MatSetFromOptions_MPIAIJ, 2538 0, 2539 0, 2540 MatFindZeroDiagonals_MPIAIJ, 2541 /*80*/ 0, 2542 0, 2543 0, 2544 /*83*/ MatLoad_MPIAIJ, 2545 0, 2546 0, 2547 0, 2548 0, 2549 0, 2550 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2551 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2552 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2553 MatPtAP_MPIAIJ_MPIAIJ, 2554 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2555 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2556 0, 2557 0, 2558 0, 2559 0, 2560 /*99*/ 0, 2561 0, 2562 0, 2563 MatConjugate_MPIAIJ, 2564 0, 2565 /*104*/MatSetValuesRow_MPIAIJ, 2566 MatRealPart_MPIAIJ, 2567 MatImaginaryPart_MPIAIJ, 2568 0, 2569 0, 2570 /*109*/0, 2571 0, 2572 MatGetRowMin_MPIAIJ, 2573 0, 2574 MatMissingDiagonal_MPIAIJ, 2575 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2576 0, 2577 MatGetGhosts_MPIAIJ, 2578 0, 2579 0, 2580 /*119*/0, 2581 0, 2582 0, 2583 0, 2584 MatGetMultiProcBlock_MPIAIJ, 2585 /*124*/MatFindNonzeroRows_MPIAIJ, 2586 MatGetColumnNorms_MPIAIJ, 2587 MatInvertBlockDiagonal_MPIAIJ, 2588 0, 2589 MatCreateSubMatricesMPI_MPIAIJ, 2590 /*129*/0, 2591 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2592 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2593 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2594 0, 2595 /*134*/0, 2596 0, 2597 0, 2598 0, 2599 0, 2600 /*139*/MatSetBlockSizes_MPIAIJ, 2601 0, 2602 0, 2603 MatFDColoringSetUp_MPIXAIJ, 2604 MatFindOffBlockDiagonalEntries_MPIAIJ, 2605 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2606 }; 2607 2608 /* ----------------------------------------------------------------------------------------*/ 2609 2610 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2611 { 2612 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2613 PetscErrorCode ierr; 2614 2615 PetscFunctionBegin; 2616 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2617 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2618 PetscFunctionReturn(0); 2619 } 2620 2621 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2622 { 2623 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2624 PetscErrorCode ierr; 2625 2626 PetscFunctionBegin; 2627 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2628 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2629 PetscFunctionReturn(0); 2630 } 2631 2632 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2633 { 2634 Mat_MPIAIJ *b; 2635 PetscErrorCode ierr; 2636 2637 PetscFunctionBegin; 2638 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2639 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2640 b = (Mat_MPIAIJ*)B->data; 2641 2642 #if defined(PETSC_USE_CTABLE) 2643 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2644 #else 2645 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2646 #endif 2647 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2648 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2649 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2650 2651 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2652 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2653 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2654 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2655 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2656 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2657 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2658 2659 if (!B->preallocated) { 2660 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2661 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2662 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2663 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2664 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2665 } 2666 2667 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2668 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2669 B->preallocated = PETSC_TRUE; 2670 B->was_assembled = PETSC_FALSE; 2671 B->assembled = PETSC_FALSE;; 2672 PetscFunctionReturn(0); 2673 } 2674 2675 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2676 { 2677 Mat mat; 2678 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2679 PetscErrorCode ierr; 2680 2681 PetscFunctionBegin; 2682 *newmat = 0; 2683 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2684 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2685 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2686 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2687 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2688 a = (Mat_MPIAIJ*)mat->data; 2689 2690 mat->factortype = matin->factortype; 2691 mat->assembled = PETSC_TRUE; 2692 mat->insertmode = NOT_SET_VALUES; 2693 mat->preallocated = PETSC_TRUE; 2694 2695 a->size = oldmat->size; 2696 a->rank = oldmat->rank; 2697 a->donotstash = oldmat->donotstash; 2698 a->roworiented = oldmat->roworiented; 2699 a->rowindices = 0; 2700 a->rowvalues = 0; 2701 a->getrowactive = PETSC_FALSE; 2702 2703 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2704 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2705 2706 if (oldmat->colmap) { 2707 #if defined(PETSC_USE_CTABLE) 2708 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2709 #else 2710 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2711 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2712 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2713 #endif 2714 } else a->colmap = 0; 2715 if (oldmat->garray) { 2716 PetscInt len; 2717 len = oldmat->B->cmap->n; 2718 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2719 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2720 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2721 } else a->garray = 0; 2722 2723 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2724 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2725 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2727 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2731 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2732 *newmat = mat; 2733 PetscFunctionReturn(0); 2734 } 2735 2736 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2737 { 2738 PetscScalar *vals,*svals; 2739 MPI_Comm comm; 2740 PetscErrorCode ierr; 2741 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2742 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2743 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2744 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2745 PetscInt cend,cstart,n,*rowners; 2746 int fd; 2747 PetscInt bs = newMat->rmap->bs; 2748 2749 PetscFunctionBegin; 2750 /* force binary viewer to load .info file if it has not yet done so */ 2751 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2752 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2753 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2754 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2755 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2756 if (!rank) { 2757 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2758 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2759 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2760 } 2761 2762 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2763 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2764 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2765 if (bs < 0) bs = 1; 2766 2767 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2768 M = header[1]; N = header[2]; 2769 2770 /* If global sizes are set, check if they are consistent with that given in the file */ 2771 if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M); 2772 if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N); 2773 2774 /* determine ownership of all (block) rows */ 2775 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2776 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2777 else m = newMat->rmap->n; /* Set by user */ 2778 2779 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2780 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2781 2782 /* First process needs enough room for process with most rows */ 2783 if (!rank) { 2784 mmax = rowners[1]; 2785 for (i=2; i<=size; i++) { 2786 mmax = PetscMax(mmax, rowners[i]); 2787 } 2788 } else mmax = -1; /* unused, but compilers complain */ 2789 2790 rowners[0] = 0; 2791 for (i=2; i<=size; i++) { 2792 rowners[i] += rowners[i-1]; 2793 } 2794 rstart = rowners[rank]; 2795 rend = rowners[rank+1]; 2796 2797 /* distribute row lengths to all processors */ 2798 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2799 if (!rank) { 2800 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2801 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2802 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2803 for (j=0; j<m; j++) { 2804 procsnz[0] += ourlens[j]; 2805 } 2806 for (i=1; i<size; i++) { 2807 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2808 /* calculate the number of nonzeros on each processor */ 2809 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2810 procsnz[i] += rowlengths[j]; 2811 } 2812 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2813 } 2814 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2815 } else { 2816 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2817 } 2818 2819 if (!rank) { 2820 /* determine max buffer needed and allocate it */ 2821 maxnz = 0; 2822 for (i=0; i<size; i++) { 2823 maxnz = PetscMax(maxnz,procsnz[i]); 2824 } 2825 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2826 2827 /* read in my part of the matrix column indices */ 2828 nz = procsnz[0]; 2829 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2830 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2831 2832 /* read in every one elses and ship off */ 2833 for (i=1; i<size; i++) { 2834 nz = procsnz[i]; 2835 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2836 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2837 } 2838 ierr = PetscFree(cols);CHKERRQ(ierr); 2839 } else { 2840 /* determine buffer space needed for message */ 2841 nz = 0; 2842 for (i=0; i<m; i++) { 2843 nz += ourlens[i]; 2844 } 2845 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2846 2847 /* receive message of column indices*/ 2848 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2849 } 2850 2851 /* determine column ownership if matrix is not square */ 2852 if (N != M) { 2853 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2854 else n = newMat->cmap->n; 2855 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2856 cstart = cend - n; 2857 } else { 2858 cstart = rstart; 2859 cend = rend; 2860 n = cend - cstart; 2861 } 2862 2863 /* loop over local rows, determining number of off diagonal entries */ 2864 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2865 jj = 0; 2866 for (i=0; i<m; i++) { 2867 for (j=0; j<ourlens[i]; j++) { 2868 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2869 jj++; 2870 } 2871 } 2872 2873 for (i=0; i<m; i++) { 2874 ourlens[i] -= offlens[i]; 2875 } 2876 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2877 2878 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2879 2880 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2881 2882 for (i=0; i<m; i++) { 2883 ourlens[i] += offlens[i]; 2884 } 2885 2886 if (!rank) { 2887 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2888 2889 /* read in my part of the matrix numerical values */ 2890 nz = procsnz[0]; 2891 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2892 2893 /* insert into matrix */ 2894 jj = rstart; 2895 smycols = mycols; 2896 svals = vals; 2897 for (i=0; i<m; i++) { 2898 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2899 smycols += ourlens[i]; 2900 svals += ourlens[i]; 2901 jj++; 2902 } 2903 2904 /* read in other processors and ship out */ 2905 for (i=1; i<size; i++) { 2906 nz = procsnz[i]; 2907 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2908 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2909 } 2910 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2911 } else { 2912 /* receive numeric values */ 2913 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2914 2915 /* receive message of values*/ 2916 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2917 2918 /* insert into matrix */ 2919 jj = rstart; 2920 smycols = mycols; 2921 svals = vals; 2922 for (i=0; i<m; i++) { 2923 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2924 smycols += ourlens[i]; 2925 svals += ourlens[i]; 2926 jj++; 2927 } 2928 } 2929 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2930 ierr = PetscFree(vals);CHKERRQ(ierr); 2931 ierr = PetscFree(mycols);CHKERRQ(ierr); 2932 ierr = PetscFree(rowners);CHKERRQ(ierr); 2933 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2934 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2935 PetscFunctionReturn(0); 2936 } 2937 2938 /* Not scalable because of ISAllGather() unless getting all columns. */ 2939 PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq) 2940 { 2941 PetscErrorCode ierr; 2942 IS iscol_local; 2943 PetscBool isstride; 2944 PetscMPIInt lisstride=0,gisstride; 2945 2946 PetscFunctionBegin; 2947 /* check if we are grabbing all columns*/ 2948 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2949 2950 if (isstride) { 2951 PetscInt start,len,mstart,mlen; 2952 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2953 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2954 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2955 if (mstart == start && mlen-mstart == len) lisstride = 1; 2956 } 2957 2958 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2959 if (gisstride) { 2960 PetscInt N; 2961 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2962 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2963 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2964 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2965 } else { 2966 PetscInt cbs; 2967 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2968 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2969 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2970 } 2971 2972 *isseq = iscol_local; 2973 PetscFunctionReturn(0); 2974 } 2975 2976 /* 2977 Used for avoiding ISAllGather() and global size of iscol_local (see MatCreateSubMatrix_MPIAIJ_nonscalable) 2978 2979 Input Parameters: 2980 mat - matrix 2981 iscol - parallel column index set; its local indices are a subset of local columns of mat, 2982 i.e., mat->cstart <= iscol[i] < mat->cend 2983 Output Parameter: 2984 iscol_sub - sequential column index set, a subset of iscol 2985 iscmap - column map; iscmap[i] indicates global location of iscol_sub[i] in iscol 2986 */ 2987 PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS iscol,IS *iscol_sub,IS *iscmap) 2988 { 2989 PetscErrorCode ierr; 2990 Vec x,cmap; 2991 const PetscInt *is_idx; 2992 PetscScalar *xarray,*cmaparray; 2993 PetscInt ncols,isstart,*idx,*camp,count; 2994 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 2995 Mat B=a->B; 2996 Vec lvec=a->lvec,lcmap; 2997 PetscInt i,cstart,cend,Bn=B->cmap->N; 2998 MPI_Comm comm; 2999 3000 PetscFunctionBegin; 3001 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3002 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 3003 3004 /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */ 3005 ierr = MatCreateVecs(mat,&x,NULL);CHKERRQ(ierr); 3006 ierr = VecDuplicate(x,&cmap);CHKERRQ(ierr); 3007 ierr = VecSet(x,-1.0);CHKERRQ(ierr); 3008 3009 /* get start indices */ 3010 ierr = MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3011 isstart -= ncols; 3012 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3013 3014 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3015 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 3016 ierr = VecGetArray(cmap,&cmaparray);CHKERRQ(ierr); 3017 for (i=0; i<ncols; i++) { 3018 xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i]; 3019 cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */ 3020 } 3021 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 3022 ierr = VecRestoreArray(cmap,&cmaparray);CHKERRQ(ierr); 3023 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3024 3025 /* (2) scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */ 3026 ierr = VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3027 3028 ierr = VecDuplicate(lvec,&lcmap);CHKERRQ(ierr); 3029 3030 ierr = VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3031 ierr = VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3032 3033 count = ncols + Bn; 3034 ierr = PetscMalloc2(count,&idx,count,&camp);CHKERRQ(ierr); 3035 3036 ierr = VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3037 3038 /* (3) create scalable iscol_sub (a subset of iscol) and iscmap */ 3039 /* local column indices */ 3040 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3041 for (i=0; i<ncols; i++) { 3042 idx[i] = is_idx[i]; 3043 camp[i] = i + isstart; /* global index of iscol = column index in submat */ 3044 } 3045 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3046 count = ncols; 3047 3048 /* off-process column indices */ 3049 ierr = VecGetArray(lvec,&xarray);CHKERRQ(ierr); 3050 ierr = VecGetArray(lcmap,&cmaparray);CHKERRQ(ierr); 3051 for (i=0; i<Bn; i++) { 3052 if (xarray[i] > -1.0) { 3053 idx[count] = (PetscInt)xarray[i]; 3054 camp[count++] = cmaparray[i]; /* column index in submat */ 3055 } 3056 } 3057 ierr = VecRestoreArray(lvec,&xarray);CHKERRQ(ierr); 3058 ierr = VecRestoreArray(lcmap,&cmaparray);CHKERRQ(ierr); 3059 3060 ierr = PetscSortIntWithArray(count,camp,idx);CHKERRQ(ierr); 3061 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_sub);CHKERRQ(ierr); 3062 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,camp,PETSC_COPY_VALUES,iscmap);CHKERRQ(ierr); 3063 3064 ierr = PetscFree2(idx,camp);CHKERRQ(ierr); 3065 ierr = VecDestroy(&x);CHKERRQ(ierr); 3066 ierr = VecDestroy(&cmap);CHKERRQ(ierr); 3067 ierr = VecDestroy(&lcmap);CHKERRQ(ierr); 3068 PetscFunctionReturn(0); 3069 } 3070 3071 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3072 { 3073 PetscErrorCode ierr; 3074 IS iscol_local; 3075 PetscInt csize; 3076 PetscInt n,i,j,rstart,rend; 3077 PetscBool sameRowDist=PETSC_FALSE,tsameRowDist; 3078 MPI_Comm comm; 3079 3080 PetscFunctionBegin; 3081 /* If isrow has same processor distribution as mat, 3082 call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */ 3083 if (call == MAT_REUSE_MATRIX) { 3084 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3085 if (iscol_local) tsameRowDist = PETSC_TRUE; 3086 } else { 3087 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3088 if (!n) { 3089 sameRowDist = PETSC_TRUE; 3090 } else { 3091 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3092 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3093 if (i >= rstart && j < rend) sameRowDist = PETSC_TRUE; 3094 } 3095 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3096 ierr = MPIU_Allreduce(&sameRowDist,&tsameRowDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3097 } 3098 3099 if (tsameRowDist) { 3100 ierr = MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3101 PetscFunctionReturn(0); 3102 } 3103 3104 /* General case: iscol -> iscol_local which has global size of iscol */ 3105 if (call == MAT_REUSE_MATRIX) { 3106 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3107 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3108 } else { 3109 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3110 } 3111 3112 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3113 ierr = MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3114 3115 if (call == MAT_INITIAL_MATRIX) { 3116 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3117 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3118 } 3119 PetscFunctionReturn(0); 3120 } 3121 3122 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3123 3124 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3125 { 3126 PetscErrorCode ierr; 3127 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3128 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3129 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3130 Mat M,Msub,B=a->B; 3131 MatScalar *aa; 3132 Mat_SeqAIJ *aij; 3133 PetscInt *garray = a->garray,*colsub,Ncols; 3134 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3135 IS iscol_sub,iscmap; 3136 const PetscInt *is_idx,*cmap; 3137 PetscBool sameColDist=PETSC_FALSE,tsameColDist,allcolumns=PETSC_FALSE; 3138 IS iscol_local=NULL; 3139 MPI_Comm comm; 3140 3141 PetscFunctionBegin; 3142 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3143 3144 if (call == MAT_INITIAL_MATRIX) { 3145 /* If iscol has same processor distribution as mat, then use a scalable routine */ 3146 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3147 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); 3148 if (!n) { 3149 sameColDist = PETSC_TRUE; 3150 } else { 3151 ierr = ISGetMinMax(iscol,&i,&j);CHKERRQ(ierr); 3152 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3153 if (i >= cstart && j < cend) sameColDist = PETSC_TRUE; 3154 } 3155 ierr = MPIU_Allreduce(&sameColDist,&tsameColDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3156 3157 /* (1) Create scalable iscol_sub and iscmap */ 3158 if (tsameColDist) { 3159 /* iscol has same processor distribution as mat, use a scalable routine to generate iscol_sub and iscmap */ 3160 ierr = ISGetSeqIS_SameColDist_Private(mat,iscol,&iscol_sub,&iscmap);CHKERRQ(ierr); 3161 3162 } else { /* iscol -> nonscalable iscol_local, then get scalable iscol_sub and iscmap */ 3163 PetscBool flg; 3164 3165 /* iscol -> nonscalable iscol_local */ 3166 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3167 ierr = ISGetLocalSize(iscol_local,&n);CHKERRQ(ierr); /* local size of iscol_local = global columns of newmat */ 3168 if (n != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != Ncols %d",n,Ncols); 3169 3170 /* Check for special case: each processor gets entire matrix columns */ 3171 ierr = ISIdentity(iscol_local,&flg);CHKERRQ(ierr); 3172 if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3173 if (allcolumns) { 3174 iscol_sub = iscol_local; 3175 ierr = PetscObjectReference((PetscObject)iscol_local);CHKERRQ(ierr); 3176 ierr = ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);CHKERRQ(ierr); 3177 3178 } else { /* iscol_local -> iscol_sub and iscmap */ 3179 PetscInt *idx,*cmap1,k; 3180 3181 /* implementation below requires iscol_local be sorted, it can have duplicate indices */ 3182 ierr = ISSorted(iscol_local,&flg);CHKERRQ(ierr); 3183 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unsorted iscol_local is not implemented yet"); 3184 3185 ierr = PetscMalloc2(Ncols,&idx,Ncols,&cmap1);CHKERRQ(ierr); 3186 ierr = ISGetIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3187 count = 0; 3188 k = 0; 3189 for (i=0; i<Ncols; i++) { 3190 j = is_idx[i]; 3191 if (j >= cstart && j < cend) { 3192 /* diagonal part of mat */ 3193 idx[count] = j; 3194 cmap1[count++] = i; /* column index in submat */ 3195 } else { 3196 /* off-diagonal part of mat */ 3197 if (j == garray[k]) { 3198 idx[count] = j; 3199 cmap1[count++] = i; /* column index in submat */ 3200 } else if (j > garray[k]) { 3201 while (j > garray[k] && k < Bn-1) k++; 3202 if (j == garray[k]) { 3203 idx[count] = j; 3204 cmap1[count++] = i; /* column index in submat */ 3205 } 3206 } 3207 } 3208 } 3209 ierr = ISRestoreIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3210 3211 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3212 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3213 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3214 } 3215 } 3216 3217 /* (2) Create sequential Msub */ 3218 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);CHKERRQ(ierr); 3219 3220 } else { /* call == MAT_REUSE_MATRIX */ 3221 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3222 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3223 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3224 3225 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3226 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3227 3228 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3229 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3230 3231 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3232 } 3233 3234 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3235 aij = (Mat_SeqAIJ*)(Msub)->data; 3236 ii = aij->i; 3237 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3238 3239 /* 3240 m - number of local rows 3241 Ncols - number of columns (same on all processors) 3242 rstart - first row in new global matrix generated 3243 */ 3244 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3245 3246 if (call == MAT_INITIAL_MATRIX) { 3247 /* (3) Create parallel newmat */ 3248 PetscMPIInt rank,size; 3249 PetscInt csize; 3250 3251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3252 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3253 3254 /* 3255 Determine the number of non-zeros in the diagonal and off-diagonal 3256 portions of the matrix in order to do correct preallocation 3257 */ 3258 3259 /* first get start and end of "diagonal" columns */ 3260 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3261 if (csize == PETSC_DECIDE) { 3262 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3263 if (mglobal == Ncols) { /* square matrix */ 3264 nlocal = m; 3265 } else { 3266 nlocal = Ncols/size + ((Ncols % size) > rank); 3267 } 3268 } else { 3269 nlocal = csize; 3270 } 3271 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3272 rstart = rend - nlocal; 3273 if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols); 3274 3275 /* next, compute all the lengths */ 3276 jj = aij->j; 3277 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3278 olens = dlens + m; 3279 for (i=0; i<m; i++) { 3280 jend = ii[i+1] - ii[i]; 3281 olen = 0; 3282 dlen = 0; 3283 for (j=0; j<jend; j++) { 3284 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3285 else dlen++; 3286 jj++; 3287 } 3288 olens[i] = olen; 3289 dlens[i] = dlen; 3290 } 3291 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3292 3293 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3294 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 3295 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3296 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3297 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3298 ierr = PetscFree(dlens);CHKERRQ(ierr); 3299 } else { 3300 M = *newmat; 3301 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3302 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3303 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3304 /* 3305 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3306 rather than the slower MatSetValues(). 3307 */ 3308 M->was_assembled = PETSC_TRUE; 3309 M->assembled = PETSC_FALSE; 3310 } 3311 3312 /* (4) Set values of Msub to *newmat */ 3313 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3314 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3315 3316 jj = aij->j; 3317 aa = aij->a; 3318 for (i=0; i<m; i++) { 3319 row = rstart + i; 3320 nz = ii[i+1] - ii[i]; 3321 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3322 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3323 jj += nz; aa += nz; 3324 } 3325 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3326 3327 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3328 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3329 *newmat = M; 3330 3331 ierr = PetscFree(colsub);CHKERRQ(ierr); 3332 3333 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3334 if (call == MAT_INITIAL_MATRIX) { 3335 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3336 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3337 3338 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3339 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3340 3341 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3342 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3343 3344 if (iscol_local) { 3345 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3346 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3347 } 3348 } 3349 PetscFunctionReturn(0); 3350 } 3351 3352 /* 3353 Not great since it makes two copies of the submatrix, first an SeqAIJ 3354 in local and then by concatenating the local matrices the end result. 3355 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3356 3357 Note: This requires a sequential iscol with all indices. 3358 */ 3359 PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3360 { 3361 PetscErrorCode ierr; 3362 PetscMPIInt rank,size; 3363 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3364 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3365 Mat M,Mreuse; 3366 MatScalar *aa,*vwork; 3367 MPI_Comm comm; 3368 Mat_SeqAIJ *aij; 3369 PetscBool colflag,allcolumns=PETSC_FALSE; 3370 3371 PetscFunctionBegin; 3372 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3373 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3374 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3375 3376 /* Check for special case: each processor gets entire matrix columns */ 3377 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3378 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3379 if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3380 3381 if (call == MAT_REUSE_MATRIX) { 3382 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3383 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3384 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3385 } else { 3386 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3387 } 3388 3389 /* 3390 m - number of local rows 3391 n - number of columns (same on all processors) 3392 rstart - first row in new global matrix generated 3393 */ 3394 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3395 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3396 if (call == MAT_INITIAL_MATRIX) { 3397 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3398 ii = aij->i; 3399 jj = aij->j; 3400 3401 /* 3402 Determine the number of non-zeros in the diagonal and off-diagonal 3403 portions of the matrix in order to do correct preallocation 3404 */ 3405 3406 /* first get start and end of "diagonal" columns */ 3407 if (csize == PETSC_DECIDE) { 3408 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3409 if (mglobal == n) { /* square matrix */ 3410 nlocal = m; 3411 } else { 3412 nlocal = n/size + ((n % size) > rank); 3413 } 3414 } else { 3415 nlocal = csize; 3416 } 3417 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3418 rstart = rend - nlocal; 3419 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3420 3421 /* next, compute all the lengths */ 3422 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3423 olens = dlens + m; 3424 for (i=0; i<m; i++) { 3425 jend = ii[i+1] - ii[i]; 3426 olen = 0; 3427 dlen = 0; 3428 for (j=0; j<jend; j++) { 3429 if (*jj < rstart || *jj >= rend) olen++; 3430 else dlen++; 3431 jj++; 3432 } 3433 olens[i] = olen; 3434 dlens[i] = dlen; 3435 } 3436 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3437 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3438 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3439 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3440 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3441 ierr = PetscFree(dlens);CHKERRQ(ierr); 3442 } else { 3443 PetscInt ml,nl; 3444 3445 M = *newmat; 3446 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3447 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3448 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3449 /* 3450 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3451 rather than the slower MatSetValues(). 3452 */ 3453 M->was_assembled = PETSC_TRUE; 3454 M->assembled = PETSC_FALSE; 3455 } 3456 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3457 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3458 ii = aij->i; 3459 jj = aij->j; 3460 aa = aij->a; 3461 for (i=0; i<m; i++) { 3462 row = rstart + i; 3463 nz = ii[i+1] - ii[i]; 3464 cwork = jj; jj += nz; 3465 vwork = aa; aa += nz; 3466 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3467 } 3468 3469 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3470 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3471 *newmat = M; 3472 3473 /* save submatrix used in processor for next request */ 3474 if (call == MAT_INITIAL_MATRIX) { 3475 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3476 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3477 } 3478 PetscFunctionReturn(0); 3479 } 3480 3481 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3482 { 3483 PetscInt m,cstart, cend,j,nnz,i,d; 3484 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3485 const PetscInt *JJ; 3486 PetscScalar *values; 3487 PetscErrorCode ierr; 3488 PetscBool nooffprocentries; 3489 3490 PetscFunctionBegin; 3491 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3492 3493 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3494 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3495 m = B->rmap->n; 3496 cstart = B->cmap->rstart; 3497 cend = B->cmap->rend; 3498 rstart = B->rmap->rstart; 3499 3500 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3501 3502 #if defined(PETSC_USE_DEBUGGING) 3503 for (i=0; i<m; i++) { 3504 nnz = Ii[i+1]- Ii[i]; 3505 JJ = J + Ii[i]; 3506 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3507 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3508 if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N); 3509 } 3510 #endif 3511 3512 for (i=0; i<m; i++) { 3513 nnz = Ii[i+1]- Ii[i]; 3514 JJ = J + Ii[i]; 3515 nnz_max = PetscMax(nnz_max,nnz); 3516 d = 0; 3517 for (j=0; j<nnz; j++) { 3518 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3519 } 3520 d_nnz[i] = d; 3521 o_nnz[i] = nnz - d; 3522 } 3523 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3524 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3525 3526 if (v) values = (PetscScalar*)v; 3527 else { 3528 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3529 } 3530 3531 for (i=0; i<m; i++) { 3532 ii = i + rstart; 3533 nnz = Ii[i+1]- Ii[i]; 3534 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3535 } 3536 nooffprocentries = B->nooffprocentries; 3537 B->nooffprocentries = PETSC_TRUE; 3538 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3539 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3540 B->nooffprocentries = nooffprocentries; 3541 3542 if (!v) { 3543 ierr = PetscFree(values);CHKERRQ(ierr); 3544 } 3545 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3546 PetscFunctionReturn(0); 3547 } 3548 3549 /*@ 3550 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3551 (the default parallel PETSc format). 3552 3553 Collective on MPI_Comm 3554 3555 Input Parameters: 3556 + B - the matrix 3557 . i - the indices into j for the start of each local row (starts with zero) 3558 . j - the column indices for each local row (starts with zero) 3559 - v - optional values in the matrix 3560 3561 Level: developer 3562 3563 Notes: 3564 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3565 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3566 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3567 3568 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3569 3570 The format which is used for the sparse matrix input, is equivalent to a 3571 row-major ordering.. i.e for the following matrix, the input data expected is 3572 as shown 3573 3574 $ 1 0 0 3575 $ 2 0 3 P0 3576 $ ------- 3577 $ 4 5 6 P1 3578 $ 3579 $ Process0 [P0]: rows_owned=[0,1] 3580 $ i = {0,1,3} [size = nrow+1 = 2+1] 3581 $ j = {0,0,2} [size = 3] 3582 $ v = {1,2,3} [size = 3] 3583 $ 3584 $ Process1 [P1]: rows_owned=[2] 3585 $ i = {0,3} [size = nrow+1 = 1+1] 3586 $ j = {0,1,2} [size = 3] 3587 $ v = {4,5,6} [size = 3] 3588 3589 .keywords: matrix, aij, compressed row, sparse, parallel 3590 3591 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3592 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3593 @*/ 3594 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3595 { 3596 PetscErrorCode ierr; 3597 3598 PetscFunctionBegin; 3599 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3600 PetscFunctionReturn(0); 3601 } 3602 3603 /*@C 3604 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3605 (the default parallel PETSc format). For good matrix assembly performance 3606 the user should preallocate the matrix storage by setting the parameters 3607 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3608 performance can be increased by more than a factor of 50. 3609 3610 Collective on MPI_Comm 3611 3612 Input Parameters: 3613 + B - the matrix 3614 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3615 (same value is used for all local rows) 3616 . d_nnz - array containing the number of nonzeros in the various rows of the 3617 DIAGONAL portion of the local submatrix (possibly different for each row) 3618 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3619 The size of this array is equal to the number of local rows, i.e 'm'. 3620 For matrices that will be factored, you must leave room for (and set) 3621 the diagonal entry even if it is zero. 3622 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3623 submatrix (same value is used for all local rows). 3624 - o_nnz - array containing the number of nonzeros in the various rows of the 3625 OFF-DIAGONAL portion of the local submatrix (possibly different for 3626 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3627 structure. The size of this array is equal to the number 3628 of local rows, i.e 'm'. 3629 3630 If the *_nnz parameter is given then the *_nz parameter is ignored 3631 3632 The AIJ format (also called the Yale sparse matrix format or 3633 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3634 storage. The stored row and column indices begin with zero. 3635 See Users-Manual: ch_mat for details. 3636 3637 The parallel matrix is partitioned such that the first m0 rows belong to 3638 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3639 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3640 3641 The DIAGONAL portion of the local submatrix of a processor can be defined 3642 as the submatrix which is obtained by extraction the part corresponding to 3643 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3644 first row that belongs to the processor, r2 is the last row belonging to 3645 the this processor, and c1-c2 is range of indices of the local part of a 3646 vector suitable for applying the matrix to. This is an mxn matrix. In the 3647 common case of a square matrix, the row and column ranges are the same and 3648 the DIAGONAL part is also square. The remaining portion of the local 3649 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3650 3651 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3652 3653 You can call MatGetInfo() to get information on how effective the preallocation was; 3654 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3655 You can also run with the option -info and look for messages with the string 3656 malloc in them to see if additional memory allocation was needed. 3657 3658 Example usage: 3659 3660 Consider the following 8x8 matrix with 34 non-zero values, that is 3661 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3662 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3663 as follows: 3664 3665 .vb 3666 1 2 0 | 0 3 0 | 0 4 3667 Proc0 0 5 6 | 7 0 0 | 8 0 3668 9 0 10 | 11 0 0 | 12 0 3669 ------------------------------------- 3670 13 0 14 | 15 16 17 | 0 0 3671 Proc1 0 18 0 | 19 20 21 | 0 0 3672 0 0 0 | 22 23 0 | 24 0 3673 ------------------------------------- 3674 Proc2 25 26 27 | 0 0 28 | 29 0 3675 30 0 0 | 31 32 33 | 0 34 3676 .ve 3677 3678 This can be represented as a collection of submatrices as: 3679 3680 .vb 3681 A B C 3682 D E F 3683 G H I 3684 .ve 3685 3686 Where the submatrices A,B,C are owned by proc0, D,E,F are 3687 owned by proc1, G,H,I are owned by proc2. 3688 3689 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3690 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3691 The 'M','N' parameters are 8,8, and have the same values on all procs. 3692 3693 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3694 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3695 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3696 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3697 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3698 matrix, ans [DF] as another SeqAIJ matrix. 3699 3700 When d_nz, o_nz parameters are specified, d_nz storage elements are 3701 allocated for every row of the local diagonal submatrix, and o_nz 3702 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3703 One way to choose d_nz and o_nz is to use the max nonzerors per local 3704 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3705 In this case, the values of d_nz,o_nz are: 3706 .vb 3707 proc0 : dnz = 2, o_nz = 2 3708 proc1 : dnz = 3, o_nz = 2 3709 proc2 : dnz = 1, o_nz = 4 3710 .ve 3711 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3712 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3713 for proc3. i.e we are using 12+15+10=37 storage locations to store 3714 34 values. 3715 3716 When d_nnz, o_nnz parameters are specified, the storage is specified 3717 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3718 In the above case the values for d_nnz,o_nnz are: 3719 .vb 3720 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3721 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3722 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3723 .ve 3724 Here the space allocated is sum of all the above values i.e 34, and 3725 hence pre-allocation is perfect. 3726 3727 Level: intermediate 3728 3729 .keywords: matrix, aij, compressed row, sparse, parallel 3730 3731 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3732 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3733 @*/ 3734 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3735 { 3736 PetscErrorCode ierr; 3737 3738 PetscFunctionBegin; 3739 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3740 PetscValidType(B,1); 3741 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3742 PetscFunctionReturn(0); 3743 } 3744 3745 /*@ 3746 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3747 CSR format the local rows. 3748 3749 Collective on MPI_Comm 3750 3751 Input Parameters: 3752 + comm - MPI communicator 3753 . m - number of local rows (Cannot be PETSC_DECIDE) 3754 . n - This value should be the same as the local size used in creating the 3755 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3756 calculated if N is given) For square matrices n is almost always m. 3757 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3758 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3759 . i - row indices 3760 . j - column indices 3761 - a - matrix values 3762 3763 Output Parameter: 3764 . mat - the matrix 3765 3766 Level: intermediate 3767 3768 Notes: 3769 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3770 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3771 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3772 3773 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3774 3775 The format which is used for the sparse matrix input, is equivalent to a 3776 row-major ordering.. i.e for the following matrix, the input data expected is 3777 as shown 3778 3779 $ 1 0 0 3780 $ 2 0 3 P0 3781 $ ------- 3782 $ 4 5 6 P1 3783 $ 3784 $ Process0 [P0]: rows_owned=[0,1] 3785 $ i = {0,1,3} [size = nrow+1 = 2+1] 3786 $ j = {0,0,2} [size = 3] 3787 $ v = {1,2,3} [size = 3] 3788 $ 3789 $ Process1 [P1]: rows_owned=[2] 3790 $ i = {0,3} [size = nrow+1 = 1+1] 3791 $ j = {0,1,2} [size = 3] 3792 $ v = {4,5,6} [size = 3] 3793 3794 .keywords: matrix, aij, compressed row, sparse, parallel 3795 3796 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3797 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3798 @*/ 3799 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3800 { 3801 PetscErrorCode ierr; 3802 3803 PetscFunctionBegin; 3804 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3805 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3806 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3807 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3808 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3809 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3810 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3811 PetscFunctionReturn(0); 3812 } 3813 3814 /*@C 3815 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3816 (the default parallel PETSc format). For good matrix assembly performance 3817 the user should preallocate the matrix storage by setting the parameters 3818 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3819 performance can be increased by more than a factor of 50. 3820 3821 Collective on MPI_Comm 3822 3823 Input Parameters: 3824 + comm - MPI communicator 3825 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3826 This value should be the same as the local size used in creating the 3827 y vector for the matrix-vector product y = Ax. 3828 . n - This value should be the same as the local size used in creating the 3829 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3830 calculated if N is given) For square matrices n is almost always m. 3831 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3832 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3833 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3834 (same value is used for all local rows) 3835 . d_nnz - array containing the number of nonzeros in the various rows of the 3836 DIAGONAL portion of the local submatrix (possibly different for each row) 3837 or NULL, if d_nz is used to specify the nonzero structure. 3838 The size of this array is equal to the number of local rows, i.e 'm'. 3839 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3840 submatrix (same value is used for all local rows). 3841 - o_nnz - array containing the number of nonzeros in the various rows of the 3842 OFF-DIAGONAL portion of the local submatrix (possibly different for 3843 each row) or NULL, if o_nz is used to specify the nonzero 3844 structure. The size of this array is equal to the number 3845 of local rows, i.e 'm'. 3846 3847 Output Parameter: 3848 . A - the matrix 3849 3850 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3851 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3852 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3853 3854 Notes: 3855 If the *_nnz parameter is given then the *_nz parameter is ignored 3856 3857 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3858 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3859 storage requirements for this matrix. 3860 3861 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3862 processor than it must be used on all processors that share the object for 3863 that argument. 3864 3865 The user MUST specify either the local or global matrix dimensions 3866 (possibly both). 3867 3868 The parallel matrix is partitioned across processors such that the 3869 first m0 rows belong to process 0, the next m1 rows belong to 3870 process 1, the next m2 rows belong to process 2 etc.. where 3871 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3872 values corresponding to [m x N] submatrix. 3873 3874 The columns are logically partitioned with the n0 columns belonging 3875 to 0th partition, the next n1 columns belonging to the next 3876 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3877 3878 The DIAGONAL portion of the local submatrix on any given processor 3879 is the submatrix corresponding to the rows and columns m,n 3880 corresponding to the given processor. i.e diagonal matrix on 3881 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3882 etc. The remaining portion of the local submatrix [m x (N-n)] 3883 constitute the OFF-DIAGONAL portion. The example below better 3884 illustrates this concept. 3885 3886 For a square global matrix we define each processor's diagonal portion 3887 to be its local rows and the corresponding columns (a square submatrix); 3888 each processor's off-diagonal portion encompasses the remainder of the 3889 local matrix (a rectangular submatrix). 3890 3891 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3892 3893 When calling this routine with a single process communicator, a matrix of 3894 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3895 type of communicator, use the construction mechanism: 3896 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3897 3898 By default, this format uses inodes (identical nodes) when possible. 3899 We search for consecutive rows with the same nonzero structure, thereby 3900 reusing matrix information to achieve increased efficiency. 3901 3902 Options Database Keys: 3903 + -mat_no_inode - Do not use inodes 3904 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3905 - -mat_aij_oneindex - Internally use indexing starting at 1 3906 rather than 0. Note that when calling MatSetValues(), 3907 the user still MUST index entries starting at 0! 3908 3909 3910 Example usage: 3911 3912 Consider the following 8x8 matrix with 34 non-zero values, that is 3913 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3914 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3915 as follows: 3916 3917 .vb 3918 1 2 0 | 0 3 0 | 0 4 3919 Proc0 0 5 6 | 7 0 0 | 8 0 3920 9 0 10 | 11 0 0 | 12 0 3921 ------------------------------------- 3922 13 0 14 | 15 16 17 | 0 0 3923 Proc1 0 18 0 | 19 20 21 | 0 0 3924 0 0 0 | 22 23 0 | 24 0 3925 ------------------------------------- 3926 Proc2 25 26 27 | 0 0 28 | 29 0 3927 30 0 0 | 31 32 33 | 0 34 3928 .ve 3929 3930 This can be represented as a collection of submatrices as: 3931 3932 .vb 3933 A B C 3934 D E F 3935 G H I 3936 .ve 3937 3938 Where the submatrices A,B,C are owned by proc0, D,E,F are 3939 owned by proc1, G,H,I are owned by proc2. 3940 3941 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3942 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3943 The 'M','N' parameters are 8,8, and have the same values on all procs. 3944 3945 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3946 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3947 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3948 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3949 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3950 matrix, ans [DF] as another SeqAIJ matrix. 3951 3952 When d_nz, o_nz parameters are specified, d_nz storage elements are 3953 allocated for every row of the local diagonal submatrix, and o_nz 3954 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3955 One way to choose d_nz and o_nz is to use the max nonzerors per local 3956 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3957 In this case, the values of d_nz,o_nz are: 3958 .vb 3959 proc0 : dnz = 2, o_nz = 2 3960 proc1 : dnz = 3, o_nz = 2 3961 proc2 : dnz = 1, o_nz = 4 3962 .ve 3963 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3964 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3965 for proc3. i.e we are using 12+15+10=37 storage locations to store 3966 34 values. 3967 3968 When d_nnz, o_nnz parameters are specified, the storage is specified 3969 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3970 In the above case the values for d_nnz,o_nnz are: 3971 .vb 3972 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3973 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3974 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3975 .ve 3976 Here the space allocated is sum of all the above values i.e 34, and 3977 hence pre-allocation is perfect. 3978 3979 Level: intermediate 3980 3981 .keywords: matrix, aij, compressed row, sparse, parallel 3982 3983 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3984 MATMPIAIJ, MatCreateMPIAIJWithArrays() 3985 @*/ 3986 PetscErrorCode MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3987 { 3988 PetscErrorCode ierr; 3989 PetscMPIInt size; 3990 3991 PetscFunctionBegin; 3992 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3993 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3994 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3995 if (size > 1) { 3996 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3997 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3998 } else { 3999 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4000 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4001 } 4002 PetscFunctionReturn(0); 4003 } 4004 4005 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4006 { 4007 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4008 PetscBool flg; 4009 PetscErrorCode ierr; 4010 4011 PetscFunctionBegin; 4012 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4013 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4014 if (Ad) *Ad = a->A; 4015 if (Ao) *Ao = a->B; 4016 if (colmap) *colmap = a->garray; 4017 PetscFunctionReturn(0); 4018 } 4019 4020 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4021 { 4022 PetscErrorCode ierr; 4023 PetscInt m,N,i,rstart,nnz,Ii; 4024 PetscInt *indx; 4025 PetscScalar *values; 4026 4027 PetscFunctionBegin; 4028 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4029 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4030 PetscInt *dnz,*onz,sum,bs,cbs; 4031 4032 if (n == PETSC_DECIDE) { 4033 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4034 } 4035 /* Check sum(n) = N */ 4036 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4037 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4038 4039 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4040 rstart -= m; 4041 4042 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4043 for (i=0; i<m; i++) { 4044 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4045 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4046 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4047 } 4048 4049 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4050 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4051 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4052 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4053 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4054 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4055 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4056 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4057 } 4058 4059 /* numeric phase */ 4060 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4061 for (i=0; i<m; i++) { 4062 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4063 Ii = i + rstart; 4064 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4065 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4066 } 4067 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4068 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4069 PetscFunctionReturn(0); 4070 } 4071 4072 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4073 { 4074 PetscErrorCode ierr; 4075 PetscMPIInt rank; 4076 PetscInt m,N,i,rstart,nnz; 4077 size_t len; 4078 const PetscInt *indx; 4079 PetscViewer out; 4080 char *name; 4081 Mat B; 4082 const PetscScalar *values; 4083 4084 PetscFunctionBegin; 4085 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4086 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4087 /* Should this be the type of the diagonal block of A? */ 4088 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4089 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4090 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4091 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4092 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4093 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4094 for (i=0; i<m; i++) { 4095 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4096 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4097 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4098 } 4099 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4100 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4101 4102 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4103 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4104 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4105 sprintf(name,"%s.%d",outfile,rank); 4106 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4107 ierr = PetscFree(name);CHKERRQ(ierr); 4108 ierr = MatView(B,out);CHKERRQ(ierr); 4109 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4110 ierr = MatDestroy(&B);CHKERRQ(ierr); 4111 PetscFunctionReturn(0); 4112 } 4113 4114 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4115 { 4116 PetscErrorCode ierr; 4117 Mat_Merge_SeqsToMPI *merge; 4118 PetscContainer container; 4119 4120 PetscFunctionBegin; 4121 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4122 if (container) { 4123 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4124 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4125 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4126 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4127 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4128 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4129 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4130 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4131 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4132 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4133 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4134 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4135 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4136 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4137 ierr = PetscFree(merge);CHKERRQ(ierr); 4138 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4139 } 4140 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4141 PetscFunctionReturn(0); 4142 } 4143 4144 #include <../src/mat/utils/freespace.h> 4145 #include <petscbt.h> 4146 4147 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4148 { 4149 PetscErrorCode ierr; 4150 MPI_Comm comm; 4151 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4152 PetscMPIInt size,rank,taga,*len_s; 4153 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4154 PetscInt proc,m; 4155 PetscInt **buf_ri,**buf_rj; 4156 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4157 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4158 MPI_Request *s_waits,*r_waits; 4159 MPI_Status *status; 4160 MatScalar *aa=a->a; 4161 MatScalar **abuf_r,*ba_i; 4162 Mat_Merge_SeqsToMPI *merge; 4163 PetscContainer container; 4164 4165 PetscFunctionBegin; 4166 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4167 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4168 4169 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4170 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4171 4172 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4173 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4174 4175 bi = merge->bi; 4176 bj = merge->bj; 4177 buf_ri = merge->buf_ri; 4178 buf_rj = merge->buf_rj; 4179 4180 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4181 owners = merge->rowmap->range; 4182 len_s = merge->len_s; 4183 4184 /* send and recv matrix values */ 4185 /*-----------------------------*/ 4186 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4187 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4188 4189 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4190 for (proc=0,k=0; proc<size; proc++) { 4191 if (!len_s[proc]) continue; 4192 i = owners[proc]; 4193 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4194 k++; 4195 } 4196 4197 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4198 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4199 ierr = PetscFree(status);CHKERRQ(ierr); 4200 4201 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4202 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4203 4204 /* insert mat values of mpimat */ 4205 /*----------------------------*/ 4206 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4207 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4208 4209 for (k=0; k<merge->nrecv; k++) { 4210 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4211 nrows = *(buf_ri_k[k]); 4212 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4213 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4214 } 4215 4216 /* set values of ba */ 4217 m = merge->rowmap->n; 4218 for (i=0; i<m; i++) { 4219 arow = owners[rank] + i; 4220 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4221 bnzi = bi[i+1] - bi[i]; 4222 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4223 4224 /* add local non-zero vals of this proc's seqmat into ba */ 4225 anzi = ai[arow+1] - ai[arow]; 4226 aj = a->j + ai[arow]; 4227 aa = a->a + ai[arow]; 4228 nextaj = 0; 4229 for (j=0; nextaj<anzi; j++) { 4230 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4231 ba_i[j] += aa[nextaj++]; 4232 } 4233 } 4234 4235 /* add received vals into ba */ 4236 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4237 /* i-th row */ 4238 if (i == *nextrow[k]) { 4239 anzi = *(nextai[k]+1) - *nextai[k]; 4240 aj = buf_rj[k] + *(nextai[k]); 4241 aa = abuf_r[k] + *(nextai[k]); 4242 nextaj = 0; 4243 for (j=0; nextaj<anzi; j++) { 4244 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4245 ba_i[j] += aa[nextaj++]; 4246 } 4247 } 4248 nextrow[k]++; nextai[k]++; 4249 } 4250 } 4251 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4252 } 4253 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4254 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4255 4256 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4257 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4258 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4259 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4260 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4261 PetscFunctionReturn(0); 4262 } 4263 4264 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4265 { 4266 PetscErrorCode ierr; 4267 Mat B_mpi; 4268 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4269 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4270 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4271 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4272 PetscInt len,proc,*dnz,*onz,bs,cbs; 4273 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4274 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4275 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4276 MPI_Status *status; 4277 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4278 PetscBT lnkbt; 4279 Mat_Merge_SeqsToMPI *merge; 4280 PetscContainer container; 4281 4282 PetscFunctionBegin; 4283 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4284 4285 /* make sure it is a PETSc comm */ 4286 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4287 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4288 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4289 4290 ierr = PetscNew(&merge);CHKERRQ(ierr); 4291 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4292 4293 /* determine row ownership */ 4294 /*---------------------------------------------------------*/ 4295 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4296 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4297 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4298 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4299 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4300 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4301 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4302 4303 m = merge->rowmap->n; 4304 owners = merge->rowmap->range; 4305 4306 /* determine the number of messages to send, their lengths */ 4307 /*---------------------------------------------------------*/ 4308 len_s = merge->len_s; 4309 4310 len = 0; /* length of buf_si[] */ 4311 merge->nsend = 0; 4312 for (proc=0; proc<size; proc++) { 4313 len_si[proc] = 0; 4314 if (proc == rank) { 4315 len_s[proc] = 0; 4316 } else { 4317 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4318 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4319 } 4320 if (len_s[proc]) { 4321 merge->nsend++; 4322 nrows = 0; 4323 for (i=owners[proc]; i<owners[proc+1]; i++) { 4324 if (ai[i+1] > ai[i]) nrows++; 4325 } 4326 len_si[proc] = 2*(nrows+1); 4327 len += len_si[proc]; 4328 } 4329 } 4330 4331 /* determine the number and length of messages to receive for ij-structure */ 4332 /*-------------------------------------------------------------------------*/ 4333 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4334 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4335 4336 /* post the Irecv of j-structure */ 4337 /*-------------------------------*/ 4338 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4339 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4340 4341 /* post the Isend of j-structure */ 4342 /*--------------------------------*/ 4343 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4344 4345 for (proc=0, k=0; proc<size; proc++) { 4346 if (!len_s[proc]) continue; 4347 i = owners[proc]; 4348 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4349 k++; 4350 } 4351 4352 /* receives and sends of j-structure are complete */ 4353 /*------------------------------------------------*/ 4354 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4355 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4356 4357 /* send and recv i-structure */ 4358 /*---------------------------*/ 4359 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4360 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4361 4362 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4363 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4364 for (proc=0,k=0; proc<size; proc++) { 4365 if (!len_s[proc]) continue; 4366 /* form outgoing message for i-structure: 4367 buf_si[0]: nrows to be sent 4368 [1:nrows]: row index (global) 4369 [nrows+1:2*nrows+1]: i-structure index 4370 */ 4371 /*-------------------------------------------*/ 4372 nrows = len_si[proc]/2 - 1; 4373 buf_si_i = buf_si + nrows+1; 4374 buf_si[0] = nrows; 4375 buf_si_i[0] = 0; 4376 nrows = 0; 4377 for (i=owners[proc]; i<owners[proc+1]; i++) { 4378 anzi = ai[i+1] - ai[i]; 4379 if (anzi) { 4380 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4381 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4382 nrows++; 4383 } 4384 } 4385 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4386 k++; 4387 buf_si += len_si[proc]; 4388 } 4389 4390 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4391 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4392 4393 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4394 for (i=0; i<merge->nrecv; i++) { 4395 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 4396 } 4397 4398 ierr = PetscFree(len_si);CHKERRQ(ierr); 4399 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4400 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4401 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4402 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4403 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4404 ierr = PetscFree(status);CHKERRQ(ierr); 4405 4406 /* compute a local seq matrix in each processor */ 4407 /*----------------------------------------------*/ 4408 /* allocate bi array and free space for accumulating nonzero column info */ 4409 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4410 bi[0] = 0; 4411 4412 /* create and initialize a linked list */ 4413 nlnk = N+1; 4414 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4415 4416 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4417 len = ai[owners[rank+1]] - ai[owners[rank]]; 4418 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4419 4420 current_space = free_space; 4421 4422 /* determine symbolic info for each local row */ 4423 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4424 4425 for (k=0; k<merge->nrecv; k++) { 4426 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4427 nrows = *buf_ri_k[k]; 4428 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4429 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4430 } 4431 4432 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4433 len = 0; 4434 for (i=0; i<m; i++) { 4435 bnzi = 0; 4436 /* add local non-zero cols of this proc's seqmat into lnk */ 4437 arow = owners[rank] + i; 4438 anzi = ai[arow+1] - ai[arow]; 4439 aj = a->j + ai[arow]; 4440 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4441 bnzi += nlnk; 4442 /* add received col data into lnk */ 4443 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4444 if (i == *nextrow[k]) { /* i-th row */ 4445 anzi = *(nextai[k]+1) - *nextai[k]; 4446 aj = buf_rj[k] + *nextai[k]; 4447 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4448 bnzi += nlnk; 4449 nextrow[k]++; nextai[k]++; 4450 } 4451 } 4452 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4453 4454 /* if free space is not available, make more free space */ 4455 if (current_space->local_remaining<bnzi) { 4456 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4457 nspacedouble++; 4458 } 4459 /* copy data into free space, then initialize lnk */ 4460 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4461 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4462 4463 current_space->array += bnzi; 4464 current_space->local_used += bnzi; 4465 current_space->local_remaining -= bnzi; 4466 4467 bi[i+1] = bi[i] + bnzi; 4468 } 4469 4470 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4471 4472 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4473 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4474 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4475 4476 /* create symbolic parallel matrix B_mpi */ 4477 /*---------------------------------------*/ 4478 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4479 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4480 if (n==PETSC_DECIDE) { 4481 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4482 } else { 4483 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4484 } 4485 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4486 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4487 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4488 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4489 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4490 4491 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4492 B_mpi->assembled = PETSC_FALSE; 4493 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4494 merge->bi = bi; 4495 merge->bj = bj; 4496 merge->buf_ri = buf_ri; 4497 merge->buf_rj = buf_rj; 4498 merge->coi = NULL; 4499 merge->coj = NULL; 4500 merge->owners_co = NULL; 4501 4502 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4503 4504 /* attach the supporting struct to B_mpi for reuse */ 4505 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4506 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4507 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4508 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4509 *mpimat = B_mpi; 4510 4511 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4512 PetscFunctionReturn(0); 4513 } 4514 4515 /*@C 4516 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4517 matrices from each processor 4518 4519 Collective on MPI_Comm 4520 4521 Input Parameters: 4522 + comm - the communicators the parallel matrix will live on 4523 . seqmat - the input sequential matrices 4524 . m - number of local rows (or PETSC_DECIDE) 4525 . n - number of local columns (or PETSC_DECIDE) 4526 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4527 4528 Output Parameter: 4529 . mpimat - the parallel matrix generated 4530 4531 Level: advanced 4532 4533 Notes: 4534 The dimensions of the sequential matrix in each processor MUST be the same. 4535 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4536 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4537 @*/ 4538 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4539 { 4540 PetscErrorCode ierr; 4541 PetscMPIInt size; 4542 4543 PetscFunctionBegin; 4544 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4545 if (size == 1) { 4546 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4547 if (scall == MAT_INITIAL_MATRIX) { 4548 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4549 } else { 4550 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4551 } 4552 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4553 PetscFunctionReturn(0); 4554 } 4555 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4556 if (scall == MAT_INITIAL_MATRIX) { 4557 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4558 } 4559 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4560 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4561 PetscFunctionReturn(0); 4562 } 4563 4564 /*@ 4565 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4566 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4567 with MatGetSize() 4568 4569 Not Collective 4570 4571 Input Parameters: 4572 + A - the matrix 4573 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4574 4575 Output Parameter: 4576 . A_loc - the local sequential matrix generated 4577 4578 Level: developer 4579 4580 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4581 4582 @*/ 4583 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4584 { 4585 PetscErrorCode ierr; 4586 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4587 Mat_SeqAIJ *mat,*a,*b; 4588 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4589 MatScalar *aa,*ba,*cam; 4590 PetscScalar *ca; 4591 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4592 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4593 PetscBool match; 4594 MPI_Comm comm; 4595 PetscMPIInt size; 4596 4597 PetscFunctionBegin; 4598 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4599 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4600 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4601 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4602 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4603 4604 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4605 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4606 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4607 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4608 aa = a->a; ba = b->a; 4609 if (scall == MAT_INITIAL_MATRIX) { 4610 if (size == 1) { 4611 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4612 PetscFunctionReturn(0); 4613 } 4614 4615 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4616 ci[0] = 0; 4617 for (i=0; i<am; i++) { 4618 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4619 } 4620 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4621 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4622 k = 0; 4623 for (i=0; i<am; i++) { 4624 ncols_o = bi[i+1] - bi[i]; 4625 ncols_d = ai[i+1] - ai[i]; 4626 /* off-diagonal portion of A */ 4627 for (jo=0; jo<ncols_o; jo++) { 4628 col = cmap[*bj]; 4629 if (col >= cstart) break; 4630 cj[k] = col; bj++; 4631 ca[k++] = *ba++; 4632 } 4633 /* diagonal portion of A */ 4634 for (j=0; j<ncols_d; j++) { 4635 cj[k] = cstart + *aj++; 4636 ca[k++] = *aa++; 4637 } 4638 /* off-diagonal portion of A */ 4639 for (j=jo; j<ncols_o; j++) { 4640 cj[k] = cmap[*bj++]; 4641 ca[k++] = *ba++; 4642 } 4643 } 4644 /* put together the new matrix */ 4645 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4646 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4647 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4648 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4649 mat->free_a = PETSC_TRUE; 4650 mat->free_ij = PETSC_TRUE; 4651 mat->nonew = 0; 4652 } else if (scall == MAT_REUSE_MATRIX) { 4653 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4654 ci = mat->i; cj = mat->j; cam = mat->a; 4655 for (i=0; i<am; i++) { 4656 /* off-diagonal portion of A */ 4657 ncols_o = bi[i+1] - bi[i]; 4658 for (jo=0; jo<ncols_o; jo++) { 4659 col = cmap[*bj]; 4660 if (col >= cstart) break; 4661 *cam++ = *ba++; bj++; 4662 } 4663 /* diagonal portion of A */ 4664 ncols_d = ai[i+1] - ai[i]; 4665 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4666 /* off-diagonal portion of A */ 4667 for (j=jo; j<ncols_o; j++) { 4668 *cam++ = *ba++; bj++; 4669 } 4670 } 4671 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4672 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4673 PetscFunctionReturn(0); 4674 } 4675 4676 /*@C 4677 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4678 4679 Not Collective 4680 4681 Input Parameters: 4682 + A - the matrix 4683 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4684 - row, col - index sets of rows and columns to extract (or NULL) 4685 4686 Output Parameter: 4687 . A_loc - the local sequential matrix generated 4688 4689 Level: developer 4690 4691 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4692 4693 @*/ 4694 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4695 { 4696 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4697 PetscErrorCode ierr; 4698 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4699 IS isrowa,iscola; 4700 Mat *aloc; 4701 PetscBool match; 4702 4703 PetscFunctionBegin; 4704 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4705 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4706 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4707 if (!row) { 4708 start = A->rmap->rstart; end = A->rmap->rend; 4709 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4710 } else { 4711 isrowa = *row; 4712 } 4713 if (!col) { 4714 start = A->cmap->rstart; 4715 cmap = a->garray; 4716 nzA = a->A->cmap->n; 4717 nzB = a->B->cmap->n; 4718 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4719 ncols = 0; 4720 for (i=0; i<nzB; i++) { 4721 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4722 else break; 4723 } 4724 imark = i; 4725 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4726 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4727 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4728 } else { 4729 iscola = *col; 4730 } 4731 if (scall != MAT_INITIAL_MATRIX) { 4732 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4733 aloc[0] = *A_loc; 4734 } 4735 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4736 *A_loc = aloc[0]; 4737 ierr = PetscFree(aloc);CHKERRQ(ierr); 4738 if (!row) { 4739 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4740 } 4741 if (!col) { 4742 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4743 } 4744 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4745 PetscFunctionReturn(0); 4746 } 4747 4748 /*@C 4749 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4750 4751 Collective on Mat 4752 4753 Input Parameters: 4754 + A,B - the matrices in mpiaij format 4755 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4756 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4757 4758 Output Parameter: 4759 + rowb, colb - index sets of rows and columns of B to extract 4760 - B_seq - the sequential matrix generated 4761 4762 Level: developer 4763 4764 @*/ 4765 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4766 { 4767 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4768 PetscErrorCode ierr; 4769 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4770 IS isrowb,iscolb; 4771 Mat *bseq=NULL; 4772 4773 PetscFunctionBegin; 4774 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4775 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4776 } 4777 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4778 4779 if (scall == MAT_INITIAL_MATRIX) { 4780 start = A->cmap->rstart; 4781 cmap = a->garray; 4782 nzA = a->A->cmap->n; 4783 nzB = a->B->cmap->n; 4784 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4785 ncols = 0; 4786 for (i=0; i<nzB; i++) { /* row < local row index */ 4787 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4788 else break; 4789 } 4790 imark = i; 4791 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4792 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4793 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4794 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4795 } else { 4796 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4797 isrowb = *rowb; iscolb = *colb; 4798 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4799 bseq[0] = *B_seq; 4800 } 4801 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4802 *B_seq = bseq[0]; 4803 ierr = PetscFree(bseq);CHKERRQ(ierr); 4804 if (!rowb) { 4805 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4806 } else { 4807 *rowb = isrowb; 4808 } 4809 if (!colb) { 4810 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4811 } else { 4812 *colb = iscolb; 4813 } 4814 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4815 PetscFunctionReturn(0); 4816 } 4817 4818 /* 4819 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4820 of the OFF-DIAGONAL portion of local A 4821 4822 Collective on Mat 4823 4824 Input Parameters: 4825 + A,B - the matrices in mpiaij format 4826 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4827 4828 Output Parameter: 4829 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4830 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4831 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4832 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4833 4834 Level: developer 4835 4836 */ 4837 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4838 { 4839 VecScatter_MPI_General *gen_to,*gen_from; 4840 PetscErrorCode ierr; 4841 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4842 Mat_SeqAIJ *b_oth; 4843 VecScatter ctx =a->Mvctx; 4844 MPI_Comm comm; 4845 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4846 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4847 PetscInt *rvalues,*svalues; 4848 MatScalar *b_otha,*bufa,*bufA; 4849 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4850 MPI_Request *rwaits = NULL,*swaits = NULL; 4851 MPI_Status *sstatus,rstatus; 4852 PetscMPIInt jj,size; 4853 PetscInt *cols,sbs,rbs; 4854 PetscScalar *vals; 4855 4856 PetscFunctionBegin; 4857 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4858 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4859 4860 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4861 SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4862 } 4863 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4864 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4865 4866 if (size == 1) { 4867 startsj_s = NULL; 4868 bufa_ptr = NULL; 4869 *B_oth = NULL; 4870 PetscFunctionReturn(0); 4871 } 4872 4873 gen_to = (VecScatter_MPI_General*)ctx->todata; 4874 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4875 nrecvs = gen_from->n; 4876 nsends = gen_to->n; 4877 4878 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4879 srow = gen_to->indices; /* local row index to be sent */ 4880 sstarts = gen_to->starts; 4881 sprocs = gen_to->procs; 4882 sstatus = gen_to->sstatus; 4883 sbs = gen_to->bs; 4884 rstarts = gen_from->starts; 4885 rprocs = gen_from->procs; 4886 rbs = gen_from->bs; 4887 4888 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4889 if (scall == MAT_INITIAL_MATRIX) { 4890 /* i-array */ 4891 /*---------*/ 4892 /* post receives */ 4893 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4894 for (i=0; i<nrecvs; i++) { 4895 rowlen = rvalues + rstarts[i]*rbs; 4896 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4897 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4898 } 4899 4900 /* pack the outgoing message */ 4901 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4902 4903 sstartsj[0] = 0; 4904 rstartsj[0] = 0; 4905 len = 0; /* total length of j or a array to be sent */ 4906 k = 0; 4907 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4908 for (i=0; i<nsends; i++) { 4909 rowlen = svalues + sstarts[i]*sbs; 4910 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4911 for (j=0; j<nrows; j++) { 4912 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4913 for (l=0; l<sbs; l++) { 4914 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4915 4916 rowlen[j*sbs+l] = ncols; 4917 4918 len += ncols; 4919 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4920 } 4921 k++; 4922 } 4923 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4924 4925 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4926 } 4927 /* recvs and sends of i-array are completed */ 4928 i = nrecvs; 4929 while (i--) { 4930 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4931 } 4932 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4933 ierr = PetscFree(svalues);CHKERRQ(ierr); 4934 4935 /* allocate buffers for sending j and a arrays */ 4936 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4937 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4938 4939 /* create i-array of B_oth */ 4940 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4941 4942 b_othi[0] = 0; 4943 len = 0; /* total length of j or a array to be received */ 4944 k = 0; 4945 for (i=0; i<nrecvs; i++) { 4946 rowlen = rvalues + rstarts[i]*rbs; 4947 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4948 for (j=0; j<nrows; j++) { 4949 b_othi[k+1] = b_othi[k] + rowlen[j]; 4950 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4951 k++; 4952 } 4953 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4954 } 4955 ierr = PetscFree(rvalues);CHKERRQ(ierr); 4956 4957 /* allocate space for j and a arrrays of B_oth */ 4958 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4959 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4960 4961 /* j-array */ 4962 /*---------*/ 4963 /* post receives of j-array */ 4964 for (i=0; i<nrecvs; i++) { 4965 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4966 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4967 } 4968 4969 /* pack the outgoing message j-array */ 4970 k = 0; 4971 for (i=0; i<nsends; i++) { 4972 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4973 bufJ = bufj+sstartsj[i]; 4974 for (j=0; j<nrows; j++) { 4975 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4976 for (ll=0; ll<sbs; ll++) { 4977 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4978 for (l=0; l<ncols; l++) { 4979 *bufJ++ = cols[l]; 4980 } 4981 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4982 } 4983 } 4984 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4985 } 4986 4987 /* recvs and sends of j-array are completed */ 4988 i = nrecvs; 4989 while (i--) { 4990 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4991 } 4992 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4993 } else if (scall == MAT_REUSE_MATRIX) { 4994 sstartsj = *startsj_s; 4995 rstartsj = *startsj_r; 4996 bufa = *bufa_ptr; 4997 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4998 b_otha = b_oth->a; 4999 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5000 5001 /* a-array */ 5002 /*---------*/ 5003 /* post receives of a-array */ 5004 for (i=0; i<nrecvs; i++) { 5005 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5006 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5007 } 5008 5009 /* pack the outgoing message a-array */ 5010 k = 0; 5011 for (i=0; i<nsends; i++) { 5012 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5013 bufA = bufa+sstartsj[i]; 5014 for (j=0; j<nrows; j++) { 5015 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5016 for (ll=0; ll<sbs; ll++) { 5017 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5018 for (l=0; l<ncols; l++) { 5019 *bufA++ = vals[l]; 5020 } 5021 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5022 } 5023 } 5024 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5025 } 5026 /* recvs and sends of a-array are completed */ 5027 i = nrecvs; 5028 while (i--) { 5029 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5030 } 5031 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5032 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5033 5034 if (scall == MAT_INITIAL_MATRIX) { 5035 /* put together the new matrix */ 5036 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5037 5038 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5039 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5040 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5041 b_oth->free_a = PETSC_TRUE; 5042 b_oth->free_ij = PETSC_TRUE; 5043 b_oth->nonew = 0; 5044 5045 ierr = PetscFree(bufj);CHKERRQ(ierr); 5046 if (!startsj_s || !bufa_ptr) { 5047 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5048 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5049 } else { 5050 *startsj_s = sstartsj; 5051 *startsj_r = rstartsj; 5052 *bufa_ptr = bufa; 5053 } 5054 } 5055 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5056 PetscFunctionReturn(0); 5057 } 5058 5059 /*@C 5060 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5061 5062 Not Collective 5063 5064 Input Parameters: 5065 . A - The matrix in mpiaij format 5066 5067 Output Parameter: 5068 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5069 . colmap - A map from global column index to local index into lvec 5070 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5071 5072 Level: developer 5073 5074 @*/ 5075 #if defined(PETSC_USE_CTABLE) 5076 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5077 #else 5078 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5079 #endif 5080 { 5081 Mat_MPIAIJ *a; 5082 5083 PetscFunctionBegin; 5084 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5085 PetscValidPointer(lvec, 2); 5086 PetscValidPointer(colmap, 3); 5087 PetscValidPointer(multScatter, 4); 5088 a = (Mat_MPIAIJ*) A->data; 5089 if (lvec) *lvec = a->lvec; 5090 if (colmap) *colmap = a->colmap; 5091 if (multScatter) *multScatter = a->Mvctx; 5092 PetscFunctionReturn(0); 5093 } 5094 5095 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5096 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5097 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5098 #if defined(PETSC_HAVE_ELEMENTAL) 5099 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5100 #endif 5101 #if defined(PETSC_HAVE_HYPRE) 5102 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5103 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5104 #endif 5105 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5106 5107 /* 5108 Computes (B'*A')' since computing B*A directly is untenable 5109 5110 n p p 5111 ( ) ( ) ( ) 5112 m ( A ) * n ( B ) = m ( C ) 5113 ( ) ( ) ( ) 5114 5115 */ 5116 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5117 { 5118 PetscErrorCode ierr; 5119 Mat At,Bt,Ct; 5120 5121 PetscFunctionBegin; 5122 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5123 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5124 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5125 ierr = MatDestroy(&At);CHKERRQ(ierr); 5126 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5127 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5128 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5129 PetscFunctionReturn(0); 5130 } 5131 5132 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5133 { 5134 PetscErrorCode ierr; 5135 PetscInt m=A->rmap->n,n=B->cmap->n; 5136 Mat Cmat; 5137 5138 PetscFunctionBegin; 5139 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 5140 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5141 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5142 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5143 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5144 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5145 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5146 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5147 5148 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5149 5150 *C = Cmat; 5151 PetscFunctionReturn(0); 5152 } 5153 5154 /* ----------------------------------------------------------------*/ 5155 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5156 { 5157 PetscErrorCode ierr; 5158 5159 PetscFunctionBegin; 5160 if (scall == MAT_INITIAL_MATRIX) { 5161 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5162 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5163 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5164 } 5165 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5166 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5167 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5168 PetscFunctionReturn(0); 5169 } 5170 5171 /*MC 5172 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5173 5174 Options Database Keys: 5175 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5176 5177 Level: beginner 5178 5179 .seealso: MatCreateAIJ() 5180 M*/ 5181 5182 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5183 { 5184 Mat_MPIAIJ *b; 5185 PetscErrorCode ierr; 5186 PetscMPIInt size; 5187 5188 PetscFunctionBegin; 5189 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5190 5191 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5192 B->data = (void*)b; 5193 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5194 B->assembled = PETSC_FALSE; 5195 B->insertmode = NOT_SET_VALUES; 5196 b->size = size; 5197 5198 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5199 5200 /* build cache for off array entries formed */ 5201 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5202 5203 b->donotstash = PETSC_FALSE; 5204 b->colmap = 0; 5205 b->garray = 0; 5206 b->roworiented = PETSC_TRUE; 5207 5208 /* stuff used for matrix vector multiply */ 5209 b->lvec = NULL; 5210 b->Mvctx = NULL; 5211 5212 /* stuff for MatGetRow() */ 5213 b->rowindices = 0; 5214 b->rowvalues = 0; 5215 b->getrowactive = PETSC_FALSE; 5216 5217 /* flexible pointer used in CUSP/CUSPARSE classes */ 5218 b->spptr = NULL; 5219 5220 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5221 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5222 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5223 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5224 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5225 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5226 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5227 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5228 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5229 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5230 #if defined(PETSC_HAVE_ELEMENTAL) 5231 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5232 #endif 5233 #if defined(PETSC_HAVE_HYPRE) 5234 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5235 #endif 5236 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5237 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5238 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5239 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5240 #if defined(PETSC_HAVE_HYPRE) 5241 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5242 #endif 5243 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5244 PetscFunctionReturn(0); 5245 } 5246 5247 /*@C 5248 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5249 and "off-diagonal" part of the matrix in CSR format. 5250 5251 Collective on MPI_Comm 5252 5253 Input Parameters: 5254 + comm - MPI communicator 5255 . m - number of local rows (Cannot be PETSC_DECIDE) 5256 . n - This value should be the same as the local size used in creating the 5257 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5258 calculated if N is given) For square matrices n is almost always m. 5259 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5260 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5261 . i - row indices for "diagonal" portion of matrix 5262 . j - column indices 5263 . a - matrix values 5264 . oi - row indices for "off-diagonal" portion of matrix 5265 . oj - column indices 5266 - oa - matrix values 5267 5268 Output Parameter: 5269 . mat - the matrix 5270 5271 Level: advanced 5272 5273 Notes: 5274 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5275 must free the arrays once the matrix has been destroyed and not before. 5276 5277 The i and j indices are 0 based 5278 5279 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5280 5281 This sets local rows and cannot be used to set off-processor values. 5282 5283 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5284 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5285 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5286 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5287 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5288 communication if it is known that only local entries will be set. 5289 5290 .keywords: matrix, aij, compressed row, sparse, parallel 5291 5292 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5293 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5294 @*/ 5295 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5296 { 5297 PetscErrorCode ierr; 5298 Mat_MPIAIJ *maij; 5299 5300 PetscFunctionBegin; 5301 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5302 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5303 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5304 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5305 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5306 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5307 maij = (Mat_MPIAIJ*) (*mat)->data; 5308 5309 (*mat)->preallocated = PETSC_TRUE; 5310 5311 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5312 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5313 5314 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5315 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5316 5317 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5318 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5319 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5320 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5321 5322 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5323 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5324 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5325 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5326 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5327 PetscFunctionReturn(0); 5328 } 5329 5330 /* 5331 Special version for direct calls from Fortran 5332 */ 5333 #include <petsc/private/fortranimpl.h> 5334 5335 /* Change these macros so can be used in void function */ 5336 #undef CHKERRQ 5337 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5338 #undef SETERRQ2 5339 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5340 #undef SETERRQ3 5341 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5342 #undef SETERRQ 5343 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5344 5345 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5346 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5347 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5348 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5349 #else 5350 #endif 5351 PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5352 { 5353 Mat mat = *mmat; 5354 PetscInt m = *mm, n = *mn; 5355 InsertMode addv = *maddv; 5356 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5357 PetscScalar value; 5358 PetscErrorCode ierr; 5359 5360 MatCheckPreallocated(mat,1); 5361 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5362 5363 #if defined(PETSC_USE_DEBUG) 5364 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5365 #endif 5366 { 5367 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5368 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5369 PetscBool roworiented = aij->roworiented; 5370 5371 /* Some Variables required in the macro */ 5372 Mat A = aij->A; 5373 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5374 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5375 MatScalar *aa = a->a; 5376 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5377 Mat B = aij->B; 5378 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5379 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5380 MatScalar *ba = b->a; 5381 5382 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5383 PetscInt nonew = a->nonew; 5384 MatScalar *ap1,*ap2; 5385 5386 PetscFunctionBegin; 5387 for (i=0; i<m; i++) { 5388 if (im[i] < 0) continue; 5389 #if defined(PETSC_USE_DEBUG) 5390 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5391 #endif 5392 if (im[i] >= rstart && im[i] < rend) { 5393 row = im[i] - rstart; 5394 lastcol1 = -1; 5395 rp1 = aj + ai[row]; 5396 ap1 = aa + ai[row]; 5397 rmax1 = aimax[row]; 5398 nrow1 = ailen[row]; 5399 low1 = 0; 5400 high1 = nrow1; 5401 lastcol2 = -1; 5402 rp2 = bj + bi[row]; 5403 ap2 = ba + bi[row]; 5404 rmax2 = bimax[row]; 5405 nrow2 = bilen[row]; 5406 low2 = 0; 5407 high2 = nrow2; 5408 5409 for (j=0; j<n; j++) { 5410 if (roworiented) value = v[i*n+j]; 5411 else value = v[i+j*m]; 5412 if (in[j] >= cstart && in[j] < cend) { 5413 col = in[j] - cstart; 5414 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5415 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5416 } else if (in[j] < 0) continue; 5417 #if defined(PETSC_USE_DEBUG) 5418 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 5419 #endif 5420 else { 5421 if (mat->was_assembled) { 5422 if (!aij->colmap) { 5423 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5424 } 5425 #if defined(PETSC_USE_CTABLE) 5426 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5427 col--; 5428 #else 5429 col = aij->colmap[in[j]] - 1; 5430 #endif 5431 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5432 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5433 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5434 col = in[j]; 5435 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5436 B = aij->B; 5437 b = (Mat_SeqAIJ*)B->data; 5438 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5439 rp2 = bj + bi[row]; 5440 ap2 = ba + bi[row]; 5441 rmax2 = bimax[row]; 5442 nrow2 = bilen[row]; 5443 low2 = 0; 5444 high2 = nrow2; 5445 bm = aij->B->rmap->n; 5446 ba = b->a; 5447 } 5448 } else col = in[j]; 5449 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5450 } 5451 } 5452 } else if (!aij->donotstash) { 5453 if (roworiented) { 5454 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5455 } else { 5456 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5457 } 5458 } 5459 } 5460 } 5461 PetscFunctionReturnVoid(); 5462 } 5463 5464