1 2 3 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 4 #include <petsc/private/vecimpl.h> 5 #include <petsc/private/isimpl.h> 6 #include <petscblaslapack.h> 7 #include <petscsf.h> 8 9 /*MC 10 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 11 12 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 13 and MATMPIAIJ otherwise. As a result, for single process communicators, 14 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 15 for communicators controlling multiple processes. It is recommended that you call both of 16 the above preallocation routines for simplicity. 17 18 Options Database Keys: 19 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 20 21 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 22 enough exist. 23 24 Level: beginner 25 26 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ 27 M*/ 28 29 /*MC 30 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 31 32 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 33 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 34 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 35 for communicators controlling multiple processes. It is recommended that you call both of 36 the above preallocation routines for simplicity. 37 38 Options Database Keys: 39 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 40 41 Level: beginner 42 43 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 44 M*/ 45 46 PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 51 PetscFunctionBegin; 52 if (mat->A) { 53 ierr = MatSetBlockSizes(mat->A,rbs,cbs);CHKERRQ(ierr); 54 ierr = MatSetBlockSizes(mat->B,rbs,1);CHKERRQ(ierr); 55 } 56 PetscFunctionReturn(0); 57 } 58 59 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 60 { 61 PetscErrorCode ierr; 62 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 63 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 64 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 65 const PetscInt *ia,*ib; 66 const MatScalar *aa,*bb; 67 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 68 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 69 70 PetscFunctionBegin; 71 *keptrows = 0; 72 ia = a->i; 73 ib = b->i; 74 for (i=0; i<m; i++) { 75 na = ia[i+1] - ia[i]; 76 nb = ib[i+1] - ib[i]; 77 if (!na && !nb) { 78 cnt++; 79 goto ok1; 80 } 81 aa = a->a + ia[i]; 82 for (j=0; j<na; j++) { 83 if (aa[j] != 0.0) goto ok1; 84 } 85 bb = b->a + ib[i]; 86 for (j=0; j <nb; j++) { 87 if (bb[j] != 0.0) goto ok1; 88 } 89 cnt++; 90 ok1:; 91 } 92 ierr = MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 93 if (!n0rows) PetscFunctionReturn(0); 94 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 95 cnt = 0; 96 for (i=0; i<m; i++) { 97 na = ia[i+1] - ia[i]; 98 nb = ib[i+1] - ib[i]; 99 if (!na && !nb) continue; 100 aa = a->a + ia[i]; 101 for (j=0; j<na;j++) { 102 if (aa[j] != 0.0) { 103 rows[cnt++] = rstart + i; 104 goto ok2; 105 } 106 } 107 bb = b->a + ib[i]; 108 for (j=0; j<nb; j++) { 109 if (bb[j] != 0.0) { 110 rows[cnt++] = rstart + i; 111 goto ok2; 112 } 113 } 114 ok2:; 115 } 116 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 117 PetscFunctionReturn(0); 118 } 119 120 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 121 { 122 PetscErrorCode ierr; 123 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 124 125 PetscFunctionBegin; 126 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 127 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 128 } else { 129 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 130 } 131 PetscFunctionReturn(0); 132 } 133 134 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 135 { 136 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 137 PetscErrorCode ierr; 138 PetscInt i,rstart,nrows,*rows; 139 140 PetscFunctionBegin; 141 *zrows = NULL; 142 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 143 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 144 for (i=0; i<nrows; i++) rows[i] += rstart; 145 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 146 PetscFunctionReturn(0); 147 } 148 149 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 150 { 151 PetscErrorCode ierr; 152 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 153 PetscInt i,n,*garray = aij->garray; 154 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 155 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 156 PetscReal *work; 157 158 PetscFunctionBegin; 159 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 160 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 161 if (type == NORM_2) { 162 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 163 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 164 } 165 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 166 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 167 } 168 } else if (type == NORM_1) { 169 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 170 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 171 } 172 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 173 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 174 } 175 } else if (type == NORM_INFINITY) { 176 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 177 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 178 } 179 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 180 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 181 } 182 183 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 184 if (type == NORM_INFINITY) { 185 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 186 } else { 187 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 188 } 189 ierr = PetscFree(work);CHKERRQ(ierr); 190 if (type == NORM_2) { 191 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 192 } 193 PetscFunctionReturn(0); 194 } 195 196 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 197 { 198 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 199 IS sis,gis; 200 PetscErrorCode ierr; 201 const PetscInt *isis,*igis; 202 PetscInt n,*iis,nsis,ngis,rstart,i; 203 204 PetscFunctionBegin; 205 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 206 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 207 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 208 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 209 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 210 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 211 212 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 213 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 215 n = ngis + nsis; 216 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 217 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 218 for (i=0; i<n; i++) iis[i] += rstart; 219 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 220 221 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 222 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 223 ierr = ISDestroy(&sis);CHKERRQ(ierr); 224 ierr = ISDestroy(&gis);CHKERRQ(ierr); 225 PetscFunctionReturn(0); 226 } 227 228 /* 229 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 230 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 231 232 Only for square matrices 233 234 Used by a preconditioner, hence PETSC_EXTERN 235 */ 236 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 237 { 238 PetscMPIInt rank,size; 239 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 240 PetscErrorCode ierr; 241 Mat mat; 242 Mat_SeqAIJ *gmata; 243 PetscMPIInt tag; 244 MPI_Status status; 245 PetscBool aij; 246 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 247 248 PetscFunctionBegin; 249 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 250 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 251 if (!rank) { 252 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 253 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 254 } 255 if (reuse == MAT_INITIAL_MATRIX) { 256 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 257 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 258 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 259 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 260 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 261 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 262 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 263 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 264 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 265 266 rowners[0] = 0; 267 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 268 rstart = rowners[rank]; 269 rend = rowners[rank+1]; 270 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 271 if (!rank) { 272 gmata = (Mat_SeqAIJ*) gmat->data; 273 /* send row lengths to all processors */ 274 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 275 for (i=1; i<size; i++) { 276 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 277 } 278 /* determine number diagonal and off-diagonal counts */ 279 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 280 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 281 jj = 0; 282 for (i=0; i<m; i++) { 283 for (j=0; j<dlens[i]; j++) { 284 if (gmata->j[jj] < rstart) ld[i]++; 285 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 286 jj++; 287 } 288 } 289 /* send column indices to other processes */ 290 for (i=1; i<size; i++) { 291 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 292 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 } 295 296 /* send numerical values to other processes */ 297 for (i=1; i<size; i++) { 298 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 299 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 300 } 301 gmataa = gmata->a; 302 gmataj = gmata->j; 303 304 } else { 305 /* receive row lengths */ 306 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 307 /* receive column indices */ 308 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 309 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 310 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 311 /* determine number diagonal and off-diagonal counts */ 312 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 313 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 314 jj = 0; 315 for (i=0; i<m; i++) { 316 for (j=0; j<dlens[i]; j++) { 317 if (gmataj[jj] < rstart) ld[i]++; 318 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 319 jj++; 320 } 321 } 322 /* receive numerical values */ 323 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 324 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 325 } 326 /* set preallocation */ 327 for (i=0; i<m; i++) { 328 dlens[i] -= olens[i]; 329 } 330 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 331 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 332 333 for (i=0; i<m; i++) { 334 dlens[i] += olens[i]; 335 } 336 cnt = 0; 337 for (i=0; i<m; i++) { 338 row = rstart + i; 339 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 340 cnt += dlens[i]; 341 } 342 if (rank) { 343 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 344 } 345 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 346 ierr = PetscFree(rowners);CHKERRQ(ierr); 347 348 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 349 350 *inmat = mat; 351 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 352 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 353 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 354 mat = *inmat; 355 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 356 if (!rank) { 357 /* send numerical values to other processes */ 358 gmata = (Mat_SeqAIJ*) gmat->data; 359 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 360 gmataa = gmata->a; 361 for (i=1; i<size; i++) { 362 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 363 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 364 } 365 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 366 } else { 367 /* receive numerical values from process 0*/ 368 nz = Ad->nz + Ao->nz; 369 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 370 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 371 } 372 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 373 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 374 ad = Ad->a; 375 ao = Ao->a; 376 if (mat->rmap->n) { 377 i = 0; 378 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 379 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 380 } 381 for (i=1; i<mat->rmap->n; i++) { 382 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 383 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 384 } 385 i--; 386 if (mat->rmap->n) { 387 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 388 } 389 if (rank) { 390 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 391 } 392 } 393 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 PetscFunctionReturn(0); 396 } 397 398 /* 399 Local utility routine that creates a mapping from the global column 400 number to the local number in the off-diagonal part of the local 401 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 402 a slightly higher hash table cost; without it it is not scalable (each processor 403 has an order N integer array but is fast to acess. 404 */ 405 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 406 { 407 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 408 PetscErrorCode ierr; 409 PetscInt n = aij->B->cmap->n,i; 410 411 PetscFunctionBegin; 412 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 413 #if defined(PETSC_USE_CTABLE) 414 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 415 for (i=0; i<n; i++) { 416 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 417 } 418 #else 419 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 420 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 421 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 422 #endif 423 PetscFunctionReturn(0); 424 } 425 426 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 427 { \ 428 if (col <= lastcol1) low1 = 0; \ 429 else high1 = nrow1; \ 430 lastcol1 = col;\ 431 while (high1-low1 > 5) { \ 432 t = (low1+high1)/2; \ 433 if (rp1[t] > col) high1 = t; \ 434 else low1 = t; \ 435 } \ 436 for (_i=low1; _i<high1; _i++) { \ 437 if (rp1[_i] > col) break; \ 438 if (rp1[_i] == col) { \ 439 if (addv == ADD_VALUES) ap1[_i] += value; \ 440 else ap1[_i] = value; \ 441 goto a_noinsert; \ 442 } \ 443 } \ 444 if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 445 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 446 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 447 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 448 N = nrow1++ - 1; a->nz++; high1++; \ 449 /* shift up all the later entries in this row */ \ 450 for (ii=N; ii>=_i; ii--) { \ 451 rp1[ii+1] = rp1[ii]; \ 452 ap1[ii+1] = ap1[ii]; \ 453 } \ 454 rp1[_i] = col; \ 455 ap1[_i] = value; \ 456 A->nonzerostate++;\ 457 a_noinsert: ; \ 458 ailen[row] = nrow1; \ 459 } 460 461 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 462 { \ 463 if (col <= lastcol2) low2 = 0; \ 464 else high2 = nrow2; \ 465 lastcol2 = col; \ 466 while (high2-low2 > 5) { \ 467 t = (low2+high2)/2; \ 468 if (rp2[t] > col) high2 = t; \ 469 else low2 = t; \ 470 } \ 471 for (_i=low2; _i<high2; _i++) { \ 472 if (rp2[_i] > col) break; \ 473 if (rp2[_i] == col) { \ 474 if (addv == ADD_VALUES) ap2[_i] += value; \ 475 else ap2[_i] = value; \ 476 goto b_noinsert; \ 477 } \ 478 } \ 479 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 480 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 481 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 482 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 483 N = nrow2++ - 1; b->nz++; high2++; \ 484 /* shift up all the later entries in this row */ \ 485 for (ii=N; ii>=_i; ii--) { \ 486 rp2[ii+1] = rp2[ii]; \ 487 ap2[ii+1] = ap2[ii]; \ 488 } \ 489 rp2[_i] = col; \ 490 ap2[_i] = value; \ 491 B->nonzerostate++; \ 492 b_noinsert: ; \ 493 bilen[row] = nrow2; \ 494 } 495 496 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 497 { 498 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 499 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 500 PetscErrorCode ierr; 501 PetscInt l,*garray = mat->garray,diag; 502 503 PetscFunctionBegin; 504 /* code only works for square matrices A */ 505 506 /* find size of row to the left of the diagonal part */ 507 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 508 row = row - diag; 509 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 510 if (garray[b->j[b->i[row]+l]] > diag) break; 511 } 512 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 513 514 /* diagonal part */ 515 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 516 517 /* right of diagonal part */ 518 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 519 PetscFunctionReturn(0); 520 } 521 522 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 523 { 524 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 525 PetscScalar value; 526 PetscErrorCode ierr; 527 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 528 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 529 PetscBool roworiented = aij->roworiented; 530 531 /* Some Variables required in the macro */ 532 Mat A = aij->A; 533 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 534 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 535 MatScalar *aa = a->a; 536 PetscBool ignorezeroentries = a->ignorezeroentries; 537 Mat B = aij->B; 538 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 539 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 540 MatScalar *ba = b->a; 541 542 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 543 PetscInt nonew; 544 MatScalar *ap1,*ap2; 545 546 PetscFunctionBegin; 547 for (i=0; i<m; i++) { 548 if (im[i] < 0) continue; 549 #if defined(PETSC_USE_DEBUG) 550 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 551 #endif 552 if (im[i] >= rstart && im[i] < rend) { 553 row = im[i] - rstart; 554 lastcol1 = -1; 555 rp1 = aj + ai[row]; 556 ap1 = aa + ai[row]; 557 rmax1 = aimax[row]; 558 nrow1 = ailen[row]; 559 low1 = 0; 560 high1 = nrow1; 561 lastcol2 = -1; 562 rp2 = bj + bi[row]; 563 ap2 = ba + bi[row]; 564 rmax2 = bimax[row]; 565 nrow2 = bilen[row]; 566 low2 = 0; 567 high2 = nrow2; 568 569 for (j=0; j<n; j++) { 570 if (roworiented) value = v[i*n+j]; 571 else value = v[i+j*m]; 572 if (in[j] >= cstart && in[j] < cend) { 573 col = in[j] - cstart; 574 nonew = a->nonew; 575 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 576 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 577 } else if (in[j] < 0) continue; 578 #if defined(PETSC_USE_DEBUG) 579 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 580 #endif 581 else { 582 if (mat->was_assembled) { 583 if (!aij->colmap) { 584 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 585 } 586 #if defined(PETSC_USE_CTABLE) 587 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 588 col--; 589 #else 590 col = aij->colmap[in[j]] - 1; 591 #endif 592 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 593 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 594 col = in[j]; 595 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 596 B = aij->B; 597 b = (Mat_SeqAIJ*)B->data; 598 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 599 rp2 = bj + bi[row]; 600 ap2 = ba + bi[row]; 601 rmax2 = bimax[row]; 602 nrow2 = bilen[row]; 603 low2 = 0; 604 high2 = nrow2; 605 bm = aij->B->rmap->n; 606 ba = b->a; 607 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 608 } else col = in[j]; 609 nonew = b->nonew; 610 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 611 } 612 } 613 } else { 614 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 615 if (!aij->donotstash) { 616 mat->assembled = PETSC_FALSE; 617 if (roworiented) { 618 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 619 } else { 620 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } 622 } 623 } 624 } 625 PetscFunctionReturn(0); 626 } 627 628 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 629 { 630 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 631 PetscErrorCode ierr; 632 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 633 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 634 635 PetscFunctionBegin; 636 for (i=0; i<m; i++) { 637 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 638 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 639 if (idxm[i] >= rstart && idxm[i] < rend) { 640 row = idxm[i] - rstart; 641 for (j=0; j<n; j++) { 642 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 643 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 644 if (idxn[j] >= cstart && idxn[j] < cend) { 645 col = idxn[j] - cstart; 646 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 647 } else { 648 if (!aij->colmap) { 649 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 650 } 651 #if defined(PETSC_USE_CTABLE) 652 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 653 col--; 654 #else 655 col = aij->colmap[idxn[j]] - 1; 656 #endif 657 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 658 else { 659 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 660 } 661 } 662 } 663 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 664 } 665 PetscFunctionReturn(0); 666 } 667 668 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 669 670 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 671 { 672 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 673 PetscErrorCode ierr; 674 PetscInt nstash,reallocs; 675 676 PetscFunctionBegin; 677 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 678 679 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 680 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 681 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 682 PetscFunctionReturn(0); 683 } 684 685 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 686 { 687 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 688 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 689 PetscErrorCode ierr; 690 PetscMPIInt n; 691 PetscInt i,j,rstart,ncols,flg; 692 PetscInt *row,*col; 693 PetscBool other_disassembled; 694 PetscScalar *val; 695 696 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 697 698 PetscFunctionBegin; 699 if (!aij->donotstash && !mat->nooffprocentries) { 700 while (1) { 701 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 702 if (!flg) break; 703 704 for (i=0; i<n; ) { 705 /* Now identify the consecutive vals belonging to the same row */ 706 for (j=i,rstart=row[j]; j<n; j++) { 707 if (row[j] != rstart) break; 708 } 709 if (j < n) ncols = j-i; 710 else ncols = n-i; 711 /* Now assemble all these values with a single function call */ 712 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 713 714 i = j; 715 } 716 } 717 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 718 } 719 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 720 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 721 722 /* determine if any processor has disassembled, if so we must 723 also disassemble ourselfs, in order that we may reassemble. */ 724 /* 725 if nonzero structure of submatrix B cannot change then we know that 726 no processor disassembled thus we can skip this stuff 727 */ 728 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 729 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 730 if (mat->was_assembled && !other_disassembled) { 731 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 732 } 733 } 734 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 735 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 736 } 737 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 738 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 739 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 740 741 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 742 743 aij->rowvalues = 0; 744 745 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 746 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 747 748 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 749 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 750 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 751 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 752 } 753 PetscFunctionReturn(0); 754 } 755 756 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 757 { 758 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 759 PetscErrorCode ierr; 760 761 PetscFunctionBegin; 762 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 763 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 764 PetscFunctionReturn(0); 765 } 766 767 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 768 { 769 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 770 PetscInt *lrows; 771 PetscInt r, len; 772 PetscErrorCode ierr; 773 774 PetscFunctionBegin; 775 /* get locally owned rows */ 776 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 777 /* fix right hand side if needed */ 778 if (x && b) { 779 const PetscScalar *xx; 780 PetscScalar *bb; 781 782 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 783 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 784 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 785 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 786 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 787 } 788 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 789 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 790 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 791 PetscBool cong; 792 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 793 if (cong) A->congruentlayouts = 1; 794 else A->congruentlayouts = 0; 795 } 796 if ((diag != 0.0) && A->congruentlayouts) { 797 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 798 } else if (diag != 0.0) { 799 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 800 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 801 for (r = 0; r < len; ++r) { 802 const PetscInt row = lrows[r] + A->rmap->rstart; 803 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 804 } 805 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 806 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 807 } else { 808 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 809 } 810 ierr = PetscFree(lrows);CHKERRQ(ierr); 811 812 /* only change matrix nonzero state if pattern was allowed to be changed */ 813 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 814 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 815 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 816 } 817 PetscFunctionReturn(0); 818 } 819 820 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 821 { 822 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 823 PetscErrorCode ierr; 824 PetscMPIInt n = A->rmap->n; 825 PetscInt i,j,r,m,p = 0,len = 0; 826 PetscInt *lrows,*owners = A->rmap->range; 827 PetscSFNode *rrows; 828 PetscSF sf; 829 const PetscScalar *xx; 830 PetscScalar *bb,*mask; 831 Vec xmask,lmask; 832 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 833 const PetscInt *aj, *ii,*ridx; 834 PetscScalar *aa; 835 836 PetscFunctionBegin; 837 /* Create SF where leaves are input rows and roots are owned rows */ 838 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 839 for (r = 0; r < n; ++r) lrows[r] = -1; 840 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 841 for (r = 0; r < N; ++r) { 842 const PetscInt idx = rows[r]; 843 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 844 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 845 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 846 } 847 rrows[r].rank = p; 848 rrows[r].index = rows[r] - owners[p]; 849 } 850 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 851 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 852 /* Collect flags for rows to be zeroed */ 853 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 854 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 855 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 856 /* Compress and put in row numbers */ 857 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 858 /* zero diagonal part of matrix */ 859 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 860 /* handle off diagonal part of matrix */ 861 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 862 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 863 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 864 for (i=0; i<len; i++) bb[lrows[i]] = 1; 865 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 866 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 867 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 868 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 869 if (x) { 870 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 871 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 872 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 873 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 874 } 875 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 876 /* remove zeroed rows of off diagonal matrix */ 877 ii = aij->i; 878 for (i=0; i<len; i++) { 879 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 880 } 881 /* loop over all elements of off process part of matrix zeroing removed columns*/ 882 if (aij->compressedrow.use) { 883 m = aij->compressedrow.nrows; 884 ii = aij->compressedrow.i; 885 ridx = aij->compressedrow.rindex; 886 for (i=0; i<m; i++) { 887 n = ii[i+1] - ii[i]; 888 aj = aij->j + ii[i]; 889 aa = aij->a + ii[i]; 890 891 for (j=0; j<n; j++) { 892 if (PetscAbsScalar(mask[*aj])) { 893 if (b) bb[*ridx] -= *aa*xx[*aj]; 894 *aa = 0.0; 895 } 896 aa++; 897 aj++; 898 } 899 ridx++; 900 } 901 } else { /* do not use compressed row format */ 902 m = l->B->rmap->n; 903 for (i=0; i<m; i++) { 904 n = ii[i+1] - ii[i]; 905 aj = aij->j + ii[i]; 906 aa = aij->a + ii[i]; 907 for (j=0; j<n; j++) { 908 if (PetscAbsScalar(mask[*aj])) { 909 if (b) bb[i] -= *aa*xx[*aj]; 910 *aa = 0.0; 911 } 912 aa++; 913 aj++; 914 } 915 } 916 } 917 if (x) { 918 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 919 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 920 } 921 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 922 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 923 ierr = PetscFree(lrows);CHKERRQ(ierr); 924 925 /* only change matrix nonzero state if pattern was allowed to be changed */ 926 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 927 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 928 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 929 } 930 PetscFunctionReturn(0); 931 } 932 933 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 934 { 935 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 936 PetscErrorCode ierr; 937 PetscInt nt; 938 939 PetscFunctionBegin; 940 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 941 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 942 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 943 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 944 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 946 PetscFunctionReturn(0); 947 } 948 949 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 950 { 951 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 952 PetscErrorCode ierr; 953 954 PetscFunctionBegin; 955 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 956 PetscFunctionReturn(0); 957 } 958 959 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 960 { 961 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 962 PetscErrorCode ierr; 963 964 PetscFunctionBegin; 965 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 966 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 967 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } 971 972 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 973 { 974 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 975 PetscErrorCode ierr; 976 PetscBool merged; 977 978 PetscFunctionBegin; 979 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 980 /* do nondiagonal part */ 981 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 982 if (!merged) { 983 /* send it on its way */ 984 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 985 /* do local part */ 986 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 987 /* receive remote parts: note this assumes the values are not actually */ 988 /* added in yy until the next line, */ 989 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 990 } else { 991 /* do local part */ 992 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 993 /* send it on its way */ 994 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 995 /* values actually were received in the Begin() but we need to call this nop */ 996 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 } 998 PetscFunctionReturn(0); 999 } 1000 1001 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1002 { 1003 MPI_Comm comm; 1004 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1005 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1006 IS Me,Notme; 1007 PetscErrorCode ierr; 1008 PetscInt M,N,first,last,*notme,i; 1009 PetscMPIInt size; 1010 1011 PetscFunctionBegin; 1012 /* Easy test: symmetric diagonal block */ 1013 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1014 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1015 if (!*f) PetscFunctionReturn(0); 1016 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1017 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1018 if (size == 1) PetscFunctionReturn(0); 1019 1020 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1021 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1022 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1023 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1024 for (i=0; i<first; i++) notme[i] = i; 1025 for (i=last; i<M; i++) notme[i-last+first] = i; 1026 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1027 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1028 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1029 Aoff = Aoffs[0]; 1030 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1031 Boff = Boffs[0]; 1032 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1033 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1034 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1035 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1036 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1037 ierr = PetscFree(notme);CHKERRQ(ierr); 1038 PetscFunctionReturn(0); 1039 } 1040 1041 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1042 { 1043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1044 PetscErrorCode ierr; 1045 1046 PetscFunctionBegin; 1047 /* do nondiagonal part */ 1048 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1049 /* send it on its way */ 1050 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1051 /* do local part */ 1052 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1053 /* receive remote parts */ 1054 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 /* 1059 This only works correctly for square matrices where the subblock A->A is the 1060 diagonal block 1061 */ 1062 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1063 { 1064 PetscErrorCode ierr; 1065 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1066 1067 PetscFunctionBegin; 1068 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1069 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1070 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1071 PetscFunctionReturn(0); 1072 } 1073 1074 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1075 { 1076 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1077 PetscErrorCode ierr; 1078 1079 PetscFunctionBegin; 1080 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1081 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1082 PetscFunctionReturn(0); 1083 } 1084 1085 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1086 { 1087 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 #if defined(PETSC_USE_LOG) 1092 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1093 #endif 1094 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1095 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1096 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1097 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1098 #if defined(PETSC_USE_CTABLE) 1099 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1100 #else 1101 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1102 #endif 1103 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1104 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1105 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1106 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1107 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1108 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1109 1110 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1118 #if defined(PETSC_HAVE_ELEMENTAL) 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1120 #endif 1121 #if defined(PETSC_HAVE_HYPRE) 1122 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1123 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1124 #endif 1125 PetscFunctionReturn(0); 1126 } 1127 1128 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1129 { 1130 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1131 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1132 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1133 PetscErrorCode ierr; 1134 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1135 int fd; 1136 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1137 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1138 PetscScalar *column_values; 1139 PetscInt message_count,flowcontrolcount; 1140 FILE *file; 1141 1142 PetscFunctionBegin; 1143 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1144 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1145 nz = A->nz + B->nz; 1146 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1147 if (!rank) { 1148 header[0] = MAT_FILE_CLASSID; 1149 header[1] = mat->rmap->N; 1150 header[2] = mat->cmap->N; 1151 1152 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1153 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1154 /* get largest number of rows any processor has */ 1155 rlen = mat->rmap->n; 1156 range = mat->rmap->range; 1157 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1158 } else { 1159 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1160 rlen = mat->rmap->n; 1161 } 1162 1163 /* load up the local row counts */ 1164 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1165 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1166 1167 /* store the row lengths to the file */ 1168 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1169 if (!rank) { 1170 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1171 for (i=1; i<size; i++) { 1172 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1173 rlen = range[i+1] - range[i]; 1174 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1175 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1176 } 1177 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1178 } else { 1179 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1180 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1181 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1182 } 1183 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1184 1185 /* load up the local column indices */ 1186 nzmax = nz; /* th processor needs space a largest processor needs */ 1187 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1188 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1189 cnt = 0; 1190 for (i=0; i<mat->rmap->n; i++) { 1191 for (j=B->i[i]; j<B->i[i+1]; j++) { 1192 if ((col = garray[B->j[j]]) > cstart) break; 1193 column_indices[cnt++] = col; 1194 } 1195 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1196 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1197 } 1198 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1199 1200 /* store the column indices to the file */ 1201 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1202 if (!rank) { 1203 MPI_Status status; 1204 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1205 for (i=1; i<size; i++) { 1206 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1207 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1208 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1209 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1210 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1211 } 1212 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1213 } else { 1214 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1215 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1216 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1217 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1218 } 1219 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1220 1221 /* load up the local column values */ 1222 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1223 cnt = 0; 1224 for (i=0; i<mat->rmap->n; i++) { 1225 for (j=B->i[i]; j<B->i[i+1]; j++) { 1226 if (garray[B->j[j]] > cstart) break; 1227 column_values[cnt++] = B->a[j]; 1228 } 1229 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1230 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1231 } 1232 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1233 1234 /* store the column values to the file */ 1235 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1236 if (!rank) { 1237 MPI_Status status; 1238 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1239 for (i=1; i<size; i++) { 1240 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1241 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1242 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1243 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1244 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1245 } 1246 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1247 } else { 1248 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1249 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1250 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1251 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1252 } 1253 ierr = PetscFree(column_values);CHKERRQ(ierr); 1254 1255 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1256 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1257 PetscFunctionReturn(0); 1258 } 1259 1260 #include <petscdraw.h> 1261 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1262 { 1263 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1264 PetscErrorCode ierr; 1265 PetscMPIInt rank = aij->rank,size = aij->size; 1266 PetscBool isdraw,iascii,isbinary; 1267 PetscViewer sviewer; 1268 PetscViewerFormat format; 1269 1270 PetscFunctionBegin; 1271 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1272 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1274 if (iascii) { 1275 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1276 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1277 MatInfo info; 1278 PetscBool inodes; 1279 1280 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1281 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1282 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1283 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1284 if (!inodes) { 1285 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1286 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1287 } else { 1288 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1289 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1290 } 1291 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1292 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1293 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1297 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1298 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1299 PetscFunctionReturn(0); 1300 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1301 PetscInt inodecount,inodelimit,*inodes; 1302 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1303 if (inodes) { 1304 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1305 } else { 1306 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1307 } 1308 PetscFunctionReturn(0); 1309 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1310 PetscFunctionReturn(0); 1311 } 1312 } else if (isbinary) { 1313 if (size == 1) { 1314 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1315 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1316 } else { 1317 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1318 } 1319 PetscFunctionReturn(0); 1320 } else if (isdraw) { 1321 PetscDraw draw; 1322 PetscBool isnull; 1323 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1324 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1325 if (isnull) PetscFunctionReturn(0); 1326 } 1327 1328 { 1329 /* assemble the entire matrix onto first processor. */ 1330 Mat A; 1331 Mat_SeqAIJ *Aloc; 1332 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1333 MatScalar *a; 1334 1335 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1336 if (!rank) { 1337 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1338 } else { 1339 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1340 } 1341 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1342 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1343 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1344 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1345 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1346 1347 /* copy over the A part */ 1348 Aloc = (Mat_SeqAIJ*)aij->A->data; 1349 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1350 row = mat->rmap->rstart; 1351 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1352 for (i=0; i<m; i++) { 1353 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1354 row++; 1355 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1356 } 1357 aj = Aloc->j; 1358 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1359 1360 /* copy over the B part */ 1361 Aloc = (Mat_SeqAIJ*)aij->B->data; 1362 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1363 row = mat->rmap->rstart; 1364 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1365 ct = cols; 1366 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1367 for (i=0; i<m; i++) { 1368 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1369 row++; 1370 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1371 } 1372 ierr = PetscFree(ct);CHKERRQ(ierr); 1373 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1374 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1375 /* 1376 Everyone has to call to draw the matrix since the graphics waits are 1377 synchronized across all processors that share the PetscDraw object 1378 */ 1379 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1380 if (!rank) { 1381 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1382 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1383 } 1384 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1385 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1386 ierr = MatDestroy(&A);CHKERRQ(ierr); 1387 } 1388 PetscFunctionReturn(0); 1389 } 1390 1391 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1392 { 1393 PetscErrorCode ierr; 1394 PetscBool iascii,isdraw,issocket,isbinary; 1395 1396 PetscFunctionBegin; 1397 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1398 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1401 if (iascii || isdraw || isbinary || issocket) { 1402 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1403 } 1404 PetscFunctionReturn(0); 1405 } 1406 1407 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1408 { 1409 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1410 PetscErrorCode ierr; 1411 Vec bb1 = 0; 1412 PetscBool hasop; 1413 1414 PetscFunctionBegin; 1415 if (flag == SOR_APPLY_UPPER) { 1416 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1417 PetscFunctionReturn(0); 1418 } 1419 1420 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1421 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1422 } 1423 1424 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1425 if (flag & SOR_ZERO_INITIAL_GUESS) { 1426 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1427 its--; 1428 } 1429 1430 while (its--) { 1431 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1432 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1433 1434 /* update rhs: bb1 = bb - B*x */ 1435 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1436 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1437 1438 /* local sweep */ 1439 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1440 } 1441 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1442 if (flag & SOR_ZERO_INITIAL_GUESS) { 1443 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1444 its--; 1445 } 1446 while (its--) { 1447 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1448 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1449 1450 /* update rhs: bb1 = bb - B*x */ 1451 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1452 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1453 1454 /* local sweep */ 1455 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1456 } 1457 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1458 if (flag & SOR_ZERO_INITIAL_GUESS) { 1459 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1460 its--; 1461 } 1462 while (its--) { 1463 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1464 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1465 1466 /* update rhs: bb1 = bb - B*x */ 1467 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1468 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1469 1470 /* local sweep */ 1471 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1472 } 1473 } else if (flag & SOR_EISENSTAT) { 1474 Vec xx1; 1475 1476 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1477 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1478 1479 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1480 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1481 if (!mat->diag) { 1482 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1483 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1484 } 1485 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1486 if (hasop) { 1487 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1488 } else { 1489 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1490 } 1491 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1492 1493 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1494 1495 /* local sweep */ 1496 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1497 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1498 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1499 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1500 1501 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1502 1503 matin->factorerrortype = mat->A->factorerrortype; 1504 PetscFunctionReturn(0); 1505 } 1506 1507 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1508 { 1509 Mat aA,aB,Aperm; 1510 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1511 PetscScalar *aa,*ba; 1512 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1513 PetscSF rowsf,sf; 1514 IS parcolp = NULL; 1515 PetscBool done; 1516 PetscErrorCode ierr; 1517 1518 PetscFunctionBegin; 1519 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1520 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1521 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1522 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1523 1524 /* Invert row permutation to find out where my rows should go */ 1525 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1526 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1527 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1528 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1529 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1530 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1531 1532 /* Invert column permutation to find out where my columns should go */ 1533 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1534 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1535 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1536 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1537 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1538 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1539 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1540 1541 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1542 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1543 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1544 1545 /* Find out where my gcols should go */ 1546 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1547 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1548 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1549 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1550 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1551 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1552 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1553 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1554 1555 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1556 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1557 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1558 for (i=0; i<m; i++) { 1559 PetscInt row = rdest[i],rowner; 1560 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1561 for (j=ai[i]; j<ai[i+1]; j++) { 1562 PetscInt cowner,col = cdest[aj[j]]; 1563 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1564 if (rowner == cowner) dnnz[i]++; 1565 else onnz[i]++; 1566 } 1567 for (j=bi[i]; j<bi[i+1]; j++) { 1568 PetscInt cowner,col = gcdest[bj[j]]; 1569 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1570 if (rowner == cowner) dnnz[i]++; 1571 else onnz[i]++; 1572 } 1573 } 1574 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1575 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1578 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1579 1580 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1581 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1582 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1583 for (i=0; i<m; i++) { 1584 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1585 PetscInt j0,rowlen; 1586 rowlen = ai[i+1] - ai[i]; 1587 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1588 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1589 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1590 } 1591 rowlen = bi[i+1] - bi[i]; 1592 for (j0=j=0; j<rowlen; j0=j) { 1593 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1594 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1595 } 1596 } 1597 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1598 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1599 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1600 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1601 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1602 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1603 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1604 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1605 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1606 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1607 *B = Aperm; 1608 PetscFunctionReturn(0); 1609 } 1610 1611 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1612 { 1613 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1614 PetscErrorCode ierr; 1615 1616 PetscFunctionBegin; 1617 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1618 if (ghosts) *ghosts = aij->garray; 1619 PetscFunctionReturn(0); 1620 } 1621 1622 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1623 { 1624 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1625 Mat A = mat->A,B = mat->B; 1626 PetscErrorCode ierr; 1627 PetscReal isend[5],irecv[5]; 1628 1629 PetscFunctionBegin; 1630 info->block_size = 1.0; 1631 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1632 1633 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1634 isend[3] = info->memory; isend[4] = info->mallocs; 1635 1636 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1637 1638 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1639 isend[3] += info->memory; isend[4] += info->mallocs; 1640 if (flag == MAT_LOCAL) { 1641 info->nz_used = isend[0]; 1642 info->nz_allocated = isend[1]; 1643 info->nz_unneeded = isend[2]; 1644 info->memory = isend[3]; 1645 info->mallocs = isend[4]; 1646 } else if (flag == MAT_GLOBAL_MAX) { 1647 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1648 1649 info->nz_used = irecv[0]; 1650 info->nz_allocated = irecv[1]; 1651 info->nz_unneeded = irecv[2]; 1652 info->memory = irecv[3]; 1653 info->mallocs = irecv[4]; 1654 } else if (flag == MAT_GLOBAL_SUM) { 1655 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1656 1657 info->nz_used = irecv[0]; 1658 info->nz_allocated = irecv[1]; 1659 info->nz_unneeded = irecv[2]; 1660 info->memory = irecv[3]; 1661 info->mallocs = irecv[4]; 1662 } 1663 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1664 info->fill_ratio_needed = 0; 1665 info->factor_mallocs = 0; 1666 PetscFunctionReturn(0); 1667 } 1668 1669 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1670 { 1671 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1672 PetscErrorCode ierr; 1673 1674 PetscFunctionBegin; 1675 switch (op) { 1676 case MAT_NEW_NONZERO_LOCATIONS: 1677 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1678 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1679 case MAT_KEEP_NONZERO_PATTERN: 1680 case MAT_NEW_NONZERO_LOCATION_ERR: 1681 case MAT_USE_INODES: 1682 case MAT_IGNORE_ZERO_ENTRIES: 1683 MatCheckPreallocated(A,1); 1684 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1685 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1686 break; 1687 case MAT_ROW_ORIENTED: 1688 MatCheckPreallocated(A,1); 1689 a->roworiented = flg; 1690 1691 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1692 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1693 break; 1694 case MAT_NEW_DIAGONALS: 1695 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1696 break; 1697 case MAT_IGNORE_OFF_PROC_ENTRIES: 1698 a->donotstash = flg; 1699 break; 1700 case MAT_SPD: 1701 A->spd_set = PETSC_TRUE; 1702 A->spd = flg; 1703 if (flg) { 1704 A->symmetric = PETSC_TRUE; 1705 A->structurally_symmetric = PETSC_TRUE; 1706 A->symmetric_set = PETSC_TRUE; 1707 A->structurally_symmetric_set = PETSC_TRUE; 1708 } 1709 break; 1710 case MAT_SYMMETRIC: 1711 MatCheckPreallocated(A,1); 1712 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1713 break; 1714 case MAT_STRUCTURALLY_SYMMETRIC: 1715 MatCheckPreallocated(A,1); 1716 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1717 break; 1718 case MAT_HERMITIAN: 1719 MatCheckPreallocated(A,1); 1720 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1721 break; 1722 case MAT_SYMMETRY_ETERNAL: 1723 MatCheckPreallocated(A,1); 1724 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1725 break; 1726 case MAT_SUBMAT_SINGLEIS: 1727 A->submat_singleis = flg; 1728 break; 1729 default: 1730 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1731 } 1732 PetscFunctionReturn(0); 1733 } 1734 1735 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1736 { 1737 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1738 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1739 PetscErrorCode ierr; 1740 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1741 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1742 PetscInt *cmap,*idx_p; 1743 1744 PetscFunctionBegin; 1745 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1746 mat->getrowactive = PETSC_TRUE; 1747 1748 if (!mat->rowvalues && (idx || v)) { 1749 /* 1750 allocate enough space to hold information from the longest row. 1751 */ 1752 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1753 PetscInt max = 1,tmp; 1754 for (i=0; i<matin->rmap->n; i++) { 1755 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1756 if (max < tmp) max = tmp; 1757 } 1758 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1759 } 1760 1761 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1762 lrow = row - rstart; 1763 1764 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1765 if (!v) {pvA = 0; pvB = 0;} 1766 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1767 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1768 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1769 nztot = nzA + nzB; 1770 1771 cmap = mat->garray; 1772 if (v || idx) { 1773 if (nztot) { 1774 /* Sort by increasing column numbers, assuming A and B already sorted */ 1775 PetscInt imark = -1; 1776 if (v) { 1777 *v = v_p = mat->rowvalues; 1778 for (i=0; i<nzB; i++) { 1779 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1780 else break; 1781 } 1782 imark = i; 1783 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1784 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1785 } 1786 if (idx) { 1787 *idx = idx_p = mat->rowindices; 1788 if (imark > -1) { 1789 for (i=0; i<imark; i++) { 1790 idx_p[i] = cmap[cworkB[i]]; 1791 } 1792 } else { 1793 for (i=0; i<nzB; i++) { 1794 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1795 else break; 1796 } 1797 imark = i; 1798 } 1799 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1800 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1801 } 1802 } else { 1803 if (idx) *idx = 0; 1804 if (v) *v = 0; 1805 } 1806 } 1807 *nz = nztot; 1808 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1809 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1810 PetscFunctionReturn(0); 1811 } 1812 1813 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1814 { 1815 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1816 1817 PetscFunctionBegin; 1818 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1819 aij->getrowactive = PETSC_FALSE; 1820 PetscFunctionReturn(0); 1821 } 1822 1823 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1824 { 1825 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1826 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1827 PetscErrorCode ierr; 1828 PetscInt i,j,cstart = mat->cmap->rstart; 1829 PetscReal sum = 0.0; 1830 MatScalar *v; 1831 1832 PetscFunctionBegin; 1833 if (aij->size == 1) { 1834 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1835 } else { 1836 if (type == NORM_FROBENIUS) { 1837 v = amat->a; 1838 for (i=0; i<amat->nz; i++) { 1839 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1840 } 1841 v = bmat->a; 1842 for (i=0; i<bmat->nz; i++) { 1843 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1844 } 1845 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1846 *norm = PetscSqrtReal(*norm); 1847 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1848 } else if (type == NORM_1) { /* max column norm */ 1849 PetscReal *tmp,*tmp2; 1850 PetscInt *jj,*garray = aij->garray; 1851 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1852 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1853 *norm = 0.0; 1854 v = amat->a; jj = amat->j; 1855 for (j=0; j<amat->nz; j++) { 1856 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1857 } 1858 v = bmat->a; jj = bmat->j; 1859 for (j=0; j<bmat->nz; j++) { 1860 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1861 } 1862 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1863 for (j=0; j<mat->cmap->N; j++) { 1864 if (tmp2[j] > *norm) *norm = tmp2[j]; 1865 } 1866 ierr = PetscFree(tmp);CHKERRQ(ierr); 1867 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1868 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1869 } else if (type == NORM_INFINITY) { /* max row norm */ 1870 PetscReal ntemp = 0.0; 1871 for (j=0; j<aij->A->rmap->n; j++) { 1872 v = amat->a + amat->i[j]; 1873 sum = 0.0; 1874 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1875 sum += PetscAbsScalar(*v); v++; 1876 } 1877 v = bmat->a + bmat->i[j]; 1878 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1879 sum += PetscAbsScalar(*v); v++; 1880 } 1881 if (sum > ntemp) ntemp = sum; 1882 } 1883 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1884 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1885 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1886 } 1887 PetscFunctionReturn(0); 1888 } 1889 1890 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1891 { 1892 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1893 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1894 PetscErrorCode ierr; 1895 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1896 PetscInt cstart = A->cmap->rstart,ncol; 1897 Mat B; 1898 MatScalar *array; 1899 1900 PetscFunctionBegin; 1901 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1902 1903 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1904 ai = Aloc->i; aj = Aloc->j; 1905 bi = Bloc->i; bj = Bloc->j; 1906 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1907 PetscInt *d_nnz,*g_nnz,*o_nnz; 1908 PetscSFNode *oloc; 1909 PETSC_UNUSED PetscSF sf; 1910 1911 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1912 /* compute d_nnz for preallocation */ 1913 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1914 for (i=0; i<ai[ma]; i++) { 1915 d_nnz[aj[i]]++; 1916 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1917 } 1918 /* compute local off-diagonal contributions */ 1919 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1920 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1921 /* map those to global */ 1922 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1923 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1924 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1925 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1926 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1927 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1928 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1929 1930 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1931 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1932 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1933 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1934 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1935 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1936 } else { 1937 B = *matout; 1938 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1939 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1940 } 1941 1942 /* copy over the A part */ 1943 array = Aloc->a; 1944 row = A->rmap->rstart; 1945 for (i=0; i<ma; i++) { 1946 ncol = ai[i+1]-ai[i]; 1947 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1948 row++; 1949 array += ncol; aj += ncol; 1950 } 1951 aj = Aloc->j; 1952 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1953 1954 /* copy over the B part */ 1955 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1956 array = Bloc->a; 1957 row = A->rmap->rstart; 1958 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1959 cols_tmp = cols; 1960 for (i=0; i<mb; i++) { 1961 ncol = bi[i+1]-bi[i]; 1962 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1963 row++; 1964 array += ncol; cols_tmp += ncol; 1965 } 1966 ierr = PetscFree(cols);CHKERRQ(ierr); 1967 1968 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1969 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1970 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1971 *matout = B; 1972 } else { 1973 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1974 } 1975 PetscFunctionReturn(0); 1976 } 1977 1978 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1979 { 1980 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1981 Mat a = aij->A,b = aij->B; 1982 PetscErrorCode ierr; 1983 PetscInt s1,s2,s3; 1984 1985 PetscFunctionBegin; 1986 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1987 if (rr) { 1988 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1989 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1990 /* Overlap communication with computation. */ 1991 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1992 } 1993 if (ll) { 1994 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1995 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1996 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1997 } 1998 /* scale the diagonal block */ 1999 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2000 2001 if (rr) { 2002 /* Do a scatter end and then right scale the off-diagonal block */ 2003 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2004 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2005 } 2006 PetscFunctionReturn(0); 2007 } 2008 2009 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2010 { 2011 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2012 PetscErrorCode ierr; 2013 2014 PetscFunctionBegin; 2015 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2016 PetscFunctionReturn(0); 2017 } 2018 2019 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2020 { 2021 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2022 Mat a,b,c,d; 2023 PetscBool flg; 2024 PetscErrorCode ierr; 2025 2026 PetscFunctionBegin; 2027 a = matA->A; b = matA->B; 2028 c = matB->A; d = matB->B; 2029 2030 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2031 if (flg) { 2032 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2033 } 2034 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2035 PetscFunctionReturn(0); 2036 } 2037 2038 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2039 { 2040 PetscErrorCode ierr; 2041 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2042 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2043 2044 PetscFunctionBegin; 2045 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2046 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2047 /* because of the column compression in the off-processor part of the matrix a->B, 2048 the number of columns in a->B and b->B may be different, hence we cannot call 2049 the MatCopy() directly on the two parts. If need be, we can provide a more 2050 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2051 then copying the submatrices */ 2052 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2053 } else { 2054 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2055 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2056 } 2057 PetscFunctionReturn(0); 2058 } 2059 2060 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2061 { 2062 PetscErrorCode ierr; 2063 2064 PetscFunctionBegin; 2065 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2066 PetscFunctionReturn(0); 2067 } 2068 2069 /* 2070 Computes the number of nonzeros per row needed for preallocation when X and Y 2071 have different nonzero structure. 2072 */ 2073 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2074 { 2075 PetscInt i,j,k,nzx,nzy; 2076 2077 PetscFunctionBegin; 2078 /* Set the number of nonzeros in the new matrix */ 2079 for (i=0; i<m; i++) { 2080 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2081 nzx = xi[i+1] - xi[i]; 2082 nzy = yi[i+1] - yi[i]; 2083 nnz[i] = 0; 2084 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2085 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2086 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2087 nnz[i]++; 2088 } 2089 for (; k<nzy; k++) nnz[i]++; 2090 } 2091 PetscFunctionReturn(0); 2092 } 2093 2094 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2095 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2096 { 2097 PetscErrorCode ierr; 2098 PetscInt m = Y->rmap->N; 2099 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2100 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2101 2102 PetscFunctionBegin; 2103 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2104 PetscFunctionReturn(0); 2105 } 2106 2107 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2108 { 2109 PetscErrorCode ierr; 2110 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2111 PetscBLASInt bnz,one=1; 2112 Mat_SeqAIJ *x,*y; 2113 2114 PetscFunctionBegin; 2115 if (str == SAME_NONZERO_PATTERN) { 2116 PetscScalar alpha = a; 2117 x = (Mat_SeqAIJ*)xx->A->data; 2118 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2119 y = (Mat_SeqAIJ*)yy->A->data; 2120 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2121 x = (Mat_SeqAIJ*)xx->B->data; 2122 y = (Mat_SeqAIJ*)yy->B->data; 2123 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2124 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2125 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2126 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2127 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2128 } else { 2129 Mat B; 2130 PetscInt *nnz_d,*nnz_o; 2131 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2132 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2133 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2134 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2135 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2136 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2137 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2138 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2139 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2140 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2141 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2142 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2143 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2144 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2145 } 2146 PetscFunctionReturn(0); 2147 } 2148 2149 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2150 2151 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2152 { 2153 #if defined(PETSC_USE_COMPLEX) 2154 PetscErrorCode ierr; 2155 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2156 2157 PetscFunctionBegin; 2158 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2159 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2160 #else 2161 PetscFunctionBegin; 2162 #endif 2163 PetscFunctionReturn(0); 2164 } 2165 2166 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2167 { 2168 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2169 PetscErrorCode ierr; 2170 2171 PetscFunctionBegin; 2172 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2173 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2174 PetscFunctionReturn(0); 2175 } 2176 2177 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2178 { 2179 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2180 PetscErrorCode ierr; 2181 2182 PetscFunctionBegin; 2183 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2184 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2185 PetscFunctionReturn(0); 2186 } 2187 2188 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2189 { 2190 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2191 PetscErrorCode ierr; 2192 PetscInt i,*idxb = 0; 2193 PetscScalar *va,*vb; 2194 Vec vtmp; 2195 2196 PetscFunctionBegin; 2197 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2198 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2199 if (idx) { 2200 for (i=0; i<A->rmap->n; i++) { 2201 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2202 } 2203 } 2204 2205 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2206 if (idx) { 2207 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2208 } 2209 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2210 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2211 2212 for (i=0; i<A->rmap->n; i++) { 2213 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2214 va[i] = vb[i]; 2215 if (idx) idx[i] = a->garray[idxb[i]]; 2216 } 2217 } 2218 2219 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2220 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2221 ierr = PetscFree(idxb);CHKERRQ(ierr); 2222 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2223 PetscFunctionReturn(0); 2224 } 2225 2226 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2227 { 2228 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2229 PetscErrorCode ierr; 2230 PetscInt i,*idxb = 0; 2231 PetscScalar *va,*vb; 2232 Vec vtmp; 2233 2234 PetscFunctionBegin; 2235 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2236 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2237 if (idx) { 2238 for (i=0; i<A->cmap->n; i++) { 2239 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2240 } 2241 } 2242 2243 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2244 if (idx) { 2245 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2246 } 2247 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2248 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2249 2250 for (i=0; i<A->rmap->n; i++) { 2251 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2252 va[i] = vb[i]; 2253 if (idx) idx[i] = a->garray[idxb[i]]; 2254 } 2255 } 2256 2257 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2258 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2259 ierr = PetscFree(idxb);CHKERRQ(ierr); 2260 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2261 PetscFunctionReturn(0); 2262 } 2263 2264 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2265 { 2266 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2267 PetscInt n = A->rmap->n; 2268 PetscInt cstart = A->cmap->rstart; 2269 PetscInt *cmap = mat->garray; 2270 PetscInt *diagIdx, *offdiagIdx; 2271 Vec diagV, offdiagV; 2272 PetscScalar *a, *diagA, *offdiagA; 2273 PetscInt r; 2274 PetscErrorCode ierr; 2275 2276 PetscFunctionBegin; 2277 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2278 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2279 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2280 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2281 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2282 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2283 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2284 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2285 for (r = 0; r < n; ++r) { 2286 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2287 a[r] = diagA[r]; 2288 idx[r] = cstart + diagIdx[r]; 2289 } else { 2290 a[r] = offdiagA[r]; 2291 idx[r] = cmap[offdiagIdx[r]]; 2292 } 2293 } 2294 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2295 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2296 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2297 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2298 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2299 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2300 PetscFunctionReturn(0); 2301 } 2302 2303 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2304 { 2305 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2306 PetscInt n = A->rmap->n; 2307 PetscInt cstart = A->cmap->rstart; 2308 PetscInt *cmap = mat->garray; 2309 PetscInt *diagIdx, *offdiagIdx; 2310 Vec diagV, offdiagV; 2311 PetscScalar *a, *diagA, *offdiagA; 2312 PetscInt r; 2313 PetscErrorCode ierr; 2314 2315 PetscFunctionBegin; 2316 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2317 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2318 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2319 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2320 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2321 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2322 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2323 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2324 for (r = 0; r < n; ++r) { 2325 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2326 a[r] = diagA[r]; 2327 idx[r] = cstart + diagIdx[r]; 2328 } else { 2329 a[r] = offdiagA[r]; 2330 idx[r] = cmap[offdiagIdx[r]]; 2331 } 2332 } 2333 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2334 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2335 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2336 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2337 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2338 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2339 PetscFunctionReturn(0); 2340 } 2341 2342 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2343 { 2344 PetscErrorCode ierr; 2345 Mat *dummy; 2346 2347 PetscFunctionBegin; 2348 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2349 *newmat = *dummy; 2350 ierr = PetscFree(dummy);CHKERRQ(ierr); 2351 PetscFunctionReturn(0); 2352 } 2353 2354 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2355 { 2356 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2357 PetscErrorCode ierr; 2358 2359 PetscFunctionBegin; 2360 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2361 A->factorerrortype = a->A->factorerrortype; 2362 PetscFunctionReturn(0); 2363 } 2364 2365 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2366 { 2367 PetscErrorCode ierr; 2368 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2369 2370 PetscFunctionBegin; 2371 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2372 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2373 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2374 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2375 PetscFunctionReturn(0); 2376 } 2377 2378 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2379 { 2380 PetscFunctionBegin; 2381 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2382 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2383 PetscFunctionReturn(0); 2384 } 2385 2386 /*@ 2387 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2388 2389 Collective on Mat 2390 2391 Input Parameters: 2392 + A - the matrix 2393 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2394 2395 Level: advanced 2396 2397 @*/ 2398 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2399 { 2400 PetscErrorCode ierr; 2401 2402 PetscFunctionBegin; 2403 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2404 PetscFunctionReturn(0); 2405 } 2406 2407 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2408 { 2409 PetscErrorCode ierr; 2410 PetscBool sc = PETSC_FALSE,flg; 2411 2412 PetscFunctionBegin; 2413 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2414 ierr = PetscObjectOptionsBegin((PetscObject)A); 2415 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2416 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2417 if (flg) { 2418 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2419 } 2420 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2425 { 2426 PetscErrorCode ierr; 2427 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2428 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2429 2430 PetscFunctionBegin; 2431 if (!Y->preallocated) { 2432 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2433 } else if (!aij->nz) { 2434 PetscInt nonew = aij->nonew; 2435 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2436 aij->nonew = nonew; 2437 } 2438 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2439 PetscFunctionReturn(0); 2440 } 2441 2442 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2443 { 2444 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2445 PetscErrorCode ierr; 2446 2447 PetscFunctionBegin; 2448 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2449 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2450 if (d) { 2451 PetscInt rstart; 2452 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2453 *d += rstart; 2454 2455 } 2456 PetscFunctionReturn(0); 2457 } 2458 2459 2460 /* -------------------------------------------------------------------*/ 2461 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2462 MatGetRow_MPIAIJ, 2463 MatRestoreRow_MPIAIJ, 2464 MatMult_MPIAIJ, 2465 /* 4*/ MatMultAdd_MPIAIJ, 2466 MatMultTranspose_MPIAIJ, 2467 MatMultTransposeAdd_MPIAIJ, 2468 0, 2469 0, 2470 0, 2471 /*10*/ 0, 2472 0, 2473 0, 2474 MatSOR_MPIAIJ, 2475 MatTranspose_MPIAIJ, 2476 /*15*/ MatGetInfo_MPIAIJ, 2477 MatEqual_MPIAIJ, 2478 MatGetDiagonal_MPIAIJ, 2479 MatDiagonalScale_MPIAIJ, 2480 MatNorm_MPIAIJ, 2481 /*20*/ MatAssemblyBegin_MPIAIJ, 2482 MatAssemblyEnd_MPIAIJ, 2483 MatSetOption_MPIAIJ, 2484 MatZeroEntries_MPIAIJ, 2485 /*24*/ MatZeroRows_MPIAIJ, 2486 0, 2487 0, 2488 0, 2489 0, 2490 /*29*/ MatSetUp_MPIAIJ, 2491 0, 2492 0, 2493 MatGetDiagonalBlock_MPIAIJ, 2494 0, 2495 /*34*/ MatDuplicate_MPIAIJ, 2496 0, 2497 0, 2498 0, 2499 0, 2500 /*39*/ MatAXPY_MPIAIJ, 2501 MatCreateSubMatrices_MPIAIJ, 2502 MatIncreaseOverlap_MPIAIJ, 2503 MatGetValues_MPIAIJ, 2504 MatCopy_MPIAIJ, 2505 /*44*/ MatGetRowMax_MPIAIJ, 2506 MatScale_MPIAIJ, 2507 MatShift_MPIAIJ, 2508 MatDiagonalSet_MPIAIJ, 2509 MatZeroRowsColumns_MPIAIJ, 2510 /*49*/ MatSetRandom_MPIAIJ, 2511 0, 2512 0, 2513 0, 2514 0, 2515 /*54*/ MatFDColoringCreate_MPIXAIJ, 2516 0, 2517 MatSetUnfactored_MPIAIJ, 2518 MatPermute_MPIAIJ, 2519 0, 2520 /*59*/ MatCreateSubMatrix_MPIAIJ, 2521 MatDestroy_MPIAIJ, 2522 MatView_MPIAIJ, 2523 0, 2524 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2525 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2526 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2527 0, 2528 0, 2529 0, 2530 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2531 MatGetRowMinAbs_MPIAIJ, 2532 0, 2533 0, 2534 0, 2535 0, 2536 /*75*/ MatFDColoringApply_AIJ, 2537 MatSetFromOptions_MPIAIJ, 2538 0, 2539 0, 2540 MatFindZeroDiagonals_MPIAIJ, 2541 /*80*/ 0, 2542 0, 2543 0, 2544 /*83*/ MatLoad_MPIAIJ, 2545 0, 2546 0, 2547 0, 2548 0, 2549 0, 2550 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2551 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2552 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2553 MatPtAP_MPIAIJ_MPIAIJ, 2554 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2555 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2556 0, 2557 0, 2558 0, 2559 0, 2560 /*99*/ 0, 2561 0, 2562 0, 2563 MatConjugate_MPIAIJ, 2564 0, 2565 /*104*/MatSetValuesRow_MPIAIJ, 2566 MatRealPart_MPIAIJ, 2567 MatImaginaryPart_MPIAIJ, 2568 0, 2569 0, 2570 /*109*/0, 2571 0, 2572 MatGetRowMin_MPIAIJ, 2573 0, 2574 MatMissingDiagonal_MPIAIJ, 2575 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2576 0, 2577 MatGetGhosts_MPIAIJ, 2578 0, 2579 0, 2580 /*119*/0, 2581 0, 2582 0, 2583 0, 2584 MatGetMultiProcBlock_MPIAIJ, 2585 /*124*/MatFindNonzeroRows_MPIAIJ, 2586 MatGetColumnNorms_MPIAIJ, 2587 MatInvertBlockDiagonal_MPIAIJ, 2588 0, 2589 MatCreateSubMatricesMPI_MPIAIJ, 2590 /*129*/0, 2591 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2592 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2593 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2594 0, 2595 /*134*/0, 2596 0, 2597 0, 2598 0, 2599 0, 2600 /*139*/MatSetBlockSizes_MPIAIJ, 2601 0, 2602 0, 2603 MatFDColoringSetUp_MPIXAIJ, 2604 MatFindOffBlockDiagonalEntries_MPIAIJ, 2605 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2606 }; 2607 2608 /* ----------------------------------------------------------------------------------------*/ 2609 2610 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2611 { 2612 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2613 PetscErrorCode ierr; 2614 2615 PetscFunctionBegin; 2616 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2617 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2618 PetscFunctionReturn(0); 2619 } 2620 2621 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2622 { 2623 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2624 PetscErrorCode ierr; 2625 2626 PetscFunctionBegin; 2627 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2628 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2629 PetscFunctionReturn(0); 2630 } 2631 2632 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2633 { 2634 Mat_MPIAIJ *b; 2635 PetscErrorCode ierr; 2636 2637 PetscFunctionBegin; 2638 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2639 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2640 b = (Mat_MPIAIJ*)B->data; 2641 2642 #if defined(PETSC_USE_CTABLE) 2643 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2644 #else 2645 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2646 #endif 2647 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2648 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2649 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2650 2651 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2652 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2653 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2654 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2655 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2656 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2657 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2658 2659 if (!B->preallocated) { 2660 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2661 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2662 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2663 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2664 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2665 } 2666 2667 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2668 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2669 B->preallocated = PETSC_TRUE; 2670 B->was_assembled = PETSC_FALSE; 2671 B->assembled = PETSC_FALSE;; 2672 PetscFunctionReturn(0); 2673 } 2674 2675 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2676 { 2677 Mat mat; 2678 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2679 PetscErrorCode ierr; 2680 2681 PetscFunctionBegin; 2682 *newmat = 0; 2683 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2684 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2685 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2686 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2687 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2688 a = (Mat_MPIAIJ*)mat->data; 2689 2690 mat->factortype = matin->factortype; 2691 mat->assembled = PETSC_TRUE; 2692 mat->insertmode = NOT_SET_VALUES; 2693 mat->preallocated = PETSC_TRUE; 2694 2695 a->size = oldmat->size; 2696 a->rank = oldmat->rank; 2697 a->donotstash = oldmat->donotstash; 2698 a->roworiented = oldmat->roworiented; 2699 a->rowindices = 0; 2700 a->rowvalues = 0; 2701 a->getrowactive = PETSC_FALSE; 2702 2703 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2704 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2705 2706 if (oldmat->colmap) { 2707 #if defined(PETSC_USE_CTABLE) 2708 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2709 #else 2710 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2711 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2712 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2713 #endif 2714 } else a->colmap = 0; 2715 if (oldmat->garray) { 2716 PetscInt len; 2717 len = oldmat->B->cmap->n; 2718 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2719 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2720 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2721 } else a->garray = 0; 2722 2723 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2724 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2725 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2727 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2731 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2732 *newmat = mat; 2733 PetscFunctionReturn(0); 2734 } 2735 2736 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2737 { 2738 PetscScalar *vals,*svals; 2739 MPI_Comm comm; 2740 PetscErrorCode ierr; 2741 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2742 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2743 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2744 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2745 PetscInt cend,cstart,n,*rowners; 2746 int fd; 2747 PetscInt bs = newMat->rmap->bs; 2748 2749 PetscFunctionBegin; 2750 /* force binary viewer to load .info file if it has not yet done so */ 2751 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2752 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2753 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2754 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2755 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2756 if (!rank) { 2757 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2758 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2759 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2760 } 2761 2762 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2763 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2764 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2765 if (bs < 0) bs = 1; 2766 2767 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2768 M = header[1]; N = header[2]; 2769 2770 /* If global sizes are set, check if they are consistent with that given in the file */ 2771 if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M); 2772 if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N); 2773 2774 /* determine ownership of all (block) rows */ 2775 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2776 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2777 else m = newMat->rmap->n; /* Set by user */ 2778 2779 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2780 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2781 2782 /* First process needs enough room for process with most rows */ 2783 if (!rank) { 2784 mmax = rowners[1]; 2785 for (i=2; i<=size; i++) { 2786 mmax = PetscMax(mmax, rowners[i]); 2787 } 2788 } else mmax = -1; /* unused, but compilers complain */ 2789 2790 rowners[0] = 0; 2791 for (i=2; i<=size; i++) { 2792 rowners[i] += rowners[i-1]; 2793 } 2794 rstart = rowners[rank]; 2795 rend = rowners[rank+1]; 2796 2797 /* distribute row lengths to all processors */ 2798 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2799 if (!rank) { 2800 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2801 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2802 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2803 for (j=0; j<m; j++) { 2804 procsnz[0] += ourlens[j]; 2805 } 2806 for (i=1; i<size; i++) { 2807 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2808 /* calculate the number of nonzeros on each processor */ 2809 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2810 procsnz[i] += rowlengths[j]; 2811 } 2812 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2813 } 2814 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2815 } else { 2816 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2817 } 2818 2819 if (!rank) { 2820 /* determine max buffer needed and allocate it */ 2821 maxnz = 0; 2822 for (i=0; i<size; i++) { 2823 maxnz = PetscMax(maxnz,procsnz[i]); 2824 } 2825 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2826 2827 /* read in my part of the matrix column indices */ 2828 nz = procsnz[0]; 2829 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2830 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2831 2832 /* read in every one elses and ship off */ 2833 for (i=1; i<size; i++) { 2834 nz = procsnz[i]; 2835 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2836 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2837 } 2838 ierr = PetscFree(cols);CHKERRQ(ierr); 2839 } else { 2840 /* determine buffer space needed for message */ 2841 nz = 0; 2842 for (i=0; i<m; i++) { 2843 nz += ourlens[i]; 2844 } 2845 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2846 2847 /* receive message of column indices*/ 2848 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2849 } 2850 2851 /* determine column ownership if matrix is not square */ 2852 if (N != M) { 2853 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2854 else n = newMat->cmap->n; 2855 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2856 cstart = cend - n; 2857 } else { 2858 cstart = rstart; 2859 cend = rend; 2860 n = cend - cstart; 2861 } 2862 2863 /* loop over local rows, determining number of off diagonal entries */ 2864 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2865 jj = 0; 2866 for (i=0; i<m; i++) { 2867 for (j=0; j<ourlens[i]; j++) { 2868 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2869 jj++; 2870 } 2871 } 2872 2873 for (i=0; i<m; i++) { 2874 ourlens[i] -= offlens[i]; 2875 } 2876 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2877 2878 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2879 2880 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2881 2882 for (i=0; i<m; i++) { 2883 ourlens[i] += offlens[i]; 2884 } 2885 2886 if (!rank) { 2887 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2888 2889 /* read in my part of the matrix numerical values */ 2890 nz = procsnz[0]; 2891 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2892 2893 /* insert into matrix */ 2894 jj = rstart; 2895 smycols = mycols; 2896 svals = vals; 2897 for (i=0; i<m; i++) { 2898 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2899 smycols += ourlens[i]; 2900 svals += ourlens[i]; 2901 jj++; 2902 } 2903 2904 /* read in other processors and ship out */ 2905 for (i=1; i<size; i++) { 2906 nz = procsnz[i]; 2907 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2908 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2909 } 2910 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2911 } else { 2912 /* receive numeric values */ 2913 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2914 2915 /* receive message of values*/ 2916 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2917 2918 /* insert into matrix */ 2919 jj = rstart; 2920 smycols = mycols; 2921 svals = vals; 2922 for (i=0; i<m; i++) { 2923 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2924 smycols += ourlens[i]; 2925 svals += ourlens[i]; 2926 jj++; 2927 } 2928 } 2929 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2930 ierr = PetscFree(vals);CHKERRQ(ierr); 2931 ierr = PetscFree(mycols);CHKERRQ(ierr); 2932 ierr = PetscFree(rowners);CHKERRQ(ierr); 2933 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2934 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2935 PetscFunctionReturn(0); 2936 } 2937 2938 /* Not scalable because of ISAllGather() unless getting all columns. */ 2939 PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq) 2940 { 2941 PetscErrorCode ierr; 2942 IS iscol_local; 2943 PetscBool isstride; 2944 PetscMPIInt lisstride=0,gisstride; 2945 2946 PetscFunctionBegin; 2947 /* check if we are grabbing all columns*/ 2948 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2949 2950 if (isstride) { 2951 PetscInt start,len,mstart,mlen; 2952 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2953 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2954 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2955 if (mstart == start && mlen-mstart == len) lisstride = 1; 2956 } 2957 2958 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2959 if (gisstride) { 2960 PetscInt N; 2961 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2962 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2963 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2964 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2965 } else { 2966 PetscInt cbs; 2967 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2968 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2969 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2970 } 2971 2972 *isseq = iscol_local; 2973 PetscFunctionReturn(0); 2974 } 2975 2976 /* 2977 Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local 2978 (see MatCreateSubMatrix_MPIAIJ_nonscalable) 2979 2980 Input Parameters: 2981 mat - matrix 2982 isrow - parallel row index set; its local indices are a subset of local columns of mat, 2983 i.e., mat->rstart <= isrow[i] < mat->rend 2984 iscol - parallel column index set; its local indices are a subset of local columns of mat, 2985 i.e., mat->cstart <= iscol[i] < mat->cend 2986 Output Parameter: 2987 isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A 2988 iscol_o - sequential column index set for retrieving mat->B 2989 garray - column map; garray[i] indicates global location of iscol_o[i] in iscol 2990 */ 2991 PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[]) 2992 { 2993 PetscErrorCode ierr; 2994 Vec x,cmap; 2995 const PetscInt *is_idx; 2996 PetscScalar *xarray,*cmaparray; 2997 PetscInt ncols,isstart,*idx,m,rstart,*cmap1,count; 2998 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 2999 Mat B=a->B; 3000 Vec lvec=a->lvec,lcmap; 3001 PetscInt i,cstart,cend,Bn=B->cmap->N; 3002 MPI_Comm comm; 3003 3004 PetscFunctionBegin; 3005 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3006 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 3007 3008 /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */ 3009 ierr = MatCreateVecs(mat,&x,NULL);CHKERRQ(ierr); 3010 ierr = VecDuplicate(x,&cmap);CHKERRQ(ierr); 3011 ierr = VecSet(x,-1.0);CHKERRQ(ierr); 3012 3013 /* Get start indices */ 3014 ierr = MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3015 isstart -= ncols; 3016 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3017 3018 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3019 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 3020 ierr = VecGetArray(cmap,&cmaparray);CHKERRQ(ierr); 3021 ierr = PetscMalloc1(ncols,&idx);CHKERRQ(ierr); 3022 for (i=0; i<ncols; i++) { 3023 xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i]; 3024 cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */ 3025 idx[i] = is_idx[i]-cstart; /* local index of iscol[i] */ 3026 } 3027 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 3028 ierr = VecRestoreArray(cmap,&cmaparray);CHKERRQ(ierr); 3029 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3030 3031 /* Get iscol_d */ 3032 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);CHKERRQ(ierr); 3033 ierr = ISGetBlockSize(iscol,&i);CHKERRQ(ierr); 3034 ierr = ISSetBlockSize(*iscol_d,i);CHKERRQ(ierr); 3035 3036 /* Get isrow_d */ 3037 ierr = ISGetLocalSize(isrow,&m);CHKERRQ(ierr); 3038 rstart = mat->rmap->rstart; 3039 ierr = PetscMalloc1(m,&idx);CHKERRQ(ierr); 3040 ierr = ISGetIndices(isrow,&is_idx);CHKERRQ(ierr); 3041 for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart; 3042 ierr = ISRestoreIndices(isrow,&is_idx);CHKERRQ(ierr); 3043 3044 ierr = ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);CHKERRQ(ierr); 3045 ierr = ISGetBlockSize(isrow,&i);CHKERRQ(ierr); 3046 ierr = ISSetBlockSize(*isrow_d,i);CHKERRQ(ierr); 3047 3048 /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */ 3049 ierr = VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3050 3051 ierr = VecDuplicate(lvec,&lcmap);CHKERRQ(ierr); 3052 3053 ierr = VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3054 ierr = VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3055 ierr = VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3056 3057 /* (3) create sequential iscol_o (a subset of iscol) and isgarray */ 3058 /* off-process column indices */ 3059 count = 0; 3060 ierr = PetscMalloc1(Bn,&idx);CHKERRQ(ierr); 3061 ierr = PetscMalloc1(Bn,&cmap1);CHKERRQ(ierr); 3062 3063 ierr = VecGetArray(lvec,&xarray);CHKERRQ(ierr); 3064 ierr = VecGetArray(lcmap,&cmaparray);CHKERRQ(ierr); 3065 for (i=0; i<Bn; i++) { 3066 if (PetscRealPart(xarray[i]) > -1.0) { 3067 idx[count] = i; /* local column index in off-diagonal part B */ 3068 cmap1[count++] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */ 3069 } 3070 } 3071 ierr = VecRestoreArray(lvec,&xarray);CHKERRQ(ierr); 3072 ierr = VecRestoreArray(lcmap,&cmaparray);CHKERRQ(ierr); 3073 3074 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);CHKERRQ(ierr); 3075 ierr = ISGetBlockSize(iscol,&i);CHKERRQ(ierr); 3076 ierr = ISSetBlockSize(*iscol_o,i);CHKERRQ(ierr); 3077 ierr = PetscFree(idx);CHKERRQ(ierr); 3078 3079 *garray = cmap1; 3080 3081 ierr = VecDestroy(&x);CHKERRQ(ierr); 3082 ierr = VecDestroy(&cmap);CHKERRQ(ierr); 3083 ierr = VecDestroy(&lcmap);CHKERRQ(ierr); 3084 PetscFunctionReturn(0); 3085 } 3086 3087 /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */ 3088 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat) 3089 { 3090 PetscErrorCode ierr; 3091 Mat_MPIAIJ *a = (Mat_MPIAIJ*)mat->data,*asub; 3092 Mat M = NULL; 3093 MPI_Comm comm; 3094 IS iscol_d,isrow_d,iscol_o; 3095 Mat Asub = NULL,Bsub = NULL; 3096 PetscInt n; 3097 3098 PetscFunctionBegin; 3099 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3100 3101 if (call == MAT_REUSE_MATRIX) { 3102 /* Retrieve isrow_d, iscol_d and iscol_o from submat */ 3103 ierr = PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);CHKERRQ(ierr); 3104 if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse"); 3105 3106 ierr = PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);CHKERRQ(ierr); 3107 if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse"); 3108 3109 ierr = PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);CHKERRQ(ierr); 3110 if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse"); 3111 3112 /* Update diagonal and off-diagonal portions of submat */ 3113 asub = (Mat_MPIAIJ*)(*submat)->data; 3114 ierr = MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);CHKERRQ(ierr); 3115 ierr = ISGetLocalSize(iscol_o,&n);CHKERRQ(ierr); 3116 if (n) { 3117 ierr = MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);CHKERRQ(ierr); 3118 } 3119 ierr = MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3120 ierr = MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3121 3122 } else { /* call == MAT_INITIAL_MATRIX) */ 3123 const PetscInt *garray; 3124 PetscInt BsubN; 3125 3126 /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */ 3127 ierr = ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);CHKERRQ(ierr); 3128 3129 /* Create local submatrices Asub and Bsub */ 3130 ierr = MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);CHKERRQ(ierr); 3131 ierr = MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);CHKERRQ(ierr); 3132 3133 /* Create submatrix M */ 3134 ierr = MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);CHKERRQ(ierr); 3135 3136 /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */ 3137 asub = (Mat_MPIAIJ*)M->data; 3138 3139 ierr = ISGetLocalSize(iscol_o,&BsubN);CHKERRQ(ierr); 3140 n = asub->B->cmap->N; 3141 if (BsubN > n) { 3142 /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */ 3143 const PetscInt *idx; 3144 PetscInt i,j,*idx_new,*subgarray = asub->garray; 3145 ierr = PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);CHKERRQ(ierr); 3146 3147 ierr = PetscMalloc1(n,&idx_new);CHKERRQ(ierr); 3148 j = 0; 3149 ierr = ISGetIndices(iscol_o,&idx);CHKERRQ(ierr); 3150 for (i=0; i<n; i++) { 3151 if (j >= BsubN) break; 3152 while (subgarray[i] > garray[j]) j++; 3153 3154 if (subgarray[i] == garray[j]) { 3155 idx_new[i] = idx[j++]; 3156 } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]); 3157 } 3158 ierr = ISRestoreIndices(iscol_o,&idx);CHKERRQ(ierr); 3159 3160 ierr = ISDestroy(&iscol_o);CHKERRQ(ierr); 3161 ierr = ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);CHKERRQ(ierr); 3162 3163 } else if (BsubN < n) { 3164 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N); 3165 } 3166 3167 ierr = PetscFree(garray);CHKERRQ(ierr); 3168 *submat = M; 3169 3170 /* Save isrow_d, iscol_d and iscol_o used in processor for next request */ 3171 ierr = PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);CHKERRQ(ierr); 3172 ierr = ISDestroy(&isrow_d);CHKERRQ(ierr); 3173 3174 ierr = PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);CHKERRQ(ierr); 3175 ierr = ISDestroy(&iscol_d);CHKERRQ(ierr); 3176 3177 ierr = PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);CHKERRQ(ierr); 3178 ierr = ISDestroy(&iscol_o);CHKERRQ(ierr); 3179 } 3180 PetscFunctionReturn(0); 3181 } 3182 3183 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3184 { 3185 PetscErrorCode ierr; 3186 IS iscol_local,isrow_d; 3187 PetscInt csize; 3188 PetscInt n,i,j,start,end; 3189 PetscBool sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2]; 3190 MPI_Comm comm; 3191 3192 PetscFunctionBegin; 3193 /* If isrow has same processor distribution as mat, 3194 call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */ 3195 if (call == MAT_REUSE_MATRIX) { 3196 ierr = PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);CHKERRQ(ierr); 3197 if (isrow_d) { 3198 sameRowDist = PETSC_TRUE; 3199 tsameDist[1] = PETSC_TRUE; /* sameColDist */ 3200 } else { 3201 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3202 if (iscol_local) { 3203 sameRowDist = PETSC_TRUE; 3204 tsameDist[1] = PETSC_FALSE; /* !sameColDist */ 3205 } 3206 } 3207 } else { 3208 /* Check if isrow has same processor distribution as mat */ 3209 sameDist[0] = PETSC_FALSE; 3210 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3211 if (!n) { 3212 sameDist[0] = PETSC_TRUE; 3213 } else { 3214 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3215 ierr = MatGetOwnershipRange(mat,&start,&end);CHKERRQ(ierr); 3216 if (i >= start && j < end) { 3217 sameDist[0] = PETSC_TRUE; 3218 } 3219 } 3220 3221 /* Check if iscol has same processor distribution as mat */ 3222 sameDist[1] = PETSC_FALSE; 3223 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3224 if (!n) { 3225 sameDist[1] = PETSC_TRUE; 3226 } else { 3227 ierr = ISGetMinMax(iscol,&i,&j);CHKERRQ(ierr); 3228 ierr = MatGetOwnershipRangeColumn(mat,&start,&end);CHKERRQ(ierr); 3229 if (i >= start && j < end) sameDist[1] = PETSC_TRUE; 3230 } 3231 3232 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3233 ierr = MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3234 sameRowDist = tsameDist[0]; 3235 } 3236 3237 if (sameRowDist) { 3238 if (tsameDist[1]) { /* sameRowDist & sameColDist */ 3239 /* isrow and iscol have same processor distribution as mat */ 3240 ierr = MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3241 } else { /* sameRowDist */ 3242 /* isrow has same processor distribution as mat */ 3243 ierr = MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3244 } 3245 PetscFunctionReturn(0); 3246 } 3247 3248 /* General case: iscol -> iscol_local which has global size of iscol */ 3249 if (call == MAT_REUSE_MATRIX) { 3250 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3251 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3252 } else { 3253 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3254 } 3255 3256 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3257 ierr = MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3258 3259 if (call == MAT_INITIAL_MATRIX) { 3260 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3261 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3262 } 3263 PetscFunctionReturn(0); 3264 } 3265 3266 /*@C 3267 MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal" 3268 and "off-diagonal" part of the matrix in CSR format. 3269 3270 Collective on MPI_Comm 3271 3272 Input Parameters: 3273 + comm - MPI communicator 3274 . A - "diagonal" portion of matrix 3275 . B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine 3276 - garray - global index of B columns 3277 3278 Output Parameter: 3279 . mat - the matrix, with input A as its local diagonal matrix 3280 Level: advanced 3281 3282 Notes: 3283 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix. 3284 A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore. 3285 3286 .seealso: MatCreateMPIAIJWithSplitArrays() 3287 @*/ 3288 PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat) 3289 { 3290 PetscErrorCode ierr; 3291 Mat_MPIAIJ *maij; 3292 Mat_SeqAIJ *b=(Mat_SeqAIJ*)B->data,*bnew; 3293 PetscInt *oi=b->i,*oj=b->j,i,nz,col; 3294 PetscScalar *oa=b->a; 3295 Mat Bnew; 3296 PetscInt m,n,N; 3297 3298 PetscFunctionBegin; 3299 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3300 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 3301 if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N); 3302 if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs); 3303 if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); 3304 3305 /* Get global columns of mat */ 3306 ierr = MPIU_Allreduce(&n,&N,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 3307 3308 ierr = MatSetSizes(*mat,m,n,PETSC_DECIDE,N);CHKERRQ(ierr); 3309 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3310 ierr = MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 3311 maij = (Mat_MPIAIJ*)(*mat)->data; 3312 3313 (*mat)->preallocated = PETSC_TRUE; 3314 3315 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 3316 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 3317 3318 /* Set A as diagonal portion of *mat */ 3319 maij->A = A; 3320 3321 nz = oi[m]; 3322 for (i=0; i<nz; i++) { 3323 col = oj[i]; 3324 oj[i] = garray[col]; 3325 } 3326 3327 /* Set Bnew as off-diagonal portion of *mat */ 3328 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);CHKERRQ(ierr); 3329 bnew = (Mat_SeqAIJ*)Bnew->data; 3330 bnew->maxnz = b->maxnz; /* allocated nonzeros of B */ 3331 maij->B = Bnew; 3332 3333 if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N); 3334 3335 b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */ 3336 b->free_a = PETSC_FALSE; 3337 b->free_ij = PETSC_FALSE; 3338 ierr = MatDestroy(&B);CHKERRQ(ierr); 3339 3340 bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */ 3341 bnew->free_a = PETSC_TRUE; 3342 bnew->free_ij = PETSC_TRUE; 3343 3344 /* condense columns of maij->B */ 3345 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 3346 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3347 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3348 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 3349 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3350 PetscFunctionReturn(0); 3351 } 3352 3353 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3354 3355 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3356 { 3357 PetscErrorCode ierr; 3358 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3359 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3360 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3361 Mat M,Msub,B=a->B; 3362 MatScalar *aa; 3363 Mat_SeqAIJ *aij; 3364 PetscInt *garray = a->garray,*colsub,Ncols; 3365 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3366 IS iscol_sub,iscmap; 3367 const PetscInt *is_idx,*cmap; 3368 PetscBool allcolumns=PETSC_FALSE; 3369 IS iscol_local=NULL; 3370 MPI_Comm comm; 3371 3372 PetscFunctionBegin; 3373 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3374 3375 if (call == MAT_REUSE_MATRIX) { 3376 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3377 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3378 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3379 3380 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3381 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3382 3383 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3384 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3385 3386 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3387 3388 } else { /* call == MAT_INITIAL_MATRIX) */ 3389 PetscBool flg; 3390 3391 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3392 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); 3393 3394 /* (1) iscol -> nonscalable iscol_local */ 3395 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3396 ierr = ISGetLocalSize(iscol_local,&n);CHKERRQ(ierr); /* local size of iscol_local = global columns of newmat */ 3397 if (n != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != Ncols %d",n,Ncols); 3398 3399 /* Check for special case: each processor gets entire matrix columns */ 3400 ierr = ISIdentity(iscol_local,&flg);CHKERRQ(ierr); 3401 if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3402 if (allcolumns) { 3403 iscol_sub = iscol_local; 3404 ierr = PetscObjectReference((PetscObject)iscol_local);CHKERRQ(ierr); 3405 ierr = ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);CHKERRQ(ierr); 3406 3407 } else { 3408 /* (2) iscol_local -> iscol_sub and iscmap */ 3409 PetscInt *idx,*cmap1,k,cbs; 3410 3411 /* implementation below requires iscol_local be sorted, it can have duplicate indices */ 3412 ierr = ISSorted(iscol_local,&flg);CHKERRQ(ierr); 3413 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unsorted iscol_local is not implemented yet"); 3414 3415 ierr = PetscMalloc1(Ncols,&idx);CHKERRQ(ierr); 3416 ierr = PetscMalloc1(Ncols,&cmap1);CHKERRQ(ierr); 3417 ierr = ISGetIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3418 count = 0; 3419 k = 0; 3420 for (i=0; i<Ncols; i++) { 3421 j = is_idx[i]; 3422 if (j >= cstart && j < cend) { 3423 /* diagonal part of mat */ 3424 idx[count] = j; 3425 cmap1[count++] = i; /* column index in submat */ 3426 } else if (Bn) { 3427 /* off-diagonal part of mat */ 3428 if (j == garray[k]) { 3429 idx[count] = j; 3430 cmap1[count++] = i; /* column index in submat */ 3431 } else if (j > garray[k]) { 3432 while (j > garray[k] && k < Bn-1) k++; 3433 if (j == garray[k]) { 3434 idx[count] = j; 3435 cmap1[count++] = i; /* column index in submat */ 3436 } 3437 } 3438 } 3439 } 3440 ierr = ISRestoreIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3441 3442 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);CHKERRQ(ierr); 3443 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3444 ierr = ISSetBlockSize(iscol_sub,cbs);CHKERRQ(ierr); 3445 3446 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);CHKERRQ(ierr); 3447 } 3448 3449 /* (3) Create sequential Msub */ 3450 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);CHKERRQ(ierr); 3451 } 3452 3453 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3454 aij = (Mat_SeqAIJ*)(Msub)->data; 3455 ii = aij->i; 3456 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3457 3458 /* 3459 m - number of local rows 3460 Ncols - number of columns (same on all processors) 3461 rstart - first row in new global matrix generated 3462 */ 3463 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3464 3465 if (call == MAT_INITIAL_MATRIX) { 3466 /* (4) Create parallel newmat */ 3467 PetscMPIInt rank,size; 3468 PetscInt csize; 3469 3470 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3471 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3472 3473 /* 3474 Determine the number of non-zeros in the diagonal and off-diagonal 3475 portions of the matrix in order to do correct preallocation 3476 */ 3477 3478 /* first get start and end of "diagonal" columns */ 3479 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3480 if (csize == PETSC_DECIDE) { 3481 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3482 if (mglobal == Ncols) { /* square matrix */ 3483 nlocal = m; 3484 } else { 3485 nlocal = Ncols/size + ((Ncols % size) > rank); 3486 } 3487 } else { 3488 nlocal = csize; 3489 } 3490 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3491 rstart = rend - nlocal; 3492 if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols); 3493 3494 /* next, compute all the lengths */ 3495 jj = aij->j; 3496 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3497 olens = dlens + m; 3498 for (i=0; i<m; i++) { 3499 jend = ii[i+1] - ii[i]; 3500 olen = 0; 3501 dlen = 0; 3502 for (j=0; j<jend; j++) { 3503 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3504 else dlen++; 3505 jj++; 3506 } 3507 olens[i] = olen; 3508 dlens[i] = dlen; 3509 } 3510 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3511 3512 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3513 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 3514 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3515 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3516 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3517 ierr = PetscFree(dlens);CHKERRQ(ierr); 3518 3519 } else { /* call == MAT_REUSE_MATRIX */ 3520 M = *newmat; 3521 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3522 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3523 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3524 /* 3525 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3526 rather than the slower MatSetValues(). 3527 */ 3528 M->was_assembled = PETSC_TRUE; 3529 M->assembled = PETSC_FALSE; 3530 } 3531 3532 /* (5) Set values of Msub to *newmat */ 3533 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3534 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3535 3536 jj = aij->j; 3537 aa = aij->a; 3538 for (i=0; i<m; i++) { 3539 row = rstart + i; 3540 nz = ii[i+1] - ii[i]; 3541 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3542 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3543 jj += nz; aa += nz; 3544 } 3545 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3546 3547 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3548 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3549 3550 ierr = PetscFree(colsub);CHKERRQ(ierr); 3551 3552 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3553 if (call == MAT_INITIAL_MATRIX) { 3554 *newmat = M; 3555 ierr = PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3556 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3557 3558 ierr = PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3559 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3560 3561 ierr = PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3562 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3563 3564 if (iscol_local) { 3565 ierr = PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3566 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3567 } 3568 } 3569 PetscFunctionReturn(0); 3570 } 3571 3572 /* 3573 Not great since it makes two copies of the submatrix, first an SeqAIJ 3574 in local and then by concatenating the local matrices the end result. 3575 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3576 3577 Note: This requires a sequential iscol with all indices. 3578 */ 3579 PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3580 { 3581 PetscErrorCode ierr; 3582 PetscMPIInt rank,size; 3583 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3584 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3585 Mat M,Mreuse; 3586 MatScalar *aa,*vwork; 3587 MPI_Comm comm; 3588 Mat_SeqAIJ *aij; 3589 PetscBool colflag,allcolumns=PETSC_FALSE; 3590 3591 PetscFunctionBegin; 3592 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3593 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3594 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3595 3596 /* Check for special case: each processor gets entire matrix columns */ 3597 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3598 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3599 if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3600 3601 if (call == MAT_REUSE_MATRIX) { 3602 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3603 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3604 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3605 } else { 3606 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3607 } 3608 3609 /* 3610 m - number of local rows 3611 n - number of columns (same on all processors) 3612 rstart - first row in new global matrix generated 3613 */ 3614 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3615 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3616 if (call == MAT_INITIAL_MATRIX) { 3617 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3618 ii = aij->i; 3619 jj = aij->j; 3620 3621 /* 3622 Determine the number of non-zeros in the diagonal and off-diagonal 3623 portions of the matrix in order to do correct preallocation 3624 */ 3625 3626 /* first get start and end of "diagonal" columns */ 3627 if (csize == PETSC_DECIDE) { 3628 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3629 if (mglobal == n) { /* square matrix */ 3630 nlocal = m; 3631 } else { 3632 nlocal = n/size + ((n % size) > rank); 3633 } 3634 } else { 3635 nlocal = csize; 3636 } 3637 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3638 rstart = rend - nlocal; 3639 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); 3640 3641 /* next, compute all the lengths */ 3642 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3643 olens = dlens + m; 3644 for (i=0; i<m; i++) { 3645 jend = ii[i+1] - ii[i]; 3646 olen = 0; 3647 dlen = 0; 3648 for (j=0; j<jend; j++) { 3649 if (*jj < rstart || *jj >= rend) olen++; 3650 else dlen++; 3651 jj++; 3652 } 3653 olens[i] = olen; 3654 dlens[i] = dlen; 3655 } 3656 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3657 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3658 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3659 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3660 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3661 ierr = PetscFree(dlens);CHKERRQ(ierr); 3662 } else { 3663 PetscInt ml,nl; 3664 3665 M = *newmat; 3666 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3667 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3668 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3669 /* 3670 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3671 rather than the slower MatSetValues(). 3672 */ 3673 M->was_assembled = PETSC_TRUE; 3674 M->assembled = PETSC_FALSE; 3675 } 3676 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3677 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3678 ii = aij->i; 3679 jj = aij->j; 3680 aa = aij->a; 3681 for (i=0; i<m; i++) { 3682 row = rstart + i; 3683 nz = ii[i+1] - ii[i]; 3684 cwork = jj; jj += nz; 3685 vwork = aa; aa += nz; 3686 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3687 } 3688 3689 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3690 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3691 *newmat = M; 3692 3693 /* save submatrix used in processor for next request */ 3694 if (call == MAT_INITIAL_MATRIX) { 3695 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3696 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3697 } 3698 PetscFunctionReturn(0); 3699 } 3700 3701 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3702 { 3703 PetscInt m,cstart, cend,j,nnz,i,d; 3704 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3705 const PetscInt *JJ; 3706 PetscScalar *values; 3707 PetscErrorCode ierr; 3708 PetscBool nooffprocentries; 3709 3710 PetscFunctionBegin; 3711 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3712 3713 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3714 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3715 m = B->rmap->n; 3716 cstart = B->cmap->rstart; 3717 cend = B->cmap->rend; 3718 rstart = B->rmap->rstart; 3719 3720 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3721 3722 #if defined(PETSC_USE_DEBUGGING) 3723 for (i=0; i<m; i++) { 3724 nnz = Ii[i+1]- Ii[i]; 3725 JJ = J + Ii[i]; 3726 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3727 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3728 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); 3729 } 3730 #endif 3731 3732 for (i=0; i<m; i++) { 3733 nnz = Ii[i+1]- Ii[i]; 3734 JJ = J + Ii[i]; 3735 nnz_max = PetscMax(nnz_max,nnz); 3736 d = 0; 3737 for (j=0; j<nnz; j++) { 3738 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3739 } 3740 d_nnz[i] = d; 3741 o_nnz[i] = nnz - d; 3742 } 3743 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3744 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3745 3746 if (v) values = (PetscScalar*)v; 3747 else { 3748 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3749 } 3750 3751 for (i=0; i<m; i++) { 3752 ii = i + rstart; 3753 nnz = Ii[i+1]- Ii[i]; 3754 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3755 } 3756 nooffprocentries = B->nooffprocentries; 3757 B->nooffprocentries = PETSC_TRUE; 3758 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3759 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3760 B->nooffprocentries = nooffprocentries; 3761 3762 if (!v) { 3763 ierr = PetscFree(values);CHKERRQ(ierr); 3764 } 3765 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3766 PetscFunctionReturn(0); 3767 } 3768 3769 /*@ 3770 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3771 (the default parallel PETSc format). 3772 3773 Collective on MPI_Comm 3774 3775 Input Parameters: 3776 + B - the matrix 3777 . i - the indices into j for the start of each local row (starts with zero) 3778 . j - the column indices for each local row (starts with zero) 3779 - v - optional values in the matrix 3780 3781 Level: developer 3782 3783 Notes: 3784 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3785 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3786 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3787 3788 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3789 3790 The format which is used for the sparse matrix input, is equivalent to a 3791 row-major ordering.. i.e for the following matrix, the input data expected is 3792 as shown 3793 3794 $ 1 0 0 3795 $ 2 0 3 P0 3796 $ ------- 3797 $ 4 5 6 P1 3798 $ 3799 $ Process0 [P0]: rows_owned=[0,1] 3800 $ i = {0,1,3} [size = nrow+1 = 2+1] 3801 $ j = {0,0,2} [size = 3] 3802 $ v = {1,2,3} [size = 3] 3803 $ 3804 $ Process1 [P1]: rows_owned=[2] 3805 $ i = {0,3} [size = nrow+1 = 1+1] 3806 $ j = {0,1,2} [size = 3] 3807 $ v = {4,5,6} [size = 3] 3808 3809 .keywords: matrix, aij, compressed row, sparse, parallel 3810 3811 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3812 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3813 @*/ 3814 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3815 { 3816 PetscErrorCode ierr; 3817 3818 PetscFunctionBegin; 3819 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3820 PetscFunctionReturn(0); 3821 } 3822 3823 /*@C 3824 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3825 (the default parallel PETSc format). For good matrix assembly performance 3826 the user should preallocate the matrix storage by setting the parameters 3827 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3828 performance can be increased by more than a factor of 50. 3829 3830 Collective on MPI_Comm 3831 3832 Input Parameters: 3833 + B - the matrix 3834 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3835 (same value is used for all local rows) 3836 . d_nnz - array containing the number of nonzeros in the various rows of the 3837 DIAGONAL portion of the local submatrix (possibly different for each row) 3838 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3839 The size of this array is equal to the number of local rows, i.e 'm'. 3840 For matrices that will be factored, you must leave room for (and set) 3841 the diagonal entry even if it is zero. 3842 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3843 submatrix (same value is used for all local rows). 3844 - o_nnz - array containing the number of nonzeros in the various rows of the 3845 OFF-DIAGONAL portion of the local submatrix (possibly different for 3846 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3847 structure. The size of this array is equal to the number 3848 of local rows, i.e 'm'. 3849 3850 If the *_nnz parameter is given then the *_nz parameter is ignored 3851 3852 The AIJ format (also called the Yale sparse matrix format or 3853 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3854 storage. The stored row and column indices begin with zero. 3855 See Users-Manual: ch_mat for details. 3856 3857 The parallel matrix is partitioned such that the first m0 rows belong to 3858 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3859 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3860 3861 The DIAGONAL portion of the local submatrix of a processor can be defined 3862 as the submatrix which is obtained by extraction the part corresponding to 3863 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3864 first row that belongs to the processor, r2 is the last row belonging to 3865 the this processor, and c1-c2 is range of indices of the local part of a 3866 vector suitable for applying the matrix to. This is an mxn matrix. In the 3867 common case of a square matrix, the row and column ranges are the same and 3868 the DIAGONAL part is also square. The remaining portion of the local 3869 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3870 3871 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3872 3873 You can call MatGetInfo() to get information on how effective the preallocation was; 3874 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3875 You can also run with the option -info and look for messages with the string 3876 malloc in them to see if additional memory allocation was needed. 3877 3878 Example usage: 3879 3880 Consider the following 8x8 matrix with 34 non-zero values, that is 3881 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3882 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3883 as follows: 3884 3885 .vb 3886 1 2 0 | 0 3 0 | 0 4 3887 Proc0 0 5 6 | 7 0 0 | 8 0 3888 9 0 10 | 11 0 0 | 12 0 3889 ------------------------------------- 3890 13 0 14 | 15 16 17 | 0 0 3891 Proc1 0 18 0 | 19 20 21 | 0 0 3892 0 0 0 | 22 23 0 | 24 0 3893 ------------------------------------- 3894 Proc2 25 26 27 | 0 0 28 | 29 0 3895 30 0 0 | 31 32 33 | 0 34 3896 .ve 3897 3898 This can be represented as a collection of submatrices as: 3899 3900 .vb 3901 A B C 3902 D E F 3903 G H I 3904 .ve 3905 3906 Where the submatrices A,B,C are owned by proc0, D,E,F are 3907 owned by proc1, G,H,I are owned by proc2. 3908 3909 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3910 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3911 The 'M','N' parameters are 8,8, and have the same values on all procs. 3912 3913 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3914 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3915 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3916 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3917 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3918 matrix, ans [DF] as another SeqAIJ matrix. 3919 3920 When d_nz, o_nz parameters are specified, d_nz storage elements are 3921 allocated for every row of the local diagonal submatrix, and o_nz 3922 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3923 One way to choose d_nz and o_nz is to use the max nonzerors per local 3924 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3925 In this case, the values of d_nz,o_nz are: 3926 .vb 3927 proc0 : dnz = 2, o_nz = 2 3928 proc1 : dnz = 3, o_nz = 2 3929 proc2 : dnz = 1, o_nz = 4 3930 .ve 3931 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3932 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3933 for proc3. i.e we are using 12+15+10=37 storage locations to store 3934 34 values. 3935 3936 When d_nnz, o_nnz parameters are specified, the storage is specified 3937 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3938 In the above case the values for d_nnz,o_nnz are: 3939 .vb 3940 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3941 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3942 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3943 .ve 3944 Here the space allocated is sum of all the above values i.e 34, and 3945 hence pre-allocation is perfect. 3946 3947 Level: intermediate 3948 3949 .keywords: matrix, aij, compressed row, sparse, parallel 3950 3951 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3952 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3953 @*/ 3954 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3955 { 3956 PetscErrorCode ierr; 3957 3958 PetscFunctionBegin; 3959 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3960 PetscValidType(B,1); 3961 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3962 PetscFunctionReturn(0); 3963 } 3964 3965 /*@ 3966 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3967 CSR format the local rows. 3968 3969 Collective on MPI_Comm 3970 3971 Input Parameters: 3972 + comm - MPI communicator 3973 . m - number of local rows (Cannot be PETSC_DECIDE) 3974 . n - This value should be the same as the local size used in creating the 3975 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3976 calculated if N is given) For square matrices n is almost always m. 3977 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3978 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3979 . i - row indices 3980 . j - column indices 3981 - a - matrix values 3982 3983 Output Parameter: 3984 . mat - the matrix 3985 3986 Level: intermediate 3987 3988 Notes: 3989 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3990 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3991 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3992 3993 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3994 3995 The format which is used for the sparse matrix input, is equivalent to a 3996 row-major ordering.. i.e for the following matrix, the input data expected is 3997 as shown 3998 3999 $ 1 0 0 4000 $ 2 0 3 P0 4001 $ ------- 4002 $ 4 5 6 P1 4003 $ 4004 $ Process0 [P0]: rows_owned=[0,1] 4005 $ i = {0,1,3} [size = nrow+1 = 2+1] 4006 $ j = {0,0,2} [size = 3] 4007 $ v = {1,2,3} [size = 3] 4008 $ 4009 $ Process1 [P1]: rows_owned=[2] 4010 $ i = {0,3} [size = nrow+1 = 1+1] 4011 $ j = {0,1,2} [size = 3] 4012 $ v = {4,5,6} [size = 3] 4013 4014 .keywords: matrix, aij, compressed row, sparse, parallel 4015 4016 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4017 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4018 @*/ 4019 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4020 { 4021 PetscErrorCode ierr; 4022 4023 PetscFunctionBegin; 4024 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4025 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4026 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4027 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4028 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4029 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4030 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4031 PetscFunctionReturn(0); 4032 } 4033 4034 /*@C 4035 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4036 (the default parallel PETSc format). For good matrix assembly performance 4037 the user should preallocate the matrix storage by setting the parameters 4038 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4039 performance can be increased by more than a factor of 50. 4040 4041 Collective on MPI_Comm 4042 4043 Input Parameters: 4044 + comm - MPI communicator 4045 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4046 This value should be the same as the local size used in creating the 4047 y vector for the matrix-vector product y = Ax. 4048 . n - This value should be the same as the local size used in creating the 4049 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4050 calculated if N is given) For square matrices n is almost always m. 4051 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4052 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4053 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4054 (same value is used for all local rows) 4055 . d_nnz - array containing the number of nonzeros in the various rows of the 4056 DIAGONAL portion of the local submatrix (possibly different for each row) 4057 or NULL, if d_nz is used to specify the nonzero structure. 4058 The size of this array is equal to the number of local rows, i.e 'm'. 4059 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4060 submatrix (same value is used for all local rows). 4061 - o_nnz - array containing the number of nonzeros in the various rows of the 4062 OFF-DIAGONAL portion of the local submatrix (possibly different for 4063 each row) or NULL, if o_nz is used to specify the nonzero 4064 structure. The size of this array is equal to the number 4065 of local rows, i.e 'm'. 4066 4067 Output Parameter: 4068 . A - the matrix 4069 4070 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4071 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4072 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4073 4074 Notes: 4075 If the *_nnz parameter is given then the *_nz parameter is ignored 4076 4077 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4078 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4079 storage requirements for this matrix. 4080 4081 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4082 processor than it must be used on all processors that share the object for 4083 that argument. 4084 4085 The user MUST specify either the local or global matrix dimensions 4086 (possibly both). 4087 4088 The parallel matrix is partitioned across processors such that the 4089 first m0 rows belong to process 0, the next m1 rows belong to 4090 process 1, the next m2 rows belong to process 2 etc.. where 4091 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4092 values corresponding to [m x N] submatrix. 4093 4094 The columns are logically partitioned with the n0 columns belonging 4095 to 0th partition, the next n1 columns belonging to the next 4096 partition etc.. where n0,n1,n2... are the input parameter 'n'. 4097 4098 The DIAGONAL portion of the local submatrix on any given processor 4099 is the submatrix corresponding to the rows and columns m,n 4100 corresponding to the given processor. i.e diagonal matrix on 4101 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4102 etc. The remaining portion of the local submatrix [m x (N-n)] 4103 constitute the OFF-DIAGONAL portion. The example below better 4104 illustrates this concept. 4105 4106 For a square global matrix we define each processor's diagonal portion 4107 to be its local rows and the corresponding columns (a square submatrix); 4108 each processor's off-diagonal portion encompasses the remainder of the 4109 local matrix (a rectangular submatrix). 4110 4111 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4112 4113 When calling this routine with a single process communicator, a matrix of 4114 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 4115 type of communicator, use the construction mechanism: 4116 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4117 4118 By default, this format uses inodes (identical nodes) when possible. 4119 We search for consecutive rows with the same nonzero structure, thereby 4120 reusing matrix information to achieve increased efficiency. 4121 4122 Options Database Keys: 4123 + -mat_no_inode - Do not use inodes 4124 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4125 - -mat_aij_oneindex - Internally use indexing starting at 1 4126 rather than 0. Note that when calling MatSetValues(), 4127 the user still MUST index entries starting at 0! 4128 4129 4130 Example usage: 4131 4132 Consider the following 8x8 matrix with 34 non-zero values, that is 4133 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4134 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4135 as follows: 4136 4137 .vb 4138 1 2 0 | 0 3 0 | 0 4 4139 Proc0 0 5 6 | 7 0 0 | 8 0 4140 9 0 10 | 11 0 0 | 12 0 4141 ------------------------------------- 4142 13 0 14 | 15 16 17 | 0 0 4143 Proc1 0 18 0 | 19 20 21 | 0 0 4144 0 0 0 | 22 23 0 | 24 0 4145 ------------------------------------- 4146 Proc2 25 26 27 | 0 0 28 | 29 0 4147 30 0 0 | 31 32 33 | 0 34 4148 .ve 4149 4150 This can be represented as a collection of submatrices as: 4151 4152 .vb 4153 A B C 4154 D E F 4155 G H I 4156 .ve 4157 4158 Where the submatrices A,B,C are owned by proc0, D,E,F are 4159 owned by proc1, G,H,I are owned by proc2. 4160 4161 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4162 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4163 The 'M','N' parameters are 8,8, and have the same values on all procs. 4164 4165 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4166 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4167 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4168 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4169 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4170 matrix, ans [DF] as another SeqAIJ matrix. 4171 4172 When d_nz, o_nz parameters are specified, d_nz storage elements are 4173 allocated for every row of the local diagonal submatrix, and o_nz 4174 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4175 One way to choose d_nz and o_nz is to use the max nonzerors per local 4176 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4177 In this case, the values of d_nz,o_nz are: 4178 .vb 4179 proc0 : dnz = 2, o_nz = 2 4180 proc1 : dnz = 3, o_nz = 2 4181 proc2 : dnz = 1, o_nz = 4 4182 .ve 4183 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4184 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4185 for proc3. i.e we are using 12+15+10=37 storage locations to store 4186 34 values. 4187 4188 When d_nnz, o_nnz parameters are specified, the storage is specified 4189 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4190 In the above case the values for d_nnz,o_nnz are: 4191 .vb 4192 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4193 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4194 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4195 .ve 4196 Here the space allocated is sum of all the above values i.e 34, and 4197 hence pre-allocation is perfect. 4198 4199 Level: intermediate 4200 4201 .keywords: matrix, aij, compressed row, sparse, parallel 4202 4203 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4204 MATMPIAIJ, MatCreateMPIAIJWithArrays() 4205 @*/ 4206 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) 4207 { 4208 PetscErrorCode ierr; 4209 PetscMPIInt size; 4210 4211 PetscFunctionBegin; 4212 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4213 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4214 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4215 if (size > 1) { 4216 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4217 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4218 } else { 4219 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4220 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4221 } 4222 PetscFunctionReturn(0); 4223 } 4224 4225 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4226 { 4227 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4228 PetscBool flg; 4229 PetscErrorCode ierr; 4230 4231 PetscFunctionBegin; 4232 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4233 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4234 if (Ad) *Ad = a->A; 4235 if (Ao) *Ao = a->B; 4236 if (colmap) *colmap = a->garray; 4237 PetscFunctionReturn(0); 4238 } 4239 4240 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4241 { 4242 PetscErrorCode ierr; 4243 PetscInt m,N,i,rstart,nnz,Ii; 4244 PetscInt *indx; 4245 PetscScalar *values; 4246 4247 PetscFunctionBegin; 4248 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4249 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4250 PetscInt *dnz,*onz,sum,bs,cbs; 4251 4252 if (n == PETSC_DECIDE) { 4253 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4254 } 4255 /* Check sum(n) = N */ 4256 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4257 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4258 4259 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4260 rstart -= m; 4261 4262 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4263 for (i=0; i<m; i++) { 4264 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4265 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4266 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4267 } 4268 4269 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4270 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4271 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4272 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4273 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4274 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4275 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4276 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4277 } 4278 4279 /* numeric phase */ 4280 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4281 for (i=0; i<m; i++) { 4282 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4283 Ii = i + rstart; 4284 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4285 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4286 } 4287 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4288 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4289 PetscFunctionReturn(0); 4290 } 4291 4292 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4293 { 4294 PetscErrorCode ierr; 4295 PetscMPIInt rank; 4296 PetscInt m,N,i,rstart,nnz; 4297 size_t len; 4298 const PetscInt *indx; 4299 PetscViewer out; 4300 char *name; 4301 Mat B; 4302 const PetscScalar *values; 4303 4304 PetscFunctionBegin; 4305 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4306 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4307 /* Should this be the type of the diagonal block of A? */ 4308 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4309 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4310 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4311 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4312 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4313 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4314 for (i=0; i<m; i++) { 4315 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4316 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4317 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4318 } 4319 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4320 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4321 4322 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4323 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4324 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4325 sprintf(name,"%s.%d",outfile,rank); 4326 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4327 ierr = PetscFree(name);CHKERRQ(ierr); 4328 ierr = MatView(B,out);CHKERRQ(ierr); 4329 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4330 ierr = MatDestroy(&B);CHKERRQ(ierr); 4331 PetscFunctionReturn(0); 4332 } 4333 4334 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4335 { 4336 PetscErrorCode ierr; 4337 Mat_Merge_SeqsToMPI *merge; 4338 PetscContainer container; 4339 4340 PetscFunctionBegin; 4341 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4342 if (container) { 4343 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4344 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4345 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4346 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4347 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4348 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4349 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4350 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4351 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4352 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4353 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4354 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4355 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4356 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4357 ierr = PetscFree(merge);CHKERRQ(ierr); 4358 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4359 } 4360 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4361 PetscFunctionReturn(0); 4362 } 4363 4364 #include <../src/mat/utils/freespace.h> 4365 #include <petscbt.h> 4366 4367 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4368 { 4369 PetscErrorCode ierr; 4370 MPI_Comm comm; 4371 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4372 PetscMPIInt size,rank,taga,*len_s; 4373 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4374 PetscInt proc,m; 4375 PetscInt **buf_ri,**buf_rj; 4376 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4377 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4378 MPI_Request *s_waits,*r_waits; 4379 MPI_Status *status; 4380 MatScalar *aa=a->a; 4381 MatScalar **abuf_r,*ba_i; 4382 Mat_Merge_SeqsToMPI *merge; 4383 PetscContainer container; 4384 4385 PetscFunctionBegin; 4386 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4387 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4388 4389 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4390 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4391 4392 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4393 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4394 4395 bi = merge->bi; 4396 bj = merge->bj; 4397 buf_ri = merge->buf_ri; 4398 buf_rj = merge->buf_rj; 4399 4400 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4401 owners = merge->rowmap->range; 4402 len_s = merge->len_s; 4403 4404 /* send and recv matrix values */ 4405 /*-----------------------------*/ 4406 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4407 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4408 4409 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4410 for (proc=0,k=0; proc<size; proc++) { 4411 if (!len_s[proc]) continue; 4412 i = owners[proc]; 4413 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4414 k++; 4415 } 4416 4417 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4418 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4419 ierr = PetscFree(status);CHKERRQ(ierr); 4420 4421 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4422 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4423 4424 /* insert mat values of mpimat */ 4425 /*----------------------------*/ 4426 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4427 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4428 4429 for (k=0; k<merge->nrecv; k++) { 4430 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4431 nrows = *(buf_ri_k[k]); 4432 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4433 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4434 } 4435 4436 /* set values of ba */ 4437 m = merge->rowmap->n; 4438 for (i=0; i<m; i++) { 4439 arow = owners[rank] + i; 4440 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4441 bnzi = bi[i+1] - bi[i]; 4442 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4443 4444 /* add local non-zero vals of this proc's seqmat into ba */ 4445 anzi = ai[arow+1] - ai[arow]; 4446 aj = a->j + ai[arow]; 4447 aa = a->a + ai[arow]; 4448 nextaj = 0; 4449 for (j=0; nextaj<anzi; j++) { 4450 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4451 ba_i[j] += aa[nextaj++]; 4452 } 4453 } 4454 4455 /* add received vals into ba */ 4456 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4457 /* i-th row */ 4458 if (i == *nextrow[k]) { 4459 anzi = *(nextai[k]+1) - *nextai[k]; 4460 aj = buf_rj[k] + *(nextai[k]); 4461 aa = abuf_r[k] + *(nextai[k]); 4462 nextaj = 0; 4463 for (j=0; nextaj<anzi; j++) { 4464 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4465 ba_i[j] += aa[nextaj++]; 4466 } 4467 } 4468 nextrow[k]++; nextai[k]++; 4469 } 4470 } 4471 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4472 } 4473 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4474 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4475 4476 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4477 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4478 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4479 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4480 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4481 PetscFunctionReturn(0); 4482 } 4483 4484 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4485 { 4486 PetscErrorCode ierr; 4487 Mat B_mpi; 4488 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4489 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4490 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4491 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4492 PetscInt len,proc,*dnz,*onz,bs,cbs; 4493 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4494 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4495 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4496 MPI_Status *status; 4497 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4498 PetscBT lnkbt; 4499 Mat_Merge_SeqsToMPI *merge; 4500 PetscContainer container; 4501 4502 PetscFunctionBegin; 4503 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4504 4505 /* make sure it is a PETSc comm */ 4506 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4507 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4508 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4509 4510 ierr = PetscNew(&merge);CHKERRQ(ierr); 4511 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4512 4513 /* determine row ownership */ 4514 /*---------------------------------------------------------*/ 4515 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4516 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4517 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4518 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4519 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4520 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4521 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4522 4523 m = merge->rowmap->n; 4524 owners = merge->rowmap->range; 4525 4526 /* determine the number of messages to send, their lengths */ 4527 /*---------------------------------------------------------*/ 4528 len_s = merge->len_s; 4529 4530 len = 0; /* length of buf_si[] */ 4531 merge->nsend = 0; 4532 for (proc=0; proc<size; proc++) { 4533 len_si[proc] = 0; 4534 if (proc == rank) { 4535 len_s[proc] = 0; 4536 } else { 4537 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4538 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4539 } 4540 if (len_s[proc]) { 4541 merge->nsend++; 4542 nrows = 0; 4543 for (i=owners[proc]; i<owners[proc+1]; i++) { 4544 if (ai[i+1] > ai[i]) nrows++; 4545 } 4546 len_si[proc] = 2*(nrows+1); 4547 len += len_si[proc]; 4548 } 4549 } 4550 4551 /* determine the number and length of messages to receive for ij-structure */ 4552 /*-------------------------------------------------------------------------*/ 4553 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4554 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4555 4556 /* post the Irecv of j-structure */ 4557 /*-------------------------------*/ 4558 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4559 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4560 4561 /* post the Isend of j-structure */ 4562 /*--------------------------------*/ 4563 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4564 4565 for (proc=0, k=0; proc<size; proc++) { 4566 if (!len_s[proc]) continue; 4567 i = owners[proc]; 4568 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4569 k++; 4570 } 4571 4572 /* receives and sends of j-structure are complete */ 4573 /*------------------------------------------------*/ 4574 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4575 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4576 4577 /* send and recv i-structure */ 4578 /*---------------------------*/ 4579 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4580 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4581 4582 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4583 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4584 for (proc=0,k=0; proc<size; proc++) { 4585 if (!len_s[proc]) continue; 4586 /* form outgoing message for i-structure: 4587 buf_si[0]: nrows to be sent 4588 [1:nrows]: row index (global) 4589 [nrows+1:2*nrows+1]: i-structure index 4590 */ 4591 /*-------------------------------------------*/ 4592 nrows = len_si[proc]/2 - 1; 4593 buf_si_i = buf_si + nrows+1; 4594 buf_si[0] = nrows; 4595 buf_si_i[0] = 0; 4596 nrows = 0; 4597 for (i=owners[proc]; i<owners[proc+1]; i++) { 4598 anzi = ai[i+1] - ai[i]; 4599 if (anzi) { 4600 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4601 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4602 nrows++; 4603 } 4604 } 4605 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4606 k++; 4607 buf_si += len_si[proc]; 4608 } 4609 4610 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4611 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4612 4613 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4614 for (i=0; i<merge->nrecv; i++) { 4615 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); 4616 } 4617 4618 ierr = PetscFree(len_si);CHKERRQ(ierr); 4619 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4620 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4621 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4622 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4623 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4624 ierr = PetscFree(status);CHKERRQ(ierr); 4625 4626 /* compute a local seq matrix in each processor */ 4627 /*----------------------------------------------*/ 4628 /* allocate bi array and free space for accumulating nonzero column info */ 4629 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4630 bi[0] = 0; 4631 4632 /* create and initialize a linked list */ 4633 nlnk = N+1; 4634 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4635 4636 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4637 len = ai[owners[rank+1]] - ai[owners[rank]]; 4638 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4639 4640 current_space = free_space; 4641 4642 /* determine symbolic info for each local row */ 4643 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4644 4645 for (k=0; k<merge->nrecv; k++) { 4646 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4647 nrows = *buf_ri_k[k]; 4648 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4649 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4650 } 4651 4652 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4653 len = 0; 4654 for (i=0; i<m; i++) { 4655 bnzi = 0; 4656 /* add local non-zero cols of this proc's seqmat into lnk */ 4657 arow = owners[rank] + i; 4658 anzi = ai[arow+1] - ai[arow]; 4659 aj = a->j + ai[arow]; 4660 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4661 bnzi += nlnk; 4662 /* add received col data into lnk */ 4663 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4664 if (i == *nextrow[k]) { /* i-th row */ 4665 anzi = *(nextai[k]+1) - *nextai[k]; 4666 aj = buf_rj[k] + *nextai[k]; 4667 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4668 bnzi += nlnk; 4669 nextrow[k]++; nextai[k]++; 4670 } 4671 } 4672 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4673 4674 /* if free space is not available, make more free space */ 4675 if (current_space->local_remaining<bnzi) { 4676 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4677 nspacedouble++; 4678 } 4679 /* copy data into free space, then initialize lnk */ 4680 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4681 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4682 4683 current_space->array += bnzi; 4684 current_space->local_used += bnzi; 4685 current_space->local_remaining -= bnzi; 4686 4687 bi[i+1] = bi[i] + bnzi; 4688 } 4689 4690 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4691 4692 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4693 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4694 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4695 4696 /* create symbolic parallel matrix B_mpi */ 4697 /*---------------------------------------*/ 4698 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4699 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4700 if (n==PETSC_DECIDE) { 4701 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4702 } else { 4703 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4704 } 4705 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4706 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4707 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4708 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4709 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4710 4711 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4712 B_mpi->assembled = PETSC_FALSE; 4713 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4714 merge->bi = bi; 4715 merge->bj = bj; 4716 merge->buf_ri = buf_ri; 4717 merge->buf_rj = buf_rj; 4718 merge->coi = NULL; 4719 merge->coj = NULL; 4720 merge->owners_co = NULL; 4721 4722 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4723 4724 /* attach the supporting struct to B_mpi for reuse */ 4725 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4726 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4727 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4728 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4729 *mpimat = B_mpi; 4730 4731 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4732 PetscFunctionReturn(0); 4733 } 4734 4735 /*@C 4736 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4737 matrices from each processor 4738 4739 Collective on MPI_Comm 4740 4741 Input Parameters: 4742 + comm - the communicators the parallel matrix will live on 4743 . seqmat - the input sequential matrices 4744 . m - number of local rows (or PETSC_DECIDE) 4745 . n - number of local columns (or PETSC_DECIDE) 4746 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4747 4748 Output Parameter: 4749 . mpimat - the parallel matrix generated 4750 4751 Level: advanced 4752 4753 Notes: 4754 The dimensions of the sequential matrix in each processor MUST be the same. 4755 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4756 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4757 @*/ 4758 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4759 { 4760 PetscErrorCode ierr; 4761 PetscMPIInt size; 4762 4763 PetscFunctionBegin; 4764 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4765 if (size == 1) { 4766 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4767 if (scall == MAT_INITIAL_MATRIX) { 4768 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4769 } else { 4770 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4771 } 4772 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4773 PetscFunctionReturn(0); 4774 } 4775 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4776 if (scall == MAT_INITIAL_MATRIX) { 4777 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4778 } 4779 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4780 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4781 PetscFunctionReturn(0); 4782 } 4783 4784 /*@ 4785 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4786 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4787 with MatGetSize() 4788 4789 Not Collective 4790 4791 Input Parameters: 4792 + A - the matrix 4793 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4794 4795 Output Parameter: 4796 . A_loc - the local sequential matrix generated 4797 4798 Level: developer 4799 4800 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4801 4802 @*/ 4803 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4804 { 4805 PetscErrorCode ierr; 4806 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4807 Mat_SeqAIJ *mat,*a,*b; 4808 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4809 MatScalar *aa,*ba,*cam; 4810 PetscScalar *ca; 4811 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4812 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4813 PetscBool match; 4814 MPI_Comm comm; 4815 PetscMPIInt size; 4816 4817 PetscFunctionBegin; 4818 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4819 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4820 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4821 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4822 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4823 4824 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4825 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4826 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4827 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4828 aa = a->a; ba = b->a; 4829 if (scall == MAT_INITIAL_MATRIX) { 4830 if (size == 1) { 4831 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4832 PetscFunctionReturn(0); 4833 } 4834 4835 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4836 ci[0] = 0; 4837 for (i=0; i<am; i++) { 4838 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4839 } 4840 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4841 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4842 k = 0; 4843 for (i=0; i<am; i++) { 4844 ncols_o = bi[i+1] - bi[i]; 4845 ncols_d = ai[i+1] - ai[i]; 4846 /* off-diagonal portion of A */ 4847 for (jo=0; jo<ncols_o; jo++) { 4848 col = cmap[*bj]; 4849 if (col >= cstart) break; 4850 cj[k] = col; bj++; 4851 ca[k++] = *ba++; 4852 } 4853 /* diagonal portion of A */ 4854 for (j=0; j<ncols_d; j++) { 4855 cj[k] = cstart + *aj++; 4856 ca[k++] = *aa++; 4857 } 4858 /* off-diagonal portion of A */ 4859 for (j=jo; j<ncols_o; j++) { 4860 cj[k] = cmap[*bj++]; 4861 ca[k++] = *ba++; 4862 } 4863 } 4864 /* put together the new matrix */ 4865 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4866 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4867 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4868 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4869 mat->free_a = PETSC_TRUE; 4870 mat->free_ij = PETSC_TRUE; 4871 mat->nonew = 0; 4872 } else if (scall == MAT_REUSE_MATRIX) { 4873 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4874 ci = mat->i; cj = mat->j; cam = mat->a; 4875 for (i=0; i<am; i++) { 4876 /* off-diagonal portion of A */ 4877 ncols_o = bi[i+1] - bi[i]; 4878 for (jo=0; jo<ncols_o; jo++) { 4879 col = cmap[*bj]; 4880 if (col >= cstart) break; 4881 *cam++ = *ba++; bj++; 4882 } 4883 /* diagonal portion of A */ 4884 ncols_d = ai[i+1] - ai[i]; 4885 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4886 /* off-diagonal portion of A */ 4887 for (j=jo; j<ncols_o; j++) { 4888 *cam++ = *ba++; bj++; 4889 } 4890 } 4891 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4892 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4893 PetscFunctionReturn(0); 4894 } 4895 4896 /*@C 4897 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4898 4899 Not Collective 4900 4901 Input Parameters: 4902 + A - the matrix 4903 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4904 - row, col - index sets of rows and columns to extract (or NULL) 4905 4906 Output Parameter: 4907 . A_loc - the local sequential matrix generated 4908 4909 Level: developer 4910 4911 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4912 4913 @*/ 4914 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4915 { 4916 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4917 PetscErrorCode ierr; 4918 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4919 IS isrowa,iscola; 4920 Mat *aloc; 4921 PetscBool match; 4922 4923 PetscFunctionBegin; 4924 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4925 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4926 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4927 if (!row) { 4928 start = A->rmap->rstart; end = A->rmap->rend; 4929 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4930 } else { 4931 isrowa = *row; 4932 } 4933 if (!col) { 4934 start = A->cmap->rstart; 4935 cmap = a->garray; 4936 nzA = a->A->cmap->n; 4937 nzB = a->B->cmap->n; 4938 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4939 ncols = 0; 4940 for (i=0; i<nzB; i++) { 4941 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4942 else break; 4943 } 4944 imark = i; 4945 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4946 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4947 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4948 } else { 4949 iscola = *col; 4950 } 4951 if (scall != MAT_INITIAL_MATRIX) { 4952 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4953 aloc[0] = *A_loc; 4954 } 4955 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4956 *A_loc = aloc[0]; 4957 ierr = PetscFree(aloc);CHKERRQ(ierr); 4958 if (!row) { 4959 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4960 } 4961 if (!col) { 4962 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4963 } 4964 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4965 PetscFunctionReturn(0); 4966 } 4967 4968 /*@C 4969 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4970 4971 Collective on Mat 4972 4973 Input Parameters: 4974 + A,B - the matrices in mpiaij format 4975 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4976 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4977 4978 Output Parameter: 4979 + rowb, colb - index sets of rows and columns of B to extract 4980 - B_seq - the sequential matrix generated 4981 4982 Level: developer 4983 4984 @*/ 4985 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4986 { 4987 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4988 PetscErrorCode ierr; 4989 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4990 IS isrowb,iscolb; 4991 Mat *bseq=NULL; 4992 4993 PetscFunctionBegin; 4994 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4995 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); 4996 } 4997 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4998 4999 if (scall == MAT_INITIAL_MATRIX) { 5000 start = A->cmap->rstart; 5001 cmap = a->garray; 5002 nzA = a->A->cmap->n; 5003 nzB = a->B->cmap->n; 5004 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 5005 ncols = 0; 5006 for (i=0; i<nzB; i++) { /* row < local row index */ 5007 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5008 else break; 5009 } 5010 imark = i; 5011 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5012 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5013 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5014 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5015 } else { 5016 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5017 isrowb = *rowb; iscolb = *colb; 5018 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 5019 bseq[0] = *B_seq; 5020 } 5021 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5022 *B_seq = bseq[0]; 5023 ierr = PetscFree(bseq);CHKERRQ(ierr); 5024 if (!rowb) { 5025 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5026 } else { 5027 *rowb = isrowb; 5028 } 5029 if (!colb) { 5030 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5031 } else { 5032 *colb = iscolb; 5033 } 5034 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5035 PetscFunctionReturn(0); 5036 } 5037 5038 /* 5039 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5040 of the OFF-DIAGONAL portion of local A 5041 5042 Collective on Mat 5043 5044 Input Parameters: 5045 + A,B - the matrices in mpiaij format 5046 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5047 5048 Output Parameter: 5049 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5050 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5051 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5052 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5053 5054 Level: developer 5055 5056 */ 5057 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5058 { 5059 VecScatter_MPI_General *gen_to,*gen_from; 5060 PetscErrorCode ierr; 5061 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5062 Mat_SeqAIJ *b_oth; 5063 VecScatter ctx =a->Mvctx; 5064 MPI_Comm comm; 5065 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5066 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5067 PetscInt *rvalues,*svalues; 5068 MatScalar *b_otha,*bufa,*bufA; 5069 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5070 MPI_Request *rwaits = NULL,*swaits = NULL; 5071 MPI_Status *sstatus,rstatus; 5072 PetscMPIInt jj,size; 5073 PetscInt *cols,sbs,rbs; 5074 PetscScalar *vals; 5075 5076 PetscFunctionBegin; 5077 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5078 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5079 5080 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5081 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); 5082 } 5083 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5084 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5085 5086 if (size == 1) { 5087 startsj_s = NULL; 5088 bufa_ptr = NULL; 5089 *B_oth = NULL; 5090 PetscFunctionReturn(0); 5091 } 5092 5093 gen_to = (VecScatter_MPI_General*)ctx->todata; 5094 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5095 nrecvs = gen_from->n; 5096 nsends = gen_to->n; 5097 5098 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 5099 srow = gen_to->indices; /* local row index to be sent */ 5100 sstarts = gen_to->starts; 5101 sprocs = gen_to->procs; 5102 sstatus = gen_to->sstatus; 5103 sbs = gen_to->bs; 5104 rstarts = gen_from->starts; 5105 rprocs = gen_from->procs; 5106 rbs = gen_from->bs; 5107 5108 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5109 if (scall == MAT_INITIAL_MATRIX) { 5110 /* i-array */ 5111 /*---------*/ 5112 /* post receives */ 5113 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 5114 for (i=0; i<nrecvs; i++) { 5115 rowlen = rvalues + rstarts[i]*rbs; 5116 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5117 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5118 } 5119 5120 /* pack the outgoing message */ 5121 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 5122 5123 sstartsj[0] = 0; 5124 rstartsj[0] = 0; 5125 len = 0; /* total length of j or a array to be sent */ 5126 k = 0; 5127 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 5128 for (i=0; i<nsends; i++) { 5129 rowlen = svalues + sstarts[i]*sbs; 5130 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5131 for (j=0; j<nrows; j++) { 5132 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5133 for (l=0; l<sbs; l++) { 5134 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5135 5136 rowlen[j*sbs+l] = ncols; 5137 5138 len += ncols; 5139 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5140 } 5141 k++; 5142 } 5143 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5144 5145 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5146 } 5147 /* recvs and sends of i-array are completed */ 5148 i = nrecvs; 5149 while (i--) { 5150 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5151 } 5152 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5153 ierr = PetscFree(svalues);CHKERRQ(ierr); 5154 5155 /* allocate buffers for sending j and a arrays */ 5156 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 5157 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 5158 5159 /* create i-array of B_oth */ 5160 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 5161 5162 b_othi[0] = 0; 5163 len = 0; /* total length of j or a array to be received */ 5164 k = 0; 5165 for (i=0; i<nrecvs; i++) { 5166 rowlen = rvalues + rstarts[i]*rbs; 5167 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 5168 for (j=0; j<nrows; j++) { 5169 b_othi[k+1] = b_othi[k] + rowlen[j]; 5170 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 5171 k++; 5172 } 5173 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5174 } 5175 ierr = PetscFree(rvalues);CHKERRQ(ierr); 5176 5177 /* allocate space for j and a arrrays of B_oth */ 5178 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 5179 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 5180 5181 /* j-array */ 5182 /*---------*/ 5183 /* post receives of j-array */ 5184 for (i=0; i<nrecvs; i++) { 5185 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5186 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5187 } 5188 5189 /* pack the outgoing message j-array */ 5190 k = 0; 5191 for (i=0; i<nsends; i++) { 5192 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5193 bufJ = bufj+sstartsj[i]; 5194 for (j=0; j<nrows; j++) { 5195 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5196 for (ll=0; ll<sbs; ll++) { 5197 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5198 for (l=0; l<ncols; l++) { 5199 *bufJ++ = cols[l]; 5200 } 5201 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5202 } 5203 } 5204 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5205 } 5206 5207 /* recvs and sends of j-array are completed */ 5208 i = nrecvs; 5209 while (i--) { 5210 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5211 } 5212 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5213 } else if (scall == MAT_REUSE_MATRIX) { 5214 sstartsj = *startsj_s; 5215 rstartsj = *startsj_r; 5216 bufa = *bufa_ptr; 5217 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5218 b_otha = b_oth->a; 5219 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5220 5221 /* a-array */ 5222 /*---------*/ 5223 /* post receives of a-array */ 5224 for (i=0; i<nrecvs; i++) { 5225 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5226 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5227 } 5228 5229 /* pack the outgoing message a-array */ 5230 k = 0; 5231 for (i=0; i<nsends; i++) { 5232 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5233 bufA = bufa+sstartsj[i]; 5234 for (j=0; j<nrows; j++) { 5235 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5236 for (ll=0; ll<sbs; ll++) { 5237 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5238 for (l=0; l<ncols; l++) { 5239 *bufA++ = vals[l]; 5240 } 5241 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5242 } 5243 } 5244 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5245 } 5246 /* recvs and sends of a-array are completed */ 5247 i = nrecvs; 5248 while (i--) { 5249 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5250 } 5251 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5252 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5253 5254 if (scall == MAT_INITIAL_MATRIX) { 5255 /* put together the new matrix */ 5256 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5257 5258 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5259 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5260 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5261 b_oth->free_a = PETSC_TRUE; 5262 b_oth->free_ij = PETSC_TRUE; 5263 b_oth->nonew = 0; 5264 5265 ierr = PetscFree(bufj);CHKERRQ(ierr); 5266 if (!startsj_s || !bufa_ptr) { 5267 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5268 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5269 } else { 5270 *startsj_s = sstartsj; 5271 *startsj_r = rstartsj; 5272 *bufa_ptr = bufa; 5273 } 5274 } 5275 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5276 PetscFunctionReturn(0); 5277 } 5278 5279 /*@C 5280 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5281 5282 Not Collective 5283 5284 Input Parameters: 5285 . A - The matrix in mpiaij format 5286 5287 Output Parameter: 5288 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5289 . colmap - A map from global column index to local index into lvec 5290 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5291 5292 Level: developer 5293 5294 @*/ 5295 #if defined(PETSC_USE_CTABLE) 5296 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5297 #else 5298 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5299 #endif 5300 { 5301 Mat_MPIAIJ *a; 5302 5303 PetscFunctionBegin; 5304 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5305 PetscValidPointer(lvec, 2); 5306 PetscValidPointer(colmap, 3); 5307 PetscValidPointer(multScatter, 4); 5308 a = (Mat_MPIAIJ*) A->data; 5309 if (lvec) *lvec = a->lvec; 5310 if (colmap) *colmap = a->colmap; 5311 if (multScatter) *multScatter = a->Mvctx; 5312 PetscFunctionReturn(0); 5313 } 5314 5315 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5316 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5317 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5318 #if defined(PETSC_HAVE_ELEMENTAL) 5319 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5320 #endif 5321 #if defined(PETSC_HAVE_HYPRE) 5322 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5323 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5324 #endif 5325 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5326 5327 /* 5328 Computes (B'*A')' since computing B*A directly is untenable 5329 5330 n p p 5331 ( ) ( ) ( ) 5332 m ( A ) * n ( B ) = m ( C ) 5333 ( ) ( ) ( ) 5334 5335 */ 5336 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5337 { 5338 PetscErrorCode ierr; 5339 Mat At,Bt,Ct; 5340 5341 PetscFunctionBegin; 5342 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5343 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5344 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5345 ierr = MatDestroy(&At);CHKERRQ(ierr); 5346 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5347 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5348 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5349 PetscFunctionReturn(0); 5350 } 5351 5352 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5353 { 5354 PetscErrorCode ierr; 5355 PetscInt m=A->rmap->n,n=B->cmap->n; 5356 Mat Cmat; 5357 5358 PetscFunctionBegin; 5359 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); 5360 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5361 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5362 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5363 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5364 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5365 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5366 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5367 5368 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5369 5370 *C = Cmat; 5371 PetscFunctionReturn(0); 5372 } 5373 5374 /* ----------------------------------------------------------------*/ 5375 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5376 { 5377 PetscErrorCode ierr; 5378 5379 PetscFunctionBegin; 5380 if (scall == MAT_INITIAL_MATRIX) { 5381 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5382 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5383 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5384 } 5385 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5386 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5387 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5388 PetscFunctionReturn(0); 5389 } 5390 5391 /*MC 5392 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5393 5394 Options Database Keys: 5395 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5396 5397 Level: beginner 5398 5399 .seealso: MatCreateAIJ() 5400 M*/ 5401 5402 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5403 { 5404 Mat_MPIAIJ *b; 5405 PetscErrorCode ierr; 5406 PetscMPIInt size; 5407 5408 PetscFunctionBegin; 5409 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5410 5411 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5412 B->data = (void*)b; 5413 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5414 B->assembled = PETSC_FALSE; 5415 B->insertmode = NOT_SET_VALUES; 5416 b->size = size; 5417 5418 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5419 5420 /* build cache for off array entries formed */ 5421 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5422 5423 b->donotstash = PETSC_FALSE; 5424 b->colmap = 0; 5425 b->garray = 0; 5426 b->roworiented = PETSC_TRUE; 5427 5428 /* stuff used for matrix vector multiply */ 5429 b->lvec = NULL; 5430 b->Mvctx = NULL; 5431 5432 /* stuff for MatGetRow() */ 5433 b->rowindices = 0; 5434 b->rowvalues = 0; 5435 b->getrowactive = PETSC_FALSE; 5436 5437 /* flexible pointer used in CUSP/CUSPARSE classes */ 5438 b->spptr = NULL; 5439 5440 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5441 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5442 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5443 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5444 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5445 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5446 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5447 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5448 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5449 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5450 #if defined(PETSC_HAVE_ELEMENTAL) 5451 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5452 #endif 5453 #if defined(PETSC_HAVE_HYPRE) 5454 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5455 #endif 5456 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5457 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5458 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5459 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5460 #if defined(PETSC_HAVE_HYPRE) 5461 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5462 #endif 5463 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5464 PetscFunctionReturn(0); 5465 } 5466 5467 /*@C 5468 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5469 and "off-diagonal" part of the matrix in CSR format. 5470 5471 Collective on MPI_Comm 5472 5473 Input Parameters: 5474 + comm - MPI communicator 5475 . m - number of local rows (Cannot be PETSC_DECIDE) 5476 . n - This value should be the same as the local size used in creating the 5477 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5478 calculated if N is given) For square matrices n is almost always m. 5479 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5480 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5481 . i - row indices for "diagonal" portion of matrix 5482 . j - column indices 5483 . a - matrix values 5484 . oi - row indices for "off-diagonal" portion of matrix 5485 . oj - column indices 5486 - oa - matrix values 5487 5488 Output Parameter: 5489 . mat - the matrix 5490 5491 Level: advanced 5492 5493 Notes: 5494 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5495 must free the arrays once the matrix has been destroyed and not before. 5496 5497 The i and j indices are 0 based 5498 5499 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5500 5501 This sets local rows and cannot be used to set off-processor values. 5502 5503 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5504 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5505 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5506 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5507 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5508 communication if it is known that only local entries will be set. 5509 5510 .keywords: matrix, aij, compressed row, sparse, parallel 5511 5512 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5513 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5514 @*/ 5515 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) 5516 { 5517 PetscErrorCode ierr; 5518 Mat_MPIAIJ *maij; 5519 5520 PetscFunctionBegin; 5521 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5522 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5523 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5524 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5525 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5526 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5527 maij = (Mat_MPIAIJ*) (*mat)->data; 5528 5529 (*mat)->preallocated = PETSC_TRUE; 5530 5531 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5532 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5533 5534 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5535 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5536 5537 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5538 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5539 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5540 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5541 5542 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5543 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5544 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5545 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5546 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5547 PetscFunctionReturn(0); 5548 } 5549 5550 /* 5551 Special version for direct calls from Fortran 5552 */ 5553 #include <petsc/private/fortranimpl.h> 5554 5555 /* Change these macros so can be used in void function */ 5556 #undef CHKERRQ 5557 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5558 #undef SETERRQ2 5559 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5560 #undef SETERRQ3 5561 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5562 #undef SETERRQ 5563 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5564 5565 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5566 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5567 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5568 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5569 #else 5570 #endif 5571 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) 5572 { 5573 Mat mat = *mmat; 5574 PetscInt m = *mm, n = *mn; 5575 InsertMode addv = *maddv; 5576 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5577 PetscScalar value; 5578 PetscErrorCode ierr; 5579 5580 MatCheckPreallocated(mat,1); 5581 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5582 5583 #if defined(PETSC_USE_DEBUG) 5584 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5585 #endif 5586 { 5587 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5588 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5589 PetscBool roworiented = aij->roworiented; 5590 5591 /* Some Variables required in the macro */ 5592 Mat A = aij->A; 5593 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5594 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5595 MatScalar *aa = a->a; 5596 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5597 Mat B = aij->B; 5598 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5599 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5600 MatScalar *ba = b->a; 5601 5602 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5603 PetscInt nonew = a->nonew; 5604 MatScalar *ap1,*ap2; 5605 5606 PetscFunctionBegin; 5607 for (i=0; i<m; i++) { 5608 if (im[i] < 0) continue; 5609 #if defined(PETSC_USE_DEBUG) 5610 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); 5611 #endif 5612 if (im[i] >= rstart && im[i] < rend) { 5613 row = im[i] - rstart; 5614 lastcol1 = -1; 5615 rp1 = aj + ai[row]; 5616 ap1 = aa + ai[row]; 5617 rmax1 = aimax[row]; 5618 nrow1 = ailen[row]; 5619 low1 = 0; 5620 high1 = nrow1; 5621 lastcol2 = -1; 5622 rp2 = bj + bi[row]; 5623 ap2 = ba + bi[row]; 5624 rmax2 = bimax[row]; 5625 nrow2 = bilen[row]; 5626 low2 = 0; 5627 high2 = nrow2; 5628 5629 for (j=0; j<n; j++) { 5630 if (roworiented) value = v[i*n+j]; 5631 else value = v[i+j*m]; 5632 if (in[j] >= cstart && in[j] < cend) { 5633 col = in[j] - cstart; 5634 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5635 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5636 } else if (in[j] < 0) continue; 5637 #if defined(PETSC_USE_DEBUG) 5638 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); 5639 #endif 5640 else { 5641 if (mat->was_assembled) { 5642 if (!aij->colmap) { 5643 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5644 } 5645 #if defined(PETSC_USE_CTABLE) 5646 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5647 col--; 5648 #else 5649 col = aij->colmap[in[j]] - 1; 5650 #endif 5651 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5652 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5653 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5654 col = in[j]; 5655 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5656 B = aij->B; 5657 b = (Mat_SeqAIJ*)B->data; 5658 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5659 rp2 = bj + bi[row]; 5660 ap2 = ba + bi[row]; 5661 rmax2 = bimax[row]; 5662 nrow2 = bilen[row]; 5663 low2 = 0; 5664 high2 = nrow2; 5665 bm = aij->B->rmap->n; 5666 ba = b->a; 5667 } 5668 } else col = in[j]; 5669 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5670 } 5671 } 5672 } else if (!aij->donotstash) { 5673 if (roworiented) { 5674 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5675 } else { 5676 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5677 } 5678 } 5679 } 5680 } 5681 PetscFunctionReturnVoid(); 5682 } 5683 5684