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,start,end; 3077 PetscBool sameRowDist,sameDist[2],tsameDist[2]; 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) sameRowDist = PETSC_TRUE; 3086 } else { 3087 /* check if isrow has same processor distribution as mat */ 3088 sameDist[0] = PETSC_FALSE; 3089 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3090 if (!n) { 3091 sameDist[0] = PETSC_TRUE; 3092 } else { 3093 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3094 ierr = MatGetOwnershipRange(mat,&start,&end);CHKERRQ(ierr); 3095 if (i >= start && j < end) { 3096 sameDist[0] = PETSC_TRUE; 3097 } 3098 } 3099 3100 /* check if iscol has same processor distribution as mat */ 3101 sameDist[1] = PETSC_FALSE; 3102 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3103 if (!n) { 3104 sameDist[1] = PETSC_TRUE; 3105 } else { 3106 ierr = ISGetMinMax(iscol,&i,&j);CHKERRQ(ierr); 3107 ierr = MatGetOwnershipRangeColumn(mat,&start,&end);CHKERRQ(ierr); 3108 if (i >= start && j < end) sameDist[1] = PETSC_TRUE; 3109 } 3110 3111 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3112 ierr = MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3113 sameRowDist = tsameDist[0]; 3114 } 3115 3116 if (sameRowDist) { 3117 ierr = MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,call,tsameDist[1],newmat);CHKERRQ(ierr); 3118 PetscFunctionReturn(0); 3119 } 3120 3121 /* General case: iscol -> iscol_local which has global size of iscol */ 3122 if (call == MAT_REUSE_MATRIX) { 3123 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3124 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3125 } else { 3126 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3127 } 3128 3129 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3130 ierr = MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3131 3132 if (call == MAT_INITIAL_MATRIX) { 3133 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3134 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3135 } 3136 PetscFunctionReturn(0); 3137 } 3138 3139 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3140 3141 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,MatReuse call,PetscBool sameColDist,Mat *newmat) 3142 { 3143 PetscErrorCode ierr; 3144 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3145 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3146 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3147 Mat M,Msub,B=a->B; 3148 MatScalar *aa; 3149 Mat_SeqAIJ *aij; 3150 PetscInt *garray = a->garray,*colsub,Ncols; 3151 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3152 IS iscol_sub,iscmap; 3153 const PetscInt *is_idx,*cmap; 3154 PetscBool allcolumns=PETSC_FALSE; 3155 IS iscol_local=NULL; 3156 MPI_Comm comm; 3157 3158 PetscFunctionBegin; 3159 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3160 3161 if (call == MAT_INITIAL_MATRIX) { 3162 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3163 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); 3164 3165 /* (1) Create scalable iscol_sub and iscmap */ 3166 if (sameColDist) { 3167 /* iscol has same processor distribution as mat, use a scalable routine to generate iscol_sub and iscmap */ 3168 ierr = ISGetSeqIS_SameColDist_Private(mat,iscol,&iscol_sub,&iscmap);CHKERRQ(ierr); 3169 3170 } else { /* iscol -> nonscalable iscol_local, then get scalable iscol_sub and iscmap */ 3171 PetscBool flg; 3172 3173 /* iscol -> nonscalable iscol_local */ 3174 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3175 ierr = ISGetLocalSize(iscol_local,&n);CHKERRQ(ierr); /* local size of iscol_local = global columns of newmat */ 3176 if (n != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != Ncols %d",n,Ncols); 3177 3178 /* Check for special case: each processor gets entire matrix columns */ 3179 ierr = ISIdentity(iscol_local,&flg);CHKERRQ(ierr); 3180 if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3181 if (allcolumns) { 3182 iscol_sub = iscol_local; 3183 ierr = PetscObjectReference((PetscObject)iscol_local);CHKERRQ(ierr); 3184 ierr = ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);CHKERRQ(ierr); 3185 3186 } else { /* iscol_local -> iscol_sub and iscmap */ 3187 PetscInt *idx,*cmap1,k; 3188 3189 /* implementation below requires iscol_local be sorted, it can have duplicate indices */ 3190 ierr = ISSorted(iscol_local,&flg);CHKERRQ(ierr); 3191 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unsorted iscol_local is not implemented yet"); 3192 3193 ierr = PetscMalloc2(Ncols,&idx,Ncols,&cmap1);CHKERRQ(ierr); 3194 ierr = ISGetIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3195 count = 0; 3196 k = 0; 3197 for (i=0; i<Ncols; i++) { 3198 j = is_idx[i]; 3199 if (j >= cstart && j < cend) { 3200 /* diagonal part of mat */ 3201 idx[count] = j; 3202 cmap1[count++] = i; /* column index in submat */ 3203 } else { 3204 /* off-diagonal part of mat */ 3205 if (j == garray[k]) { 3206 idx[count] = j; 3207 cmap1[count++] = i; /* column index in submat */ 3208 } else if (j > garray[k]) { 3209 while (j > garray[k] && k < Bn-1) k++; 3210 if (j == garray[k]) { 3211 idx[count] = j; 3212 cmap1[count++] = i; /* column index in submat */ 3213 } 3214 } 3215 } 3216 } 3217 ierr = ISRestoreIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3218 3219 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3220 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3221 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3222 } 3223 } 3224 3225 /* (2) Create sequential Msub */ 3226 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);CHKERRQ(ierr); 3227 3228 } else { /* call == MAT_REUSE_MATRIX */ 3229 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3230 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3231 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3232 3233 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3234 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3235 3236 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3237 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3238 3239 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3240 } 3241 3242 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3243 aij = (Mat_SeqAIJ*)(Msub)->data; 3244 ii = aij->i; 3245 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3246 3247 /* 3248 m - number of local rows 3249 Ncols - number of columns (same on all processors) 3250 rstart - first row in new global matrix generated 3251 */ 3252 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3253 3254 if (call == MAT_INITIAL_MATRIX) { 3255 /* (3) Create parallel newmat */ 3256 PetscMPIInt rank,size; 3257 PetscInt csize; 3258 3259 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3260 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3261 3262 /* 3263 Determine the number of non-zeros in the diagonal and off-diagonal 3264 portions of the matrix in order to do correct preallocation 3265 */ 3266 3267 /* first get start and end of "diagonal" columns */ 3268 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3269 if (csize == PETSC_DECIDE) { 3270 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3271 if (mglobal == Ncols) { /* square matrix */ 3272 nlocal = m; 3273 } else { 3274 nlocal = Ncols/size + ((Ncols % size) > rank); 3275 } 3276 } else { 3277 nlocal = csize; 3278 } 3279 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3280 rstart = rend - nlocal; 3281 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); 3282 3283 /* next, compute all the lengths */ 3284 jj = aij->j; 3285 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3286 olens = dlens + m; 3287 for (i=0; i<m; i++) { 3288 jend = ii[i+1] - ii[i]; 3289 olen = 0; 3290 dlen = 0; 3291 for (j=0; j<jend; j++) { 3292 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3293 else dlen++; 3294 jj++; 3295 } 3296 olens[i] = olen; 3297 dlens[i] = dlen; 3298 } 3299 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3300 3301 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3302 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 3303 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3304 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3305 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3306 ierr = PetscFree(dlens);CHKERRQ(ierr); 3307 } else { 3308 M = *newmat; 3309 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3310 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3311 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3312 /* 3313 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3314 rather than the slower MatSetValues(). 3315 */ 3316 M->was_assembled = PETSC_TRUE; 3317 M->assembled = PETSC_FALSE; 3318 } 3319 3320 /* (4) Set values of Msub to *newmat */ 3321 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3322 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3323 3324 jj = aij->j; 3325 aa = aij->a; 3326 for (i=0; i<m; i++) { 3327 row = rstart + i; 3328 nz = ii[i+1] - ii[i]; 3329 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3330 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3331 jj += nz; aa += nz; 3332 } 3333 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3334 3335 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3336 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3337 *newmat = M; 3338 3339 ierr = PetscFree(colsub);CHKERRQ(ierr); 3340 3341 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3342 if (call == MAT_INITIAL_MATRIX) { 3343 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3344 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3345 3346 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3347 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3348 3349 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3350 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3351 3352 if (iscol_local) { 3353 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3354 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3355 } 3356 } 3357 PetscFunctionReturn(0); 3358 } 3359 3360 /* 3361 Not great since it makes two copies of the submatrix, first an SeqAIJ 3362 in local and then by concatenating the local matrices the end result. 3363 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3364 3365 Note: This requires a sequential iscol with all indices. 3366 */ 3367 PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3368 { 3369 PetscErrorCode ierr; 3370 PetscMPIInt rank,size; 3371 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3372 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3373 Mat M,Mreuse; 3374 MatScalar *aa,*vwork; 3375 MPI_Comm comm; 3376 Mat_SeqAIJ *aij; 3377 PetscBool colflag,allcolumns=PETSC_FALSE; 3378 3379 PetscFunctionBegin; 3380 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3381 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3382 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3383 3384 /* Check for special case: each processor gets entire matrix columns */ 3385 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3386 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3387 if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3388 3389 if (call == MAT_REUSE_MATRIX) { 3390 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3391 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3392 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3393 } else { 3394 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3395 } 3396 3397 /* 3398 m - number of local rows 3399 n - number of columns (same on all processors) 3400 rstart - first row in new global matrix generated 3401 */ 3402 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3403 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3404 if (call == MAT_INITIAL_MATRIX) { 3405 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3406 ii = aij->i; 3407 jj = aij->j; 3408 3409 /* 3410 Determine the number of non-zeros in the diagonal and off-diagonal 3411 portions of the matrix in order to do correct preallocation 3412 */ 3413 3414 /* first get start and end of "diagonal" columns */ 3415 if (csize == PETSC_DECIDE) { 3416 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3417 if (mglobal == n) { /* square matrix */ 3418 nlocal = m; 3419 } else { 3420 nlocal = n/size + ((n % size) > rank); 3421 } 3422 } else { 3423 nlocal = csize; 3424 } 3425 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3426 rstart = rend - nlocal; 3427 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); 3428 3429 /* next, compute all the lengths */ 3430 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3431 olens = dlens + m; 3432 for (i=0; i<m; i++) { 3433 jend = ii[i+1] - ii[i]; 3434 olen = 0; 3435 dlen = 0; 3436 for (j=0; j<jend; j++) { 3437 if (*jj < rstart || *jj >= rend) olen++; 3438 else dlen++; 3439 jj++; 3440 } 3441 olens[i] = olen; 3442 dlens[i] = dlen; 3443 } 3444 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3445 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3446 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3447 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3448 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3449 ierr = PetscFree(dlens);CHKERRQ(ierr); 3450 } else { 3451 PetscInt ml,nl; 3452 3453 M = *newmat; 3454 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3455 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3456 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3457 /* 3458 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3459 rather than the slower MatSetValues(). 3460 */ 3461 M->was_assembled = PETSC_TRUE; 3462 M->assembled = PETSC_FALSE; 3463 } 3464 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3465 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3466 ii = aij->i; 3467 jj = aij->j; 3468 aa = aij->a; 3469 for (i=0; i<m; i++) { 3470 row = rstart + i; 3471 nz = ii[i+1] - ii[i]; 3472 cwork = jj; jj += nz; 3473 vwork = aa; aa += nz; 3474 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3475 } 3476 3477 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3478 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3479 *newmat = M; 3480 3481 /* save submatrix used in processor for next request */ 3482 if (call == MAT_INITIAL_MATRIX) { 3483 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3484 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3485 } 3486 PetscFunctionReturn(0); 3487 } 3488 3489 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3490 { 3491 PetscInt m,cstart, cend,j,nnz,i,d; 3492 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3493 const PetscInt *JJ; 3494 PetscScalar *values; 3495 PetscErrorCode ierr; 3496 PetscBool nooffprocentries; 3497 3498 PetscFunctionBegin; 3499 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3500 3501 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3502 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3503 m = B->rmap->n; 3504 cstart = B->cmap->rstart; 3505 cend = B->cmap->rend; 3506 rstart = B->rmap->rstart; 3507 3508 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3509 3510 #if defined(PETSC_USE_DEBUGGING) 3511 for (i=0; i<m; i++) { 3512 nnz = Ii[i+1]- Ii[i]; 3513 JJ = J + Ii[i]; 3514 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3515 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3516 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); 3517 } 3518 #endif 3519 3520 for (i=0; i<m; i++) { 3521 nnz = Ii[i+1]- Ii[i]; 3522 JJ = J + Ii[i]; 3523 nnz_max = PetscMax(nnz_max,nnz); 3524 d = 0; 3525 for (j=0; j<nnz; j++) { 3526 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3527 } 3528 d_nnz[i] = d; 3529 o_nnz[i] = nnz - d; 3530 } 3531 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3532 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3533 3534 if (v) values = (PetscScalar*)v; 3535 else { 3536 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3537 } 3538 3539 for (i=0; i<m; i++) { 3540 ii = i + rstart; 3541 nnz = Ii[i+1]- Ii[i]; 3542 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3543 } 3544 nooffprocentries = B->nooffprocentries; 3545 B->nooffprocentries = PETSC_TRUE; 3546 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3547 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3548 B->nooffprocentries = nooffprocentries; 3549 3550 if (!v) { 3551 ierr = PetscFree(values);CHKERRQ(ierr); 3552 } 3553 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3554 PetscFunctionReturn(0); 3555 } 3556 3557 /*@ 3558 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3559 (the default parallel PETSc format). 3560 3561 Collective on MPI_Comm 3562 3563 Input Parameters: 3564 + B - the matrix 3565 . i - the indices into j for the start of each local row (starts with zero) 3566 . j - the column indices for each local row (starts with zero) 3567 - v - optional values in the matrix 3568 3569 Level: developer 3570 3571 Notes: 3572 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3573 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3574 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3575 3576 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3577 3578 The format which is used for the sparse matrix input, is equivalent to a 3579 row-major ordering.. i.e for the following matrix, the input data expected is 3580 as shown 3581 3582 $ 1 0 0 3583 $ 2 0 3 P0 3584 $ ------- 3585 $ 4 5 6 P1 3586 $ 3587 $ Process0 [P0]: rows_owned=[0,1] 3588 $ i = {0,1,3} [size = nrow+1 = 2+1] 3589 $ j = {0,0,2} [size = 3] 3590 $ v = {1,2,3} [size = 3] 3591 $ 3592 $ Process1 [P1]: rows_owned=[2] 3593 $ i = {0,3} [size = nrow+1 = 1+1] 3594 $ j = {0,1,2} [size = 3] 3595 $ v = {4,5,6} [size = 3] 3596 3597 .keywords: matrix, aij, compressed row, sparse, parallel 3598 3599 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3600 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3601 @*/ 3602 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3603 { 3604 PetscErrorCode ierr; 3605 3606 PetscFunctionBegin; 3607 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3608 PetscFunctionReturn(0); 3609 } 3610 3611 /*@C 3612 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3613 (the default parallel PETSc format). For good matrix assembly performance 3614 the user should preallocate the matrix storage by setting the parameters 3615 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3616 performance can be increased by more than a factor of 50. 3617 3618 Collective on MPI_Comm 3619 3620 Input Parameters: 3621 + B - the matrix 3622 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3623 (same value is used for all local rows) 3624 . d_nnz - array containing the number of nonzeros in the various rows of the 3625 DIAGONAL portion of the local submatrix (possibly different for each row) 3626 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3627 The size of this array is equal to the number of local rows, i.e 'm'. 3628 For matrices that will be factored, you must leave room for (and set) 3629 the diagonal entry even if it is zero. 3630 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3631 submatrix (same value is used for all local rows). 3632 - o_nnz - array containing the number of nonzeros in the various rows of the 3633 OFF-DIAGONAL portion of the local submatrix (possibly different for 3634 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3635 structure. The size of this array is equal to the number 3636 of local rows, i.e 'm'. 3637 3638 If the *_nnz parameter is given then the *_nz parameter is ignored 3639 3640 The AIJ format (also called the Yale sparse matrix format or 3641 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3642 storage. The stored row and column indices begin with zero. 3643 See Users-Manual: ch_mat for details. 3644 3645 The parallel matrix is partitioned such that the first m0 rows belong to 3646 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3647 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3648 3649 The DIAGONAL portion of the local submatrix of a processor can be defined 3650 as the submatrix which is obtained by extraction the part corresponding to 3651 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3652 first row that belongs to the processor, r2 is the last row belonging to 3653 the this processor, and c1-c2 is range of indices of the local part of a 3654 vector suitable for applying the matrix to. This is an mxn matrix. In the 3655 common case of a square matrix, the row and column ranges are the same and 3656 the DIAGONAL part is also square. The remaining portion of the local 3657 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3658 3659 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3660 3661 You can call MatGetInfo() to get information on how effective the preallocation was; 3662 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3663 You can also run with the option -info and look for messages with the string 3664 malloc in them to see if additional memory allocation was needed. 3665 3666 Example usage: 3667 3668 Consider the following 8x8 matrix with 34 non-zero values, that is 3669 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3670 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3671 as follows: 3672 3673 .vb 3674 1 2 0 | 0 3 0 | 0 4 3675 Proc0 0 5 6 | 7 0 0 | 8 0 3676 9 0 10 | 11 0 0 | 12 0 3677 ------------------------------------- 3678 13 0 14 | 15 16 17 | 0 0 3679 Proc1 0 18 0 | 19 20 21 | 0 0 3680 0 0 0 | 22 23 0 | 24 0 3681 ------------------------------------- 3682 Proc2 25 26 27 | 0 0 28 | 29 0 3683 30 0 0 | 31 32 33 | 0 34 3684 .ve 3685 3686 This can be represented as a collection of submatrices as: 3687 3688 .vb 3689 A B C 3690 D E F 3691 G H I 3692 .ve 3693 3694 Where the submatrices A,B,C are owned by proc0, D,E,F are 3695 owned by proc1, G,H,I are owned by proc2. 3696 3697 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3698 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3699 The 'M','N' parameters are 8,8, and have the same values on all procs. 3700 3701 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3702 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3703 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3704 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3705 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3706 matrix, ans [DF] as another SeqAIJ matrix. 3707 3708 When d_nz, o_nz parameters are specified, d_nz storage elements are 3709 allocated for every row of the local diagonal submatrix, and o_nz 3710 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3711 One way to choose d_nz and o_nz is to use the max nonzerors per local 3712 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3713 In this case, the values of d_nz,o_nz are: 3714 .vb 3715 proc0 : dnz = 2, o_nz = 2 3716 proc1 : dnz = 3, o_nz = 2 3717 proc2 : dnz = 1, o_nz = 4 3718 .ve 3719 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3720 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3721 for proc3. i.e we are using 12+15+10=37 storage locations to store 3722 34 values. 3723 3724 When d_nnz, o_nnz parameters are specified, the storage is specified 3725 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3726 In the above case the values for d_nnz,o_nnz are: 3727 .vb 3728 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3729 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3730 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3731 .ve 3732 Here the space allocated is sum of all the above values i.e 34, and 3733 hence pre-allocation is perfect. 3734 3735 Level: intermediate 3736 3737 .keywords: matrix, aij, compressed row, sparse, parallel 3738 3739 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3740 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3741 @*/ 3742 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3743 { 3744 PetscErrorCode ierr; 3745 3746 PetscFunctionBegin; 3747 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3748 PetscValidType(B,1); 3749 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3750 PetscFunctionReturn(0); 3751 } 3752 3753 /*@ 3754 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3755 CSR format the local rows. 3756 3757 Collective on MPI_Comm 3758 3759 Input Parameters: 3760 + comm - MPI communicator 3761 . m - number of local rows (Cannot be PETSC_DECIDE) 3762 . n - This value should be the same as the local size used in creating the 3763 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3764 calculated if N is given) For square matrices n is almost always m. 3765 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3766 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3767 . i - row indices 3768 . j - column indices 3769 - a - matrix values 3770 3771 Output Parameter: 3772 . mat - the matrix 3773 3774 Level: intermediate 3775 3776 Notes: 3777 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3778 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3779 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3780 3781 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3782 3783 The format which is used for the sparse matrix input, is equivalent to a 3784 row-major ordering.. i.e for the following matrix, the input data expected is 3785 as shown 3786 3787 $ 1 0 0 3788 $ 2 0 3 P0 3789 $ ------- 3790 $ 4 5 6 P1 3791 $ 3792 $ Process0 [P0]: rows_owned=[0,1] 3793 $ i = {0,1,3} [size = nrow+1 = 2+1] 3794 $ j = {0,0,2} [size = 3] 3795 $ v = {1,2,3} [size = 3] 3796 $ 3797 $ Process1 [P1]: rows_owned=[2] 3798 $ i = {0,3} [size = nrow+1 = 1+1] 3799 $ j = {0,1,2} [size = 3] 3800 $ v = {4,5,6} [size = 3] 3801 3802 .keywords: matrix, aij, compressed row, sparse, parallel 3803 3804 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3805 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3806 @*/ 3807 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3808 { 3809 PetscErrorCode ierr; 3810 3811 PetscFunctionBegin; 3812 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3813 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3814 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3815 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3816 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3817 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3818 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3819 PetscFunctionReturn(0); 3820 } 3821 3822 /*@C 3823 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3824 (the default parallel PETSc format). For good matrix assembly performance 3825 the user should preallocate the matrix storage by setting the parameters 3826 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3827 performance can be increased by more than a factor of 50. 3828 3829 Collective on MPI_Comm 3830 3831 Input Parameters: 3832 + comm - MPI communicator 3833 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3834 This value should be the same as the local size used in creating the 3835 y vector for the matrix-vector product y = Ax. 3836 . n - This value should be the same as the local size used in creating the 3837 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3838 calculated if N is given) For square matrices n is almost always m. 3839 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3840 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3841 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3842 (same value is used for all local rows) 3843 . d_nnz - array containing the number of nonzeros in the various rows of the 3844 DIAGONAL portion of the local submatrix (possibly different for each row) 3845 or NULL, if d_nz is used to specify the nonzero structure. 3846 The size of this array is equal to the number of local rows, i.e 'm'. 3847 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3848 submatrix (same value is used for all local rows). 3849 - o_nnz - array containing the number of nonzeros in the various rows of the 3850 OFF-DIAGONAL portion of the local submatrix (possibly different for 3851 each row) or NULL, if o_nz is used to specify the nonzero 3852 structure. The size of this array is equal to the number 3853 of local rows, i.e 'm'. 3854 3855 Output Parameter: 3856 . A - the matrix 3857 3858 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3859 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3860 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3861 3862 Notes: 3863 If the *_nnz parameter is given then the *_nz parameter is ignored 3864 3865 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3866 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3867 storage requirements for this matrix. 3868 3869 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3870 processor than it must be used on all processors that share the object for 3871 that argument. 3872 3873 The user MUST specify either the local or global matrix dimensions 3874 (possibly both). 3875 3876 The parallel matrix is partitioned across processors such that the 3877 first m0 rows belong to process 0, the next m1 rows belong to 3878 process 1, the next m2 rows belong to process 2 etc.. where 3879 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3880 values corresponding to [m x N] submatrix. 3881 3882 The columns are logically partitioned with the n0 columns belonging 3883 to 0th partition, the next n1 columns belonging to the next 3884 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3885 3886 The DIAGONAL portion of the local submatrix on any given processor 3887 is the submatrix corresponding to the rows and columns m,n 3888 corresponding to the given processor. i.e diagonal matrix on 3889 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3890 etc. The remaining portion of the local submatrix [m x (N-n)] 3891 constitute the OFF-DIAGONAL portion. The example below better 3892 illustrates this concept. 3893 3894 For a square global matrix we define each processor's diagonal portion 3895 to be its local rows and the corresponding columns (a square submatrix); 3896 each processor's off-diagonal portion encompasses the remainder of the 3897 local matrix (a rectangular submatrix). 3898 3899 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3900 3901 When calling this routine with a single process communicator, a matrix of 3902 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3903 type of communicator, use the construction mechanism: 3904 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3905 3906 By default, this format uses inodes (identical nodes) when possible. 3907 We search for consecutive rows with the same nonzero structure, thereby 3908 reusing matrix information to achieve increased efficiency. 3909 3910 Options Database Keys: 3911 + -mat_no_inode - Do not use inodes 3912 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3913 - -mat_aij_oneindex - Internally use indexing starting at 1 3914 rather than 0. Note that when calling MatSetValues(), 3915 the user still MUST index entries starting at 0! 3916 3917 3918 Example usage: 3919 3920 Consider the following 8x8 matrix with 34 non-zero values, that is 3921 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3922 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3923 as follows: 3924 3925 .vb 3926 1 2 0 | 0 3 0 | 0 4 3927 Proc0 0 5 6 | 7 0 0 | 8 0 3928 9 0 10 | 11 0 0 | 12 0 3929 ------------------------------------- 3930 13 0 14 | 15 16 17 | 0 0 3931 Proc1 0 18 0 | 19 20 21 | 0 0 3932 0 0 0 | 22 23 0 | 24 0 3933 ------------------------------------- 3934 Proc2 25 26 27 | 0 0 28 | 29 0 3935 30 0 0 | 31 32 33 | 0 34 3936 .ve 3937 3938 This can be represented as a collection of submatrices as: 3939 3940 .vb 3941 A B C 3942 D E F 3943 G H I 3944 .ve 3945 3946 Where the submatrices A,B,C are owned by proc0, D,E,F are 3947 owned by proc1, G,H,I are owned by proc2. 3948 3949 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3950 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3951 The 'M','N' parameters are 8,8, and have the same values on all procs. 3952 3953 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3954 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3955 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3956 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3957 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3958 matrix, ans [DF] as another SeqAIJ matrix. 3959 3960 When d_nz, o_nz parameters are specified, d_nz storage elements are 3961 allocated for every row of the local diagonal submatrix, and o_nz 3962 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3963 One way to choose d_nz and o_nz is to use the max nonzerors per local 3964 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3965 In this case, the values of d_nz,o_nz are: 3966 .vb 3967 proc0 : dnz = 2, o_nz = 2 3968 proc1 : dnz = 3, o_nz = 2 3969 proc2 : dnz = 1, o_nz = 4 3970 .ve 3971 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3972 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3973 for proc3. i.e we are using 12+15+10=37 storage locations to store 3974 34 values. 3975 3976 When d_nnz, o_nnz parameters are specified, the storage is specified 3977 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3978 In the above case the values for d_nnz,o_nnz are: 3979 .vb 3980 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3981 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3982 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3983 .ve 3984 Here the space allocated is sum of all the above values i.e 34, and 3985 hence pre-allocation is perfect. 3986 3987 Level: intermediate 3988 3989 .keywords: matrix, aij, compressed row, sparse, parallel 3990 3991 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3992 MATMPIAIJ, MatCreateMPIAIJWithArrays() 3993 @*/ 3994 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) 3995 { 3996 PetscErrorCode ierr; 3997 PetscMPIInt size; 3998 3999 PetscFunctionBegin; 4000 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4001 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4002 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4003 if (size > 1) { 4004 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4005 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4006 } else { 4007 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4008 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4009 } 4010 PetscFunctionReturn(0); 4011 } 4012 4013 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4014 { 4015 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4016 PetscBool flg; 4017 PetscErrorCode ierr; 4018 4019 PetscFunctionBegin; 4020 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4021 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4022 if (Ad) *Ad = a->A; 4023 if (Ao) *Ao = a->B; 4024 if (colmap) *colmap = a->garray; 4025 PetscFunctionReturn(0); 4026 } 4027 4028 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4029 { 4030 PetscErrorCode ierr; 4031 PetscInt m,N,i,rstart,nnz,Ii; 4032 PetscInt *indx; 4033 PetscScalar *values; 4034 4035 PetscFunctionBegin; 4036 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4037 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4038 PetscInt *dnz,*onz,sum,bs,cbs; 4039 4040 if (n == PETSC_DECIDE) { 4041 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4042 } 4043 /* Check sum(n) = N */ 4044 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4045 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4046 4047 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4048 rstart -= m; 4049 4050 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4051 for (i=0; i<m; i++) { 4052 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4053 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4054 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4055 } 4056 4057 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4058 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4059 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4060 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4061 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4062 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4063 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4064 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4065 } 4066 4067 /* numeric phase */ 4068 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4069 for (i=0; i<m; i++) { 4070 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4071 Ii = i + rstart; 4072 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4073 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4074 } 4075 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4076 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4077 PetscFunctionReturn(0); 4078 } 4079 4080 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4081 { 4082 PetscErrorCode ierr; 4083 PetscMPIInt rank; 4084 PetscInt m,N,i,rstart,nnz; 4085 size_t len; 4086 const PetscInt *indx; 4087 PetscViewer out; 4088 char *name; 4089 Mat B; 4090 const PetscScalar *values; 4091 4092 PetscFunctionBegin; 4093 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4094 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4095 /* Should this be the type of the diagonal block of A? */ 4096 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4097 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4098 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4099 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4100 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4101 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4102 for (i=0; i<m; i++) { 4103 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4104 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4105 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4106 } 4107 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4108 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4109 4110 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4111 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4112 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4113 sprintf(name,"%s.%d",outfile,rank); 4114 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4115 ierr = PetscFree(name);CHKERRQ(ierr); 4116 ierr = MatView(B,out);CHKERRQ(ierr); 4117 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4118 ierr = MatDestroy(&B);CHKERRQ(ierr); 4119 PetscFunctionReturn(0); 4120 } 4121 4122 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4123 { 4124 PetscErrorCode ierr; 4125 Mat_Merge_SeqsToMPI *merge; 4126 PetscContainer container; 4127 4128 PetscFunctionBegin; 4129 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4130 if (container) { 4131 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4132 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4133 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4134 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4135 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4136 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4137 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4138 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4139 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4140 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4141 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4142 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4143 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4144 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4145 ierr = PetscFree(merge);CHKERRQ(ierr); 4146 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4147 } 4148 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4149 PetscFunctionReturn(0); 4150 } 4151 4152 #include <../src/mat/utils/freespace.h> 4153 #include <petscbt.h> 4154 4155 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4156 { 4157 PetscErrorCode ierr; 4158 MPI_Comm comm; 4159 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4160 PetscMPIInt size,rank,taga,*len_s; 4161 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4162 PetscInt proc,m; 4163 PetscInt **buf_ri,**buf_rj; 4164 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4165 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4166 MPI_Request *s_waits,*r_waits; 4167 MPI_Status *status; 4168 MatScalar *aa=a->a; 4169 MatScalar **abuf_r,*ba_i; 4170 Mat_Merge_SeqsToMPI *merge; 4171 PetscContainer container; 4172 4173 PetscFunctionBegin; 4174 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4175 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4176 4177 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4178 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4179 4180 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4181 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4182 4183 bi = merge->bi; 4184 bj = merge->bj; 4185 buf_ri = merge->buf_ri; 4186 buf_rj = merge->buf_rj; 4187 4188 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4189 owners = merge->rowmap->range; 4190 len_s = merge->len_s; 4191 4192 /* send and recv matrix values */ 4193 /*-----------------------------*/ 4194 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4195 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4196 4197 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4198 for (proc=0,k=0; proc<size; proc++) { 4199 if (!len_s[proc]) continue; 4200 i = owners[proc]; 4201 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4202 k++; 4203 } 4204 4205 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4206 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4207 ierr = PetscFree(status);CHKERRQ(ierr); 4208 4209 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4210 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4211 4212 /* insert mat values of mpimat */ 4213 /*----------------------------*/ 4214 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4215 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4216 4217 for (k=0; k<merge->nrecv; k++) { 4218 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4219 nrows = *(buf_ri_k[k]); 4220 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4221 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4222 } 4223 4224 /* set values of ba */ 4225 m = merge->rowmap->n; 4226 for (i=0; i<m; i++) { 4227 arow = owners[rank] + i; 4228 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4229 bnzi = bi[i+1] - bi[i]; 4230 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4231 4232 /* add local non-zero vals of this proc's seqmat into ba */ 4233 anzi = ai[arow+1] - ai[arow]; 4234 aj = a->j + ai[arow]; 4235 aa = a->a + ai[arow]; 4236 nextaj = 0; 4237 for (j=0; nextaj<anzi; j++) { 4238 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4239 ba_i[j] += aa[nextaj++]; 4240 } 4241 } 4242 4243 /* add received vals into ba */ 4244 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4245 /* i-th row */ 4246 if (i == *nextrow[k]) { 4247 anzi = *(nextai[k]+1) - *nextai[k]; 4248 aj = buf_rj[k] + *(nextai[k]); 4249 aa = abuf_r[k] + *(nextai[k]); 4250 nextaj = 0; 4251 for (j=0; nextaj<anzi; j++) { 4252 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4253 ba_i[j] += aa[nextaj++]; 4254 } 4255 } 4256 nextrow[k]++; nextai[k]++; 4257 } 4258 } 4259 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4260 } 4261 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4262 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4263 4264 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4265 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4266 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4267 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4268 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4269 PetscFunctionReturn(0); 4270 } 4271 4272 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4273 { 4274 PetscErrorCode ierr; 4275 Mat B_mpi; 4276 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4277 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4278 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4279 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4280 PetscInt len,proc,*dnz,*onz,bs,cbs; 4281 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4282 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4283 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4284 MPI_Status *status; 4285 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4286 PetscBT lnkbt; 4287 Mat_Merge_SeqsToMPI *merge; 4288 PetscContainer container; 4289 4290 PetscFunctionBegin; 4291 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4292 4293 /* make sure it is a PETSc comm */ 4294 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4295 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4296 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4297 4298 ierr = PetscNew(&merge);CHKERRQ(ierr); 4299 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4300 4301 /* determine row ownership */ 4302 /*---------------------------------------------------------*/ 4303 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4304 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4305 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4306 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4307 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4308 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4309 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4310 4311 m = merge->rowmap->n; 4312 owners = merge->rowmap->range; 4313 4314 /* determine the number of messages to send, their lengths */ 4315 /*---------------------------------------------------------*/ 4316 len_s = merge->len_s; 4317 4318 len = 0; /* length of buf_si[] */ 4319 merge->nsend = 0; 4320 for (proc=0; proc<size; proc++) { 4321 len_si[proc] = 0; 4322 if (proc == rank) { 4323 len_s[proc] = 0; 4324 } else { 4325 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4326 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4327 } 4328 if (len_s[proc]) { 4329 merge->nsend++; 4330 nrows = 0; 4331 for (i=owners[proc]; i<owners[proc+1]; i++) { 4332 if (ai[i+1] > ai[i]) nrows++; 4333 } 4334 len_si[proc] = 2*(nrows+1); 4335 len += len_si[proc]; 4336 } 4337 } 4338 4339 /* determine the number and length of messages to receive for ij-structure */ 4340 /*-------------------------------------------------------------------------*/ 4341 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4342 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4343 4344 /* post the Irecv of j-structure */ 4345 /*-------------------------------*/ 4346 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4347 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4348 4349 /* post the Isend of j-structure */ 4350 /*--------------------------------*/ 4351 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4352 4353 for (proc=0, k=0; proc<size; proc++) { 4354 if (!len_s[proc]) continue; 4355 i = owners[proc]; 4356 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4357 k++; 4358 } 4359 4360 /* receives and sends of j-structure are complete */ 4361 /*------------------------------------------------*/ 4362 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4363 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4364 4365 /* send and recv i-structure */ 4366 /*---------------------------*/ 4367 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4368 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4369 4370 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4371 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4372 for (proc=0,k=0; proc<size; proc++) { 4373 if (!len_s[proc]) continue; 4374 /* form outgoing message for i-structure: 4375 buf_si[0]: nrows to be sent 4376 [1:nrows]: row index (global) 4377 [nrows+1:2*nrows+1]: i-structure index 4378 */ 4379 /*-------------------------------------------*/ 4380 nrows = len_si[proc]/2 - 1; 4381 buf_si_i = buf_si + nrows+1; 4382 buf_si[0] = nrows; 4383 buf_si_i[0] = 0; 4384 nrows = 0; 4385 for (i=owners[proc]; i<owners[proc+1]; i++) { 4386 anzi = ai[i+1] - ai[i]; 4387 if (anzi) { 4388 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4389 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4390 nrows++; 4391 } 4392 } 4393 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4394 k++; 4395 buf_si += len_si[proc]; 4396 } 4397 4398 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4399 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4400 4401 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4402 for (i=0; i<merge->nrecv; i++) { 4403 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); 4404 } 4405 4406 ierr = PetscFree(len_si);CHKERRQ(ierr); 4407 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4408 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4409 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4410 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4411 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4412 ierr = PetscFree(status);CHKERRQ(ierr); 4413 4414 /* compute a local seq matrix in each processor */ 4415 /*----------------------------------------------*/ 4416 /* allocate bi array and free space for accumulating nonzero column info */ 4417 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4418 bi[0] = 0; 4419 4420 /* create and initialize a linked list */ 4421 nlnk = N+1; 4422 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4423 4424 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4425 len = ai[owners[rank+1]] - ai[owners[rank]]; 4426 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4427 4428 current_space = free_space; 4429 4430 /* determine symbolic info for each local row */ 4431 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4432 4433 for (k=0; k<merge->nrecv; k++) { 4434 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4435 nrows = *buf_ri_k[k]; 4436 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4437 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4438 } 4439 4440 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4441 len = 0; 4442 for (i=0; i<m; i++) { 4443 bnzi = 0; 4444 /* add local non-zero cols of this proc's seqmat into lnk */ 4445 arow = owners[rank] + i; 4446 anzi = ai[arow+1] - ai[arow]; 4447 aj = a->j + ai[arow]; 4448 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4449 bnzi += nlnk; 4450 /* add received col data into lnk */ 4451 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4452 if (i == *nextrow[k]) { /* i-th row */ 4453 anzi = *(nextai[k]+1) - *nextai[k]; 4454 aj = buf_rj[k] + *nextai[k]; 4455 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4456 bnzi += nlnk; 4457 nextrow[k]++; nextai[k]++; 4458 } 4459 } 4460 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4461 4462 /* if free space is not available, make more free space */ 4463 if (current_space->local_remaining<bnzi) { 4464 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4465 nspacedouble++; 4466 } 4467 /* copy data into free space, then initialize lnk */ 4468 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4469 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4470 4471 current_space->array += bnzi; 4472 current_space->local_used += bnzi; 4473 current_space->local_remaining -= bnzi; 4474 4475 bi[i+1] = bi[i] + bnzi; 4476 } 4477 4478 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4479 4480 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4481 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4482 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4483 4484 /* create symbolic parallel matrix B_mpi */ 4485 /*---------------------------------------*/ 4486 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4487 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4488 if (n==PETSC_DECIDE) { 4489 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4490 } else { 4491 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4492 } 4493 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4494 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4495 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4496 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4497 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4498 4499 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4500 B_mpi->assembled = PETSC_FALSE; 4501 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4502 merge->bi = bi; 4503 merge->bj = bj; 4504 merge->buf_ri = buf_ri; 4505 merge->buf_rj = buf_rj; 4506 merge->coi = NULL; 4507 merge->coj = NULL; 4508 merge->owners_co = NULL; 4509 4510 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4511 4512 /* attach the supporting struct to B_mpi for reuse */ 4513 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4514 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4515 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4516 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4517 *mpimat = B_mpi; 4518 4519 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4520 PetscFunctionReturn(0); 4521 } 4522 4523 /*@C 4524 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4525 matrices from each processor 4526 4527 Collective on MPI_Comm 4528 4529 Input Parameters: 4530 + comm - the communicators the parallel matrix will live on 4531 . seqmat - the input sequential matrices 4532 . m - number of local rows (or PETSC_DECIDE) 4533 . n - number of local columns (or PETSC_DECIDE) 4534 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4535 4536 Output Parameter: 4537 . mpimat - the parallel matrix generated 4538 4539 Level: advanced 4540 4541 Notes: 4542 The dimensions of the sequential matrix in each processor MUST be the same. 4543 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4544 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4545 @*/ 4546 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4547 { 4548 PetscErrorCode ierr; 4549 PetscMPIInt size; 4550 4551 PetscFunctionBegin; 4552 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4553 if (size == 1) { 4554 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4555 if (scall == MAT_INITIAL_MATRIX) { 4556 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4557 } else { 4558 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4559 } 4560 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4561 PetscFunctionReturn(0); 4562 } 4563 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4564 if (scall == MAT_INITIAL_MATRIX) { 4565 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4566 } 4567 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4568 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4569 PetscFunctionReturn(0); 4570 } 4571 4572 /*@ 4573 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4574 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4575 with MatGetSize() 4576 4577 Not Collective 4578 4579 Input Parameters: 4580 + A - the matrix 4581 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4582 4583 Output Parameter: 4584 . A_loc - the local sequential matrix generated 4585 4586 Level: developer 4587 4588 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4589 4590 @*/ 4591 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4592 { 4593 PetscErrorCode ierr; 4594 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4595 Mat_SeqAIJ *mat,*a,*b; 4596 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4597 MatScalar *aa,*ba,*cam; 4598 PetscScalar *ca; 4599 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4600 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4601 PetscBool match; 4602 MPI_Comm comm; 4603 PetscMPIInt size; 4604 4605 PetscFunctionBegin; 4606 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4607 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4608 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4609 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4610 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4611 4612 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4613 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4614 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4615 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4616 aa = a->a; ba = b->a; 4617 if (scall == MAT_INITIAL_MATRIX) { 4618 if (size == 1) { 4619 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4620 PetscFunctionReturn(0); 4621 } 4622 4623 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4624 ci[0] = 0; 4625 for (i=0; i<am; i++) { 4626 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4627 } 4628 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4629 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4630 k = 0; 4631 for (i=0; i<am; i++) { 4632 ncols_o = bi[i+1] - bi[i]; 4633 ncols_d = ai[i+1] - ai[i]; 4634 /* off-diagonal portion of A */ 4635 for (jo=0; jo<ncols_o; jo++) { 4636 col = cmap[*bj]; 4637 if (col >= cstart) break; 4638 cj[k] = col; bj++; 4639 ca[k++] = *ba++; 4640 } 4641 /* diagonal portion of A */ 4642 for (j=0; j<ncols_d; j++) { 4643 cj[k] = cstart + *aj++; 4644 ca[k++] = *aa++; 4645 } 4646 /* off-diagonal portion of A */ 4647 for (j=jo; j<ncols_o; j++) { 4648 cj[k] = cmap[*bj++]; 4649 ca[k++] = *ba++; 4650 } 4651 } 4652 /* put together the new matrix */ 4653 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4654 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4655 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4656 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4657 mat->free_a = PETSC_TRUE; 4658 mat->free_ij = PETSC_TRUE; 4659 mat->nonew = 0; 4660 } else if (scall == MAT_REUSE_MATRIX) { 4661 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4662 ci = mat->i; cj = mat->j; cam = mat->a; 4663 for (i=0; i<am; i++) { 4664 /* off-diagonal portion of A */ 4665 ncols_o = bi[i+1] - bi[i]; 4666 for (jo=0; jo<ncols_o; jo++) { 4667 col = cmap[*bj]; 4668 if (col >= cstart) break; 4669 *cam++ = *ba++; bj++; 4670 } 4671 /* diagonal portion of A */ 4672 ncols_d = ai[i+1] - ai[i]; 4673 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4674 /* off-diagonal portion of A */ 4675 for (j=jo; j<ncols_o; j++) { 4676 *cam++ = *ba++; bj++; 4677 } 4678 } 4679 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4680 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4681 PetscFunctionReturn(0); 4682 } 4683 4684 /*@C 4685 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4686 4687 Not Collective 4688 4689 Input Parameters: 4690 + A - the matrix 4691 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4692 - row, col - index sets of rows and columns to extract (or NULL) 4693 4694 Output Parameter: 4695 . A_loc - the local sequential matrix generated 4696 4697 Level: developer 4698 4699 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4700 4701 @*/ 4702 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4703 { 4704 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4705 PetscErrorCode ierr; 4706 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4707 IS isrowa,iscola; 4708 Mat *aloc; 4709 PetscBool match; 4710 4711 PetscFunctionBegin; 4712 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4713 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4714 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4715 if (!row) { 4716 start = A->rmap->rstart; end = A->rmap->rend; 4717 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4718 } else { 4719 isrowa = *row; 4720 } 4721 if (!col) { 4722 start = A->cmap->rstart; 4723 cmap = a->garray; 4724 nzA = a->A->cmap->n; 4725 nzB = a->B->cmap->n; 4726 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4727 ncols = 0; 4728 for (i=0; i<nzB; i++) { 4729 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4730 else break; 4731 } 4732 imark = i; 4733 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4734 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4735 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4736 } else { 4737 iscola = *col; 4738 } 4739 if (scall != MAT_INITIAL_MATRIX) { 4740 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4741 aloc[0] = *A_loc; 4742 } 4743 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4744 *A_loc = aloc[0]; 4745 ierr = PetscFree(aloc);CHKERRQ(ierr); 4746 if (!row) { 4747 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4748 } 4749 if (!col) { 4750 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4751 } 4752 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4753 PetscFunctionReturn(0); 4754 } 4755 4756 /*@C 4757 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4758 4759 Collective on Mat 4760 4761 Input Parameters: 4762 + A,B - the matrices in mpiaij format 4763 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4764 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4765 4766 Output Parameter: 4767 + rowb, colb - index sets of rows and columns of B to extract 4768 - B_seq - the sequential matrix generated 4769 4770 Level: developer 4771 4772 @*/ 4773 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4774 { 4775 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4776 PetscErrorCode ierr; 4777 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4778 IS isrowb,iscolb; 4779 Mat *bseq=NULL; 4780 4781 PetscFunctionBegin; 4782 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4783 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); 4784 } 4785 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4786 4787 if (scall == MAT_INITIAL_MATRIX) { 4788 start = A->cmap->rstart; 4789 cmap = a->garray; 4790 nzA = a->A->cmap->n; 4791 nzB = a->B->cmap->n; 4792 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4793 ncols = 0; 4794 for (i=0; i<nzB; i++) { /* row < local row index */ 4795 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4796 else break; 4797 } 4798 imark = i; 4799 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4800 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4801 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4802 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4803 } else { 4804 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4805 isrowb = *rowb; iscolb = *colb; 4806 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4807 bseq[0] = *B_seq; 4808 } 4809 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4810 *B_seq = bseq[0]; 4811 ierr = PetscFree(bseq);CHKERRQ(ierr); 4812 if (!rowb) { 4813 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4814 } else { 4815 *rowb = isrowb; 4816 } 4817 if (!colb) { 4818 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4819 } else { 4820 *colb = iscolb; 4821 } 4822 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4823 PetscFunctionReturn(0); 4824 } 4825 4826 /* 4827 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4828 of the OFF-DIAGONAL portion of local A 4829 4830 Collective on Mat 4831 4832 Input Parameters: 4833 + A,B - the matrices in mpiaij format 4834 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4835 4836 Output Parameter: 4837 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4838 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4839 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4840 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4841 4842 Level: developer 4843 4844 */ 4845 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4846 { 4847 VecScatter_MPI_General *gen_to,*gen_from; 4848 PetscErrorCode ierr; 4849 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4850 Mat_SeqAIJ *b_oth; 4851 VecScatter ctx =a->Mvctx; 4852 MPI_Comm comm; 4853 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4854 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4855 PetscInt *rvalues,*svalues; 4856 MatScalar *b_otha,*bufa,*bufA; 4857 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4858 MPI_Request *rwaits = NULL,*swaits = NULL; 4859 MPI_Status *sstatus,rstatus; 4860 PetscMPIInt jj,size; 4861 PetscInt *cols,sbs,rbs; 4862 PetscScalar *vals; 4863 4864 PetscFunctionBegin; 4865 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4866 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4867 4868 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4869 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); 4870 } 4871 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4872 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4873 4874 if (size == 1) { 4875 startsj_s = NULL; 4876 bufa_ptr = NULL; 4877 *B_oth = NULL; 4878 PetscFunctionReturn(0); 4879 } 4880 4881 gen_to = (VecScatter_MPI_General*)ctx->todata; 4882 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4883 nrecvs = gen_from->n; 4884 nsends = gen_to->n; 4885 4886 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4887 srow = gen_to->indices; /* local row index to be sent */ 4888 sstarts = gen_to->starts; 4889 sprocs = gen_to->procs; 4890 sstatus = gen_to->sstatus; 4891 sbs = gen_to->bs; 4892 rstarts = gen_from->starts; 4893 rprocs = gen_from->procs; 4894 rbs = gen_from->bs; 4895 4896 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4897 if (scall == MAT_INITIAL_MATRIX) { 4898 /* i-array */ 4899 /*---------*/ 4900 /* post receives */ 4901 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4902 for (i=0; i<nrecvs; i++) { 4903 rowlen = rvalues + rstarts[i]*rbs; 4904 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4905 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4906 } 4907 4908 /* pack the outgoing message */ 4909 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4910 4911 sstartsj[0] = 0; 4912 rstartsj[0] = 0; 4913 len = 0; /* total length of j or a array to be sent */ 4914 k = 0; 4915 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4916 for (i=0; i<nsends; i++) { 4917 rowlen = svalues + sstarts[i]*sbs; 4918 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4919 for (j=0; j<nrows; j++) { 4920 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4921 for (l=0; l<sbs; l++) { 4922 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4923 4924 rowlen[j*sbs+l] = ncols; 4925 4926 len += ncols; 4927 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4928 } 4929 k++; 4930 } 4931 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4932 4933 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4934 } 4935 /* recvs and sends of i-array are completed */ 4936 i = nrecvs; 4937 while (i--) { 4938 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4939 } 4940 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4941 ierr = PetscFree(svalues);CHKERRQ(ierr); 4942 4943 /* allocate buffers for sending j and a arrays */ 4944 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4945 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4946 4947 /* create i-array of B_oth */ 4948 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4949 4950 b_othi[0] = 0; 4951 len = 0; /* total length of j or a array to be received */ 4952 k = 0; 4953 for (i=0; i<nrecvs; i++) { 4954 rowlen = rvalues + rstarts[i]*rbs; 4955 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4956 for (j=0; j<nrows; j++) { 4957 b_othi[k+1] = b_othi[k] + rowlen[j]; 4958 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4959 k++; 4960 } 4961 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4962 } 4963 ierr = PetscFree(rvalues);CHKERRQ(ierr); 4964 4965 /* allocate space for j and a arrrays of B_oth */ 4966 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4967 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4968 4969 /* j-array */ 4970 /*---------*/ 4971 /* post receives of j-array */ 4972 for (i=0; i<nrecvs; i++) { 4973 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4974 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4975 } 4976 4977 /* pack the outgoing message j-array */ 4978 k = 0; 4979 for (i=0; i<nsends; i++) { 4980 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4981 bufJ = bufj+sstartsj[i]; 4982 for (j=0; j<nrows; j++) { 4983 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4984 for (ll=0; ll<sbs; ll++) { 4985 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4986 for (l=0; l<ncols; l++) { 4987 *bufJ++ = cols[l]; 4988 } 4989 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4990 } 4991 } 4992 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4993 } 4994 4995 /* recvs and sends of j-array are completed */ 4996 i = nrecvs; 4997 while (i--) { 4998 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4999 } 5000 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5001 } else if (scall == MAT_REUSE_MATRIX) { 5002 sstartsj = *startsj_s; 5003 rstartsj = *startsj_r; 5004 bufa = *bufa_ptr; 5005 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5006 b_otha = b_oth->a; 5007 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5008 5009 /* a-array */ 5010 /*---------*/ 5011 /* post receives of a-array */ 5012 for (i=0; i<nrecvs; i++) { 5013 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5014 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5015 } 5016 5017 /* pack the outgoing message a-array */ 5018 k = 0; 5019 for (i=0; i<nsends; i++) { 5020 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5021 bufA = bufa+sstartsj[i]; 5022 for (j=0; j<nrows; j++) { 5023 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5024 for (ll=0; ll<sbs; ll++) { 5025 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5026 for (l=0; l<ncols; l++) { 5027 *bufA++ = vals[l]; 5028 } 5029 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5030 } 5031 } 5032 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5033 } 5034 /* recvs and sends of a-array are completed */ 5035 i = nrecvs; 5036 while (i--) { 5037 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5038 } 5039 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5040 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5041 5042 if (scall == MAT_INITIAL_MATRIX) { 5043 /* put together the new matrix */ 5044 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5045 5046 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5047 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5048 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5049 b_oth->free_a = PETSC_TRUE; 5050 b_oth->free_ij = PETSC_TRUE; 5051 b_oth->nonew = 0; 5052 5053 ierr = PetscFree(bufj);CHKERRQ(ierr); 5054 if (!startsj_s || !bufa_ptr) { 5055 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5056 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5057 } else { 5058 *startsj_s = sstartsj; 5059 *startsj_r = rstartsj; 5060 *bufa_ptr = bufa; 5061 } 5062 } 5063 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5064 PetscFunctionReturn(0); 5065 } 5066 5067 /*@C 5068 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5069 5070 Not Collective 5071 5072 Input Parameters: 5073 . A - The matrix in mpiaij format 5074 5075 Output Parameter: 5076 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5077 . colmap - A map from global column index to local index into lvec 5078 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5079 5080 Level: developer 5081 5082 @*/ 5083 #if defined(PETSC_USE_CTABLE) 5084 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5085 #else 5086 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5087 #endif 5088 { 5089 Mat_MPIAIJ *a; 5090 5091 PetscFunctionBegin; 5092 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5093 PetscValidPointer(lvec, 2); 5094 PetscValidPointer(colmap, 3); 5095 PetscValidPointer(multScatter, 4); 5096 a = (Mat_MPIAIJ*) A->data; 5097 if (lvec) *lvec = a->lvec; 5098 if (colmap) *colmap = a->colmap; 5099 if (multScatter) *multScatter = a->Mvctx; 5100 PetscFunctionReturn(0); 5101 } 5102 5103 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5104 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5105 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5106 #if defined(PETSC_HAVE_ELEMENTAL) 5107 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5108 #endif 5109 #if defined(PETSC_HAVE_HYPRE) 5110 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5111 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5112 #endif 5113 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5114 5115 /* 5116 Computes (B'*A')' since computing B*A directly is untenable 5117 5118 n p p 5119 ( ) ( ) ( ) 5120 m ( A ) * n ( B ) = m ( C ) 5121 ( ) ( ) ( ) 5122 5123 */ 5124 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5125 { 5126 PetscErrorCode ierr; 5127 Mat At,Bt,Ct; 5128 5129 PetscFunctionBegin; 5130 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5131 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5132 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5133 ierr = MatDestroy(&At);CHKERRQ(ierr); 5134 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5135 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5136 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5137 PetscFunctionReturn(0); 5138 } 5139 5140 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5141 { 5142 PetscErrorCode ierr; 5143 PetscInt m=A->rmap->n,n=B->cmap->n; 5144 Mat Cmat; 5145 5146 PetscFunctionBegin; 5147 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); 5148 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5149 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5150 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5151 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5152 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5153 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5154 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5155 5156 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5157 5158 *C = Cmat; 5159 PetscFunctionReturn(0); 5160 } 5161 5162 /* ----------------------------------------------------------------*/ 5163 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5164 { 5165 PetscErrorCode ierr; 5166 5167 PetscFunctionBegin; 5168 if (scall == MAT_INITIAL_MATRIX) { 5169 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5170 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5171 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5172 } 5173 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5174 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5175 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5176 PetscFunctionReturn(0); 5177 } 5178 5179 /*MC 5180 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5181 5182 Options Database Keys: 5183 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5184 5185 Level: beginner 5186 5187 .seealso: MatCreateAIJ() 5188 M*/ 5189 5190 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5191 { 5192 Mat_MPIAIJ *b; 5193 PetscErrorCode ierr; 5194 PetscMPIInt size; 5195 5196 PetscFunctionBegin; 5197 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5198 5199 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5200 B->data = (void*)b; 5201 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5202 B->assembled = PETSC_FALSE; 5203 B->insertmode = NOT_SET_VALUES; 5204 b->size = size; 5205 5206 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5207 5208 /* build cache for off array entries formed */ 5209 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5210 5211 b->donotstash = PETSC_FALSE; 5212 b->colmap = 0; 5213 b->garray = 0; 5214 b->roworiented = PETSC_TRUE; 5215 5216 /* stuff used for matrix vector multiply */ 5217 b->lvec = NULL; 5218 b->Mvctx = NULL; 5219 5220 /* stuff for MatGetRow() */ 5221 b->rowindices = 0; 5222 b->rowvalues = 0; 5223 b->getrowactive = PETSC_FALSE; 5224 5225 /* flexible pointer used in CUSP/CUSPARSE classes */ 5226 b->spptr = NULL; 5227 5228 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5229 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5230 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5231 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5232 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5233 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5234 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5235 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5236 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5237 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5238 #if defined(PETSC_HAVE_ELEMENTAL) 5239 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5240 #endif 5241 #if defined(PETSC_HAVE_HYPRE) 5242 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5243 #endif 5244 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5245 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5246 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5247 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5248 #if defined(PETSC_HAVE_HYPRE) 5249 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5250 #endif 5251 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5252 PetscFunctionReturn(0); 5253 } 5254 5255 /*@C 5256 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5257 and "off-diagonal" part of the matrix in CSR format. 5258 5259 Collective on MPI_Comm 5260 5261 Input Parameters: 5262 + comm - MPI communicator 5263 . m - number of local rows (Cannot be PETSC_DECIDE) 5264 . n - This value should be the same as the local size used in creating the 5265 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5266 calculated if N is given) For square matrices n is almost always m. 5267 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5268 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5269 . i - row indices for "diagonal" portion of matrix 5270 . j - column indices 5271 . a - matrix values 5272 . oi - row indices for "off-diagonal" portion of matrix 5273 . oj - column indices 5274 - oa - matrix values 5275 5276 Output Parameter: 5277 . mat - the matrix 5278 5279 Level: advanced 5280 5281 Notes: 5282 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5283 must free the arrays once the matrix has been destroyed and not before. 5284 5285 The i and j indices are 0 based 5286 5287 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5288 5289 This sets local rows and cannot be used to set off-processor values. 5290 5291 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5292 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5293 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5294 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5295 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5296 communication if it is known that only local entries will be set. 5297 5298 .keywords: matrix, aij, compressed row, sparse, parallel 5299 5300 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5301 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5302 @*/ 5303 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) 5304 { 5305 PetscErrorCode ierr; 5306 Mat_MPIAIJ *maij; 5307 5308 PetscFunctionBegin; 5309 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5310 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5311 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5312 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5313 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5314 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5315 maij = (Mat_MPIAIJ*) (*mat)->data; 5316 5317 (*mat)->preallocated = PETSC_TRUE; 5318 5319 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5320 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5321 5322 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5323 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5324 5325 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5326 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5327 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5328 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5329 5330 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5331 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5332 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5333 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5334 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5335 PetscFunctionReturn(0); 5336 } 5337 5338 /* 5339 Special version for direct calls from Fortran 5340 */ 5341 #include <petsc/private/fortranimpl.h> 5342 5343 /* Change these macros so can be used in void function */ 5344 #undef CHKERRQ 5345 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5346 #undef SETERRQ2 5347 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5348 #undef SETERRQ3 5349 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5350 #undef SETERRQ 5351 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5352 5353 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5354 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5355 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5356 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5357 #else 5358 #endif 5359 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) 5360 { 5361 Mat mat = *mmat; 5362 PetscInt m = *mm, n = *mn; 5363 InsertMode addv = *maddv; 5364 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5365 PetscScalar value; 5366 PetscErrorCode ierr; 5367 5368 MatCheckPreallocated(mat,1); 5369 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5370 5371 #if defined(PETSC_USE_DEBUG) 5372 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5373 #endif 5374 { 5375 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5376 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5377 PetscBool roworiented = aij->roworiented; 5378 5379 /* Some Variables required in the macro */ 5380 Mat A = aij->A; 5381 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5382 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5383 MatScalar *aa = a->a; 5384 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5385 Mat B = aij->B; 5386 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5387 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5388 MatScalar *ba = b->a; 5389 5390 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5391 PetscInt nonew = a->nonew; 5392 MatScalar *ap1,*ap2; 5393 5394 PetscFunctionBegin; 5395 for (i=0; i<m; i++) { 5396 if (im[i] < 0) continue; 5397 #if defined(PETSC_USE_DEBUG) 5398 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); 5399 #endif 5400 if (im[i] >= rstart && im[i] < rend) { 5401 row = im[i] - rstart; 5402 lastcol1 = -1; 5403 rp1 = aj + ai[row]; 5404 ap1 = aa + ai[row]; 5405 rmax1 = aimax[row]; 5406 nrow1 = ailen[row]; 5407 low1 = 0; 5408 high1 = nrow1; 5409 lastcol2 = -1; 5410 rp2 = bj + bi[row]; 5411 ap2 = ba + bi[row]; 5412 rmax2 = bimax[row]; 5413 nrow2 = bilen[row]; 5414 low2 = 0; 5415 high2 = nrow2; 5416 5417 for (j=0; j<n; j++) { 5418 if (roworiented) value = v[i*n+j]; 5419 else value = v[i+j*m]; 5420 if (in[j] >= cstart && in[j] < cend) { 5421 col = in[j] - cstart; 5422 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5423 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5424 } else if (in[j] < 0) continue; 5425 #if defined(PETSC_USE_DEBUG) 5426 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); 5427 #endif 5428 else { 5429 if (mat->was_assembled) { 5430 if (!aij->colmap) { 5431 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5432 } 5433 #if defined(PETSC_USE_CTABLE) 5434 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5435 col--; 5436 #else 5437 col = aij->colmap[in[j]] - 1; 5438 #endif 5439 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5440 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5441 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5442 col = in[j]; 5443 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5444 B = aij->B; 5445 b = (Mat_SeqAIJ*)B->data; 5446 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5447 rp2 = bj + bi[row]; 5448 ap2 = ba + bi[row]; 5449 rmax2 = bimax[row]; 5450 nrow2 = bilen[row]; 5451 low2 = 0; 5452 high2 = nrow2; 5453 bm = aij->B->rmap->n; 5454 ba = b->a; 5455 } 5456 } else col = in[j]; 5457 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5458 } 5459 } 5460 } else if (!aij->donotstash) { 5461 if (roworiented) { 5462 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5463 } else { 5464 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5465 } 5466 } 5467 } 5468 } 5469 PetscFunctionReturnVoid(); 5470 } 5471 5472