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 extern PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private_SameDist(Mat,IS,IS,PetscInt,MatReuse,Mat*); 2981 2982 /* isrow has same processor distribution as mat, avoid iscol_local which uses O(mat->cmap->N) ctable */ 2983 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2984 { 2985 PetscErrorCode ierr; 2986 IS iscol_local; 2987 PetscInt csize; 2988 MPI_Comm comm; 2989 PetscMPIInt rank; 2990 PetscBool sorted,sameDist = PETSC_FALSE,tsameDist; 2991 PetscInt n,i,j,cstart,cend,N; 2992 2993 PetscFunctionBegin; 2994 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2995 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2996 //ierr = ISView(iscol,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr); 2997 2998 /* If iscol has same processor distribution as mat, then use a scalable routine */ 2999 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); //must be locally sorted??? 3000 if (!sorted) printf("[%d] iscol !sorted\n",rank); 3001 3002 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3003 ierr = ISGetSize(iscol,&N);CHKERRQ(ierr); 3004 if (!n) { 3005 sameDist = PETSC_TRUE; 3006 } else { 3007 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3008 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3009 if (i >= cstart && j < cend) sameDist = PETSC_TRUE; 3010 } 3011 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3012 if (!rank) printf("[%d]..SubMatrix_MPIAIJ_SameDist ...reuse %d, sameDist for column %d \n",rank,call,tsameDist); 3013 3014 if (tsameDist) { /* get iscol_sub without calling ISAllGather() */ 3015 Vec x,cmap; 3016 const PetscInt *is_idx; 3017 PetscScalar *xarray,*cmaparray; 3018 PetscInt isstart; 3019 3020 /* find isstart */ 3021 ierr = MPI_Scan(&n,&isstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3022 isstart -= n; 3023 //printf("[%d] n %d, isstart %d\n",rank,n,isstart); 3024 3025 /* (1) iscol is a sub-vector of mat, pad it with '-1.' to form a full vector x */ 3026 ierr = MatCreateVecs(mat,&x,NULL);CHKERRQ(ierr); 3027 ierr = VecSet(x,-1.0);CHKERRQ(ierr); 3028 3029 ierr = MatCreateVecs(mat,&cmap,NULL);CHKERRQ(ierr); 3030 ierr = VecSet(cmap,-1.0);CHKERRQ(ierr); 3031 3032 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3033 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 3034 ierr = VecGetArray(cmap,&cmaparray);CHKERRQ(ierr); 3035 for (i=0; i<n; i++) { 3036 xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i]; 3037 cmaparray[is_idx[i]-cstart] = i + isstart; 3038 } 3039 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 3040 ierr = VecRestoreArray(cmap,&cmaparray);CHKERRQ(ierr); 3041 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3042 //ierr = VecView(x,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr); 3043 //ierr = VecView(cmap,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr); 3044 3045 /* (2) scatter x using aij->Mvctx to get off-process portion of x (see MatMult_MPIAIJ) */ 3046 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3047 Mat B=a->B; 3048 Vec lvec = a->lvec,lcmap; 3049 PetscInt Bn=B->cmap->N; 3050 PetscInt *garray = a->garray; 3051 3052 ierr = VecDuplicate(lvec,&lcmap);CHKERRQ(ierr); 3053 3054 ierr = VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3055 ierr = VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3056 3057 ierr = VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3058 ierr = VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3059 3060 //printf("[%d] n(lvec) %d, Bn %d\n",rank,a->lvec->map->n,Bn); 3061 if (lvec->map->n != Bn) SETERRQ2(PETSC_COMM_SELF,0,"n(lvec) %d != Bn %d",lvec->map->n,Bn); 3062 if (rank == -1) { 3063 printf("[%d] lvec:\n",rank); 3064 ierr = VecView(lvec,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 3065 } 3066 3067 /* create scalable iscol_sub (a subset of iscol) and iscmap */ 3068 PetscInt *idx,*cmap1,count; 3069 3070 ierr = PetscMalloc2(n+Bn,&idx,n+Bn,&cmap1);CHKERRQ(ierr); 3071 count = 0; 3072 3073 /* A part */ 3074 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3075 j = cstart; 3076 for (i=0; i<n; i++) { 3077 if (j >= cend) break; 3078 if (is_idx[i] == j) { 3079 idx[count] = j; 3080 cmap1[count] = i + isstart; /* column index in submat */ 3081 count++; j++; 3082 } else if (is_idx[i] > j) { 3083 while (is_idx[i] > j && j < cend-1) j++; 3084 if (is_idx[i] == j) { 3085 idx[count] = j; 3086 cmap1[count] = i + isstart; /* column index in submat */ 3087 count++; j++; 3088 } 3089 } 3090 } 3091 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3092 3093 /* B part */ 3094 ierr = VecGetArray(lvec,&xarray);CHKERRQ(ierr); 3095 ierr = VecGetArray(lcmap,&cmaparray);CHKERRQ(ierr); 3096 j = 0; 3097 for (i=0; i<Bn; i++) { 3098 if (j >= Bn) break; 3099 if ((PetscInt)xarray[i] == garray[j]) { 3100 idx[count] = garray[j]; 3101 cmap1[count] = cmaparray[i]; /* column index in submat */ 3102 count++; j++; 3103 } else if ((PetscInt)xarray[i] > garray[j]) { 3104 while ((PetscInt)xarray[i] > garray[j] && j < Bn-1) j++; 3105 if ((PetscInt)xarray[i] == garray[j]) { 3106 idx[count] = garray[j]; 3107 cmap1[count] = cmaparray[i]; /* column index in submat */ 3108 count++; j++; 3109 } 3110 } 3111 } 3112 ierr = VecRestoreArray(lvec,&xarray);CHKERRQ(ierr); 3113 ierr = VecRestoreArray(lcmap,&cmaparray);CHKERRQ(ierr); 3114 //printf("[%d] n %d + Bn %d = %d; count %d, isN %d, matN %d\n",rank,n,Bn,n+Bn,count,N,mat->cmap->N); 3115 3116 IS iscol_sub,iscmap; 3117 ierr = PetscSortInt(count,idx);CHKERRQ(ierr); 3118 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3119 3120 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3121 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3122 3123 if (rank == -1) { 3124 printf("[%d] iscmap:\n",rank); 3125 ierr = ISView(iscmap,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 3126 } 3127 3128 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3129 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3130 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3131 ierr = VecDestroy(&x);CHKERRQ(ierr); 3132 ierr = VecDestroy(&cmap);CHKERRQ(ierr); 3133 ierr = VecDestroy(&lcmap);CHKERRQ(ierr); 3134 } 3135 //----------------------------------------------- 3136 3137 /* Get nonscalable iscol_local -- will replace it with iscol_sub! */ 3138 if (call == MAT_REUSE_MATRIX) { 3139 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3140 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3141 } else { 3142 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3143 PetscBool sorted; 3144 ierr = ISSorted(iscol_local,&sorted);CHKERRQ(ierr); 3145 if (!sorted) printf("[%d] iscol_local !sorted\n",rank); 3146 } 3147 3148 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3149 ierr = MatCreateSubMatrix_MPIAIJ_Private_SameDist(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3150 3151 if (call == MAT_INITIAL_MATRIX) { 3152 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3153 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3154 } 3155 PetscFunctionReturn(0); 3156 } 3157 3158 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3159 { 3160 PetscErrorCode ierr; 3161 IS iscol_local; 3162 PetscInt csize; 3163 PetscInt n,i,j,rstart,rend; 3164 PetscBool sameDist=PETSC_FALSE,tsameDist; 3165 MPI_Comm comm; 3166 3167 PetscFunctionBegin; 3168 /* If isrow has same processor distribution as mat, then use a scalable routine */ 3169 if (call == MAT_REUSE_MATRIX) { 3170 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3171 if (iscol_local) tsameDist = PETSC_TRUE; 3172 } else { 3173 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3174 if (!n) { 3175 sameDist = PETSC_TRUE; 3176 } else { 3177 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3178 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3179 if (i >= rstart && j < rend) sameDist = PETSC_TRUE; 3180 } 3181 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3182 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3183 } 3184 3185 if (tsameDist) { 3186 ierr = MatCreateSubMatrix_MPIAIJ_SameDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3187 PetscFunctionReturn(0); 3188 } 3189 3190 /* General case */ 3191 /* --------------------------------------- */ 3192 if (call == MAT_REUSE_MATRIX) { 3193 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3194 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3195 } else { 3196 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3197 } 3198 3199 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3200 ierr = MatCreateSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3201 3202 if (call == MAT_INITIAL_MATRIX) { 3203 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3204 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3205 } 3206 PetscFunctionReturn(0); 3207 } 3208 3209 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat*); 3210 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3211 3212 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private_SameDist(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3213 { 3214 PetscErrorCode ierr; 3215 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3216 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3217 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3218 Mat M,Msub,B=a->B; 3219 MatScalar *aa; 3220 Mat_SeqAIJ *aij; 3221 PetscInt *garray = a->garray,*colsub; 3222 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3223 IS iscol_sub,iscmap; 3224 const PetscInt *is_idx,*cmap; 3225 3226 PetscFunctionBegin; 3227 MPI_Comm comm; 3228 PetscMPIInt rank; 3229 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3230 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3231 //printf("SubMatrix_MPIAIJ_Private_SameDist ...\n"); 3232 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); /* iscol should be sequential */ 3233 3234 if (call == MAT_INITIAL_MATRIX) { 3235 /* create scalable iscol_sub (a subset of iscol) */ 3236 PetscInt *idx,*cmap1; 3237 3238 PetscBool sorted; 3239 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 3240 if (!sorted) printf("iscol_local !sorted\n"); 3241 3242 ierr = PetscMalloc2(n,&idx,n,&cmap1);CHKERRQ(ierr); 3243 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3244 count = 0; 3245 3246 /* A part */ 3247 j = cstart; 3248 for (i=0; i<n; i++) { 3249 if (j >= cend) break; 3250 if (is_idx[i] == j) { 3251 idx[count] = j; 3252 cmap1[count] = i; /* column index in submat */ 3253 count++; j++; 3254 } else if (is_idx[i] > j) { 3255 while (is_idx[i] > j && j < cend-1) j++; 3256 if (is_idx[i] == j) { 3257 idx[count] = j; 3258 cmap1[count] = i; /* column index in submat */ 3259 count++; j++; 3260 } 3261 } 3262 } 3263 3264 /* B part */ 3265 j = 0; 3266 for (i=0; i<n; i++) { 3267 if (j >= Bn) break; 3268 if (is_idx[i] == garray[j]) { 3269 idx[count] = garray[j]; 3270 cmap1[count] = i; /* column index in submat */ 3271 count++; j++; 3272 } else if (is_idx[i] > garray[j]) { 3273 while (is_idx[i] > garray[j] && j < Bn-1) j++; 3274 if (is_idx[i] == garray[j]) { 3275 idx[count] = garray[j]; 3276 cmap1[count] = i; /* column index in submat */ 3277 count++; j++; 3278 } 3279 } 3280 } 3281 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3282 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3283 3284 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3285 ierr = ISSort(iscol_sub);CHKERRQ(ierr); 3286 3287 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3288 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3289 3290 //printf("\n[%d] old count %d, isN %d, matN %d\n",rank,count,n,mat->cmap->N); 3291 if (rank == -1) { 3292 printf("[%d] old iscmap:\n",rank); 3293 ierr = ISView(iscmap,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 3294 } 3295 3296 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3297 3298 } else { /* call == MAT_REUSE_MATRIX */ 3299 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3300 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3301 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3302 3303 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3304 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3305 3306 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3307 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3308 3309 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3310 } 3311 3312 aij = (Mat_SeqAIJ*)(Msub)->data; 3313 ii = aij->i; 3314 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3315 3316 /* 3317 m - number of local rows 3318 n - number of columns (same on all processors) 3319 rstart - first row in new global matrix generated 3320 */ 3321 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3322 3323 if (call == MAT_INITIAL_MATRIX) { 3324 MPI_Comm comm; 3325 PetscMPIInt rank,size; 3326 3327 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3328 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3329 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3330 3331 /* 3332 Determine the number of non-zeros in the diagonal and off-diagonal 3333 portions of the matrix in order to do correct preallocation 3334 */ 3335 3336 /* first get start and end of "diagonal" columns */ 3337 if (csize == PETSC_DECIDE) { 3338 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3339 if (mglobal == n) { /* square matrix */ 3340 nlocal = m; 3341 } else { 3342 nlocal = n/size + ((n % size) > rank); 3343 } 3344 } else { 3345 nlocal = csize; 3346 } 3347 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3348 rstart = rend - nlocal; 3349 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); 3350 3351 /* next, compute all the lengths */ 3352 jj = aij->j; 3353 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3354 olens = dlens + m; 3355 for (i=0; i<m; i++) { 3356 jend = ii[i+1] - ii[i]; 3357 olen = 0; 3358 dlen = 0; 3359 for (j=0; j<jend; j++) { 3360 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3361 else dlen++; 3362 jj++; 3363 } 3364 olens[i] = olen; 3365 dlens[i] = dlen; 3366 } 3367 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3368 3369 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3370 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3371 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3372 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3373 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3374 ierr = PetscFree(dlens);CHKERRQ(ierr); 3375 } else { 3376 M = *newmat; 3377 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3378 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3379 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3380 /* 3381 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3382 rather than the slower MatSetValues(). 3383 */ 3384 M->was_assembled = PETSC_TRUE; 3385 M->assembled = PETSC_FALSE; 3386 } 3387 3388 /* set values of Msub to *newmat */ 3389 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3390 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3391 3392 jj = aij->j; 3393 aa = aij->a; 3394 for (i=0; i<m; i++) { 3395 row = rstart + i; 3396 nz = ii[i+1] - ii[i]; 3397 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3398 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3399 jj += nz; aa += nz; 3400 } 3401 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3402 3403 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3404 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3405 *newmat = M; 3406 3407 ierr = PetscFree(colsub);CHKERRQ(ierr); 3408 3409 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3410 if (call == MAT_INITIAL_MATRIX) { 3411 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3412 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3413 3414 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3415 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3416 3417 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3418 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3419 } 3420 PetscFunctionReturn(0); 3421 } 3422 3423 /* 3424 Not great since it makes two copies of the submatrix, first an SeqAIJ 3425 in local and then by concatenating the local matrices the end result. 3426 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3427 3428 Note: This requires a sequential iscol with all indices. 3429 */ 3430 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3431 { 3432 PetscErrorCode ierr; 3433 PetscMPIInt rank,size; 3434 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3435 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3436 Mat M,Mreuse; 3437 MatScalar *aa,*vwork; 3438 MPI_Comm comm; 3439 Mat_SeqAIJ *aij; 3440 //PetscBool sameDist=PETSC_FALSE,tsameDist; 3441 3442 PetscFunctionBegin; 3443 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3444 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3445 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3446 #if 0 3447 /* If isrow has same processor distribution as mat, then use a scalable routine */ 3448 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3449 if (!n) { 3450 sameDist=PETSC_TRUE; 3451 } else { 3452 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3453 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3454 if (i >= rstart && j < rend) sameDist=PETSC_TRUE; 3455 } 3456 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3457 if (tsameDist) { 3458 ierr = MatCreateSubMatrix_MPIAIJ_Private_SameDist(mat,isrow,iscol,csize,call,newmat);CHKERRQ(ierr); 3459 PetscFunctionReturn(0); 3460 } 3461 #endif 3462 3463 if (call == MAT_REUSE_MATRIX) { 3464 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3465 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3466 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&Mreuse);CHKERRQ(ierr); 3467 } else { 3468 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&Mreuse);CHKERRQ(ierr); 3469 } 3470 3471 /* 3472 m - number of local rows 3473 n - number of columns (same on all processors) 3474 rstart - first row in new global matrix generated 3475 */ 3476 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3477 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3478 if (call == MAT_INITIAL_MATRIX) { 3479 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3480 ii = aij->i; 3481 jj = aij->j; 3482 3483 /* 3484 Determine the number of non-zeros in the diagonal and off-diagonal 3485 portions of the matrix in order to do correct preallocation 3486 */ 3487 3488 /* first get start and end of "diagonal" columns */ 3489 if (csize == PETSC_DECIDE) { 3490 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3491 if (mglobal == n) { /* square matrix */ 3492 nlocal = m; 3493 } else { 3494 nlocal = n/size + ((n % size) > rank); 3495 } 3496 } else { 3497 nlocal = csize; 3498 } 3499 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3500 rstart = rend - nlocal; 3501 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); 3502 3503 /* next, compute all the lengths */ 3504 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3505 olens = dlens + m; 3506 for (i=0; i<m; i++) { 3507 jend = ii[i+1] - ii[i]; 3508 olen = 0; 3509 dlen = 0; 3510 for (j=0; j<jend; j++) { 3511 if (*jj < rstart || *jj >= rend) olen++; 3512 else dlen++; 3513 jj++; 3514 } 3515 olens[i] = olen; 3516 dlens[i] = dlen; 3517 } 3518 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3519 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3520 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3521 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3522 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3523 ierr = PetscFree(dlens);CHKERRQ(ierr); 3524 } else { 3525 PetscInt ml,nl; 3526 3527 M = *newmat; 3528 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3529 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3530 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3531 /* 3532 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3533 rather than the slower MatSetValues(). 3534 */ 3535 M->was_assembled = PETSC_TRUE; 3536 M->assembled = PETSC_FALSE; 3537 } 3538 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3539 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3540 ii = aij->i; 3541 jj = aij->j; 3542 aa = aij->a; 3543 for (i=0; i<m; i++) { 3544 row = rstart + i; 3545 nz = ii[i+1] - ii[i]; 3546 cwork = jj; jj += nz; 3547 vwork = aa; aa += nz; 3548 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3549 } 3550 3551 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3552 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3553 *newmat = M; 3554 3555 /* save submatrix used in processor for next request */ 3556 if (call == MAT_INITIAL_MATRIX) { 3557 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3558 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3559 } 3560 PetscFunctionReturn(0); 3561 } 3562 3563 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3564 { 3565 PetscInt m,cstart, cend,j,nnz,i,d; 3566 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3567 const PetscInt *JJ; 3568 PetscScalar *values; 3569 PetscErrorCode ierr; 3570 PetscBool nooffprocentries; 3571 3572 PetscFunctionBegin; 3573 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3574 3575 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3576 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3577 m = B->rmap->n; 3578 cstart = B->cmap->rstart; 3579 cend = B->cmap->rend; 3580 rstart = B->rmap->rstart; 3581 3582 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3583 3584 #if defined(PETSC_USE_DEBUGGING) 3585 for (i=0; i<m; i++) { 3586 nnz = Ii[i+1]- Ii[i]; 3587 JJ = J + Ii[i]; 3588 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3589 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3590 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); 3591 } 3592 #endif 3593 3594 for (i=0; i<m; i++) { 3595 nnz = Ii[i+1]- Ii[i]; 3596 JJ = J + Ii[i]; 3597 nnz_max = PetscMax(nnz_max,nnz); 3598 d = 0; 3599 for (j=0; j<nnz; j++) { 3600 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3601 } 3602 d_nnz[i] = d; 3603 o_nnz[i] = nnz - d; 3604 } 3605 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3606 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3607 3608 if (v) values = (PetscScalar*)v; 3609 else { 3610 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3611 } 3612 3613 for (i=0; i<m; i++) { 3614 ii = i + rstart; 3615 nnz = Ii[i+1]- Ii[i]; 3616 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3617 } 3618 nooffprocentries = B->nooffprocentries; 3619 B->nooffprocentries = PETSC_TRUE; 3620 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3621 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3622 B->nooffprocentries = nooffprocentries; 3623 3624 if (!v) { 3625 ierr = PetscFree(values);CHKERRQ(ierr); 3626 } 3627 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3628 PetscFunctionReturn(0); 3629 } 3630 3631 /*@ 3632 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3633 (the default parallel PETSc format). 3634 3635 Collective on MPI_Comm 3636 3637 Input Parameters: 3638 + B - the matrix 3639 . i - the indices into j for the start of each local row (starts with zero) 3640 . j - the column indices for each local row (starts with zero) 3641 - v - optional values in the matrix 3642 3643 Level: developer 3644 3645 Notes: 3646 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3647 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3648 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3649 3650 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3651 3652 The format which is used for the sparse matrix input, is equivalent to a 3653 row-major ordering.. i.e for the following matrix, the input data expected is 3654 as shown 3655 3656 $ 1 0 0 3657 $ 2 0 3 P0 3658 $ ------- 3659 $ 4 5 6 P1 3660 $ 3661 $ Process0 [P0]: rows_owned=[0,1] 3662 $ i = {0,1,3} [size = nrow+1 = 2+1] 3663 $ j = {0,0,2} [size = 3] 3664 $ v = {1,2,3} [size = 3] 3665 $ 3666 $ Process1 [P1]: rows_owned=[2] 3667 $ i = {0,3} [size = nrow+1 = 1+1] 3668 $ j = {0,1,2} [size = 3] 3669 $ v = {4,5,6} [size = 3] 3670 3671 .keywords: matrix, aij, compressed row, sparse, parallel 3672 3673 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3674 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3675 @*/ 3676 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3677 { 3678 PetscErrorCode ierr; 3679 3680 PetscFunctionBegin; 3681 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3682 PetscFunctionReturn(0); 3683 } 3684 3685 /*@C 3686 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3687 (the default parallel PETSc format). For good matrix assembly performance 3688 the user should preallocate the matrix storage by setting the parameters 3689 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3690 performance can be increased by more than a factor of 50. 3691 3692 Collective on MPI_Comm 3693 3694 Input Parameters: 3695 + B - the matrix 3696 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3697 (same value is used for all local rows) 3698 . d_nnz - array containing the number of nonzeros in the various rows of the 3699 DIAGONAL portion of the local submatrix (possibly different for each row) 3700 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3701 The size of this array is equal to the number of local rows, i.e 'm'. 3702 For matrices that will be factored, you must leave room for (and set) 3703 the diagonal entry even if it is zero. 3704 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3705 submatrix (same value is used for all local rows). 3706 - o_nnz - array containing the number of nonzeros in the various rows of the 3707 OFF-DIAGONAL portion of the local submatrix (possibly different for 3708 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3709 structure. The size of this array is equal to the number 3710 of local rows, i.e 'm'. 3711 3712 If the *_nnz parameter is given then the *_nz parameter is ignored 3713 3714 The AIJ format (also called the Yale sparse matrix format or 3715 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3716 storage. The stored row and column indices begin with zero. 3717 See Users-Manual: ch_mat for details. 3718 3719 The parallel matrix is partitioned such that the first m0 rows belong to 3720 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3721 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3722 3723 The DIAGONAL portion of the local submatrix of a processor can be defined 3724 as the submatrix which is obtained by extraction the part corresponding to 3725 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3726 first row that belongs to the processor, r2 is the last row belonging to 3727 the this processor, and c1-c2 is range of indices of the local part of a 3728 vector suitable for applying the matrix to. This is an mxn matrix. In the 3729 common case of a square matrix, the row and column ranges are the same and 3730 the DIAGONAL part is also square. The remaining portion of the local 3731 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3732 3733 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3734 3735 You can call MatGetInfo() to get information on how effective the preallocation was; 3736 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3737 You can also run with the option -info and look for messages with the string 3738 malloc in them to see if additional memory allocation was needed. 3739 3740 Example usage: 3741 3742 Consider the following 8x8 matrix with 34 non-zero values, that is 3743 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3744 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3745 as follows: 3746 3747 .vb 3748 1 2 0 | 0 3 0 | 0 4 3749 Proc0 0 5 6 | 7 0 0 | 8 0 3750 9 0 10 | 11 0 0 | 12 0 3751 ------------------------------------- 3752 13 0 14 | 15 16 17 | 0 0 3753 Proc1 0 18 0 | 19 20 21 | 0 0 3754 0 0 0 | 22 23 0 | 24 0 3755 ------------------------------------- 3756 Proc2 25 26 27 | 0 0 28 | 29 0 3757 30 0 0 | 31 32 33 | 0 34 3758 .ve 3759 3760 This can be represented as a collection of submatrices as: 3761 3762 .vb 3763 A B C 3764 D E F 3765 G H I 3766 .ve 3767 3768 Where the submatrices A,B,C are owned by proc0, D,E,F are 3769 owned by proc1, G,H,I are owned by proc2. 3770 3771 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3772 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3773 The 'M','N' parameters are 8,8, and have the same values on all procs. 3774 3775 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3776 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3777 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3778 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3779 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3780 matrix, ans [DF] as another SeqAIJ matrix. 3781 3782 When d_nz, o_nz parameters are specified, d_nz storage elements are 3783 allocated for every row of the local diagonal submatrix, and o_nz 3784 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3785 One way to choose d_nz and o_nz is to use the max nonzerors per local 3786 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3787 In this case, the values of d_nz,o_nz are: 3788 .vb 3789 proc0 : dnz = 2, o_nz = 2 3790 proc1 : dnz = 3, o_nz = 2 3791 proc2 : dnz = 1, o_nz = 4 3792 .ve 3793 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3794 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3795 for proc3. i.e we are using 12+15+10=37 storage locations to store 3796 34 values. 3797 3798 When d_nnz, o_nnz parameters are specified, the storage is specified 3799 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3800 In the above case the values for d_nnz,o_nnz are: 3801 .vb 3802 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3803 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3804 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3805 .ve 3806 Here the space allocated is sum of all the above values i.e 34, and 3807 hence pre-allocation is perfect. 3808 3809 Level: intermediate 3810 3811 .keywords: matrix, aij, compressed row, sparse, parallel 3812 3813 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3814 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3815 @*/ 3816 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3817 { 3818 PetscErrorCode ierr; 3819 3820 PetscFunctionBegin; 3821 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3822 PetscValidType(B,1); 3823 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3824 PetscFunctionReturn(0); 3825 } 3826 3827 /*@ 3828 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3829 CSR format the local rows. 3830 3831 Collective on MPI_Comm 3832 3833 Input Parameters: 3834 + comm - MPI communicator 3835 . m - number of local rows (Cannot be PETSC_DECIDE) 3836 . n - This value should be the same as the local size used in creating the 3837 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3838 calculated if N is given) For square matrices n is almost always m. 3839 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3840 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3841 . i - row indices 3842 . j - column indices 3843 - a - matrix values 3844 3845 Output Parameter: 3846 . mat - the matrix 3847 3848 Level: intermediate 3849 3850 Notes: 3851 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3852 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3853 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3854 3855 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3856 3857 The format which is used for the sparse matrix input, is equivalent to a 3858 row-major ordering.. i.e for the following matrix, the input data expected is 3859 as shown 3860 3861 $ 1 0 0 3862 $ 2 0 3 P0 3863 $ ------- 3864 $ 4 5 6 P1 3865 $ 3866 $ Process0 [P0]: rows_owned=[0,1] 3867 $ i = {0,1,3} [size = nrow+1 = 2+1] 3868 $ j = {0,0,2} [size = 3] 3869 $ v = {1,2,3} [size = 3] 3870 $ 3871 $ Process1 [P1]: rows_owned=[2] 3872 $ i = {0,3} [size = nrow+1 = 1+1] 3873 $ j = {0,1,2} [size = 3] 3874 $ v = {4,5,6} [size = 3] 3875 3876 .keywords: matrix, aij, compressed row, sparse, parallel 3877 3878 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3879 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3880 @*/ 3881 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3882 { 3883 PetscErrorCode ierr; 3884 3885 PetscFunctionBegin; 3886 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3887 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3888 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3889 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3890 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3891 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3892 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3893 PetscFunctionReturn(0); 3894 } 3895 3896 /*@C 3897 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3898 (the default parallel PETSc format). For good matrix assembly performance 3899 the user should preallocate the matrix storage by setting the parameters 3900 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3901 performance can be increased by more than a factor of 50. 3902 3903 Collective on MPI_Comm 3904 3905 Input Parameters: 3906 + comm - MPI communicator 3907 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3908 This value should be the same as the local size used in creating the 3909 y vector for the matrix-vector product y = Ax. 3910 . n - This value should be the same as the local size used in creating the 3911 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3912 calculated if N is given) For square matrices n is almost always m. 3913 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3914 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3915 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3916 (same value is used for all local rows) 3917 . d_nnz - array containing the number of nonzeros in the various rows of the 3918 DIAGONAL portion of the local submatrix (possibly different for each row) 3919 or NULL, if d_nz is used to specify the nonzero structure. 3920 The size of this array is equal to the number of local rows, i.e 'm'. 3921 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3922 submatrix (same value is used for all local rows). 3923 - o_nnz - array containing the number of nonzeros in the various rows of the 3924 OFF-DIAGONAL portion of the local submatrix (possibly different for 3925 each row) or NULL, if o_nz is used to specify the nonzero 3926 structure. The size of this array is equal to the number 3927 of local rows, i.e 'm'. 3928 3929 Output Parameter: 3930 . A - the matrix 3931 3932 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3933 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3934 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3935 3936 Notes: 3937 If the *_nnz parameter is given then the *_nz parameter is ignored 3938 3939 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3940 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3941 storage requirements for this matrix. 3942 3943 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3944 processor than it must be used on all processors that share the object for 3945 that argument. 3946 3947 The user MUST specify either the local or global matrix dimensions 3948 (possibly both). 3949 3950 The parallel matrix is partitioned across processors such that the 3951 first m0 rows belong to process 0, the next m1 rows belong to 3952 process 1, the next m2 rows belong to process 2 etc.. where 3953 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3954 values corresponding to [m x N] submatrix. 3955 3956 The columns are logically partitioned with the n0 columns belonging 3957 to 0th partition, the next n1 columns belonging to the next 3958 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3959 3960 The DIAGONAL portion of the local submatrix on any given processor 3961 is the submatrix corresponding to the rows and columns m,n 3962 corresponding to the given processor. i.e diagonal matrix on 3963 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3964 etc. The remaining portion of the local submatrix [m x (N-n)] 3965 constitute the OFF-DIAGONAL portion. The example below better 3966 illustrates this concept. 3967 3968 For a square global matrix we define each processor's diagonal portion 3969 to be its local rows and the corresponding columns (a square submatrix); 3970 each processor's off-diagonal portion encompasses the remainder of the 3971 local matrix (a rectangular submatrix). 3972 3973 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3974 3975 When calling this routine with a single process communicator, a matrix of 3976 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3977 type of communicator, use the construction mechanism: 3978 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3979 3980 By default, this format uses inodes (identical nodes) when possible. 3981 We search for consecutive rows with the same nonzero structure, thereby 3982 reusing matrix information to achieve increased efficiency. 3983 3984 Options Database Keys: 3985 + -mat_no_inode - Do not use inodes 3986 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3987 - -mat_aij_oneindex - Internally use indexing starting at 1 3988 rather than 0. Note that when calling MatSetValues(), 3989 the user still MUST index entries starting at 0! 3990 3991 3992 Example usage: 3993 3994 Consider the following 8x8 matrix with 34 non-zero values, that is 3995 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3996 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3997 as follows: 3998 3999 .vb 4000 1 2 0 | 0 3 0 | 0 4 4001 Proc0 0 5 6 | 7 0 0 | 8 0 4002 9 0 10 | 11 0 0 | 12 0 4003 ------------------------------------- 4004 13 0 14 | 15 16 17 | 0 0 4005 Proc1 0 18 0 | 19 20 21 | 0 0 4006 0 0 0 | 22 23 0 | 24 0 4007 ------------------------------------- 4008 Proc2 25 26 27 | 0 0 28 | 29 0 4009 30 0 0 | 31 32 33 | 0 34 4010 .ve 4011 4012 This can be represented as a collection of submatrices as: 4013 4014 .vb 4015 A B C 4016 D E F 4017 G H I 4018 .ve 4019 4020 Where the submatrices A,B,C are owned by proc0, D,E,F are 4021 owned by proc1, G,H,I are owned by proc2. 4022 4023 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4024 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4025 The 'M','N' parameters are 8,8, and have the same values on all procs. 4026 4027 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4028 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4029 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4030 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4031 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4032 matrix, ans [DF] as another SeqAIJ matrix. 4033 4034 When d_nz, o_nz parameters are specified, d_nz storage elements are 4035 allocated for every row of the local diagonal submatrix, and o_nz 4036 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4037 One way to choose d_nz and o_nz is to use the max nonzerors per local 4038 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4039 In this case, the values of d_nz,o_nz are: 4040 .vb 4041 proc0 : dnz = 2, o_nz = 2 4042 proc1 : dnz = 3, o_nz = 2 4043 proc2 : dnz = 1, o_nz = 4 4044 .ve 4045 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4046 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4047 for proc3. i.e we are using 12+15+10=37 storage locations to store 4048 34 values. 4049 4050 When d_nnz, o_nnz parameters are specified, the storage is specified 4051 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4052 In the above case the values for d_nnz,o_nnz are: 4053 .vb 4054 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4055 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4056 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4057 .ve 4058 Here the space allocated is sum of all the above values i.e 34, and 4059 hence pre-allocation is perfect. 4060 4061 Level: intermediate 4062 4063 .keywords: matrix, aij, compressed row, sparse, parallel 4064 4065 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4066 MATMPIAIJ, MatCreateMPIAIJWithArrays() 4067 @*/ 4068 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) 4069 { 4070 PetscErrorCode ierr; 4071 PetscMPIInt size; 4072 4073 PetscFunctionBegin; 4074 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4075 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4076 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4077 if (size > 1) { 4078 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4079 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4080 } else { 4081 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4082 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4083 } 4084 PetscFunctionReturn(0); 4085 } 4086 4087 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4088 { 4089 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4090 PetscBool flg; 4091 PetscErrorCode ierr; 4092 4093 PetscFunctionBegin; 4094 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4095 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4096 if (Ad) *Ad = a->A; 4097 if (Ao) *Ao = a->B; 4098 if (colmap) *colmap = a->garray; 4099 PetscFunctionReturn(0); 4100 } 4101 4102 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4103 { 4104 PetscErrorCode ierr; 4105 PetscInt m,N,i,rstart,nnz,Ii; 4106 PetscInt *indx; 4107 PetscScalar *values; 4108 4109 PetscFunctionBegin; 4110 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4111 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4112 PetscInt *dnz,*onz,sum,bs,cbs; 4113 4114 if (n == PETSC_DECIDE) { 4115 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4116 } 4117 /* Check sum(n) = N */ 4118 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4119 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4120 4121 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4122 rstart -= m; 4123 4124 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4125 for (i=0; i<m; i++) { 4126 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4127 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4128 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4129 } 4130 4131 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4132 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4133 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4134 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4135 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4136 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4137 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4138 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4139 } 4140 4141 /* numeric phase */ 4142 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4143 for (i=0; i<m; i++) { 4144 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4145 Ii = i + rstart; 4146 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4147 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4148 } 4149 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4150 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4151 PetscFunctionReturn(0); 4152 } 4153 4154 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4155 { 4156 PetscErrorCode ierr; 4157 PetscMPIInt rank; 4158 PetscInt m,N,i,rstart,nnz; 4159 size_t len; 4160 const PetscInt *indx; 4161 PetscViewer out; 4162 char *name; 4163 Mat B; 4164 const PetscScalar *values; 4165 4166 PetscFunctionBegin; 4167 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4168 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4169 /* Should this be the type of the diagonal block of A? */ 4170 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4171 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4172 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4173 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4174 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4175 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4176 for (i=0; i<m; i++) { 4177 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4178 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4179 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4180 } 4181 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4182 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4183 4184 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4185 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4186 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4187 sprintf(name,"%s.%d",outfile,rank); 4188 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4189 ierr = PetscFree(name);CHKERRQ(ierr); 4190 ierr = MatView(B,out);CHKERRQ(ierr); 4191 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4192 ierr = MatDestroy(&B);CHKERRQ(ierr); 4193 PetscFunctionReturn(0); 4194 } 4195 4196 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4197 { 4198 PetscErrorCode ierr; 4199 Mat_Merge_SeqsToMPI *merge; 4200 PetscContainer container; 4201 4202 PetscFunctionBegin; 4203 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4204 if (container) { 4205 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4206 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4207 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4208 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4209 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4210 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4211 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4212 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4213 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4214 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4215 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4216 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4217 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4218 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4219 ierr = PetscFree(merge);CHKERRQ(ierr); 4220 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4221 } 4222 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4223 PetscFunctionReturn(0); 4224 } 4225 4226 #include <../src/mat/utils/freespace.h> 4227 #include <petscbt.h> 4228 4229 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4230 { 4231 PetscErrorCode ierr; 4232 MPI_Comm comm; 4233 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4234 PetscMPIInt size,rank,taga,*len_s; 4235 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4236 PetscInt proc,m; 4237 PetscInt **buf_ri,**buf_rj; 4238 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4239 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4240 MPI_Request *s_waits,*r_waits; 4241 MPI_Status *status; 4242 MatScalar *aa=a->a; 4243 MatScalar **abuf_r,*ba_i; 4244 Mat_Merge_SeqsToMPI *merge; 4245 PetscContainer container; 4246 4247 PetscFunctionBegin; 4248 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4249 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4250 4251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4252 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4253 4254 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4255 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4256 4257 bi = merge->bi; 4258 bj = merge->bj; 4259 buf_ri = merge->buf_ri; 4260 buf_rj = merge->buf_rj; 4261 4262 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4263 owners = merge->rowmap->range; 4264 len_s = merge->len_s; 4265 4266 /* send and recv matrix values */ 4267 /*-----------------------------*/ 4268 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4269 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4270 4271 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4272 for (proc=0,k=0; proc<size; proc++) { 4273 if (!len_s[proc]) continue; 4274 i = owners[proc]; 4275 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4276 k++; 4277 } 4278 4279 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4280 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4281 ierr = PetscFree(status);CHKERRQ(ierr); 4282 4283 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4284 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4285 4286 /* insert mat values of mpimat */ 4287 /*----------------------------*/ 4288 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4289 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4290 4291 for (k=0; k<merge->nrecv; k++) { 4292 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4293 nrows = *(buf_ri_k[k]); 4294 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4295 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4296 } 4297 4298 /* set values of ba */ 4299 m = merge->rowmap->n; 4300 for (i=0; i<m; i++) { 4301 arow = owners[rank] + i; 4302 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4303 bnzi = bi[i+1] - bi[i]; 4304 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4305 4306 /* add local non-zero vals of this proc's seqmat into ba */ 4307 anzi = ai[arow+1] - ai[arow]; 4308 aj = a->j + ai[arow]; 4309 aa = a->a + ai[arow]; 4310 nextaj = 0; 4311 for (j=0; nextaj<anzi; j++) { 4312 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4313 ba_i[j] += aa[nextaj++]; 4314 } 4315 } 4316 4317 /* add received vals into ba */ 4318 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4319 /* i-th row */ 4320 if (i == *nextrow[k]) { 4321 anzi = *(nextai[k]+1) - *nextai[k]; 4322 aj = buf_rj[k] + *(nextai[k]); 4323 aa = abuf_r[k] + *(nextai[k]); 4324 nextaj = 0; 4325 for (j=0; nextaj<anzi; j++) { 4326 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4327 ba_i[j] += aa[nextaj++]; 4328 } 4329 } 4330 nextrow[k]++; nextai[k]++; 4331 } 4332 } 4333 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4334 } 4335 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4336 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4337 4338 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4339 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4340 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4341 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4342 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4343 PetscFunctionReturn(0); 4344 } 4345 4346 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4347 { 4348 PetscErrorCode ierr; 4349 Mat B_mpi; 4350 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4351 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4352 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4353 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4354 PetscInt len,proc,*dnz,*onz,bs,cbs; 4355 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4356 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4357 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4358 MPI_Status *status; 4359 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4360 PetscBT lnkbt; 4361 Mat_Merge_SeqsToMPI *merge; 4362 PetscContainer container; 4363 4364 PetscFunctionBegin; 4365 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4366 4367 /* make sure it is a PETSc comm */ 4368 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4369 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4370 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4371 4372 ierr = PetscNew(&merge);CHKERRQ(ierr); 4373 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4374 4375 /* determine row ownership */ 4376 /*---------------------------------------------------------*/ 4377 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4378 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4379 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4380 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4381 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4382 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4383 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4384 4385 m = merge->rowmap->n; 4386 owners = merge->rowmap->range; 4387 4388 /* determine the number of messages to send, their lengths */ 4389 /*---------------------------------------------------------*/ 4390 len_s = merge->len_s; 4391 4392 len = 0; /* length of buf_si[] */ 4393 merge->nsend = 0; 4394 for (proc=0; proc<size; proc++) { 4395 len_si[proc] = 0; 4396 if (proc == rank) { 4397 len_s[proc] = 0; 4398 } else { 4399 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4400 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4401 } 4402 if (len_s[proc]) { 4403 merge->nsend++; 4404 nrows = 0; 4405 for (i=owners[proc]; i<owners[proc+1]; i++) { 4406 if (ai[i+1] > ai[i]) nrows++; 4407 } 4408 len_si[proc] = 2*(nrows+1); 4409 len += len_si[proc]; 4410 } 4411 } 4412 4413 /* determine the number and length of messages to receive for ij-structure */ 4414 /*-------------------------------------------------------------------------*/ 4415 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4416 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4417 4418 /* post the Irecv of j-structure */ 4419 /*-------------------------------*/ 4420 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4421 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4422 4423 /* post the Isend of j-structure */ 4424 /*--------------------------------*/ 4425 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4426 4427 for (proc=0, k=0; proc<size; proc++) { 4428 if (!len_s[proc]) continue; 4429 i = owners[proc]; 4430 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4431 k++; 4432 } 4433 4434 /* receives and sends of j-structure are complete */ 4435 /*------------------------------------------------*/ 4436 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4437 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4438 4439 /* send and recv i-structure */ 4440 /*---------------------------*/ 4441 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4442 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4443 4444 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4445 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4446 for (proc=0,k=0; proc<size; proc++) { 4447 if (!len_s[proc]) continue; 4448 /* form outgoing message for i-structure: 4449 buf_si[0]: nrows to be sent 4450 [1:nrows]: row index (global) 4451 [nrows+1:2*nrows+1]: i-structure index 4452 */ 4453 /*-------------------------------------------*/ 4454 nrows = len_si[proc]/2 - 1; 4455 buf_si_i = buf_si + nrows+1; 4456 buf_si[0] = nrows; 4457 buf_si_i[0] = 0; 4458 nrows = 0; 4459 for (i=owners[proc]; i<owners[proc+1]; i++) { 4460 anzi = ai[i+1] - ai[i]; 4461 if (anzi) { 4462 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4463 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4464 nrows++; 4465 } 4466 } 4467 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4468 k++; 4469 buf_si += len_si[proc]; 4470 } 4471 4472 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4473 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4474 4475 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4476 for (i=0; i<merge->nrecv; i++) { 4477 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); 4478 } 4479 4480 ierr = PetscFree(len_si);CHKERRQ(ierr); 4481 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4482 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4483 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4484 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4485 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4486 ierr = PetscFree(status);CHKERRQ(ierr); 4487 4488 /* compute a local seq matrix in each processor */ 4489 /*----------------------------------------------*/ 4490 /* allocate bi array and free space for accumulating nonzero column info */ 4491 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4492 bi[0] = 0; 4493 4494 /* create and initialize a linked list */ 4495 nlnk = N+1; 4496 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4497 4498 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4499 len = ai[owners[rank+1]] - ai[owners[rank]]; 4500 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4501 4502 current_space = free_space; 4503 4504 /* determine symbolic info for each local row */ 4505 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4506 4507 for (k=0; k<merge->nrecv; k++) { 4508 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4509 nrows = *buf_ri_k[k]; 4510 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4511 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4512 } 4513 4514 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4515 len = 0; 4516 for (i=0; i<m; i++) { 4517 bnzi = 0; 4518 /* add local non-zero cols of this proc's seqmat into lnk */ 4519 arow = owners[rank] + i; 4520 anzi = ai[arow+1] - ai[arow]; 4521 aj = a->j + ai[arow]; 4522 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4523 bnzi += nlnk; 4524 /* add received col data into lnk */ 4525 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4526 if (i == *nextrow[k]) { /* i-th row */ 4527 anzi = *(nextai[k]+1) - *nextai[k]; 4528 aj = buf_rj[k] + *nextai[k]; 4529 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4530 bnzi += nlnk; 4531 nextrow[k]++; nextai[k]++; 4532 } 4533 } 4534 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4535 4536 /* if free space is not available, make more free space */ 4537 if (current_space->local_remaining<bnzi) { 4538 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4539 nspacedouble++; 4540 } 4541 /* copy data into free space, then initialize lnk */ 4542 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4543 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4544 4545 current_space->array += bnzi; 4546 current_space->local_used += bnzi; 4547 current_space->local_remaining -= bnzi; 4548 4549 bi[i+1] = bi[i] + bnzi; 4550 } 4551 4552 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4553 4554 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4555 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4556 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4557 4558 /* create symbolic parallel matrix B_mpi */ 4559 /*---------------------------------------*/ 4560 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4561 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4562 if (n==PETSC_DECIDE) { 4563 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4564 } else { 4565 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4566 } 4567 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4568 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4569 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4570 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4571 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4572 4573 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4574 B_mpi->assembled = PETSC_FALSE; 4575 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4576 merge->bi = bi; 4577 merge->bj = bj; 4578 merge->buf_ri = buf_ri; 4579 merge->buf_rj = buf_rj; 4580 merge->coi = NULL; 4581 merge->coj = NULL; 4582 merge->owners_co = NULL; 4583 4584 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4585 4586 /* attach the supporting struct to B_mpi for reuse */ 4587 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4588 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4589 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4590 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4591 *mpimat = B_mpi; 4592 4593 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4594 PetscFunctionReturn(0); 4595 } 4596 4597 /*@C 4598 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4599 matrices from each processor 4600 4601 Collective on MPI_Comm 4602 4603 Input Parameters: 4604 + comm - the communicators the parallel matrix will live on 4605 . seqmat - the input sequential matrices 4606 . m - number of local rows (or PETSC_DECIDE) 4607 . n - number of local columns (or PETSC_DECIDE) 4608 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4609 4610 Output Parameter: 4611 . mpimat - the parallel matrix generated 4612 4613 Level: advanced 4614 4615 Notes: 4616 The dimensions of the sequential matrix in each processor MUST be the same. 4617 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4618 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4619 @*/ 4620 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4621 { 4622 PetscErrorCode ierr; 4623 PetscMPIInt size; 4624 4625 PetscFunctionBegin; 4626 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4627 if (size == 1) { 4628 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4629 if (scall == MAT_INITIAL_MATRIX) { 4630 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4631 } else { 4632 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4633 } 4634 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4635 PetscFunctionReturn(0); 4636 } 4637 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4638 if (scall == MAT_INITIAL_MATRIX) { 4639 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4640 } 4641 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4642 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4643 PetscFunctionReturn(0); 4644 } 4645 4646 /*@ 4647 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4648 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4649 with MatGetSize() 4650 4651 Not Collective 4652 4653 Input Parameters: 4654 + A - the matrix 4655 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4656 4657 Output Parameter: 4658 . A_loc - the local sequential matrix generated 4659 4660 Level: developer 4661 4662 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4663 4664 @*/ 4665 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4666 { 4667 PetscErrorCode ierr; 4668 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4669 Mat_SeqAIJ *mat,*a,*b; 4670 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4671 MatScalar *aa,*ba,*cam; 4672 PetscScalar *ca; 4673 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4674 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4675 PetscBool match; 4676 MPI_Comm comm; 4677 PetscMPIInt size; 4678 4679 PetscFunctionBegin; 4680 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4681 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4682 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4683 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4684 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4685 4686 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4687 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4688 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4689 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4690 aa = a->a; ba = b->a; 4691 if (scall == MAT_INITIAL_MATRIX) { 4692 if (size == 1) { 4693 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4694 PetscFunctionReturn(0); 4695 } 4696 4697 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4698 ci[0] = 0; 4699 for (i=0; i<am; i++) { 4700 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4701 } 4702 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4703 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4704 k = 0; 4705 for (i=0; i<am; i++) { 4706 ncols_o = bi[i+1] - bi[i]; 4707 ncols_d = ai[i+1] - ai[i]; 4708 /* off-diagonal portion of A */ 4709 for (jo=0; jo<ncols_o; jo++) { 4710 col = cmap[*bj]; 4711 if (col >= cstart) break; 4712 cj[k] = col; bj++; 4713 ca[k++] = *ba++; 4714 } 4715 /* diagonal portion of A */ 4716 for (j=0; j<ncols_d; j++) { 4717 cj[k] = cstart + *aj++; 4718 ca[k++] = *aa++; 4719 } 4720 /* off-diagonal portion of A */ 4721 for (j=jo; j<ncols_o; j++) { 4722 cj[k] = cmap[*bj++]; 4723 ca[k++] = *ba++; 4724 } 4725 } 4726 /* put together the new matrix */ 4727 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4728 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4729 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4730 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4731 mat->free_a = PETSC_TRUE; 4732 mat->free_ij = PETSC_TRUE; 4733 mat->nonew = 0; 4734 } else if (scall == MAT_REUSE_MATRIX) { 4735 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4736 ci = mat->i; cj = mat->j; cam = mat->a; 4737 for (i=0; i<am; i++) { 4738 /* off-diagonal portion of A */ 4739 ncols_o = bi[i+1] - bi[i]; 4740 for (jo=0; jo<ncols_o; jo++) { 4741 col = cmap[*bj]; 4742 if (col >= cstart) break; 4743 *cam++ = *ba++; bj++; 4744 } 4745 /* diagonal portion of A */ 4746 ncols_d = ai[i+1] - ai[i]; 4747 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4748 /* off-diagonal portion of A */ 4749 for (j=jo; j<ncols_o; j++) { 4750 *cam++ = *ba++; bj++; 4751 } 4752 } 4753 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4754 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4755 PetscFunctionReturn(0); 4756 } 4757 4758 /*@C 4759 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4760 4761 Not Collective 4762 4763 Input Parameters: 4764 + A - the matrix 4765 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4766 - row, col - index sets of rows and columns to extract (or NULL) 4767 4768 Output Parameter: 4769 . A_loc - the local sequential matrix generated 4770 4771 Level: developer 4772 4773 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4774 4775 @*/ 4776 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4777 { 4778 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4779 PetscErrorCode ierr; 4780 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4781 IS isrowa,iscola; 4782 Mat *aloc; 4783 PetscBool match; 4784 4785 PetscFunctionBegin; 4786 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4787 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4788 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4789 if (!row) { 4790 start = A->rmap->rstart; end = A->rmap->rend; 4791 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4792 } else { 4793 isrowa = *row; 4794 } 4795 if (!col) { 4796 start = A->cmap->rstart; 4797 cmap = a->garray; 4798 nzA = a->A->cmap->n; 4799 nzB = a->B->cmap->n; 4800 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4801 ncols = 0; 4802 for (i=0; i<nzB; i++) { 4803 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4804 else break; 4805 } 4806 imark = i; 4807 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4808 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4809 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4810 } else { 4811 iscola = *col; 4812 } 4813 if (scall != MAT_INITIAL_MATRIX) { 4814 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4815 aloc[0] = *A_loc; 4816 } 4817 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4818 *A_loc = aloc[0]; 4819 ierr = PetscFree(aloc);CHKERRQ(ierr); 4820 if (!row) { 4821 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4822 } 4823 if (!col) { 4824 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4825 } 4826 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4827 PetscFunctionReturn(0); 4828 } 4829 4830 /*@C 4831 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4832 4833 Collective on Mat 4834 4835 Input Parameters: 4836 + A,B - the matrices in mpiaij format 4837 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4838 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4839 4840 Output Parameter: 4841 + rowb, colb - index sets of rows and columns of B to extract 4842 - B_seq - the sequential matrix generated 4843 4844 Level: developer 4845 4846 @*/ 4847 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4848 { 4849 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4850 PetscErrorCode ierr; 4851 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4852 IS isrowb,iscolb; 4853 Mat *bseq=NULL; 4854 4855 PetscFunctionBegin; 4856 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4857 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); 4858 } 4859 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4860 4861 if (scall == MAT_INITIAL_MATRIX) { 4862 start = A->cmap->rstart; 4863 cmap = a->garray; 4864 nzA = a->A->cmap->n; 4865 nzB = a->B->cmap->n; 4866 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4867 ncols = 0; 4868 for (i=0; i<nzB; i++) { /* row < local row index */ 4869 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4870 else break; 4871 } 4872 imark = i; 4873 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4874 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4875 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4876 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4877 } else { 4878 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4879 isrowb = *rowb; iscolb = *colb; 4880 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4881 bseq[0] = *B_seq; 4882 } 4883 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4884 *B_seq = bseq[0]; 4885 ierr = PetscFree(bseq);CHKERRQ(ierr); 4886 if (!rowb) { 4887 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4888 } else { 4889 *rowb = isrowb; 4890 } 4891 if (!colb) { 4892 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4893 } else { 4894 *colb = iscolb; 4895 } 4896 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4897 PetscFunctionReturn(0); 4898 } 4899 4900 /* 4901 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4902 of the OFF-DIAGONAL portion of local A 4903 4904 Collective on Mat 4905 4906 Input Parameters: 4907 + A,B - the matrices in mpiaij format 4908 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4909 4910 Output Parameter: 4911 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4912 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4913 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4914 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4915 4916 Level: developer 4917 4918 */ 4919 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4920 { 4921 VecScatter_MPI_General *gen_to,*gen_from; 4922 PetscErrorCode ierr; 4923 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4924 Mat_SeqAIJ *b_oth; 4925 VecScatter ctx =a->Mvctx; 4926 MPI_Comm comm; 4927 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4928 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4929 PetscInt *rvalues,*svalues; 4930 MatScalar *b_otha,*bufa,*bufA; 4931 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4932 MPI_Request *rwaits = NULL,*swaits = NULL; 4933 MPI_Status *sstatus,rstatus; 4934 PetscMPIInt jj,size; 4935 PetscInt *cols,sbs,rbs; 4936 PetscScalar *vals; 4937 4938 PetscFunctionBegin; 4939 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4940 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4941 4942 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4943 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); 4944 } 4945 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4946 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4947 4948 if (size == 1) { 4949 startsj_s = NULL; 4950 bufa_ptr = NULL; 4951 *B_oth = NULL; 4952 PetscFunctionReturn(0); 4953 } 4954 4955 gen_to = (VecScatter_MPI_General*)ctx->todata; 4956 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4957 nrecvs = gen_from->n; 4958 nsends = gen_to->n; 4959 4960 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4961 srow = gen_to->indices; /* local row index to be sent */ 4962 sstarts = gen_to->starts; 4963 sprocs = gen_to->procs; 4964 sstatus = gen_to->sstatus; 4965 sbs = gen_to->bs; 4966 rstarts = gen_from->starts; 4967 rprocs = gen_from->procs; 4968 rbs = gen_from->bs; 4969 4970 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4971 if (scall == MAT_INITIAL_MATRIX) { 4972 /* i-array */ 4973 /*---------*/ 4974 /* post receives */ 4975 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4976 for (i=0; i<nrecvs; i++) { 4977 rowlen = rvalues + rstarts[i]*rbs; 4978 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4979 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4980 } 4981 4982 /* pack the outgoing message */ 4983 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4984 4985 sstartsj[0] = 0; 4986 rstartsj[0] = 0; 4987 len = 0; /* total length of j or a array to be sent */ 4988 k = 0; 4989 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4990 for (i=0; i<nsends; i++) { 4991 rowlen = svalues + sstarts[i]*sbs; 4992 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4993 for (j=0; j<nrows; j++) { 4994 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4995 for (l=0; l<sbs; l++) { 4996 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4997 4998 rowlen[j*sbs+l] = ncols; 4999 5000 len += ncols; 5001 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5002 } 5003 k++; 5004 } 5005 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5006 5007 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5008 } 5009 /* recvs and sends of i-array are completed */ 5010 i = nrecvs; 5011 while (i--) { 5012 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5013 } 5014 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5015 ierr = PetscFree(svalues);CHKERRQ(ierr); 5016 5017 /* allocate buffers for sending j and a arrays */ 5018 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 5019 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 5020 5021 /* create i-array of B_oth */ 5022 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 5023 5024 b_othi[0] = 0; 5025 len = 0; /* total length of j or a array to be received */ 5026 k = 0; 5027 for (i=0; i<nrecvs; i++) { 5028 rowlen = rvalues + rstarts[i]*rbs; 5029 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 5030 for (j=0; j<nrows; j++) { 5031 b_othi[k+1] = b_othi[k] + rowlen[j]; 5032 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 5033 k++; 5034 } 5035 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5036 } 5037 ierr = PetscFree(rvalues);CHKERRQ(ierr); 5038 5039 /* allocate space for j and a arrrays of B_oth */ 5040 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 5041 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 5042 5043 /* j-array */ 5044 /*---------*/ 5045 /* post receives of j-array */ 5046 for (i=0; i<nrecvs; i++) { 5047 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5048 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5049 } 5050 5051 /* pack the outgoing message j-array */ 5052 k = 0; 5053 for (i=0; i<nsends; i++) { 5054 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5055 bufJ = bufj+sstartsj[i]; 5056 for (j=0; j<nrows; j++) { 5057 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5058 for (ll=0; ll<sbs; ll++) { 5059 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5060 for (l=0; l<ncols; l++) { 5061 *bufJ++ = cols[l]; 5062 } 5063 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5064 } 5065 } 5066 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5067 } 5068 5069 /* recvs and sends of j-array are completed */ 5070 i = nrecvs; 5071 while (i--) { 5072 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5073 } 5074 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5075 } else if (scall == MAT_REUSE_MATRIX) { 5076 sstartsj = *startsj_s; 5077 rstartsj = *startsj_r; 5078 bufa = *bufa_ptr; 5079 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5080 b_otha = b_oth->a; 5081 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5082 5083 /* a-array */ 5084 /*---------*/ 5085 /* post receives of a-array */ 5086 for (i=0; i<nrecvs; i++) { 5087 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5088 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5089 } 5090 5091 /* pack the outgoing message a-array */ 5092 k = 0; 5093 for (i=0; i<nsends; i++) { 5094 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5095 bufA = bufa+sstartsj[i]; 5096 for (j=0; j<nrows; j++) { 5097 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5098 for (ll=0; ll<sbs; ll++) { 5099 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5100 for (l=0; l<ncols; l++) { 5101 *bufA++ = vals[l]; 5102 } 5103 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5104 } 5105 } 5106 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5107 } 5108 /* recvs and sends of a-array are completed */ 5109 i = nrecvs; 5110 while (i--) { 5111 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5112 } 5113 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5114 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5115 5116 if (scall == MAT_INITIAL_MATRIX) { 5117 /* put together the new matrix */ 5118 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5119 5120 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5121 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5122 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5123 b_oth->free_a = PETSC_TRUE; 5124 b_oth->free_ij = PETSC_TRUE; 5125 b_oth->nonew = 0; 5126 5127 ierr = PetscFree(bufj);CHKERRQ(ierr); 5128 if (!startsj_s || !bufa_ptr) { 5129 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5130 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5131 } else { 5132 *startsj_s = sstartsj; 5133 *startsj_r = rstartsj; 5134 *bufa_ptr = bufa; 5135 } 5136 } 5137 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5138 PetscFunctionReturn(0); 5139 } 5140 5141 /*@C 5142 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5143 5144 Not Collective 5145 5146 Input Parameters: 5147 . A - The matrix in mpiaij format 5148 5149 Output Parameter: 5150 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5151 . colmap - A map from global column index to local index into lvec 5152 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5153 5154 Level: developer 5155 5156 @*/ 5157 #if defined(PETSC_USE_CTABLE) 5158 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5159 #else 5160 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5161 #endif 5162 { 5163 Mat_MPIAIJ *a; 5164 5165 PetscFunctionBegin; 5166 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5167 PetscValidPointer(lvec, 2); 5168 PetscValidPointer(colmap, 3); 5169 PetscValidPointer(multScatter, 4); 5170 a = (Mat_MPIAIJ*) A->data; 5171 if (lvec) *lvec = a->lvec; 5172 if (colmap) *colmap = a->colmap; 5173 if (multScatter) *multScatter = a->Mvctx; 5174 PetscFunctionReturn(0); 5175 } 5176 5177 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5178 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5179 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5180 #if defined(PETSC_HAVE_ELEMENTAL) 5181 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5182 #endif 5183 #if defined(PETSC_HAVE_HYPRE) 5184 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5185 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5186 #endif 5187 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5188 5189 /* 5190 Computes (B'*A')' since computing B*A directly is untenable 5191 5192 n p p 5193 ( ) ( ) ( ) 5194 m ( A ) * n ( B ) = m ( C ) 5195 ( ) ( ) ( ) 5196 5197 */ 5198 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5199 { 5200 PetscErrorCode ierr; 5201 Mat At,Bt,Ct; 5202 5203 PetscFunctionBegin; 5204 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5205 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5206 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5207 ierr = MatDestroy(&At);CHKERRQ(ierr); 5208 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5209 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5210 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5211 PetscFunctionReturn(0); 5212 } 5213 5214 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5215 { 5216 PetscErrorCode ierr; 5217 PetscInt m=A->rmap->n,n=B->cmap->n; 5218 Mat Cmat; 5219 5220 PetscFunctionBegin; 5221 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); 5222 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5223 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5224 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5225 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5226 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5227 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5228 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5229 5230 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5231 5232 *C = Cmat; 5233 PetscFunctionReturn(0); 5234 } 5235 5236 /* ----------------------------------------------------------------*/ 5237 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5238 { 5239 PetscErrorCode ierr; 5240 5241 PetscFunctionBegin; 5242 if (scall == MAT_INITIAL_MATRIX) { 5243 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5244 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5245 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5246 } 5247 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5248 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5249 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5250 PetscFunctionReturn(0); 5251 } 5252 5253 /*MC 5254 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5255 5256 Options Database Keys: 5257 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5258 5259 Level: beginner 5260 5261 .seealso: MatCreateAIJ() 5262 M*/ 5263 5264 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5265 { 5266 Mat_MPIAIJ *b; 5267 PetscErrorCode ierr; 5268 PetscMPIInt size; 5269 5270 PetscFunctionBegin; 5271 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5272 5273 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5274 B->data = (void*)b; 5275 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5276 B->assembled = PETSC_FALSE; 5277 B->insertmode = NOT_SET_VALUES; 5278 b->size = size; 5279 5280 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5281 5282 /* build cache for off array entries formed */ 5283 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5284 5285 b->donotstash = PETSC_FALSE; 5286 b->colmap = 0; 5287 b->garray = 0; 5288 b->roworiented = PETSC_TRUE; 5289 5290 /* stuff used for matrix vector multiply */ 5291 b->lvec = NULL; 5292 b->Mvctx = NULL; 5293 5294 /* stuff for MatGetRow() */ 5295 b->rowindices = 0; 5296 b->rowvalues = 0; 5297 b->getrowactive = PETSC_FALSE; 5298 5299 /* flexible pointer used in CUSP/CUSPARSE classes */ 5300 b->spptr = NULL; 5301 5302 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5303 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5304 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5305 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5306 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5307 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5308 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5309 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5310 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5311 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5312 #if defined(PETSC_HAVE_ELEMENTAL) 5313 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5314 #endif 5315 #if defined(PETSC_HAVE_HYPRE) 5316 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5317 #endif 5318 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5319 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5320 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5321 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5322 #if defined(PETSC_HAVE_HYPRE) 5323 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5324 #endif 5325 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5326 PetscFunctionReturn(0); 5327 } 5328 5329 /*@C 5330 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5331 and "off-diagonal" part of the matrix in CSR format. 5332 5333 Collective on MPI_Comm 5334 5335 Input Parameters: 5336 + comm - MPI communicator 5337 . m - number of local rows (Cannot be PETSC_DECIDE) 5338 . n - This value should be the same as the local size used in creating the 5339 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5340 calculated if N is given) For square matrices n is almost always m. 5341 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5342 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5343 . i - row indices for "diagonal" portion of matrix 5344 . j - column indices 5345 . a - matrix values 5346 . oi - row indices for "off-diagonal" portion of matrix 5347 . oj - column indices 5348 - oa - matrix values 5349 5350 Output Parameter: 5351 . mat - the matrix 5352 5353 Level: advanced 5354 5355 Notes: 5356 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5357 must free the arrays once the matrix has been destroyed and not before. 5358 5359 The i and j indices are 0 based 5360 5361 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5362 5363 This sets local rows and cannot be used to set off-processor values. 5364 5365 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5366 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5367 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5368 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5369 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5370 communication if it is known that only local entries will be set. 5371 5372 .keywords: matrix, aij, compressed row, sparse, parallel 5373 5374 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5375 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5376 @*/ 5377 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) 5378 { 5379 PetscErrorCode ierr; 5380 Mat_MPIAIJ *maij; 5381 5382 PetscFunctionBegin; 5383 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5384 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5385 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5386 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5387 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5388 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5389 maij = (Mat_MPIAIJ*) (*mat)->data; 5390 5391 (*mat)->preallocated = PETSC_TRUE; 5392 5393 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5394 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5395 5396 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5397 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5398 5399 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5400 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5401 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5402 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5403 5404 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5405 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5406 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5407 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5408 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5409 PetscFunctionReturn(0); 5410 } 5411 5412 /* 5413 Special version for direct calls from Fortran 5414 */ 5415 #include <petsc/private/fortranimpl.h> 5416 5417 /* Change these macros so can be used in void function */ 5418 #undef CHKERRQ 5419 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5420 #undef SETERRQ2 5421 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5422 #undef SETERRQ3 5423 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5424 #undef SETERRQ 5425 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5426 5427 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5428 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5429 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5430 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5431 #else 5432 #endif 5433 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) 5434 { 5435 Mat mat = *mmat; 5436 PetscInt m = *mm, n = *mn; 5437 InsertMode addv = *maddv; 5438 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5439 PetscScalar value; 5440 PetscErrorCode ierr; 5441 5442 MatCheckPreallocated(mat,1); 5443 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5444 5445 #if defined(PETSC_USE_DEBUG) 5446 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5447 #endif 5448 { 5449 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5450 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5451 PetscBool roworiented = aij->roworiented; 5452 5453 /* Some Variables required in the macro */ 5454 Mat A = aij->A; 5455 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5456 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5457 MatScalar *aa = a->a; 5458 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5459 Mat B = aij->B; 5460 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5461 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5462 MatScalar *ba = b->a; 5463 5464 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5465 PetscInt nonew = a->nonew; 5466 MatScalar *ap1,*ap2; 5467 5468 PetscFunctionBegin; 5469 for (i=0; i<m; i++) { 5470 if (im[i] < 0) continue; 5471 #if defined(PETSC_USE_DEBUG) 5472 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); 5473 #endif 5474 if (im[i] >= rstart && im[i] < rend) { 5475 row = im[i] - rstart; 5476 lastcol1 = -1; 5477 rp1 = aj + ai[row]; 5478 ap1 = aa + ai[row]; 5479 rmax1 = aimax[row]; 5480 nrow1 = ailen[row]; 5481 low1 = 0; 5482 high1 = nrow1; 5483 lastcol2 = -1; 5484 rp2 = bj + bi[row]; 5485 ap2 = ba + bi[row]; 5486 rmax2 = bimax[row]; 5487 nrow2 = bilen[row]; 5488 low2 = 0; 5489 high2 = nrow2; 5490 5491 for (j=0; j<n; j++) { 5492 if (roworiented) value = v[i*n+j]; 5493 else value = v[i+j*m]; 5494 if (in[j] >= cstart && in[j] < cend) { 5495 col = in[j] - cstart; 5496 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5497 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5498 } else if (in[j] < 0) continue; 5499 #if defined(PETSC_USE_DEBUG) 5500 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); 5501 #endif 5502 else { 5503 if (mat->was_assembled) { 5504 if (!aij->colmap) { 5505 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5506 } 5507 #if defined(PETSC_USE_CTABLE) 5508 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5509 col--; 5510 #else 5511 col = aij->colmap[in[j]] - 1; 5512 #endif 5513 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5514 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5515 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5516 col = in[j]; 5517 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5518 B = aij->B; 5519 b = (Mat_SeqAIJ*)B->data; 5520 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5521 rp2 = bj + bi[row]; 5522 ap2 = ba + bi[row]; 5523 rmax2 = bimax[row]; 5524 nrow2 = bilen[row]; 5525 low2 = 0; 5526 high2 = nrow2; 5527 bm = aij->B->rmap->n; 5528 ba = b->a; 5529 } 5530 } else col = in[j]; 5531 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5532 } 5533 } 5534 } else if (!aij->donotstash) { 5535 if (roworiented) { 5536 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5537 } else { 5538 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5539 } 5540 } 5541 } 5542 } 5543 PetscFunctionReturnVoid(); 5544 } 5545 5546