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 } 133 134 135 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 136 { 137 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 138 PetscErrorCode ierr; 139 PetscInt i,rstart,nrows,*rows; 140 141 PetscFunctionBegin; 142 *zrows = NULL; 143 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 144 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 145 for (i=0; i<nrows; i++) rows[i] += rstart; 146 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 147 PetscFunctionReturn(0); 148 } 149 150 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 151 { 152 PetscErrorCode ierr; 153 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 154 PetscInt i,n,*garray = aij->garray; 155 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 156 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 157 PetscReal *work; 158 159 PetscFunctionBegin; 160 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 161 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 162 if (type == NORM_2) { 163 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 164 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 165 } 166 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 167 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 168 } 169 } else if (type == NORM_1) { 170 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 171 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 172 } 173 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 174 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 175 } 176 } else if (type == NORM_INFINITY) { 177 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 178 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 179 } 180 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 181 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 182 } 183 184 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 185 if (type == NORM_INFINITY) { 186 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 187 } else { 188 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 189 } 190 ierr = PetscFree(work);CHKERRQ(ierr); 191 if (type == NORM_2) { 192 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 193 } 194 PetscFunctionReturn(0); 195 } 196 197 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 198 { 199 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 200 IS sis,gis; 201 PetscErrorCode ierr; 202 const PetscInt *isis,*igis; 203 PetscInt n,*iis,nsis,ngis,rstart,i; 204 205 PetscFunctionBegin; 206 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 207 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 208 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 209 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 210 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 211 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 212 213 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 215 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 216 n = ngis + nsis; 217 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 218 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 219 for (i=0; i<n; i++) iis[i] += rstart; 220 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 221 222 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 223 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 224 ierr = ISDestroy(&sis);CHKERRQ(ierr); 225 ierr = ISDestroy(&gis);CHKERRQ(ierr); 226 PetscFunctionReturn(0); 227 } 228 229 /* 230 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 231 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 232 233 Only for square matrices 234 235 Used by a preconditioner, hence PETSC_EXTERN 236 */ 237 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 238 { 239 PetscMPIInt rank,size; 240 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 241 PetscErrorCode ierr; 242 Mat mat; 243 Mat_SeqAIJ *gmata; 244 PetscMPIInt tag; 245 MPI_Status status; 246 PetscBool aij; 247 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 248 249 PetscFunctionBegin; 250 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 252 if (!rank) { 253 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 254 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 255 } 256 if (reuse == MAT_INITIAL_MATRIX) { 257 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 258 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 259 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 260 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 261 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 262 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 263 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 264 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 265 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 266 267 rowners[0] = 0; 268 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 269 rstart = rowners[rank]; 270 rend = rowners[rank+1]; 271 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 272 if (!rank) { 273 gmata = (Mat_SeqAIJ*) gmat->data; 274 /* send row lengths to all processors */ 275 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 276 for (i=1; i<size; i++) { 277 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 278 } 279 /* determine number diagonal and off-diagonal counts */ 280 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 281 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 282 jj = 0; 283 for (i=0; i<m; i++) { 284 for (j=0; j<dlens[i]; j++) { 285 if (gmata->j[jj] < rstart) ld[i]++; 286 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 287 jj++; 288 } 289 } 290 /* send column indices to other processes */ 291 for (i=1; i<size; i++) { 292 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 293 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 295 } 296 297 /* send numerical values to other processes */ 298 for (i=1; i<size; i++) { 299 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 300 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 301 } 302 gmataa = gmata->a; 303 gmataj = gmata->j; 304 305 } else { 306 /* receive row lengths */ 307 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 /* receive column indices */ 309 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 311 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 312 /* determine number diagonal and off-diagonal counts */ 313 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 314 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 315 jj = 0; 316 for (i=0; i<m; i++) { 317 for (j=0; j<dlens[i]; j++) { 318 if (gmataj[jj] < rstart) ld[i]++; 319 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 320 jj++; 321 } 322 } 323 /* receive numerical values */ 324 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 325 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 326 } 327 /* set preallocation */ 328 for (i=0; i<m; i++) { 329 dlens[i] -= olens[i]; 330 } 331 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 332 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 333 334 for (i=0; i<m; i++) { 335 dlens[i] += olens[i]; 336 } 337 cnt = 0; 338 for (i=0; i<m; i++) { 339 row = rstart + i; 340 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 341 cnt += dlens[i]; 342 } 343 if (rank) { 344 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 345 } 346 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 347 ierr = PetscFree(rowners);CHKERRQ(ierr); 348 349 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 350 351 *inmat = mat; 352 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 353 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 354 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 355 mat = *inmat; 356 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 357 if (!rank) { 358 /* send numerical values to other processes */ 359 gmata = (Mat_SeqAIJ*) gmat->data; 360 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 361 gmataa = gmata->a; 362 for (i=1; i<size; i++) { 363 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 364 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 365 } 366 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 367 } else { 368 /* receive numerical values from process 0*/ 369 nz = Ad->nz + Ao->nz; 370 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 371 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 372 } 373 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 374 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 375 ad = Ad->a; 376 ao = Ao->a; 377 if (mat->rmap->n) { 378 i = 0; 379 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 380 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 381 } 382 for (i=1; i<mat->rmap->n; i++) { 383 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; 384 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 385 } 386 i--; 387 if (mat->rmap->n) { 388 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 389 } 390 if (rank) { 391 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 392 } 393 } 394 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 396 PetscFunctionReturn(0); 397 } 398 399 /* 400 Local utility routine that creates a mapping from the global column 401 number to the local number in the off-diagonal part of the local 402 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 403 a slightly higher hash table cost; without it it is not scalable (each processor 404 has an order N integer array but is fast to acess. 405 */ 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 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); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 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); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 499 { 500 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 501 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 502 PetscErrorCode ierr; 503 PetscInt l,*garray = mat->garray,diag; 504 505 PetscFunctionBegin; 506 /* code only works for square matrices A */ 507 508 /* find size of row to the left of the diagonal part */ 509 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 510 row = row - diag; 511 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 512 if (garray[b->j[b->i[row]+l]] > diag) break; 513 } 514 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 515 516 /* diagonal part */ 517 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 518 519 /* right of diagonal part */ 520 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); 521 PetscFunctionReturn(0); 522 } 523 524 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 525 { 526 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 527 PetscScalar value; 528 PetscErrorCode ierr; 529 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 530 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 531 PetscBool roworiented = aij->roworiented; 532 533 /* Some Variables required in the macro */ 534 Mat A = aij->A; 535 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 536 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 537 MatScalar *aa = a->a; 538 PetscBool ignorezeroentries = a->ignorezeroentries; 539 Mat B = aij->B; 540 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 541 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 542 MatScalar *ba = b->a; 543 544 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 545 PetscInt nonew; 546 MatScalar *ap1,*ap2; 547 548 PetscFunctionBegin; 549 for (i=0; i<m; i++) { 550 if (im[i] < 0) continue; 551 #if defined(PETSC_USE_DEBUG) 552 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); 553 #endif 554 if (im[i] >= rstart && im[i] < rend) { 555 row = im[i] - rstart; 556 lastcol1 = -1; 557 rp1 = aj + ai[row]; 558 ap1 = aa + ai[row]; 559 rmax1 = aimax[row]; 560 nrow1 = ailen[row]; 561 low1 = 0; 562 high1 = nrow1; 563 lastcol2 = -1; 564 rp2 = bj + bi[row]; 565 ap2 = ba + bi[row]; 566 rmax2 = bimax[row]; 567 nrow2 = bilen[row]; 568 low2 = 0; 569 high2 = nrow2; 570 571 for (j=0; j<n; j++) { 572 if (roworiented) value = v[i*n+j]; 573 else value = v[i+j*m]; 574 if (in[j] >= cstart && in[j] < cend) { 575 col = in[j] - cstart; 576 nonew = a->nonew; 577 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 578 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 579 } else if (in[j] < 0) continue; 580 #if defined(PETSC_USE_DEBUG) 581 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); 582 #endif 583 else { 584 if (mat->was_assembled) { 585 if (!aij->colmap) { 586 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 587 } 588 #if defined(PETSC_USE_CTABLE) 589 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 590 col--; 591 #else 592 col = aij->colmap[in[j]] - 1; 593 #endif 594 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 595 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 596 col = in[j]; 597 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 598 B = aij->B; 599 b = (Mat_SeqAIJ*)B->data; 600 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 601 rp2 = bj + bi[row]; 602 ap2 = ba + bi[row]; 603 rmax2 = bimax[row]; 604 nrow2 = bilen[row]; 605 low2 = 0; 606 high2 = nrow2; 607 bm = aij->B->rmap->n; 608 ba = b->a; 609 } 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]); 610 } else col = in[j]; 611 nonew = b->nonew; 612 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 613 } 614 } 615 } else { 616 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]); 617 if (!aij->donotstash) { 618 mat->assembled = PETSC_FALSE; 619 if (roworiented) { 620 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } else { 622 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 623 } 624 } 625 } 626 } 627 PetscFunctionReturn(0); 628 } 629 630 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 631 { 632 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 633 PetscErrorCode ierr; 634 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 635 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 636 637 PetscFunctionBegin; 638 for (i=0; i<m; i++) { 639 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 640 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); 641 if (idxm[i] >= rstart && idxm[i] < rend) { 642 row = idxm[i] - rstart; 643 for (j=0; j<n; j++) { 644 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 645 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); 646 if (idxn[j] >= cstart && idxn[j] < cend) { 647 col = idxn[j] - cstart; 648 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 649 } else { 650 if (!aij->colmap) { 651 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 652 } 653 #if defined(PETSC_USE_CTABLE) 654 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 655 col--; 656 #else 657 col = aij->colmap[idxn[j]] - 1; 658 #endif 659 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 660 else { 661 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 662 } 663 } 664 } 665 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 666 } 667 PetscFunctionReturn(0); 668 } 669 670 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 671 672 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 673 { 674 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 675 PetscErrorCode ierr; 676 PetscInt nstash,reallocs; 677 678 PetscFunctionBegin; 679 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 680 681 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 682 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 683 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 684 PetscFunctionReturn(0); 685 } 686 687 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 688 { 689 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 690 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 691 PetscErrorCode ierr; 692 PetscMPIInt n; 693 PetscInt i,j,rstart,ncols,flg; 694 PetscInt *row,*col; 695 PetscBool other_disassembled; 696 PetscScalar *val; 697 698 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 699 700 PetscFunctionBegin; 701 if (!aij->donotstash && !mat->nooffprocentries) { 702 while (1) { 703 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 704 if (!flg) break; 705 706 for (i=0; i<n; ) { 707 /* Now identify the consecutive vals belonging to the same row */ 708 for (j=i,rstart=row[j]; j<n; j++) { 709 if (row[j] != rstart) break; 710 } 711 if (j < n) ncols = j-i; 712 else ncols = n-i; 713 /* Now assemble all these values with a single function call */ 714 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 715 716 i = j; 717 } 718 } 719 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 720 } 721 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 722 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 723 724 /* determine if any processor has disassembled, if so we must 725 also disassemble ourselfs, in order that we may reassemble. */ 726 /* 727 if nonzero structure of submatrix B cannot change then we know that 728 no processor disassembled thus we can skip this stuff 729 */ 730 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 731 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 732 if (mat->was_assembled && !other_disassembled) { 733 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 734 } 735 } 736 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 737 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 738 } 739 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 740 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 741 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 742 743 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 744 745 aij->rowvalues = 0; 746 747 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 748 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 749 750 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 751 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 752 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 753 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 754 } 755 PetscFunctionReturn(0); 756 } 757 758 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 759 { 760 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 761 PetscErrorCode ierr; 762 763 PetscFunctionBegin; 764 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 765 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 766 PetscFunctionReturn(0); 767 } 768 769 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 770 { 771 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 772 PetscInt *lrows; 773 PetscInt r, len; 774 PetscErrorCode ierr; 775 776 PetscFunctionBegin; 777 /* get locally owned rows */ 778 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 779 /* fix right hand side if needed */ 780 if (x && b) { 781 const PetscScalar *xx; 782 PetscScalar *bb; 783 784 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 785 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 786 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 787 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 788 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 789 } 790 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 791 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 792 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 793 PetscBool cong; 794 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 795 if (cong) A->congruentlayouts = 1; 796 else A->congruentlayouts = 0; 797 } 798 if ((diag != 0.0) && A->congruentlayouts) { 799 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 800 } else if (diag != 0.0) { 801 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 802 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"); 803 for (r = 0; r < len; ++r) { 804 const PetscInt row = lrows[r] + A->rmap->rstart; 805 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 806 } 807 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 808 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 809 } else { 810 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 811 } 812 ierr = PetscFree(lrows);CHKERRQ(ierr); 813 814 /* only change matrix nonzero state if pattern was allowed to be changed */ 815 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 816 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 817 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 818 } 819 PetscFunctionReturn(0); 820 } 821 822 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 823 { 824 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 825 PetscErrorCode ierr; 826 PetscMPIInt n = A->rmap->n; 827 PetscInt i,j,r,m,p = 0,len = 0; 828 PetscInt *lrows,*owners = A->rmap->range; 829 PetscSFNode *rrows; 830 PetscSF sf; 831 const PetscScalar *xx; 832 PetscScalar *bb,*mask; 833 Vec xmask,lmask; 834 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 835 const PetscInt *aj, *ii,*ridx; 836 PetscScalar *aa; 837 838 PetscFunctionBegin; 839 /* Create SF where leaves are input rows and roots are owned rows */ 840 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 841 for (r = 0; r < n; ++r) lrows[r] = -1; 842 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 843 for (r = 0; r < N; ++r) { 844 const PetscInt idx = rows[r]; 845 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); 846 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 847 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 848 } 849 rrows[r].rank = p; 850 rrows[r].index = rows[r] - owners[p]; 851 } 852 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 853 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 854 /* Collect flags for rows to be zeroed */ 855 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 856 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 857 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 858 /* Compress and put in row numbers */ 859 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 860 /* zero diagonal part of matrix */ 861 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 862 /* handle off diagonal part of matrix */ 863 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 864 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 865 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 866 for (i=0; i<len; i++) bb[lrows[i]] = 1; 867 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 868 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 869 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 870 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 871 if (x) { 872 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 873 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 874 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 875 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 876 } 877 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 878 /* remove zeroed rows of off diagonal matrix */ 879 ii = aij->i; 880 for (i=0; i<len; i++) { 881 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 882 } 883 /* loop over all elements of off process part of matrix zeroing removed columns*/ 884 if (aij->compressedrow.use) { 885 m = aij->compressedrow.nrows; 886 ii = aij->compressedrow.i; 887 ridx = aij->compressedrow.rindex; 888 for (i=0; i<m; i++) { 889 n = ii[i+1] - ii[i]; 890 aj = aij->j + ii[i]; 891 aa = aij->a + ii[i]; 892 893 for (j=0; j<n; j++) { 894 if (PetscAbsScalar(mask[*aj])) { 895 if (b) bb[*ridx] -= *aa*xx[*aj]; 896 *aa = 0.0; 897 } 898 aa++; 899 aj++; 900 } 901 ridx++; 902 } 903 } else { /* do not use compressed row format */ 904 m = l->B->rmap->n; 905 for (i=0; i<m; i++) { 906 n = ii[i+1] - ii[i]; 907 aj = aij->j + ii[i]; 908 aa = aij->a + ii[i]; 909 for (j=0; j<n; j++) { 910 if (PetscAbsScalar(mask[*aj])) { 911 if (b) bb[i] -= *aa*xx[*aj]; 912 *aa = 0.0; 913 } 914 aa++; 915 aj++; 916 } 917 } 918 } 919 if (x) { 920 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 921 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 922 } 923 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 924 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 925 ierr = PetscFree(lrows);CHKERRQ(ierr); 926 927 /* only change matrix nonzero state if pattern was allowed to be changed */ 928 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 929 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 930 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 931 } 932 PetscFunctionReturn(0); 933 } 934 935 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 936 { 937 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 938 PetscErrorCode ierr; 939 PetscInt nt; 940 941 PetscFunctionBegin; 942 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 943 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); 944 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 946 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 947 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 952 { 953 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 954 PetscErrorCode ierr; 955 956 PetscFunctionBegin; 957 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 962 { 963 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 964 PetscErrorCode ierr; 965 966 PetscFunctionBegin; 967 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 969 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 970 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 975 { 976 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 977 PetscErrorCode ierr; 978 PetscBool merged; 979 980 PetscFunctionBegin; 981 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 982 /* do nondiagonal part */ 983 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 984 if (!merged) { 985 /* send it on its way */ 986 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 987 /* do local part */ 988 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 989 /* receive remote parts: note this assumes the values are not actually */ 990 /* added in yy until the next line, */ 991 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 992 } else { 993 /* do local part */ 994 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 995 /* send it on its way */ 996 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 /* values actually were received in the Begin() but we need to call this nop */ 998 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 999 } 1000 PetscFunctionReturn(0); 1001 } 1002 1003 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1004 { 1005 MPI_Comm comm; 1006 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1007 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1008 IS Me,Notme; 1009 PetscErrorCode ierr; 1010 PetscInt M,N,first,last,*notme,i; 1011 PetscMPIInt size; 1012 1013 PetscFunctionBegin; 1014 /* Easy test: symmetric diagonal block */ 1015 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1016 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1017 if (!*f) PetscFunctionReturn(0); 1018 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1019 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1020 if (size == 1) PetscFunctionReturn(0); 1021 1022 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1023 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1024 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1025 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1026 for (i=0; i<first; i++) notme[i] = i; 1027 for (i=last; i<M; i++) notme[i-last+first] = i; 1028 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1029 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1030 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1031 Aoff = Aoffs[0]; 1032 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1033 Boff = Boffs[0]; 1034 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1035 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1036 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1037 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1038 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1039 ierr = PetscFree(notme);CHKERRQ(ierr); 1040 PetscFunctionReturn(0); 1041 } 1042 1043 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1044 { 1045 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1046 PetscErrorCode ierr; 1047 1048 PetscFunctionBegin; 1049 /* do nondiagonal part */ 1050 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1051 /* send it on its way */ 1052 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1053 /* do local part */ 1054 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1055 /* receive remote parts */ 1056 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 /* 1061 This only works correctly for square matrices where the subblock A->A is the 1062 diagonal block 1063 */ 1064 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1065 { 1066 PetscErrorCode ierr; 1067 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1068 1069 PetscFunctionBegin; 1070 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1071 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"); 1072 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1073 PetscFunctionReturn(0); 1074 } 1075 1076 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1077 { 1078 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1079 PetscErrorCode ierr; 1080 1081 PetscFunctionBegin; 1082 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1083 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1084 PetscFunctionReturn(0); 1085 } 1086 1087 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1088 { 1089 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1090 PetscErrorCode ierr; 1091 1092 PetscFunctionBegin; 1093 #if defined(PETSC_USE_LOG) 1094 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1095 #endif 1096 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1097 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1098 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1099 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1100 #if defined(PETSC_USE_CTABLE) 1101 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1102 #else 1103 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1104 #endif 1105 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1106 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1107 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1108 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1109 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1110 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1111 1112 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1118 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1120 #if defined(PETSC_HAVE_ELEMENTAL) 1121 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1122 #endif 1123 #if defined(PETSC_HAVE_HYPRE) 1124 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1126 #endif 1127 PetscFunctionReturn(0); 1128 } 1129 1130 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1131 { 1132 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1133 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1134 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1135 PetscErrorCode ierr; 1136 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1137 int fd; 1138 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1139 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1140 PetscScalar *column_values; 1141 PetscInt message_count,flowcontrolcount; 1142 FILE *file; 1143 1144 PetscFunctionBegin; 1145 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1146 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1147 nz = A->nz + B->nz; 1148 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1149 if (!rank) { 1150 header[0] = MAT_FILE_CLASSID; 1151 header[1] = mat->rmap->N; 1152 header[2] = mat->cmap->N; 1153 1154 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1155 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1156 /* get largest number of rows any processor has */ 1157 rlen = mat->rmap->n; 1158 range = mat->rmap->range; 1159 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1160 } else { 1161 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1162 rlen = mat->rmap->n; 1163 } 1164 1165 /* load up the local row counts */ 1166 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1167 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]; 1168 1169 /* store the row lengths to the file */ 1170 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1171 if (!rank) { 1172 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1173 for (i=1; i<size; i++) { 1174 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1175 rlen = range[i+1] - range[i]; 1176 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1177 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1178 } 1179 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1180 } else { 1181 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1182 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1183 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1184 } 1185 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1186 1187 /* load up the local column indices */ 1188 nzmax = nz; /* th processor needs space a largest processor needs */ 1189 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1190 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1191 cnt = 0; 1192 for (i=0; i<mat->rmap->n; i++) { 1193 for (j=B->i[i]; j<B->i[i+1]; j++) { 1194 if ((col = garray[B->j[j]]) > cstart) break; 1195 column_indices[cnt++] = col; 1196 } 1197 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1198 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1199 } 1200 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); 1201 1202 /* store the column indices to the file */ 1203 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1204 if (!rank) { 1205 MPI_Status status; 1206 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1207 for (i=1; i<size; i++) { 1208 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1209 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1210 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1211 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1212 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1213 } 1214 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1215 } else { 1216 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1217 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1218 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1220 } 1221 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1222 1223 /* load up the local column values */ 1224 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1225 cnt = 0; 1226 for (i=0; i<mat->rmap->n; i++) { 1227 for (j=B->i[i]; j<B->i[i+1]; j++) { 1228 if (garray[B->j[j]] > cstart) break; 1229 column_values[cnt++] = B->a[j]; 1230 } 1231 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1232 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1233 } 1234 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); 1235 1236 /* store the column values to the file */ 1237 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1238 if (!rank) { 1239 MPI_Status status; 1240 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1241 for (i=1; i<size; i++) { 1242 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1243 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1244 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1245 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1247 } 1248 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1249 } else { 1250 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1251 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1252 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1253 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1254 } 1255 ierr = PetscFree(column_values);CHKERRQ(ierr); 1256 1257 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1258 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #include <petscdraw.h> 1263 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1264 { 1265 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1266 PetscErrorCode ierr; 1267 PetscMPIInt rank = aij->rank,size = aij->size; 1268 PetscBool isdraw,iascii,isbinary; 1269 PetscViewer sviewer; 1270 PetscViewerFormat format; 1271 1272 PetscFunctionBegin; 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1274 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1275 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1276 if (iascii) { 1277 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1278 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1279 MatInfo info; 1280 PetscBool inodes; 1281 1282 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1283 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1284 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1285 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1286 if (!inodes) { 1287 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1288 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1289 } else { 1290 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1291 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1292 } 1293 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1297 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1298 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1299 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1300 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1301 PetscFunctionReturn(0); 1302 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1303 PetscInt inodecount,inodelimit,*inodes; 1304 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1305 if (inodes) { 1306 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1307 } else { 1308 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1309 } 1310 PetscFunctionReturn(0); 1311 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1312 PetscFunctionReturn(0); 1313 } 1314 } else if (isbinary) { 1315 if (size == 1) { 1316 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1317 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1318 } else { 1319 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1320 } 1321 PetscFunctionReturn(0); 1322 } else if (isdraw) { 1323 PetscDraw draw; 1324 PetscBool isnull; 1325 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1326 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1327 if (isnull) PetscFunctionReturn(0); 1328 } 1329 1330 { 1331 /* assemble the entire matrix onto first processor. */ 1332 Mat A; 1333 Mat_SeqAIJ *Aloc; 1334 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1335 MatScalar *a; 1336 1337 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1338 if (!rank) { 1339 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1340 } else { 1341 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1342 } 1343 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1344 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1345 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1346 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1347 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1348 1349 /* copy over the A part */ 1350 Aloc = (Mat_SeqAIJ*)aij->A->data; 1351 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1352 row = mat->rmap->rstart; 1353 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1354 for (i=0; i<m; i++) { 1355 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1356 row++; 1357 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1358 } 1359 aj = Aloc->j; 1360 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1361 1362 /* copy over the B part */ 1363 Aloc = (Mat_SeqAIJ*)aij->B->data; 1364 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1365 row = mat->rmap->rstart; 1366 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1367 ct = cols; 1368 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1369 for (i=0; i<m; i++) { 1370 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1371 row++; 1372 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1373 } 1374 ierr = PetscFree(ct);CHKERRQ(ierr); 1375 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1376 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1377 /* 1378 Everyone has to call to draw the matrix since the graphics waits are 1379 synchronized across all processors that share the PetscDraw object 1380 */ 1381 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1382 if (!rank) { 1383 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1384 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1385 } 1386 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1387 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1388 ierr = MatDestroy(&A);CHKERRQ(ierr); 1389 } 1390 PetscFunctionReturn(0); 1391 } 1392 1393 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1394 { 1395 PetscErrorCode ierr; 1396 PetscBool iascii,isdraw,issocket,isbinary; 1397 1398 PetscFunctionBegin; 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1401 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1402 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1403 if (iascii || isdraw || isbinary || issocket) { 1404 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1405 } 1406 PetscFunctionReturn(0); 1407 } 1408 1409 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1410 { 1411 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1412 PetscErrorCode ierr; 1413 Vec bb1 = 0; 1414 PetscBool hasop; 1415 1416 PetscFunctionBegin; 1417 if (flag == SOR_APPLY_UPPER) { 1418 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1419 PetscFunctionReturn(0); 1420 } 1421 1422 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1423 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1424 } 1425 1426 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1427 if (flag & SOR_ZERO_INITIAL_GUESS) { 1428 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1429 its--; 1430 } 1431 1432 while (its--) { 1433 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1434 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1435 1436 /* update rhs: bb1 = bb - B*x */ 1437 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1438 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1439 1440 /* local sweep */ 1441 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1442 } 1443 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1444 if (flag & SOR_ZERO_INITIAL_GUESS) { 1445 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1446 its--; 1447 } 1448 while (its--) { 1449 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1450 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1451 1452 /* update rhs: bb1 = bb - B*x */ 1453 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1454 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1455 1456 /* local sweep */ 1457 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1458 } 1459 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1460 if (flag & SOR_ZERO_INITIAL_GUESS) { 1461 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1462 its--; 1463 } 1464 while (its--) { 1465 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1466 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1467 1468 /* update rhs: bb1 = bb - B*x */ 1469 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1470 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1471 1472 /* local sweep */ 1473 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1474 } 1475 } else if (flag & SOR_EISENSTAT) { 1476 Vec xx1; 1477 1478 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1479 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1480 1481 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1482 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1483 if (!mat->diag) { 1484 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1485 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1486 } 1487 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1488 if (hasop) { 1489 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1490 } else { 1491 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1492 } 1493 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1494 1495 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1496 1497 /* local sweep */ 1498 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1499 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1500 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1501 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1502 1503 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1504 1505 matin->factorerrortype = mat->A->factorerrortype; 1506 PetscFunctionReturn(0); 1507 } 1508 1509 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1510 { 1511 Mat aA,aB,Aperm; 1512 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1513 PetscScalar *aa,*ba; 1514 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1515 PetscSF rowsf,sf; 1516 IS parcolp = NULL; 1517 PetscBool done; 1518 PetscErrorCode ierr; 1519 1520 PetscFunctionBegin; 1521 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1522 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1523 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1524 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1525 1526 /* Invert row permutation to find out where my rows should go */ 1527 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1528 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1529 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1530 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1531 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1532 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1533 1534 /* Invert column permutation to find out where my columns should go */ 1535 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1536 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1537 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1538 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1539 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1540 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1541 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1542 1543 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1544 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1545 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1546 1547 /* Find out where my gcols should go */ 1548 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1549 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1550 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1551 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1552 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1553 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1554 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1555 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1556 1557 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1558 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1559 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1560 for (i=0; i<m; i++) { 1561 PetscInt row = rdest[i],rowner; 1562 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1563 for (j=ai[i]; j<ai[i+1]; j++) { 1564 PetscInt cowner,col = cdest[aj[j]]; 1565 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1566 if (rowner == cowner) dnnz[i]++; 1567 else onnz[i]++; 1568 } 1569 for (j=bi[i]; j<bi[i+1]; j++) { 1570 PetscInt cowner,col = gcdest[bj[j]]; 1571 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1572 if (rowner == cowner) dnnz[i]++; 1573 else onnz[i]++; 1574 } 1575 } 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1578 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1579 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1580 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1581 1582 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1583 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1584 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1585 for (i=0; i<m; i++) { 1586 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1587 PetscInt j0,rowlen; 1588 rowlen = ai[i+1] - ai[i]; 1589 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1590 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1591 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1592 } 1593 rowlen = bi[i+1] - bi[i]; 1594 for (j0=j=0; j<rowlen; j0=j) { 1595 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1596 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1597 } 1598 } 1599 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1600 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1601 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1602 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1603 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1604 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1605 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1606 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1607 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1608 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1609 *B = Aperm; 1610 PetscFunctionReturn(0); 1611 } 1612 1613 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1614 { 1615 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1616 PetscErrorCode ierr; 1617 1618 PetscFunctionBegin; 1619 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1620 if (ghosts) *ghosts = aij->garray; 1621 PetscFunctionReturn(0); 1622 } 1623 1624 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1625 { 1626 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1627 Mat A = mat->A,B = mat->B; 1628 PetscErrorCode ierr; 1629 PetscReal isend[5],irecv[5]; 1630 1631 PetscFunctionBegin; 1632 info->block_size = 1.0; 1633 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1634 1635 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1636 isend[3] = info->memory; isend[4] = info->mallocs; 1637 1638 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1639 1640 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1641 isend[3] += info->memory; isend[4] += info->mallocs; 1642 if (flag == MAT_LOCAL) { 1643 info->nz_used = isend[0]; 1644 info->nz_allocated = isend[1]; 1645 info->nz_unneeded = isend[2]; 1646 info->memory = isend[3]; 1647 info->mallocs = isend[4]; 1648 } else if (flag == MAT_GLOBAL_MAX) { 1649 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1650 1651 info->nz_used = irecv[0]; 1652 info->nz_allocated = irecv[1]; 1653 info->nz_unneeded = irecv[2]; 1654 info->memory = irecv[3]; 1655 info->mallocs = irecv[4]; 1656 } else if (flag == MAT_GLOBAL_SUM) { 1657 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1658 1659 info->nz_used = irecv[0]; 1660 info->nz_allocated = irecv[1]; 1661 info->nz_unneeded = irecv[2]; 1662 info->memory = irecv[3]; 1663 info->mallocs = irecv[4]; 1664 } 1665 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1666 info->fill_ratio_needed = 0; 1667 info->factor_mallocs = 0; 1668 PetscFunctionReturn(0); 1669 } 1670 1671 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1672 { 1673 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1674 PetscErrorCode ierr; 1675 1676 PetscFunctionBegin; 1677 switch (op) { 1678 case MAT_NEW_NONZERO_LOCATIONS: 1679 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1680 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1681 case MAT_KEEP_NONZERO_PATTERN: 1682 case MAT_NEW_NONZERO_LOCATION_ERR: 1683 case MAT_USE_INODES: 1684 case MAT_IGNORE_ZERO_ENTRIES: 1685 MatCheckPreallocated(A,1); 1686 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1687 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1688 break; 1689 case MAT_ROW_ORIENTED: 1690 MatCheckPreallocated(A,1); 1691 a->roworiented = flg; 1692 1693 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1694 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1695 break; 1696 case MAT_NEW_DIAGONALS: 1697 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1698 break; 1699 case MAT_IGNORE_OFF_PROC_ENTRIES: 1700 a->donotstash = flg; 1701 break; 1702 case MAT_SPD: 1703 A->spd_set = PETSC_TRUE; 1704 A->spd = flg; 1705 if (flg) { 1706 A->symmetric = PETSC_TRUE; 1707 A->structurally_symmetric = PETSC_TRUE; 1708 A->symmetric_set = PETSC_TRUE; 1709 A->structurally_symmetric_set = PETSC_TRUE; 1710 } 1711 break; 1712 case MAT_SYMMETRIC: 1713 MatCheckPreallocated(A,1); 1714 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1715 break; 1716 case MAT_STRUCTURALLY_SYMMETRIC: 1717 MatCheckPreallocated(A,1); 1718 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1719 break; 1720 case MAT_HERMITIAN: 1721 MatCheckPreallocated(A,1); 1722 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1723 break; 1724 case MAT_SYMMETRY_ETERNAL: 1725 MatCheckPreallocated(A,1); 1726 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1727 break; 1728 case MAT_SUBMAT_SINGLEIS: 1729 A->submat_singleis = flg; 1730 break; 1731 default: 1732 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1733 } 1734 PetscFunctionReturn(0); 1735 } 1736 1737 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1738 { 1739 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1740 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1741 PetscErrorCode ierr; 1742 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1743 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1744 PetscInt *cmap,*idx_p; 1745 1746 PetscFunctionBegin; 1747 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1748 mat->getrowactive = PETSC_TRUE; 1749 1750 if (!mat->rowvalues && (idx || v)) { 1751 /* 1752 allocate enough space to hold information from the longest row. 1753 */ 1754 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1755 PetscInt max = 1,tmp; 1756 for (i=0; i<matin->rmap->n; i++) { 1757 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1758 if (max < tmp) max = tmp; 1759 } 1760 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1761 } 1762 1763 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1764 lrow = row - rstart; 1765 1766 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1767 if (!v) {pvA = 0; pvB = 0;} 1768 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1769 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1770 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1771 nztot = nzA + nzB; 1772 1773 cmap = mat->garray; 1774 if (v || idx) { 1775 if (nztot) { 1776 /* Sort by increasing column numbers, assuming A and B already sorted */ 1777 PetscInt imark = -1; 1778 if (v) { 1779 *v = v_p = mat->rowvalues; 1780 for (i=0; i<nzB; i++) { 1781 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1782 else break; 1783 } 1784 imark = i; 1785 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1786 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1787 } 1788 if (idx) { 1789 *idx = idx_p = mat->rowindices; 1790 if (imark > -1) { 1791 for (i=0; i<imark; i++) { 1792 idx_p[i] = cmap[cworkB[i]]; 1793 } 1794 } else { 1795 for (i=0; i<nzB; i++) { 1796 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1797 else break; 1798 } 1799 imark = i; 1800 } 1801 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1802 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1803 } 1804 } else { 1805 if (idx) *idx = 0; 1806 if (v) *v = 0; 1807 } 1808 } 1809 *nz = nztot; 1810 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1811 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1812 PetscFunctionReturn(0); 1813 } 1814 1815 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1816 { 1817 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1818 1819 PetscFunctionBegin; 1820 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1821 aij->getrowactive = PETSC_FALSE; 1822 PetscFunctionReturn(0); 1823 } 1824 1825 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1826 { 1827 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1828 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1829 PetscErrorCode ierr; 1830 PetscInt i,j,cstart = mat->cmap->rstart; 1831 PetscReal sum = 0.0; 1832 MatScalar *v; 1833 1834 PetscFunctionBegin; 1835 if (aij->size == 1) { 1836 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1837 } else { 1838 if (type == NORM_FROBENIUS) { 1839 v = amat->a; 1840 for (i=0; i<amat->nz; i++) { 1841 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1842 } 1843 v = bmat->a; 1844 for (i=0; i<bmat->nz; i++) { 1845 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1846 } 1847 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1848 *norm = PetscSqrtReal(*norm); 1849 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1850 } else if (type == NORM_1) { /* max column norm */ 1851 PetscReal *tmp,*tmp2; 1852 PetscInt *jj,*garray = aij->garray; 1853 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1854 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1855 *norm = 0.0; 1856 v = amat->a; jj = amat->j; 1857 for (j=0; j<amat->nz; j++) { 1858 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1859 } 1860 v = bmat->a; jj = bmat->j; 1861 for (j=0; j<bmat->nz; j++) { 1862 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1863 } 1864 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1865 for (j=0; j<mat->cmap->N; j++) { 1866 if (tmp2[j] > *norm) *norm = tmp2[j]; 1867 } 1868 ierr = PetscFree(tmp);CHKERRQ(ierr); 1869 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1870 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1871 } else if (type == NORM_INFINITY) { /* max row norm */ 1872 PetscReal ntemp = 0.0; 1873 for (j=0; j<aij->A->rmap->n; j++) { 1874 v = amat->a + amat->i[j]; 1875 sum = 0.0; 1876 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1877 sum += PetscAbsScalar(*v); v++; 1878 } 1879 v = bmat->a + bmat->i[j]; 1880 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1881 sum += PetscAbsScalar(*v); v++; 1882 } 1883 if (sum > ntemp) ntemp = sum; 1884 } 1885 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1886 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1887 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1888 } 1889 PetscFunctionReturn(0); 1890 } 1891 1892 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1893 { 1894 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1895 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1896 PetscErrorCode ierr; 1897 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1898 PetscInt cstart = A->cmap->rstart,ncol; 1899 Mat B; 1900 MatScalar *array; 1901 1902 PetscFunctionBegin; 1903 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1904 1905 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1906 ai = Aloc->i; aj = Aloc->j; 1907 bi = Bloc->i; bj = Bloc->j; 1908 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1909 PetscInt *d_nnz,*g_nnz,*o_nnz; 1910 PetscSFNode *oloc; 1911 PETSC_UNUSED PetscSF sf; 1912 1913 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1914 /* compute d_nnz for preallocation */ 1915 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1916 for (i=0; i<ai[ma]; i++) { 1917 d_nnz[aj[i]]++; 1918 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1919 } 1920 /* compute local off-diagonal contributions */ 1921 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1922 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1923 /* map those to global */ 1924 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1925 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1926 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1927 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1928 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1929 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1930 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1931 1932 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1933 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1934 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1935 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1936 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1937 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1938 } else { 1939 B = *matout; 1940 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1941 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1942 } 1943 1944 /* copy over the A part */ 1945 array = Aloc->a; 1946 row = A->rmap->rstart; 1947 for (i=0; i<ma; i++) { 1948 ncol = ai[i+1]-ai[i]; 1949 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1950 row++; 1951 array += ncol; aj += ncol; 1952 } 1953 aj = Aloc->j; 1954 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1955 1956 /* copy over the B part */ 1957 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1958 array = Bloc->a; 1959 row = A->rmap->rstart; 1960 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1961 cols_tmp = cols; 1962 for (i=0; i<mb; i++) { 1963 ncol = bi[i+1]-bi[i]; 1964 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1965 row++; 1966 array += ncol; cols_tmp += ncol; 1967 } 1968 ierr = PetscFree(cols);CHKERRQ(ierr); 1969 1970 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1971 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1972 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1973 *matout = B; 1974 } else { 1975 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1976 } 1977 PetscFunctionReturn(0); 1978 } 1979 1980 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1981 { 1982 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1983 Mat a = aij->A,b = aij->B; 1984 PetscErrorCode ierr; 1985 PetscInt s1,s2,s3; 1986 1987 PetscFunctionBegin; 1988 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1989 if (rr) { 1990 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1991 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1992 /* Overlap communication with computation. */ 1993 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1994 } 1995 if (ll) { 1996 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1997 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1998 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1999 } 2000 /* scale the diagonal block */ 2001 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2002 2003 if (rr) { 2004 /* Do a scatter end and then right scale the off-diagonal block */ 2005 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2006 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2007 } 2008 PetscFunctionReturn(0); 2009 } 2010 2011 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2012 { 2013 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2014 PetscErrorCode ierr; 2015 2016 PetscFunctionBegin; 2017 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2018 PetscFunctionReturn(0); 2019 } 2020 2021 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2022 { 2023 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2024 Mat a,b,c,d; 2025 PetscBool flg; 2026 PetscErrorCode ierr; 2027 2028 PetscFunctionBegin; 2029 a = matA->A; b = matA->B; 2030 c = matB->A; d = matB->B; 2031 2032 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2033 if (flg) { 2034 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2035 } 2036 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2037 PetscFunctionReturn(0); 2038 } 2039 2040 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2041 { 2042 PetscErrorCode ierr; 2043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2044 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2045 2046 PetscFunctionBegin; 2047 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2048 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2049 /* because of the column compression in the off-processor part of the matrix a->B, 2050 the number of columns in a->B and b->B may be different, hence we cannot call 2051 the MatCopy() directly on the two parts. If need be, we can provide a more 2052 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2053 then copying the submatrices */ 2054 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2055 } else { 2056 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2057 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2058 } 2059 PetscFunctionReturn(0); 2060 } 2061 2062 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2063 { 2064 PetscErrorCode ierr; 2065 2066 PetscFunctionBegin; 2067 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2068 PetscFunctionReturn(0); 2069 } 2070 2071 /* 2072 Computes the number of nonzeros per row needed for preallocation when X and Y 2073 have different nonzero structure. 2074 */ 2075 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) 2076 { 2077 PetscInt i,j,k,nzx,nzy; 2078 2079 PetscFunctionBegin; 2080 /* Set the number of nonzeros in the new matrix */ 2081 for (i=0; i<m; i++) { 2082 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2083 nzx = xi[i+1] - xi[i]; 2084 nzy = yi[i+1] - yi[i]; 2085 nnz[i] = 0; 2086 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2087 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2088 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2089 nnz[i]++; 2090 } 2091 for (; k<nzy; k++) nnz[i]++; 2092 } 2093 PetscFunctionReturn(0); 2094 } 2095 2096 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2097 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2098 { 2099 PetscErrorCode ierr; 2100 PetscInt m = Y->rmap->N; 2101 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2102 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2103 2104 PetscFunctionBegin; 2105 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2106 PetscFunctionReturn(0); 2107 } 2108 2109 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2110 { 2111 PetscErrorCode ierr; 2112 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2113 PetscBLASInt bnz,one=1; 2114 Mat_SeqAIJ *x,*y; 2115 2116 PetscFunctionBegin; 2117 if (str == SAME_NONZERO_PATTERN) { 2118 PetscScalar alpha = a; 2119 x = (Mat_SeqAIJ*)xx->A->data; 2120 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2121 y = (Mat_SeqAIJ*)yy->A->data; 2122 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2123 x = (Mat_SeqAIJ*)xx->B->data; 2124 y = (Mat_SeqAIJ*)yy->B->data; 2125 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2126 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2127 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2128 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2129 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2130 } else { 2131 Mat B; 2132 PetscInt *nnz_d,*nnz_o; 2133 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2134 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2135 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2136 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2137 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2138 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2139 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2140 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2141 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2142 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2143 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2144 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2145 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2146 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2147 } 2148 PetscFunctionReturn(0); 2149 } 2150 2151 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2152 2153 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2154 { 2155 #if defined(PETSC_USE_COMPLEX) 2156 PetscErrorCode ierr; 2157 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2158 2159 PetscFunctionBegin; 2160 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2161 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2162 #else 2163 PetscFunctionBegin; 2164 #endif 2165 PetscFunctionReturn(0); 2166 } 2167 2168 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2169 { 2170 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2171 PetscErrorCode ierr; 2172 2173 PetscFunctionBegin; 2174 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2175 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2176 PetscFunctionReturn(0); 2177 } 2178 2179 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2180 { 2181 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2182 PetscErrorCode ierr; 2183 2184 PetscFunctionBegin; 2185 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2186 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2187 PetscFunctionReturn(0); 2188 } 2189 2190 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2191 { 2192 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2193 PetscErrorCode ierr; 2194 PetscInt i,*idxb = 0; 2195 PetscScalar *va,*vb; 2196 Vec vtmp; 2197 2198 PetscFunctionBegin; 2199 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2200 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2201 if (idx) { 2202 for (i=0; i<A->rmap->n; i++) { 2203 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2204 } 2205 } 2206 2207 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2208 if (idx) { 2209 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2210 } 2211 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2212 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2213 2214 for (i=0; i<A->rmap->n; i++) { 2215 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2216 va[i] = vb[i]; 2217 if (idx) idx[i] = a->garray[idxb[i]]; 2218 } 2219 } 2220 2221 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2222 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2223 ierr = PetscFree(idxb);CHKERRQ(ierr); 2224 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2225 PetscFunctionReturn(0); 2226 } 2227 2228 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2229 { 2230 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2231 PetscErrorCode ierr; 2232 PetscInt i,*idxb = 0; 2233 PetscScalar *va,*vb; 2234 Vec vtmp; 2235 2236 PetscFunctionBegin; 2237 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2238 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2239 if (idx) { 2240 for (i=0; i<A->cmap->n; i++) { 2241 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2242 } 2243 } 2244 2245 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2246 if (idx) { 2247 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2248 } 2249 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2250 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2251 2252 for (i=0; i<A->rmap->n; i++) { 2253 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2254 va[i] = vb[i]; 2255 if (idx) idx[i] = a->garray[idxb[i]]; 2256 } 2257 } 2258 2259 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2260 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2261 ierr = PetscFree(idxb);CHKERRQ(ierr); 2262 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2263 PetscFunctionReturn(0); 2264 } 2265 2266 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2267 { 2268 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2269 PetscInt n = A->rmap->n; 2270 PetscInt cstart = A->cmap->rstart; 2271 PetscInt *cmap = mat->garray; 2272 PetscInt *diagIdx, *offdiagIdx; 2273 Vec diagV, offdiagV; 2274 PetscScalar *a, *diagA, *offdiagA; 2275 PetscInt r; 2276 PetscErrorCode ierr; 2277 2278 PetscFunctionBegin; 2279 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2280 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2281 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2282 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2283 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2284 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2285 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2286 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2287 for (r = 0; r < n; ++r) { 2288 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2289 a[r] = diagA[r]; 2290 idx[r] = cstart + diagIdx[r]; 2291 } else { 2292 a[r] = offdiagA[r]; 2293 idx[r] = cmap[offdiagIdx[r]]; 2294 } 2295 } 2296 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2297 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2298 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2299 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2300 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2301 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2302 PetscFunctionReturn(0); 2303 } 2304 2305 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2306 { 2307 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2308 PetscInt n = A->rmap->n; 2309 PetscInt cstart = A->cmap->rstart; 2310 PetscInt *cmap = mat->garray; 2311 PetscInt *diagIdx, *offdiagIdx; 2312 Vec diagV, offdiagV; 2313 PetscScalar *a, *diagA, *offdiagA; 2314 PetscInt r; 2315 PetscErrorCode ierr; 2316 2317 PetscFunctionBegin; 2318 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2319 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2320 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2321 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2322 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2323 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2324 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2325 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2326 for (r = 0; r < n; ++r) { 2327 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2328 a[r] = diagA[r]; 2329 idx[r] = cstart + diagIdx[r]; 2330 } else { 2331 a[r] = offdiagA[r]; 2332 idx[r] = cmap[offdiagIdx[r]]; 2333 } 2334 } 2335 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2336 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2337 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2338 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2339 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2340 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2341 PetscFunctionReturn(0); 2342 } 2343 2344 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2345 { 2346 PetscErrorCode ierr; 2347 Mat *dummy; 2348 2349 PetscFunctionBegin; 2350 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2351 *newmat = *dummy; 2352 ierr = PetscFree(dummy);CHKERRQ(ierr); 2353 PetscFunctionReturn(0); 2354 } 2355 2356 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2357 { 2358 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2359 PetscErrorCode ierr; 2360 2361 PetscFunctionBegin; 2362 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2363 A->factorerrortype = a->A->factorerrortype; 2364 PetscFunctionReturn(0); 2365 } 2366 2367 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2368 { 2369 PetscErrorCode ierr; 2370 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2371 2372 PetscFunctionBegin; 2373 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2374 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2375 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2376 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2377 PetscFunctionReturn(0); 2378 } 2379 2380 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2381 { 2382 PetscFunctionBegin; 2383 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2384 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2385 PetscFunctionReturn(0); 2386 } 2387 2388 /*@ 2389 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2390 2391 Collective on Mat 2392 2393 Input Parameters: 2394 + A - the matrix 2395 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2396 2397 Level: advanced 2398 2399 @*/ 2400 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2401 { 2402 PetscErrorCode ierr; 2403 2404 PetscFunctionBegin; 2405 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2406 PetscFunctionReturn(0); 2407 } 2408 2409 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2410 { 2411 PetscErrorCode ierr; 2412 PetscBool sc = PETSC_FALSE,flg; 2413 2414 PetscFunctionBegin; 2415 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2416 ierr = PetscObjectOptionsBegin((PetscObject)A); 2417 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2418 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2419 if (flg) { 2420 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2421 } 2422 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2423 PetscFunctionReturn(0); 2424 } 2425 2426 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2427 { 2428 PetscErrorCode ierr; 2429 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2430 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2431 2432 PetscFunctionBegin; 2433 if (!Y->preallocated) { 2434 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2435 } else if (!aij->nz) { 2436 PetscInt nonew = aij->nonew; 2437 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2438 aij->nonew = nonew; 2439 } 2440 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2441 PetscFunctionReturn(0); 2442 } 2443 2444 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2445 { 2446 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2447 PetscErrorCode ierr; 2448 2449 PetscFunctionBegin; 2450 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2451 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2452 if (d) { 2453 PetscInt rstart; 2454 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2455 *d += rstart; 2456 2457 } 2458 PetscFunctionReturn(0); 2459 } 2460 2461 2462 /* -------------------------------------------------------------------*/ 2463 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2464 MatGetRow_MPIAIJ, 2465 MatRestoreRow_MPIAIJ, 2466 MatMult_MPIAIJ, 2467 /* 4*/ MatMultAdd_MPIAIJ, 2468 MatMultTranspose_MPIAIJ, 2469 MatMultTransposeAdd_MPIAIJ, 2470 0, 2471 0, 2472 0, 2473 /*10*/ 0, 2474 0, 2475 0, 2476 MatSOR_MPIAIJ, 2477 MatTranspose_MPIAIJ, 2478 /*15*/ MatGetInfo_MPIAIJ, 2479 MatEqual_MPIAIJ, 2480 MatGetDiagonal_MPIAIJ, 2481 MatDiagonalScale_MPIAIJ, 2482 MatNorm_MPIAIJ, 2483 /*20*/ MatAssemblyBegin_MPIAIJ, 2484 MatAssemblyEnd_MPIAIJ, 2485 MatSetOption_MPIAIJ, 2486 MatZeroEntries_MPIAIJ, 2487 /*24*/ MatZeroRows_MPIAIJ, 2488 0, 2489 0, 2490 0, 2491 0, 2492 /*29*/ MatSetUp_MPIAIJ, 2493 0, 2494 0, 2495 MatGetDiagonalBlock_MPIAIJ, 2496 0, 2497 /*34*/ MatDuplicate_MPIAIJ, 2498 0, 2499 0, 2500 0, 2501 0, 2502 /*39*/ MatAXPY_MPIAIJ, 2503 MatCreateSubMatrices_MPIAIJ, 2504 MatIncreaseOverlap_MPIAIJ, 2505 MatGetValues_MPIAIJ, 2506 MatCopy_MPIAIJ, 2507 /*44*/ MatGetRowMax_MPIAIJ, 2508 MatScale_MPIAIJ, 2509 MatShift_MPIAIJ, 2510 MatDiagonalSet_MPIAIJ, 2511 MatZeroRowsColumns_MPIAIJ, 2512 /*49*/ MatSetRandom_MPIAIJ, 2513 0, 2514 0, 2515 0, 2516 0, 2517 /*54*/ MatFDColoringCreate_MPIXAIJ, 2518 0, 2519 MatSetUnfactored_MPIAIJ, 2520 MatPermute_MPIAIJ, 2521 0, 2522 /*59*/ MatCreateSubMatrix_MPIAIJ, 2523 MatDestroy_MPIAIJ, 2524 MatView_MPIAIJ, 2525 0, 2526 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2527 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2528 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2529 0, 2530 0, 2531 0, 2532 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2533 MatGetRowMinAbs_MPIAIJ, 2534 0, 2535 0, 2536 0, 2537 0, 2538 /*75*/ MatFDColoringApply_AIJ, 2539 MatSetFromOptions_MPIAIJ, 2540 0, 2541 0, 2542 MatFindZeroDiagonals_MPIAIJ, 2543 /*80*/ 0, 2544 0, 2545 0, 2546 /*83*/ MatLoad_MPIAIJ, 2547 0, 2548 0, 2549 0, 2550 0, 2551 0, 2552 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2553 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2554 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2555 MatPtAP_MPIAIJ_MPIAIJ, 2556 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2557 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2558 0, 2559 0, 2560 0, 2561 0, 2562 /*99*/ 0, 2563 0, 2564 0, 2565 MatConjugate_MPIAIJ, 2566 0, 2567 /*104*/MatSetValuesRow_MPIAIJ, 2568 MatRealPart_MPIAIJ, 2569 MatImaginaryPart_MPIAIJ, 2570 0, 2571 0, 2572 /*109*/0, 2573 0, 2574 MatGetRowMin_MPIAIJ, 2575 0, 2576 MatMissingDiagonal_MPIAIJ, 2577 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2578 0, 2579 MatGetGhosts_MPIAIJ, 2580 0, 2581 0, 2582 /*119*/0, 2583 0, 2584 0, 2585 0, 2586 MatGetMultiProcBlock_MPIAIJ, 2587 /*124*/MatFindNonzeroRows_MPIAIJ, 2588 MatGetColumnNorms_MPIAIJ, 2589 MatInvertBlockDiagonal_MPIAIJ, 2590 0, 2591 MatCreateSubMatricesMPI_MPIAIJ, 2592 /*129*/0, 2593 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2594 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2595 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2596 0, 2597 /*134*/0, 2598 0, 2599 0, 2600 0, 2601 0, 2602 /*139*/MatSetBlockSizes_MPIAIJ, 2603 0, 2604 0, 2605 MatFDColoringSetUp_MPIXAIJ, 2606 MatFindOffBlockDiagonalEntries_MPIAIJ, 2607 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2608 }; 2609 2610 /* ----------------------------------------------------------------------------------------*/ 2611 2612 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2613 { 2614 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2615 PetscErrorCode ierr; 2616 2617 PetscFunctionBegin; 2618 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2619 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2620 PetscFunctionReturn(0); 2621 } 2622 2623 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2624 { 2625 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2626 PetscErrorCode ierr; 2627 2628 PetscFunctionBegin; 2629 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2630 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2631 PetscFunctionReturn(0); 2632 } 2633 2634 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2635 { 2636 Mat_MPIAIJ *b; 2637 PetscErrorCode ierr; 2638 2639 PetscFunctionBegin; 2640 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2641 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2642 b = (Mat_MPIAIJ*)B->data; 2643 2644 #if defined(PETSC_USE_CTABLE) 2645 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2646 #else 2647 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2648 #endif 2649 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2650 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2651 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2652 2653 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2654 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2655 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2656 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2657 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2658 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2659 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2660 2661 if (!B->preallocated) { 2662 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2663 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2664 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2665 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2666 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2667 } 2668 2669 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2670 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2671 B->preallocated = PETSC_TRUE; 2672 B->was_assembled = PETSC_FALSE; 2673 B->assembled = PETSC_FALSE;; 2674 PetscFunctionReturn(0); 2675 } 2676 2677 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2678 { 2679 Mat mat; 2680 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2681 PetscErrorCode ierr; 2682 2683 PetscFunctionBegin; 2684 *newmat = 0; 2685 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2686 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2687 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2688 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2689 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2690 a = (Mat_MPIAIJ*)mat->data; 2691 2692 mat->factortype = matin->factortype; 2693 mat->assembled = PETSC_TRUE; 2694 mat->insertmode = NOT_SET_VALUES; 2695 mat->preallocated = PETSC_TRUE; 2696 2697 a->size = oldmat->size; 2698 a->rank = oldmat->rank; 2699 a->donotstash = oldmat->donotstash; 2700 a->roworiented = oldmat->roworiented; 2701 a->rowindices = 0; 2702 a->rowvalues = 0; 2703 a->getrowactive = PETSC_FALSE; 2704 2705 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2706 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2707 2708 if (oldmat->colmap) { 2709 #if defined(PETSC_USE_CTABLE) 2710 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2711 #else 2712 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2713 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2714 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2715 #endif 2716 } else a->colmap = 0; 2717 if (oldmat->garray) { 2718 PetscInt len; 2719 len = oldmat->B->cmap->n; 2720 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2721 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2722 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2723 } else a->garray = 0; 2724 2725 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2727 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2731 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2732 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2733 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2734 *newmat = mat; 2735 PetscFunctionReturn(0); 2736 } 2737 2738 2739 2740 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2741 { 2742 PetscScalar *vals,*svals; 2743 MPI_Comm comm; 2744 PetscErrorCode ierr; 2745 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2746 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2747 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2748 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2749 PetscInt cend,cstart,n,*rowners; 2750 int fd; 2751 PetscInt bs = newMat->rmap->bs; 2752 2753 PetscFunctionBegin; 2754 /* force binary viewer to load .info file if it has not yet done so */ 2755 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2756 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2757 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2758 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2759 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2760 if (!rank) { 2761 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2762 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2763 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2764 } 2765 2766 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2767 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2768 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2769 if (bs < 0) bs = 1; 2770 2771 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2772 M = header[1]; N = header[2]; 2773 2774 /* If global sizes are set, check if they are consistent with that given in the file */ 2775 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); 2776 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); 2777 2778 /* determine ownership of all (block) rows */ 2779 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2780 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2781 else m = newMat->rmap->n; /* Set by user */ 2782 2783 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2784 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2785 2786 /* First process needs enough room for process with most rows */ 2787 if (!rank) { 2788 mmax = rowners[1]; 2789 for (i=2; i<=size; i++) { 2790 mmax = PetscMax(mmax, rowners[i]); 2791 } 2792 } else mmax = -1; /* unused, but compilers complain */ 2793 2794 rowners[0] = 0; 2795 for (i=2; i<=size; i++) { 2796 rowners[i] += rowners[i-1]; 2797 } 2798 rstart = rowners[rank]; 2799 rend = rowners[rank+1]; 2800 2801 /* distribute row lengths to all processors */ 2802 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2803 if (!rank) { 2804 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2805 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2806 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2807 for (j=0; j<m; j++) { 2808 procsnz[0] += ourlens[j]; 2809 } 2810 for (i=1; i<size; i++) { 2811 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2812 /* calculate the number of nonzeros on each processor */ 2813 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2814 procsnz[i] += rowlengths[j]; 2815 } 2816 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2817 } 2818 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2819 } else { 2820 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2821 } 2822 2823 if (!rank) { 2824 /* determine max buffer needed and allocate it */ 2825 maxnz = 0; 2826 for (i=0; i<size; i++) { 2827 maxnz = PetscMax(maxnz,procsnz[i]); 2828 } 2829 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2830 2831 /* read in my part of the matrix column indices */ 2832 nz = procsnz[0]; 2833 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2834 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2835 2836 /* read in every one elses and ship off */ 2837 for (i=1; i<size; i++) { 2838 nz = procsnz[i]; 2839 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2840 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2841 } 2842 ierr = PetscFree(cols);CHKERRQ(ierr); 2843 } else { 2844 /* determine buffer space needed for message */ 2845 nz = 0; 2846 for (i=0; i<m; i++) { 2847 nz += ourlens[i]; 2848 } 2849 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2850 2851 /* receive message of column indices*/ 2852 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2853 } 2854 2855 /* determine column ownership if matrix is not square */ 2856 if (N != M) { 2857 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2858 else n = newMat->cmap->n; 2859 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2860 cstart = cend - n; 2861 } else { 2862 cstart = rstart; 2863 cend = rend; 2864 n = cend - cstart; 2865 } 2866 2867 /* loop over local rows, determining number of off diagonal entries */ 2868 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2869 jj = 0; 2870 for (i=0; i<m; i++) { 2871 for (j=0; j<ourlens[i]; j++) { 2872 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2873 jj++; 2874 } 2875 } 2876 2877 for (i=0; i<m; i++) { 2878 ourlens[i] -= offlens[i]; 2879 } 2880 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2881 2882 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2883 2884 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2885 2886 for (i=0; i<m; i++) { 2887 ourlens[i] += offlens[i]; 2888 } 2889 2890 if (!rank) { 2891 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2892 2893 /* read in my part of the matrix numerical values */ 2894 nz = procsnz[0]; 2895 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2896 2897 /* insert into matrix */ 2898 jj = rstart; 2899 smycols = mycols; 2900 svals = vals; 2901 for (i=0; i<m; i++) { 2902 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2903 smycols += ourlens[i]; 2904 svals += ourlens[i]; 2905 jj++; 2906 } 2907 2908 /* read in other processors and ship out */ 2909 for (i=1; i<size; i++) { 2910 nz = procsnz[i]; 2911 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2912 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2913 } 2914 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2915 } else { 2916 /* receive numeric values */ 2917 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2918 2919 /* receive message of values*/ 2920 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2921 2922 /* insert into matrix */ 2923 jj = rstart; 2924 smycols = mycols; 2925 svals = vals; 2926 for (i=0; i<m; i++) { 2927 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2928 smycols += ourlens[i]; 2929 svals += ourlens[i]; 2930 jj++; 2931 } 2932 } 2933 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2934 ierr = PetscFree(vals);CHKERRQ(ierr); 2935 ierr = PetscFree(mycols);CHKERRQ(ierr); 2936 ierr = PetscFree(rowners);CHKERRQ(ierr); 2937 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2938 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2939 PetscFunctionReturn(0); 2940 } 2941 2942 /* Not scalable because of ISAllGather() unless getting all columns. */ 2943 PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq) 2944 { 2945 PetscErrorCode ierr; 2946 IS iscol_local; 2947 PetscBool isstride; 2948 PetscMPIInt lisstride=0,gisstride; 2949 2950 PetscFunctionBegin; 2951 /* check if we are grabbing all columns*/ 2952 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2953 2954 if (isstride) { 2955 PetscInt start,len,mstart,mlen; 2956 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2957 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2958 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2959 if (mstart == start && mlen-mstart == len) lisstride = 1; 2960 } 2961 2962 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2963 if (gisstride) { 2964 PetscInt N; 2965 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2966 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2967 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2968 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2969 } else { 2970 PetscInt cbs; 2971 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2972 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2973 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2974 } 2975 2976 *isseq = iscol_local; 2977 PetscFunctionReturn(0); 2978 } 2979 2980 PetscErrorCode ISGetSeqIS_SameDist_Private(Mat mat,IS iscol,IS *iscol_sub,IS *iscmap) 2981 { 2982 PetscErrorCode ierr; 2983 Vec x,cmap; 2984 const PetscInt *is_idx; 2985 PetscScalar *xarray,*cmaparray; 2986 PetscInt n,isstart,*idx,*cmap1,count; 2987 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 2988 Mat B=a->B; 2989 Vec lvec = a->lvec,lcmap; 2990 PetscInt i,j,cstart,cend,Bn=B->cmap->N,*garray = a->garray; 2991 MPI_Comm comm; 2992 PetscMPIInt rank; 2993 2994 PetscFunctionBegin; 2995 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2996 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2997 2998 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 2999 3000 /* find isstart */ 3001 ierr = MPI_Scan(&n,&isstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3002 isstart -= n; 3003 //printf("[%d] n %d, isstart %d\n",rank,n,isstart); 3004 3005 /* (1) iscol is a sub-vector of mat, pad it with '-1.' to form a full vector x */ 3006 ierr = MatCreateVecs(mat,&x,NULL);CHKERRQ(ierr); 3007 ierr = VecSet(x,-1.0);CHKERRQ(ierr); 3008 3009 ierr = MatCreateVecs(mat,&cmap,NULL);CHKERRQ(ierr); 3010 ierr = VecSet(cmap,-1.0);CHKERRQ(ierr); 3011 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<n; i++) { 3018 xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i]; 3019 cmaparray[is_idx[i]-cstart] = i + isstart; 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 = VecDuplicate(lvec,&lcmap);CHKERRQ(ierr); 3027 3028 ierr = VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3029 ierr = VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3030 3031 ierr = VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3032 ierr = VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3033 3034 if (lvec->map->n != Bn) SETERRQ2(PETSC_COMM_SELF,0,"n(lvec) %d != Bn %d",lvec->map->n,Bn); 3035 if (rank == -1) { 3036 printf("[%d] lvec:\n",rank); 3037 ierr = VecView(lvec,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 3038 } 3039 3040 /* (3) create scalable iscol_sub (a subset of iscol) and iscmap */ 3041 ierr = PetscMalloc2(n+Bn,&idx,n+Bn,&cmap1);CHKERRQ(ierr); 3042 count = 0; 3043 3044 /* A part */ 3045 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3046 j = cstart; 3047 for (i=0; i<n; i++) { 3048 if (j >= cend) break; 3049 if (is_idx[i] == j) { 3050 idx[count] = j; 3051 cmap1[count] = i + isstart; /* column index in submat */ 3052 count++; j++; 3053 } else if (is_idx[i] > j) { 3054 while (is_idx[i] > j && j < cend-1) j++; 3055 if (is_idx[i] == j) { 3056 idx[count] = j; 3057 cmap1[count] = i + isstart; /* column index in submat */ 3058 count++; j++; 3059 } 3060 } 3061 } 3062 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3063 3064 /* B part */ 3065 ierr = VecGetArray(lvec,&xarray);CHKERRQ(ierr); 3066 ierr = VecGetArray(lcmap,&cmaparray);CHKERRQ(ierr); 3067 j = 0; 3068 for (i=0; i<Bn; i++) { 3069 if (j >= Bn) break; 3070 if ((PetscInt)xarray[i] == garray[j]) { 3071 idx[count] = garray[j]; 3072 cmap1[count] = cmaparray[i]; /* column index in submat */ 3073 count++; j++; 3074 } else if ((PetscInt)xarray[i] > garray[j]) { 3075 while ((PetscInt)xarray[i] > garray[j] && j < Bn-1) j++; 3076 if ((PetscInt)xarray[i] == garray[j]) { 3077 idx[count] = garray[j]; 3078 cmap1[count] = cmaparray[i]; /* column index in submat */ 3079 count++; j++; 3080 } 3081 } 3082 } 3083 ierr = VecRestoreArray(lvec,&xarray);CHKERRQ(ierr); 3084 ierr = VecRestoreArray(lcmap,&cmaparray);CHKERRQ(ierr); 3085 //printf("[%d] n %d + Bn %d = %d; count %d, isN %d, matN %d\n",rank,n,Bn,n+Bn,count,N,mat->cmap->N); 3086 3087 ierr = PetscSortInt(count,idx);CHKERRQ(ierr); //should idx be sorted with cmap1??? 3088 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3089 3090 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_sub);CHKERRQ(ierr); 3091 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,cmap1,PETSC_COPY_VALUES,iscmap);CHKERRQ(ierr); 3092 3093 if (rank == -1) { 3094 printf("[%d] iscmap:\n",rank); 3095 ierr = ISView(*iscmap,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 3096 } 3097 3098 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3099 ierr = VecDestroy(&x);CHKERRQ(ierr); 3100 ierr = VecDestroy(&cmap);CHKERRQ(ierr); 3101 ierr = VecDestroy(&lcmap);CHKERRQ(ierr); 3102 PetscFunctionReturn(0); 3103 } 3104 3105 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3106 { 3107 PetscErrorCode ierr; 3108 IS iscol_local; 3109 PetscInt csize; 3110 PetscInt n,i,j,rstart,rend; 3111 PetscBool sameRowDist=PETSC_FALSE,tsameRowDist; 3112 MPI_Comm comm; 3113 3114 PetscFunctionBegin; 3115 /* If isrow has same processor distribution as mat, 3116 call MatCreateSubMatrix_MPIAIJ_SameDist() to avoid using a hash table with global size of iscol */ 3117 if (call == MAT_REUSE_MATRIX) { 3118 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3119 if (iscol_local) tsameRowDist = PETSC_TRUE; 3120 } else { 3121 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3122 if (!n) { 3123 sameRowDist = PETSC_TRUE; 3124 } else { 3125 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3126 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3127 if (i >= rstart && j < rend) sameRowDist = PETSC_TRUE; 3128 } 3129 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3130 ierr = MPIU_Allreduce(&sameRowDist,&tsameRowDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3131 } 3132 3133 if (tsameRowDist) { 3134 ierr = MatCreateSubMatrix_MPIAIJ_SameDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3135 PetscFunctionReturn(0); 3136 } 3137 3138 /* General case: iscol -> iscol_local which has global size of iscol */ 3139 if (call == MAT_REUSE_MATRIX) { 3140 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3141 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3142 } else { 3143 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3144 } 3145 3146 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3147 ierr = MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3148 3149 if (call == MAT_INITIAL_MATRIX) { 3150 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3151 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3152 } 3153 PetscFunctionReturn(0); 3154 } 3155 3156 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat*); 3157 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3158 3159 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3160 { 3161 PetscErrorCode ierr; 3162 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3163 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3164 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3165 Mat M,Msub,B=a->B; 3166 MatScalar *aa; 3167 Mat_SeqAIJ *aij; 3168 PetscInt *garray = a->garray,*colsub,N; 3169 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3170 IS iscol_sub,iscmap; 3171 const PetscInt *is_idx,*cmap; 3172 PetscBool sameColDist=PETSC_FALSE,tsameColDist; 3173 IS iscol_local=NULL; 3174 3175 PetscFunctionBegin; 3176 MPI_Comm comm; 3177 PetscMPIInt rank; 3178 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3179 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3180 3181 if (call == MAT_INITIAL_MATRIX) { 3182 /* If iscol has same processor distribution as mat, then use a scalable routine */ 3183 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3184 ierr = ISGetSize(iscol,&N);CHKERRQ(ierr); 3185 if (!n) { 3186 sameColDist = PETSC_TRUE; 3187 } else { 3188 ierr = ISGetMinMax(iscol,&i,&j);CHKERRQ(ierr); 3189 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3190 if (i >= cstart && j < cend) sameColDist = PETSC_TRUE; 3191 } 3192 ierr = MPIU_Allreduce(&sameColDist,&tsameColDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3193 3194 /* create scalable iscol_sub (a subset of iscol_local) */ 3195 if (tsameColDist) { 3196 ierr = ISGetSeqIS_SameDist_Private(mat,iscol,&iscol_sub,&iscmap);CHKERRQ(ierr); 3197 ierr = ISGetSize(iscol,&n);CHKERRQ(ierr); /* global size of iscol = global columns of newmat */ 3198 } else { /* iscol -> nonscalable iscol_local, then get iscol_sub and iscmap */ 3199 3200 /* (1) iscol -> nonscalable iscol_local */ 3201 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3202 ierr = ISGetLocalSize(iscol_local,&n);CHKERRQ(ierr); /* local size of iscol_local = global columns of newmat */ 3203 3204 PetscInt *idx,*cmap1; 3205 3206 ierr = PetscMalloc2(n,&idx,n,&cmap1);CHKERRQ(ierr); 3207 ierr = ISGetIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3208 count = 0; 3209 3210 /* A part */ 3211 j = cstart; 3212 for (i=0; i<n; i++) { 3213 if (j >= cend) break; 3214 if (is_idx[i] == j) { 3215 idx[count] = j; 3216 cmap1[count] = i; /* column index in submat */ 3217 count++; j++; 3218 } else if (is_idx[i] > j) { 3219 while (is_idx[i] > j && j < cend-1) j++; 3220 if (is_idx[i] == j) { 3221 idx[count] = j; 3222 cmap1[count] = i; /* column index in submat */ 3223 count++; j++; 3224 } 3225 } 3226 } 3227 3228 /* B part */ 3229 j = 0; 3230 for (i=0; i<n; i++) { 3231 if (j >= Bn) break; 3232 if (is_idx[i] == garray[j]) { 3233 idx[count] = garray[j]; 3234 cmap1[count] = i; /* column index in submat */ 3235 count++; j++; 3236 } else if (is_idx[i] > garray[j]) { 3237 while (is_idx[i] > garray[j] && j < Bn-1) j++; 3238 if (is_idx[i] == garray[j]) { 3239 idx[count] = garray[j]; 3240 cmap1[count] = i; /* column index in submat */ 3241 count++; j++; 3242 } 3243 } 3244 } 3245 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3246 ierr = ISRestoreIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3247 3248 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3249 ierr = ISSort(iscol_sub);CHKERRQ(ierr); 3250 3251 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3252 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3253 3254 } // --------- old ------------------- 3255 3256 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3257 3258 } else { /* call == MAT_REUSE_MATRIX */ 3259 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3260 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3261 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3262 3263 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3264 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3265 3266 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3267 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3268 3269 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3270 } 3271 3272 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3273 aij = (Mat_SeqAIJ*)(Msub)->data; 3274 ii = aij->i; 3275 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3276 3277 /* 3278 m - number of local rows 3279 n - number of columns (same on all processors) 3280 rstart - first row in new global matrix generated 3281 */ 3282 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3283 3284 if (call == MAT_INITIAL_MATRIX) { 3285 MPI_Comm comm; 3286 PetscMPIInt rank,size; 3287 PetscInt csize; 3288 3289 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3290 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3291 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3292 3293 /* 3294 Determine the number of non-zeros in the diagonal and off-diagonal 3295 portions of the matrix in order to do correct preallocation 3296 */ 3297 3298 /* first get start and end of "diagonal" columns */ 3299 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3300 if (csize == PETSC_DECIDE) { 3301 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3302 if (mglobal == n) { /* square matrix */ 3303 nlocal = m; 3304 } else { 3305 nlocal = n/size + ((n % size) > rank); 3306 } 3307 } else { 3308 nlocal = csize; 3309 } 3310 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3311 rstart = rend - nlocal; 3312 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); 3313 3314 /* next, compute all the lengths */ 3315 jj = aij->j; 3316 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3317 olens = dlens + m; 3318 for (i=0; i<m; i++) { 3319 jend = ii[i+1] - ii[i]; 3320 olen = 0; 3321 dlen = 0; 3322 for (j=0; j<jend; j++) { 3323 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3324 else dlen++; 3325 jj++; 3326 } 3327 olens[i] = olen; 3328 dlens[i] = dlen; 3329 } 3330 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3331 3332 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3333 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3334 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3335 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3336 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3337 ierr = PetscFree(dlens);CHKERRQ(ierr); 3338 } else { 3339 M = *newmat; 3340 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3341 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3342 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3343 /* 3344 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3345 rather than the slower MatSetValues(). 3346 */ 3347 M->was_assembled = PETSC_TRUE; 3348 M->assembled = PETSC_FALSE; 3349 } 3350 3351 /* set values of Msub to *newmat */ 3352 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3353 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3354 3355 jj = aij->j; 3356 aa = aij->a; 3357 for (i=0; i<m; i++) { 3358 row = rstart + i; 3359 nz = ii[i+1] - ii[i]; 3360 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3361 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3362 jj += nz; aa += nz; 3363 } 3364 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3365 3366 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3367 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3368 *newmat = M; 3369 3370 ierr = PetscFree(colsub);CHKERRQ(ierr); 3371 3372 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3373 if (call == MAT_INITIAL_MATRIX) { 3374 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3375 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3376 3377 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3378 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3379 3380 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3381 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3382 3383 if (iscol_local) { 3384 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3385 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3386 } 3387 } 3388 PetscFunctionReturn(0); 3389 } 3390 3391 /* 3392 Not great since it makes two copies of the submatrix, first an SeqAIJ 3393 in local and then by concatenating the local matrices the end result. 3394 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3395 3396 Note: This requires a sequential iscol with all indices. 3397 */ 3398 PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3399 { 3400 PetscErrorCode ierr; 3401 PetscMPIInt rank,size; 3402 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3403 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3404 Mat M,Mreuse; 3405 MatScalar *aa,*vwork; 3406 MPI_Comm comm; 3407 Mat_SeqAIJ *aij; 3408 3409 PetscFunctionBegin; 3410 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3411 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3412 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3413 3414 if (call == MAT_REUSE_MATRIX) { 3415 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3416 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3417 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&Mreuse);CHKERRQ(ierr); 3418 } else { 3419 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&Mreuse);CHKERRQ(ierr); 3420 } 3421 3422 /* 3423 m - number of local rows 3424 n - number of columns (same on all processors) 3425 rstart - first row in new global matrix generated 3426 */ 3427 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3428 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3429 if (call == MAT_INITIAL_MATRIX) { 3430 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3431 ii = aij->i; 3432 jj = aij->j; 3433 3434 /* 3435 Determine the number of non-zeros in the diagonal and off-diagonal 3436 portions of the matrix in order to do correct preallocation 3437 */ 3438 3439 /* first get start and end of "diagonal" columns */ 3440 if (csize == PETSC_DECIDE) { 3441 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3442 if (mglobal == n) { /* square matrix */ 3443 nlocal = m; 3444 } else { 3445 nlocal = n/size + ((n % size) > rank); 3446 } 3447 } else { 3448 nlocal = csize; 3449 } 3450 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3451 rstart = rend - nlocal; 3452 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); 3453 3454 /* next, compute all the lengths */ 3455 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3456 olens = dlens + m; 3457 for (i=0; i<m; i++) { 3458 jend = ii[i+1] - ii[i]; 3459 olen = 0; 3460 dlen = 0; 3461 for (j=0; j<jend; j++) { 3462 if (*jj < rstart || *jj >= rend) olen++; 3463 else dlen++; 3464 jj++; 3465 } 3466 olens[i] = olen; 3467 dlens[i] = dlen; 3468 } 3469 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3470 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3471 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3472 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3473 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3474 ierr = PetscFree(dlens);CHKERRQ(ierr); 3475 } else { 3476 PetscInt ml,nl; 3477 3478 M = *newmat; 3479 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3480 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3481 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3482 /* 3483 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3484 rather than the slower MatSetValues(). 3485 */ 3486 M->was_assembled = PETSC_TRUE; 3487 M->assembled = PETSC_FALSE; 3488 } 3489 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3490 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3491 ii = aij->i; 3492 jj = aij->j; 3493 aa = aij->a; 3494 for (i=0; i<m; i++) { 3495 row = rstart + i; 3496 nz = ii[i+1] - ii[i]; 3497 cwork = jj; jj += nz; 3498 vwork = aa; aa += nz; 3499 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3500 } 3501 3502 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3503 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3504 *newmat = M; 3505 3506 /* save submatrix used in processor for next request */ 3507 if (call == MAT_INITIAL_MATRIX) { 3508 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3509 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3510 } 3511 PetscFunctionReturn(0); 3512 } 3513 3514 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3515 { 3516 PetscInt m,cstart, cend,j,nnz,i,d; 3517 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3518 const PetscInt *JJ; 3519 PetscScalar *values; 3520 PetscErrorCode ierr; 3521 PetscBool nooffprocentries; 3522 3523 PetscFunctionBegin; 3524 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3525 3526 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3527 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3528 m = B->rmap->n; 3529 cstart = B->cmap->rstart; 3530 cend = B->cmap->rend; 3531 rstart = B->rmap->rstart; 3532 3533 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3534 3535 #if defined(PETSC_USE_DEBUGGING) 3536 for (i=0; i<m; i++) { 3537 nnz = Ii[i+1]- Ii[i]; 3538 JJ = J + Ii[i]; 3539 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3540 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3541 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); 3542 } 3543 #endif 3544 3545 for (i=0; i<m; i++) { 3546 nnz = Ii[i+1]- Ii[i]; 3547 JJ = J + Ii[i]; 3548 nnz_max = PetscMax(nnz_max,nnz); 3549 d = 0; 3550 for (j=0; j<nnz; j++) { 3551 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3552 } 3553 d_nnz[i] = d; 3554 o_nnz[i] = nnz - d; 3555 } 3556 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3557 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3558 3559 if (v) values = (PetscScalar*)v; 3560 else { 3561 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3562 } 3563 3564 for (i=0; i<m; i++) { 3565 ii = i + rstart; 3566 nnz = Ii[i+1]- Ii[i]; 3567 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3568 } 3569 nooffprocentries = B->nooffprocentries; 3570 B->nooffprocentries = PETSC_TRUE; 3571 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3572 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3573 B->nooffprocentries = nooffprocentries; 3574 3575 if (!v) { 3576 ierr = PetscFree(values);CHKERRQ(ierr); 3577 } 3578 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3579 PetscFunctionReturn(0); 3580 } 3581 3582 /*@ 3583 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3584 (the default parallel PETSc format). 3585 3586 Collective on MPI_Comm 3587 3588 Input Parameters: 3589 + B - the matrix 3590 . i - the indices into j for the start of each local row (starts with zero) 3591 . j - the column indices for each local row (starts with zero) 3592 - v - optional values in the matrix 3593 3594 Level: developer 3595 3596 Notes: 3597 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3598 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3599 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3600 3601 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3602 3603 The format which is used for the sparse matrix input, is equivalent to a 3604 row-major ordering.. i.e for the following matrix, the input data expected is 3605 as shown 3606 3607 $ 1 0 0 3608 $ 2 0 3 P0 3609 $ ------- 3610 $ 4 5 6 P1 3611 $ 3612 $ Process0 [P0]: rows_owned=[0,1] 3613 $ i = {0,1,3} [size = nrow+1 = 2+1] 3614 $ j = {0,0,2} [size = 3] 3615 $ v = {1,2,3} [size = 3] 3616 $ 3617 $ Process1 [P1]: rows_owned=[2] 3618 $ i = {0,3} [size = nrow+1 = 1+1] 3619 $ j = {0,1,2} [size = 3] 3620 $ v = {4,5,6} [size = 3] 3621 3622 .keywords: matrix, aij, compressed row, sparse, parallel 3623 3624 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3625 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3626 @*/ 3627 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3628 { 3629 PetscErrorCode ierr; 3630 3631 PetscFunctionBegin; 3632 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3633 PetscFunctionReturn(0); 3634 } 3635 3636 /*@C 3637 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3638 (the default parallel PETSc format). For good matrix assembly performance 3639 the user should preallocate the matrix storage by setting the parameters 3640 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3641 performance can be increased by more than a factor of 50. 3642 3643 Collective on MPI_Comm 3644 3645 Input Parameters: 3646 + B - the matrix 3647 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3648 (same value is used for all local rows) 3649 . d_nnz - array containing the number of nonzeros in the various rows of the 3650 DIAGONAL portion of the local submatrix (possibly different for each row) 3651 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3652 The size of this array is equal to the number of local rows, i.e 'm'. 3653 For matrices that will be factored, you must leave room for (and set) 3654 the diagonal entry even if it is zero. 3655 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3656 submatrix (same value is used for all local rows). 3657 - o_nnz - array containing the number of nonzeros in the various rows of the 3658 OFF-DIAGONAL portion of the local submatrix (possibly different for 3659 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3660 structure. The size of this array is equal to the number 3661 of local rows, i.e 'm'. 3662 3663 If the *_nnz parameter is given then the *_nz parameter is ignored 3664 3665 The AIJ format (also called the Yale sparse matrix format or 3666 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3667 storage. The stored row and column indices begin with zero. 3668 See Users-Manual: ch_mat for details. 3669 3670 The parallel matrix is partitioned such that the first m0 rows belong to 3671 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3672 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3673 3674 The DIAGONAL portion of the local submatrix of a processor can be defined 3675 as the submatrix which is obtained by extraction the part corresponding to 3676 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3677 first row that belongs to the processor, r2 is the last row belonging to 3678 the this processor, and c1-c2 is range of indices of the local part of a 3679 vector suitable for applying the matrix to. This is an mxn matrix. In the 3680 common case of a square matrix, the row and column ranges are the same and 3681 the DIAGONAL part is also square. The remaining portion of the local 3682 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3683 3684 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3685 3686 You can call MatGetInfo() to get information on how effective the preallocation was; 3687 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3688 You can also run with the option -info and look for messages with the string 3689 malloc in them to see if additional memory allocation was needed. 3690 3691 Example usage: 3692 3693 Consider the following 8x8 matrix with 34 non-zero values, that is 3694 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3695 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3696 as follows: 3697 3698 .vb 3699 1 2 0 | 0 3 0 | 0 4 3700 Proc0 0 5 6 | 7 0 0 | 8 0 3701 9 0 10 | 11 0 0 | 12 0 3702 ------------------------------------- 3703 13 0 14 | 15 16 17 | 0 0 3704 Proc1 0 18 0 | 19 20 21 | 0 0 3705 0 0 0 | 22 23 0 | 24 0 3706 ------------------------------------- 3707 Proc2 25 26 27 | 0 0 28 | 29 0 3708 30 0 0 | 31 32 33 | 0 34 3709 .ve 3710 3711 This can be represented as a collection of submatrices as: 3712 3713 .vb 3714 A B C 3715 D E F 3716 G H I 3717 .ve 3718 3719 Where the submatrices A,B,C are owned by proc0, D,E,F are 3720 owned by proc1, G,H,I are owned by proc2. 3721 3722 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3723 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3724 The 'M','N' parameters are 8,8, and have the same values on all procs. 3725 3726 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3727 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3728 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3729 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3730 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3731 matrix, ans [DF] as another SeqAIJ matrix. 3732 3733 When d_nz, o_nz parameters are specified, d_nz storage elements are 3734 allocated for every row of the local diagonal submatrix, and o_nz 3735 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3736 One way to choose d_nz and o_nz is to use the max nonzerors per local 3737 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3738 In this case, the values of d_nz,o_nz are: 3739 .vb 3740 proc0 : dnz = 2, o_nz = 2 3741 proc1 : dnz = 3, o_nz = 2 3742 proc2 : dnz = 1, o_nz = 4 3743 .ve 3744 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3745 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3746 for proc3. i.e we are using 12+15+10=37 storage locations to store 3747 34 values. 3748 3749 When d_nnz, o_nnz parameters are specified, the storage is specified 3750 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3751 In the above case the values for d_nnz,o_nnz are: 3752 .vb 3753 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3754 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3755 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3756 .ve 3757 Here the space allocated is sum of all the above values i.e 34, and 3758 hence pre-allocation is perfect. 3759 3760 Level: intermediate 3761 3762 .keywords: matrix, aij, compressed row, sparse, parallel 3763 3764 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3765 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3766 @*/ 3767 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3768 { 3769 PetscErrorCode ierr; 3770 3771 PetscFunctionBegin; 3772 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3773 PetscValidType(B,1); 3774 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3775 PetscFunctionReturn(0); 3776 } 3777 3778 /*@ 3779 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3780 CSR format the local rows. 3781 3782 Collective on MPI_Comm 3783 3784 Input Parameters: 3785 + comm - MPI communicator 3786 . m - number of local rows (Cannot be PETSC_DECIDE) 3787 . n - This value should be the same as the local size used in creating the 3788 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3789 calculated if N is given) For square matrices n is almost always m. 3790 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3791 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3792 . i - row indices 3793 . j - column indices 3794 - a - matrix values 3795 3796 Output Parameter: 3797 . mat - the matrix 3798 3799 Level: intermediate 3800 3801 Notes: 3802 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3803 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3804 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3805 3806 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3807 3808 The format which is used for the sparse matrix input, is equivalent to a 3809 row-major ordering.. i.e for the following matrix, the input data expected is 3810 as shown 3811 3812 $ 1 0 0 3813 $ 2 0 3 P0 3814 $ ------- 3815 $ 4 5 6 P1 3816 $ 3817 $ Process0 [P0]: rows_owned=[0,1] 3818 $ i = {0,1,3} [size = nrow+1 = 2+1] 3819 $ j = {0,0,2} [size = 3] 3820 $ v = {1,2,3} [size = 3] 3821 $ 3822 $ Process1 [P1]: rows_owned=[2] 3823 $ i = {0,3} [size = nrow+1 = 1+1] 3824 $ j = {0,1,2} [size = 3] 3825 $ v = {4,5,6} [size = 3] 3826 3827 .keywords: matrix, aij, compressed row, sparse, parallel 3828 3829 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3830 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3831 @*/ 3832 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3833 { 3834 PetscErrorCode ierr; 3835 3836 PetscFunctionBegin; 3837 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3838 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3839 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3840 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3841 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3842 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3843 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3844 PetscFunctionReturn(0); 3845 } 3846 3847 /*@C 3848 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3849 (the default parallel PETSc format). For good matrix assembly performance 3850 the user should preallocate the matrix storage by setting the parameters 3851 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3852 performance can be increased by more than a factor of 50. 3853 3854 Collective on MPI_Comm 3855 3856 Input Parameters: 3857 + comm - MPI communicator 3858 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3859 This value should be the same as the local size used in creating the 3860 y vector for the matrix-vector product y = Ax. 3861 . n - This value should be the same as the local size used in creating the 3862 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3863 calculated if N is given) For square matrices n is almost always m. 3864 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3865 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3866 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3867 (same value is used for all local rows) 3868 . d_nnz - array containing the number of nonzeros in the various rows of the 3869 DIAGONAL portion of the local submatrix (possibly different for each row) 3870 or NULL, if d_nz is used to specify the nonzero structure. 3871 The size of this array is equal to the number of local rows, i.e 'm'. 3872 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3873 submatrix (same value is used for all local rows). 3874 - o_nnz - array containing the number of nonzeros in the various rows of the 3875 OFF-DIAGONAL portion of the local submatrix (possibly different for 3876 each row) or NULL, if o_nz is used to specify the nonzero 3877 structure. The size of this array is equal to the number 3878 of local rows, i.e 'm'. 3879 3880 Output Parameter: 3881 . A - the matrix 3882 3883 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3884 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3885 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3886 3887 Notes: 3888 If the *_nnz parameter is given then the *_nz parameter is ignored 3889 3890 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3891 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3892 storage requirements for this matrix. 3893 3894 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3895 processor than it must be used on all processors that share the object for 3896 that argument. 3897 3898 The user MUST specify either the local or global matrix dimensions 3899 (possibly both). 3900 3901 The parallel matrix is partitioned across processors such that the 3902 first m0 rows belong to process 0, the next m1 rows belong to 3903 process 1, the next m2 rows belong to process 2 etc.. where 3904 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3905 values corresponding to [m x N] submatrix. 3906 3907 The columns are logically partitioned with the n0 columns belonging 3908 to 0th partition, the next n1 columns belonging to the next 3909 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3910 3911 The DIAGONAL portion of the local submatrix on any given processor 3912 is the submatrix corresponding to the rows and columns m,n 3913 corresponding to the given processor. i.e diagonal matrix on 3914 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3915 etc. The remaining portion of the local submatrix [m x (N-n)] 3916 constitute the OFF-DIAGONAL portion. The example below better 3917 illustrates this concept. 3918 3919 For a square global matrix we define each processor's diagonal portion 3920 to be its local rows and the corresponding columns (a square submatrix); 3921 each processor's off-diagonal portion encompasses the remainder of the 3922 local matrix (a rectangular submatrix). 3923 3924 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3925 3926 When calling this routine with a single process communicator, a matrix of 3927 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3928 type of communicator, use the construction mechanism: 3929 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3930 3931 By default, this format uses inodes (identical nodes) when possible. 3932 We search for consecutive rows with the same nonzero structure, thereby 3933 reusing matrix information to achieve increased efficiency. 3934 3935 Options Database Keys: 3936 + -mat_no_inode - Do not use inodes 3937 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3938 - -mat_aij_oneindex - Internally use indexing starting at 1 3939 rather than 0. Note that when calling MatSetValues(), 3940 the user still MUST index entries starting at 0! 3941 3942 3943 Example usage: 3944 3945 Consider the following 8x8 matrix with 34 non-zero values, that is 3946 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3947 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3948 as follows: 3949 3950 .vb 3951 1 2 0 | 0 3 0 | 0 4 3952 Proc0 0 5 6 | 7 0 0 | 8 0 3953 9 0 10 | 11 0 0 | 12 0 3954 ------------------------------------- 3955 13 0 14 | 15 16 17 | 0 0 3956 Proc1 0 18 0 | 19 20 21 | 0 0 3957 0 0 0 | 22 23 0 | 24 0 3958 ------------------------------------- 3959 Proc2 25 26 27 | 0 0 28 | 29 0 3960 30 0 0 | 31 32 33 | 0 34 3961 .ve 3962 3963 This can be represented as a collection of submatrices as: 3964 3965 .vb 3966 A B C 3967 D E F 3968 G H I 3969 .ve 3970 3971 Where the submatrices A,B,C are owned by proc0, D,E,F are 3972 owned by proc1, G,H,I are owned by proc2. 3973 3974 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3975 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3976 The 'M','N' parameters are 8,8, and have the same values on all procs. 3977 3978 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3979 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3980 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3981 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3982 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3983 matrix, ans [DF] as another SeqAIJ matrix. 3984 3985 When d_nz, o_nz parameters are specified, d_nz storage elements are 3986 allocated for every row of the local diagonal submatrix, and o_nz 3987 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3988 One way to choose d_nz and o_nz is to use the max nonzerors per local 3989 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3990 In this case, the values of d_nz,o_nz are: 3991 .vb 3992 proc0 : dnz = 2, o_nz = 2 3993 proc1 : dnz = 3, o_nz = 2 3994 proc2 : dnz = 1, o_nz = 4 3995 .ve 3996 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3997 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3998 for proc3. i.e we are using 12+15+10=37 storage locations to store 3999 34 values. 4000 4001 When d_nnz, o_nnz parameters are specified, the storage is specified 4002 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4003 In the above case the values for d_nnz,o_nnz are: 4004 .vb 4005 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4006 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4007 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4008 .ve 4009 Here the space allocated is sum of all the above values i.e 34, and 4010 hence pre-allocation is perfect. 4011 4012 Level: intermediate 4013 4014 .keywords: matrix, aij, compressed row, sparse, parallel 4015 4016 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4017 MATMPIAIJ, MatCreateMPIAIJWithArrays() 4018 @*/ 4019 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) 4020 { 4021 PetscErrorCode ierr; 4022 PetscMPIInt size; 4023 4024 PetscFunctionBegin; 4025 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4026 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4027 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4028 if (size > 1) { 4029 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4030 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4031 } else { 4032 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4033 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4034 } 4035 PetscFunctionReturn(0); 4036 } 4037 4038 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4039 { 4040 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4041 PetscBool flg; 4042 PetscErrorCode ierr; 4043 4044 PetscFunctionBegin; 4045 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4046 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4047 if (Ad) *Ad = a->A; 4048 if (Ao) *Ao = a->B; 4049 if (colmap) *colmap = a->garray; 4050 PetscFunctionReturn(0); 4051 } 4052 4053 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4054 { 4055 PetscErrorCode ierr; 4056 PetscInt m,N,i,rstart,nnz,Ii; 4057 PetscInt *indx; 4058 PetscScalar *values; 4059 4060 PetscFunctionBegin; 4061 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4062 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4063 PetscInt *dnz,*onz,sum,bs,cbs; 4064 4065 if (n == PETSC_DECIDE) { 4066 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4067 } 4068 /* Check sum(n) = N */ 4069 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4070 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4071 4072 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4073 rstart -= m; 4074 4075 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4076 for (i=0; i<m; i++) { 4077 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4078 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4079 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4080 } 4081 4082 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4083 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4084 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4085 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4086 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4087 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4088 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4089 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4090 } 4091 4092 /* numeric phase */ 4093 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4094 for (i=0; i<m; i++) { 4095 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4096 Ii = i + rstart; 4097 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4098 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4099 } 4100 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4101 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4102 PetscFunctionReturn(0); 4103 } 4104 4105 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4106 { 4107 PetscErrorCode ierr; 4108 PetscMPIInt rank; 4109 PetscInt m,N,i,rstart,nnz; 4110 size_t len; 4111 const PetscInt *indx; 4112 PetscViewer out; 4113 char *name; 4114 Mat B; 4115 const PetscScalar *values; 4116 4117 PetscFunctionBegin; 4118 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4119 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4120 /* Should this be the type of the diagonal block of A? */ 4121 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4122 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4123 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4124 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4125 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4126 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4127 for (i=0; i<m; i++) { 4128 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4129 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4130 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4131 } 4132 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4133 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4134 4135 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4136 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4137 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4138 sprintf(name,"%s.%d",outfile,rank); 4139 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4140 ierr = PetscFree(name);CHKERRQ(ierr); 4141 ierr = MatView(B,out);CHKERRQ(ierr); 4142 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4143 ierr = MatDestroy(&B);CHKERRQ(ierr); 4144 PetscFunctionReturn(0); 4145 } 4146 4147 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4148 { 4149 PetscErrorCode ierr; 4150 Mat_Merge_SeqsToMPI *merge; 4151 PetscContainer container; 4152 4153 PetscFunctionBegin; 4154 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4155 if (container) { 4156 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4157 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4158 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4159 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4160 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4161 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4162 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4163 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4164 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4165 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4166 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4167 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4168 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4169 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4170 ierr = PetscFree(merge);CHKERRQ(ierr); 4171 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4172 } 4173 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4174 PetscFunctionReturn(0); 4175 } 4176 4177 #include <../src/mat/utils/freespace.h> 4178 #include <petscbt.h> 4179 4180 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4181 { 4182 PetscErrorCode ierr; 4183 MPI_Comm comm; 4184 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4185 PetscMPIInt size,rank,taga,*len_s; 4186 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4187 PetscInt proc,m; 4188 PetscInt **buf_ri,**buf_rj; 4189 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4190 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4191 MPI_Request *s_waits,*r_waits; 4192 MPI_Status *status; 4193 MatScalar *aa=a->a; 4194 MatScalar **abuf_r,*ba_i; 4195 Mat_Merge_SeqsToMPI *merge; 4196 PetscContainer container; 4197 4198 PetscFunctionBegin; 4199 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4200 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4201 4202 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4203 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4204 4205 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4206 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4207 4208 bi = merge->bi; 4209 bj = merge->bj; 4210 buf_ri = merge->buf_ri; 4211 buf_rj = merge->buf_rj; 4212 4213 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4214 owners = merge->rowmap->range; 4215 len_s = merge->len_s; 4216 4217 /* send and recv matrix values */ 4218 /*-----------------------------*/ 4219 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4220 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4221 4222 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4223 for (proc=0,k=0; proc<size; proc++) { 4224 if (!len_s[proc]) continue; 4225 i = owners[proc]; 4226 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4227 k++; 4228 } 4229 4230 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4231 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4232 ierr = PetscFree(status);CHKERRQ(ierr); 4233 4234 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4235 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4236 4237 /* insert mat values of mpimat */ 4238 /*----------------------------*/ 4239 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4240 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4241 4242 for (k=0; k<merge->nrecv; k++) { 4243 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4244 nrows = *(buf_ri_k[k]); 4245 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4246 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4247 } 4248 4249 /* set values of ba */ 4250 m = merge->rowmap->n; 4251 for (i=0; i<m; i++) { 4252 arow = owners[rank] + i; 4253 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4254 bnzi = bi[i+1] - bi[i]; 4255 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4256 4257 /* add local non-zero vals of this proc's seqmat into ba */ 4258 anzi = ai[arow+1] - ai[arow]; 4259 aj = a->j + ai[arow]; 4260 aa = a->a + ai[arow]; 4261 nextaj = 0; 4262 for (j=0; nextaj<anzi; j++) { 4263 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4264 ba_i[j] += aa[nextaj++]; 4265 } 4266 } 4267 4268 /* add received vals into ba */ 4269 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4270 /* i-th row */ 4271 if (i == *nextrow[k]) { 4272 anzi = *(nextai[k]+1) - *nextai[k]; 4273 aj = buf_rj[k] + *(nextai[k]); 4274 aa = abuf_r[k] + *(nextai[k]); 4275 nextaj = 0; 4276 for (j=0; nextaj<anzi; j++) { 4277 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4278 ba_i[j] += aa[nextaj++]; 4279 } 4280 } 4281 nextrow[k]++; nextai[k]++; 4282 } 4283 } 4284 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4285 } 4286 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4287 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4288 4289 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4290 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4291 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4292 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4293 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4294 PetscFunctionReturn(0); 4295 } 4296 4297 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4298 { 4299 PetscErrorCode ierr; 4300 Mat B_mpi; 4301 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4302 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4303 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4304 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4305 PetscInt len,proc,*dnz,*onz,bs,cbs; 4306 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4307 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4308 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4309 MPI_Status *status; 4310 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4311 PetscBT lnkbt; 4312 Mat_Merge_SeqsToMPI *merge; 4313 PetscContainer container; 4314 4315 PetscFunctionBegin; 4316 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4317 4318 /* make sure it is a PETSc comm */ 4319 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4320 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4321 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4322 4323 ierr = PetscNew(&merge);CHKERRQ(ierr); 4324 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4325 4326 /* determine row ownership */ 4327 /*---------------------------------------------------------*/ 4328 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4329 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4330 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4331 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4332 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4333 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4334 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4335 4336 m = merge->rowmap->n; 4337 owners = merge->rowmap->range; 4338 4339 /* determine the number of messages to send, their lengths */ 4340 /*---------------------------------------------------------*/ 4341 len_s = merge->len_s; 4342 4343 len = 0; /* length of buf_si[] */ 4344 merge->nsend = 0; 4345 for (proc=0; proc<size; proc++) { 4346 len_si[proc] = 0; 4347 if (proc == rank) { 4348 len_s[proc] = 0; 4349 } else { 4350 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4351 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4352 } 4353 if (len_s[proc]) { 4354 merge->nsend++; 4355 nrows = 0; 4356 for (i=owners[proc]; i<owners[proc+1]; i++) { 4357 if (ai[i+1] > ai[i]) nrows++; 4358 } 4359 len_si[proc] = 2*(nrows+1); 4360 len += len_si[proc]; 4361 } 4362 } 4363 4364 /* determine the number and length of messages to receive for ij-structure */ 4365 /*-------------------------------------------------------------------------*/ 4366 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4367 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4368 4369 /* post the Irecv of j-structure */ 4370 /*-------------------------------*/ 4371 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4372 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4373 4374 /* post the Isend of j-structure */ 4375 /*--------------------------------*/ 4376 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4377 4378 for (proc=0, k=0; proc<size; proc++) { 4379 if (!len_s[proc]) continue; 4380 i = owners[proc]; 4381 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4382 k++; 4383 } 4384 4385 /* receives and sends of j-structure are complete */ 4386 /*------------------------------------------------*/ 4387 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4388 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4389 4390 /* send and recv i-structure */ 4391 /*---------------------------*/ 4392 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4393 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4394 4395 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4396 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4397 for (proc=0,k=0; proc<size; proc++) { 4398 if (!len_s[proc]) continue; 4399 /* form outgoing message for i-structure: 4400 buf_si[0]: nrows to be sent 4401 [1:nrows]: row index (global) 4402 [nrows+1:2*nrows+1]: i-structure index 4403 */ 4404 /*-------------------------------------------*/ 4405 nrows = len_si[proc]/2 - 1; 4406 buf_si_i = buf_si + nrows+1; 4407 buf_si[0] = nrows; 4408 buf_si_i[0] = 0; 4409 nrows = 0; 4410 for (i=owners[proc]; i<owners[proc+1]; i++) { 4411 anzi = ai[i+1] - ai[i]; 4412 if (anzi) { 4413 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4414 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4415 nrows++; 4416 } 4417 } 4418 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4419 k++; 4420 buf_si += len_si[proc]; 4421 } 4422 4423 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4424 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4425 4426 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4427 for (i=0; i<merge->nrecv; i++) { 4428 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); 4429 } 4430 4431 ierr = PetscFree(len_si);CHKERRQ(ierr); 4432 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4433 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4434 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4435 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4436 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4437 ierr = PetscFree(status);CHKERRQ(ierr); 4438 4439 /* compute a local seq matrix in each processor */ 4440 /*----------------------------------------------*/ 4441 /* allocate bi array and free space for accumulating nonzero column info */ 4442 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4443 bi[0] = 0; 4444 4445 /* create and initialize a linked list */ 4446 nlnk = N+1; 4447 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4448 4449 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4450 len = ai[owners[rank+1]] - ai[owners[rank]]; 4451 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4452 4453 current_space = free_space; 4454 4455 /* determine symbolic info for each local row */ 4456 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4457 4458 for (k=0; k<merge->nrecv; k++) { 4459 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4460 nrows = *buf_ri_k[k]; 4461 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4462 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4463 } 4464 4465 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4466 len = 0; 4467 for (i=0; i<m; i++) { 4468 bnzi = 0; 4469 /* add local non-zero cols of this proc's seqmat into lnk */ 4470 arow = owners[rank] + i; 4471 anzi = ai[arow+1] - ai[arow]; 4472 aj = a->j + ai[arow]; 4473 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4474 bnzi += nlnk; 4475 /* add received col data into lnk */ 4476 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4477 if (i == *nextrow[k]) { /* i-th row */ 4478 anzi = *(nextai[k]+1) - *nextai[k]; 4479 aj = buf_rj[k] + *nextai[k]; 4480 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4481 bnzi += nlnk; 4482 nextrow[k]++; nextai[k]++; 4483 } 4484 } 4485 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4486 4487 /* if free space is not available, make more free space */ 4488 if (current_space->local_remaining<bnzi) { 4489 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4490 nspacedouble++; 4491 } 4492 /* copy data into free space, then initialize lnk */ 4493 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4494 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4495 4496 current_space->array += bnzi; 4497 current_space->local_used += bnzi; 4498 current_space->local_remaining -= bnzi; 4499 4500 bi[i+1] = bi[i] + bnzi; 4501 } 4502 4503 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4504 4505 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4506 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4507 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4508 4509 /* create symbolic parallel matrix B_mpi */ 4510 /*---------------------------------------*/ 4511 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4512 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4513 if (n==PETSC_DECIDE) { 4514 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4515 } else { 4516 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4517 } 4518 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4519 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4520 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4521 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4522 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4523 4524 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4525 B_mpi->assembled = PETSC_FALSE; 4526 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4527 merge->bi = bi; 4528 merge->bj = bj; 4529 merge->buf_ri = buf_ri; 4530 merge->buf_rj = buf_rj; 4531 merge->coi = NULL; 4532 merge->coj = NULL; 4533 merge->owners_co = NULL; 4534 4535 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4536 4537 /* attach the supporting struct to B_mpi for reuse */ 4538 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4539 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4540 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4541 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4542 *mpimat = B_mpi; 4543 4544 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4545 PetscFunctionReturn(0); 4546 } 4547 4548 /*@C 4549 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4550 matrices from each processor 4551 4552 Collective on MPI_Comm 4553 4554 Input Parameters: 4555 + comm - the communicators the parallel matrix will live on 4556 . seqmat - the input sequential matrices 4557 . m - number of local rows (or PETSC_DECIDE) 4558 . n - number of local columns (or PETSC_DECIDE) 4559 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4560 4561 Output Parameter: 4562 . mpimat - the parallel matrix generated 4563 4564 Level: advanced 4565 4566 Notes: 4567 The dimensions of the sequential matrix in each processor MUST be the same. 4568 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4569 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4570 @*/ 4571 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4572 { 4573 PetscErrorCode ierr; 4574 PetscMPIInt size; 4575 4576 PetscFunctionBegin; 4577 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4578 if (size == 1) { 4579 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4580 if (scall == MAT_INITIAL_MATRIX) { 4581 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4582 } else { 4583 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4584 } 4585 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4586 PetscFunctionReturn(0); 4587 } 4588 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4589 if (scall == MAT_INITIAL_MATRIX) { 4590 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4591 } 4592 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4593 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4594 PetscFunctionReturn(0); 4595 } 4596 4597 /*@ 4598 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4599 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4600 with MatGetSize() 4601 4602 Not Collective 4603 4604 Input Parameters: 4605 + A - the matrix 4606 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4607 4608 Output Parameter: 4609 . A_loc - the local sequential matrix generated 4610 4611 Level: developer 4612 4613 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4614 4615 @*/ 4616 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4617 { 4618 PetscErrorCode ierr; 4619 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4620 Mat_SeqAIJ *mat,*a,*b; 4621 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4622 MatScalar *aa,*ba,*cam; 4623 PetscScalar *ca; 4624 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4625 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4626 PetscBool match; 4627 MPI_Comm comm; 4628 PetscMPIInt size; 4629 4630 PetscFunctionBegin; 4631 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4632 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4633 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4634 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4635 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4636 4637 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4638 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4639 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4640 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4641 aa = a->a; ba = b->a; 4642 if (scall == MAT_INITIAL_MATRIX) { 4643 if (size == 1) { 4644 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4645 PetscFunctionReturn(0); 4646 } 4647 4648 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4649 ci[0] = 0; 4650 for (i=0; i<am; i++) { 4651 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4652 } 4653 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4654 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4655 k = 0; 4656 for (i=0; i<am; i++) { 4657 ncols_o = bi[i+1] - bi[i]; 4658 ncols_d = ai[i+1] - ai[i]; 4659 /* off-diagonal portion of A */ 4660 for (jo=0; jo<ncols_o; jo++) { 4661 col = cmap[*bj]; 4662 if (col >= cstart) break; 4663 cj[k] = col; bj++; 4664 ca[k++] = *ba++; 4665 } 4666 /* diagonal portion of A */ 4667 for (j=0; j<ncols_d; j++) { 4668 cj[k] = cstart + *aj++; 4669 ca[k++] = *aa++; 4670 } 4671 /* off-diagonal portion of A */ 4672 for (j=jo; j<ncols_o; j++) { 4673 cj[k] = cmap[*bj++]; 4674 ca[k++] = *ba++; 4675 } 4676 } 4677 /* put together the new matrix */ 4678 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4679 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4680 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4681 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4682 mat->free_a = PETSC_TRUE; 4683 mat->free_ij = PETSC_TRUE; 4684 mat->nonew = 0; 4685 } else if (scall == MAT_REUSE_MATRIX) { 4686 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4687 ci = mat->i; cj = mat->j; cam = mat->a; 4688 for (i=0; i<am; i++) { 4689 /* off-diagonal portion of A */ 4690 ncols_o = bi[i+1] - bi[i]; 4691 for (jo=0; jo<ncols_o; jo++) { 4692 col = cmap[*bj]; 4693 if (col >= cstart) break; 4694 *cam++ = *ba++; bj++; 4695 } 4696 /* diagonal portion of A */ 4697 ncols_d = ai[i+1] - ai[i]; 4698 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4699 /* off-diagonal portion of A */ 4700 for (j=jo; j<ncols_o; j++) { 4701 *cam++ = *ba++; bj++; 4702 } 4703 } 4704 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4705 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4706 PetscFunctionReturn(0); 4707 } 4708 4709 /*@C 4710 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4711 4712 Not Collective 4713 4714 Input Parameters: 4715 + A - the matrix 4716 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4717 - row, col - index sets of rows and columns to extract (or NULL) 4718 4719 Output Parameter: 4720 . A_loc - the local sequential matrix generated 4721 4722 Level: developer 4723 4724 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4725 4726 @*/ 4727 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4728 { 4729 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4730 PetscErrorCode ierr; 4731 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4732 IS isrowa,iscola; 4733 Mat *aloc; 4734 PetscBool match; 4735 4736 PetscFunctionBegin; 4737 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4738 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4739 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4740 if (!row) { 4741 start = A->rmap->rstart; end = A->rmap->rend; 4742 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4743 } else { 4744 isrowa = *row; 4745 } 4746 if (!col) { 4747 start = A->cmap->rstart; 4748 cmap = a->garray; 4749 nzA = a->A->cmap->n; 4750 nzB = a->B->cmap->n; 4751 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4752 ncols = 0; 4753 for (i=0; i<nzB; i++) { 4754 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4755 else break; 4756 } 4757 imark = i; 4758 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4759 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4760 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4761 } else { 4762 iscola = *col; 4763 } 4764 if (scall != MAT_INITIAL_MATRIX) { 4765 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4766 aloc[0] = *A_loc; 4767 } 4768 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4769 *A_loc = aloc[0]; 4770 ierr = PetscFree(aloc);CHKERRQ(ierr); 4771 if (!row) { 4772 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4773 } 4774 if (!col) { 4775 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4776 } 4777 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4778 PetscFunctionReturn(0); 4779 } 4780 4781 /*@C 4782 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4783 4784 Collective on Mat 4785 4786 Input Parameters: 4787 + A,B - the matrices in mpiaij format 4788 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4789 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4790 4791 Output Parameter: 4792 + rowb, colb - index sets of rows and columns of B to extract 4793 - B_seq - the sequential matrix generated 4794 4795 Level: developer 4796 4797 @*/ 4798 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4799 { 4800 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4801 PetscErrorCode ierr; 4802 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4803 IS isrowb,iscolb; 4804 Mat *bseq=NULL; 4805 4806 PetscFunctionBegin; 4807 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4808 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); 4809 } 4810 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4811 4812 if (scall == MAT_INITIAL_MATRIX) { 4813 start = A->cmap->rstart; 4814 cmap = a->garray; 4815 nzA = a->A->cmap->n; 4816 nzB = a->B->cmap->n; 4817 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4818 ncols = 0; 4819 for (i=0; i<nzB; i++) { /* row < local row index */ 4820 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4821 else break; 4822 } 4823 imark = i; 4824 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4825 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4826 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4827 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4828 } else { 4829 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4830 isrowb = *rowb; iscolb = *colb; 4831 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4832 bseq[0] = *B_seq; 4833 } 4834 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4835 *B_seq = bseq[0]; 4836 ierr = PetscFree(bseq);CHKERRQ(ierr); 4837 if (!rowb) { 4838 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4839 } else { 4840 *rowb = isrowb; 4841 } 4842 if (!colb) { 4843 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4844 } else { 4845 *colb = iscolb; 4846 } 4847 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4848 PetscFunctionReturn(0); 4849 } 4850 4851 /* 4852 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4853 of the OFF-DIAGONAL portion of local A 4854 4855 Collective on Mat 4856 4857 Input Parameters: 4858 + A,B - the matrices in mpiaij format 4859 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4860 4861 Output Parameter: 4862 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4863 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4864 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4865 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4866 4867 Level: developer 4868 4869 */ 4870 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4871 { 4872 VecScatter_MPI_General *gen_to,*gen_from; 4873 PetscErrorCode ierr; 4874 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4875 Mat_SeqAIJ *b_oth; 4876 VecScatter ctx =a->Mvctx; 4877 MPI_Comm comm; 4878 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4879 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4880 PetscInt *rvalues,*svalues; 4881 MatScalar *b_otha,*bufa,*bufA; 4882 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4883 MPI_Request *rwaits = NULL,*swaits = NULL; 4884 MPI_Status *sstatus,rstatus; 4885 PetscMPIInt jj,size; 4886 PetscInt *cols,sbs,rbs; 4887 PetscScalar *vals; 4888 4889 PetscFunctionBegin; 4890 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4891 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4892 4893 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4894 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); 4895 } 4896 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4897 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4898 4899 if (size == 1) { 4900 startsj_s = NULL; 4901 bufa_ptr = NULL; 4902 *B_oth = NULL; 4903 PetscFunctionReturn(0); 4904 } 4905 4906 gen_to = (VecScatter_MPI_General*)ctx->todata; 4907 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4908 nrecvs = gen_from->n; 4909 nsends = gen_to->n; 4910 4911 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4912 srow = gen_to->indices; /* local row index to be sent */ 4913 sstarts = gen_to->starts; 4914 sprocs = gen_to->procs; 4915 sstatus = gen_to->sstatus; 4916 sbs = gen_to->bs; 4917 rstarts = gen_from->starts; 4918 rprocs = gen_from->procs; 4919 rbs = gen_from->bs; 4920 4921 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4922 if (scall == MAT_INITIAL_MATRIX) { 4923 /* i-array */ 4924 /*---------*/ 4925 /* post receives */ 4926 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4927 for (i=0; i<nrecvs; i++) { 4928 rowlen = rvalues + rstarts[i]*rbs; 4929 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4930 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4931 } 4932 4933 /* pack the outgoing message */ 4934 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4935 4936 sstartsj[0] = 0; 4937 rstartsj[0] = 0; 4938 len = 0; /* total length of j or a array to be sent */ 4939 k = 0; 4940 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4941 for (i=0; i<nsends; i++) { 4942 rowlen = svalues + sstarts[i]*sbs; 4943 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4944 for (j=0; j<nrows; j++) { 4945 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4946 for (l=0; l<sbs; l++) { 4947 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4948 4949 rowlen[j*sbs+l] = ncols; 4950 4951 len += ncols; 4952 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4953 } 4954 k++; 4955 } 4956 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4957 4958 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4959 } 4960 /* recvs and sends of i-array are completed */ 4961 i = nrecvs; 4962 while (i--) { 4963 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4964 } 4965 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4966 ierr = PetscFree(svalues);CHKERRQ(ierr); 4967 4968 /* allocate buffers for sending j and a arrays */ 4969 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4970 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4971 4972 /* create i-array of B_oth */ 4973 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4974 4975 b_othi[0] = 0; 4976 len = 0; /* total length of j or a array to be received */ 4977 k = 0; 4978 for (i=0; i<nrecvs; i++) { 4979 rowlen = rvalues + rstarts[i]*rbs; 4980 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4981 for (j=0; j<nrows; j++) { 4982 b_othi[k+1] = b_othi[k] + rowlen[j]; 4983 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4984 k++; 4985 } 4986 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4987 } 4988 ierr = PetscFree(rvalues);CHKERRQ(ierr); 4989 4990 /* allocate space for j and a arrrays of B_oth */ 4991 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4992 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4993 4994 /* j-array */ 4995 /*---------*/ 4996 /* post receives of j-array */ 4997 for (i=0; i<nrecvs; i++) { 4998 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4999 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5000 } 5001 5002 /* pack the outgoing message j-array */ 5003 k = 0; 5004 for (i=0; i<nsends; i++) { 5005 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5006 bufJ = bufj+sstartsj[i]; 5007 for (j=0; j<nrows; j++) { 5008 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5009 for (ll=0; ll<sbs; ll++) { 5010 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5011 for (l=0; l<ncols; l++) { 5012 *bufJ++ = cols[l]; 5013 } 5014 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5015 } 5016 } 5017 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5018 } 5019 5020 /* recvs and sends of j-array are completed */ 5021 i = nrecvs; 5022 while (i--) { 5023 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5024 } 5025 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5026 } else if (scall == MAT_REUSE_MATRIX) { 5027 sstartsj = *startsj_s; 5028 rstartsj = *startsj_r; 5029 bufa = *bufa_ptr; 5030 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5031 b_otha = b_oth->a; 5032 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5033 5034 /* a-array */ 5035 /*---------*/ 5036 /* post receives of a-array */ 5037 for (i=0; i<nrecvs; i++) { 5038 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5039 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5040 } 5041 5042 /* pack the outgoing message a-array */ 5043 k = 0; 5044 for (i=0; i<nsends; i++) { 5045 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5046 bufA = bufa+sstartsj[i]; 5047 for (j=0; j<nrows; j++) { 5048 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5049 for (ll=0; ll<sbs; ll++) { 5050 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5051 for (l=0; l<ncols; l++) { 5052 *bufA++ = vals[l]; 5053 } 5054 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5055 } 5056 } 5057 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5058 } 5059 /* recvs and sends of a-array are completed */ 5060 i = nrecvs; 5061 while (i--) { 5062 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5063 } 5064 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5065 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5066 5067 if (scall == MAT_INITIAL_MATRIX) { 5068 /* put together the new matrix */ 5069 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5070 5071 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5072 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5073 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5074 b_oth->free_a = PETSC_TRUE; 5075 b_oth->free_ij = PETSC_TRUE; 5076 b_oth->nonew = 0; 5077 5078 ierr = PetscFree(bufj);CHKERRQ(ierr); 5079 if (!startsj_s || !bufa_ptr) { 5080 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5081 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5082 } else { 5083 *startsj_s = sstartsj; 5084 *startsj_r = rstartsj; 5085 *bufa_ptr = bufa; 5086 } 5087 } 5088 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5089 PetscFunctionReturn(0); 5090 } 5091 5092 /*@C 5093 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5094 5095 Not Collective 5096 5097 Input Parameters: 5098 . A - The matrix in mpiaij format 5099 5100 Output Parameter: 5101 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5102 . colmap - A map from global column index to local index into lvec 5103 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5104 5105 Level: developer 5106 5107 @*/ 5108 #if defined(PETSC_USE_CTABLE) 5109 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5110 #else 5111 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5112 #endif 5113 { 5114 Mat_MPIAIJ *a; 5115 5116 PetscFunctionBegin; 5117 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5118 PetscValidPointer(lvec, 2); 5119 PetscValidPointer(colmap, 3); 5120 PetscValidPointer(multScatter, 4); 5121 a = (Mat_MPIAIJ*) A->data; 5122 if (lvec) *lvec = a->lvec; 5123 if (colmap) *colmap = a->colmap; 5124 if (multScatter) *multScatter = a->Mvctx; 5125 PetscFunctionReturn(0); 5126 } 5127 5128 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5129 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5130 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5131 #if defined(PETSC_HAVE_ELEMENTAL) 5132 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5133 #endif 5134 #if defined(PETSC_HAVE_HYPRE) 5135 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5136 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5137 #endif 5138 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5139 5140 /* 5141 Computes (B'*A')' since computing B*A directly is untenable 5142 5143 n p p 5144 ( ) ( ) ( ) 5145 m ( A ) * n ( B ) = m ( C ) 5146 ( ) ( ) ( ) 5147 5148 */ 5149 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5150 { 5151 PetscErrorCode ierr; 5152 Mat At,Bt,Ct; 5153 5154 PetscFunctionBegin; 5155 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5156 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5157 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5158 ierr = MatDestroy(&At);CHKERRQ(ierr); 5159 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5160 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5161 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5162 PetscFunctionReturn(0); 5163 } 5164 5165 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5166 { 5167 PetscErrorCode ierr; 5168 PetscInt m=A->rmap->n,n=B->cmap->n; 5169 Mat Cmat; 5170 5171 PetscFunctionBegin; 5172 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); 5173 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5174 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5175 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5176 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5177 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5178 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5179 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5180 5181 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5182 5183 *C = Cmat; 5184 PetscFunctionReturn(0); 5185 } 5186 5187 /* ----------------------------------------------------------------*/ 5188 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5189 { 5190 PetscErrorCode ierr; 5191 5192 PetscFunctionBegin; 5193 if (scall == MAT_INITIAL_MATRIX) { 5194 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5195 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5196 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5197 } 5198 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5199 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5200 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5201 PetscFunctionReturn(0); 5202 } 5203 5204 /*MC 5205 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5206 5207 Options Database Keys: 5208 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5209 5210 Level: beginner 5211 5212 .seealso: MatCreateAIJ() 5213 M*/ 5214 5215 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5216 { 5217 Mat_MPIAIJ *b; 5218 PetscErrorCode ierr; 5219 PetscMPIInt size; 5220 5221 PetscFunctionBegin; 5222 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5223 5224 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5225 B->data = (void*)b; 5226 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5227 B->assembled = PETSC_FALSE; 5228 B->insertmode = NOT_SET_VALUES; 5229 b->size = size; 5230 5231 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5232 5233 /* build cache for off array entries formed */ 5234 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5235 5236 b->donotstash = PETSC_FALSE; 5237 b->colmap = 0; 5238 b->garray = 0; 5239 b->roworiented = PETSC_TRUE; 5240 5241 /* stuff used for matrix vector multiply */ 5242 b->lvec = NULL; 5243 b->Mvctx = NULL; 5244 5245 /* stuff for MatGetRow() */ 5246 b->rowindices = 0; 5247 b->rowvalues = 0; 5248 b->getrowactive = PETSC_FALSE; 5249 5250 /* flexible pointer used in CUSP/CUSPARSE classes */ 5251 b->spptr = NULL; 5252 5253 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5254 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5255 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5256 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5257 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5258 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5259 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5260 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5261 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5262 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5263 #if defined(PETSC_HAVE_ELEMENTAL) 5264 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5265 #endif 5266 #if defined(PETSC_HAVE_HYPRE) 5267 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5268 #endif 5269 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5270 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5271 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5272 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5273 #if defined(PETSC_HAVE_HYPRE) 5274 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5275 #endif 5276 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5277 PetscFunctionReturn(0); 5278 } 5279 5280 /*@C 5281 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5282 and "off-diagonal" part of the matrix in CSR format. 5283 5284 Collective on MPI_Comm 5285 5286 Input Parameters: 5287 + comm - MPI communicator 5288 . m - number of local rows (Cannot be PETSC_DECIDE) 5289 . n - This value should be the same as the local size used in creating the 5290 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5291 calculated if N is given) For square matrices n is almost always m. 5292 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5293 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5294 . i - row indices for "diagonal" portion of matrix 5295 . j - column indices 5296 . a - matrix values 5297 . oi - row indices for "off-diagonal" portion of matrix 5298 . oj - column indices 5299 - oa - matrix values 5300 5301 Output Parameter: 5302 . mat - the matrix 5303 5304 Level: advanced 5305 5306 Notes: 5307 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5308 must free the arrays once the matrix has been destroyed and not before. 5309 5310 The i and j indices are 0 based 5311 5312 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5313 5314 This sets local rows and cannot be used to set off-processor values. 5315 5316 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5317 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5318 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5319 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5320 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5321 communication if it is known that only local entries will be set. 5322 5323 .keywords: matrix, aij, compressed row, sparse, parallel 5324 5325 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5326 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5327 @*/ 5328 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) 5329 { 5330 PetscErrorCode ierr; 5331 Mat_MPIAIJ *maij; 5332 5333 PetscFunctionBegin; 5334 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5335 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5336 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5337 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5338 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5339 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5340 maij = (Mat_MPIAIJ*) (*mat)->data; 5341 5342 (*mat)->preallocated = PETSC_TRUE; 5343 5344 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5345 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5346 5347 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5348 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5349 5350 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5351 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5352 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5353 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5354 5355 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5356 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5357 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5358 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5359 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5360 PetscFunctionReturn(0); 5361 } 5362 5363 /* 5364 Special version for direct calls from Fortran 5365 */ 5366 #include <petsc/private/fortranimpl.h> 5367 5368 /* Change these macros so can be used in void function */ 5369 #undef CHKERRQ 5370 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5371 #undef SETERRQ2 5372 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5373 #undef SETERRQ3 5374 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5375 #undef SETERRQ 5376 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5377 5378 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5379 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5380 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5381 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5382 #else 5383 #endif 5384 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) 5385 { 5386 Mat mat = *mmat; 5387 PetscInt m = *mm, n = *mn; 5388 InsertMode addv = *maddv; 5389 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5390 PetscScalar value; 5391 PetscErrorCode ierr; 5392 5393 MatCheckPreallocated(mat,1); 5394 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5395 5396 #if defined(PETSC_USE_DEBUG) 5397 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5398 #endif 5399 { 5400 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5401 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5402 PetscBool roworiented = aij->roworiented; 5403 5404 /* Some Variables required in the macro */ 5405 Mat A = aij->A; 5406 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5407 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5408 MatScalar *aa = a->a; 5409 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5410 Mat B = aij->B; 5411 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5412 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5413 MatScalar *ba = b->a; 5414 5415 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5416 PetscInt nonew = a->nonew; 5417 MatScalar *ap1,*ap2; 5418 5419 PetscFunctionBegin; 5420 for (i=0; i<m; i++) { 5421 if (im[i] < 0) continue; 5422 #if defined(PETSC_USE_DEBUG) 5423 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); 5424 #endif 5425 if (im[i] >= rstart && im[i] < rend) { 5426 row = im[i] - rstart; 5427 lastcol1 = -1; 5428 rp1 = aj + ai[row]; 5429 ap1 = aa + ai[row]; 5430 rmax1 = aimax[row]; 5431 nrow1 = ailen[row]; 5432 low1 = 0; 5433 high1 = nrow1; 5434 lastcol2 = -1; 5435 rp2 = bj + bi[row]; 5436 ap2 = ba + bi[row]; 5437 rmax2 = bimax[row]; 5438 nrow2 = bilen[row]; 5439 low2 = 0; 5440 high2 = nrow2; 5441 5442 for (j=0; j<n; j++) { 5443 if (roworiented) value = v[i*n+j]; 5444 else value = v[i+j*m]; 5445 if (in[j] >= cstart && in[j] < cend) { 5446 col = in[j] - cstart; 5447 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5448 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5449 } else if (in[j] < 0) continue; 5450 #if defined(PETSC_USE_DEBUG) 5451 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); 5452 #endif 5453 else { 5454 if (mat->was_assembled) { 5455 if (!aij->colmap) { 5456 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5457 } 5458 #if defined(PETSC_USE_CTABLE) 5459 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5460 col--; 5461 #else 5462 col = aij->colmap[in[j]] - 1; 5463 #endif 5464 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5465 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5466 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5467 col = in[j]; 5468 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5469 B = aij->B; 5470 b = (Mat_SeqAIJ*)B->data; 5471 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5472 rp2 = bj + bi[row]; 5473 ap2 = ba + bi[row]; 5474 rmax2 = bimax[row]; 5475 nrow2 = bilen[row]; 5476 low2 = 0; 5477 high2 = nrow2; 5478 bm = aij->B->rmap->n; 5479 ba = b->a; 5480 } 5481 } else col = in[j]; 5482 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5483 } 5484 } 5485 } else if (!aij->donotstash) { 5486 if (roworiented) { 5487 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5488 } else { 5489 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5490 } 5491 } 5492 } 5493 } 5494 PetscFunctionReturnVoid(); 5495 } 5496 5497