1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 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; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 #undef __FUNCT__ 499 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 500 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 501 { 502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 504 PetscErrorCode ierr; 505 PetscInt l,*garray = mat->garray,diag; 506 507 PetscFunctionBegin; 508 /* code only works for square matrices A */ 509 510 /* find size of row to the left of the diagonal part */ 511 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 512 row = row - diag; 513 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 514 if (garray[b->j[b->i[row]+l]] > diag) break; 515 } 516 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 517 518 /* diagonal part */ 519 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 520 521 /* right of diagonal part */ 522 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); 523 PetscFunctionReturn(0); 524 } 525 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatSetValues_MPIAIJ" 528 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 529 { 530 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 531 PetscScalar value; 532 PetscErrorCode ierr; 533 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 534 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 535 PetscBool roworiented = aij->roworiented; 536 537 /* Some Variables required in the macro */ 538 Mat A = aij->A; 539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 540 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 541 MatScalar *aa = a->a; 542 PetscBool ignorezeroentries = a->ignorezeroentries; 543 Mat B = aij->B; 544 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 545 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 546 MatScalar *ba = b->a; 547 548 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 549 PetscInt nonew; 550 MatScalar *ap1,*ap2; 551 552 PetscFunctionBegin; 553 for (i=0; i<m; i++) { 554 if (im[i] < 0) continue; 555 #if defined(PETSC_USE_DEBUG) 556 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); 557 #endif 558 if (im[i] >= rstart && im[i] < rend) { 559 row = im[i] - rstart; 560 lastcol1 = -1; 561 rp1 = aj + ai[row]; 562 ap1 = aa + ai[row]; 563 rmax1 = aimax[row]; 564 nrow1 = ailen[row]; 565 low1 = 0; 566 high1 = nrow1; 567 lastcol2 = -1; 568 rp2 = bj + bi[row]; 569 ap2 = ba + bi[row]; 570 rmax2 = bimax[row]; 571 nrow2 = bilen[row]; 572 low2 = 0; 573 high2 = nrow2; 574 575 for (j=0; j<n; j++) { 576 if (roworiented) value = v[i*n+j]; 577 else value = v[i+j*m]; 578 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 579 if (in[j] >= cstart && in[j] < cend) { 580 col = in[j] - cstart; 581 nonew = a->nonew; 582 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 583 } else if (in[j] < 0) continue; 584 #if defined(PETSC_USE_DEBUG) 585 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); 586 #endif 587 else { 588 if (mat->was_assembled) { 589 if (!aij->colmap) { 590 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 591 } 592 #if defined(PETSC_USE_CTABLE) 593 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 594 col--; 595 #else 596 col = aij->colmap[in[j]] - 1; 597 #endif 598 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 599 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 600 col = in[j]; 601 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 602 B = aij->B; 603 b = (Mat_SeqAIJ*)B->data; 604 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 605 rp2 = bj + bi[row]; 606 ap2 = ba + bi[row]; 607 rmax2 = bimax[row]; 608 nrow2 = bilen[row]; 609 low2 = 0; 610 high2 = nrow2; 611 bm = aij->B->rmap->n; 612 ba = b->a; 613 } 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]); 614 } else col = in[j]; 615 nonew = b->nonew; 616 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 617 } 618 } 619 } else { 620 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]); 621 if (!aij->donotstash) { 622 mat->assembled = PETSC_FALSE; 623 if (roworiented) { 624 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 625 } else { 626 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 627 } 628 } 629 } 630 } 631 PetscFunctionReturn(0); 632 } 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatGetValues_MPIAIJ" 636 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 641 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 642 643 PetscFunctionBegin; 644 for (i=0; i<m; i++) { 645 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 646 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); 647 if (idxm[i] >= rstart && idxm[i] < rend) { 648 row = idxm[i] - rstart; 649 for (j=0; j<n; j++) { 650 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 651 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); 652 if (idxn[j] >= cstart && idxn[j] < cend) { 653 col = idxn[j] - cstart; 654 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 655 } else { 656 if (!aij->colmap) { 657 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 658 } 659 #if defined(PETSC_USE_CTABLE) 660 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 661 col--; 662 #else 663 col = aij->colmap[idxn[j]] - 1; 664 #endif 665 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 666 else { 667 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 668 } 669 } 670 } 671 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 672 } 673 PetscFunctionReturn(0); 674 } 675 676 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 680 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 681 { 682 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 683 PetscErrorCode ierr; 684 PetscInt nstash,reallocs; 685 InsertMode addv; 686 687 PetscFunctionBegin; 688 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 689 690 /* make sure all processors are either in INSERTMODE or ADDMODE */ 691 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 692 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 693 mat->insertmode = addv; /* in case this processor had no cache */ 694 695 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 696 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 697 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 698 PetscFunctionReturn(0); 699 } 700 701 #undef __FUNCT__ 702 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 703 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 704 { 705 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 706 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 707 PetscErrorCode ierr; 708 PetscMPIInt n; 709 PetscInt i,j,rstart,ncols,flg; 710 PetscInt *row,*col; 711 PetscBool other_disassembled; 712 PetscScalar *val; 713 InsertMode addv = mat->insertmode; 714 715 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 716 717 PetscFunctionBegin; 718 if (!aij->donotstash && !mat->nooffprocentries) { 719 while (1) { 720 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 721 if (!flg) break; 722 723 for (i=0; i<n; ) { 724 /* Now identify the consecutive vals belonging to the same row */ 725 for (j=i,rstart=row[j]; j<n; j++) { 726 if (row[j] != rstart) break; 727 } 728 if (j < n) ncols = j-i; 729 else ncols = n-i; 730 /* Now assemble all these values with a single function call */ 731 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 732 733 i = j; 734 } 735 } 736 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 737 } 738 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 739 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 740 741 /* determine if any processor has disassembled, if so we must 742 also disassemble ourselfs, in order that we may reassemble. */ 743 /* 744 if nonzero structure of submatrix B cannot change then we know that 745 no processor disassembled thus we can skip this stuff 746 */ 747 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 748 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 749 if (mat->was_assembled && !other_disassembled) { 750 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 751 } 752 } 753 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 754 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 755 } 756 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 757 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 758 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 759 760 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 761 762 aij->rowvalues = 0; 763 764 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 765 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 766 767 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 768 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 769 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 770 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 771 } 772 PetscFunctionReturn(0); 773 } 774 775 #undef __FUNCT__ 776 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 777 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 778 { 779 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 780 PetscErrorCode ierr; 781 782 PetscFunctionBegin; 783 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 784 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 785 PetscFunctionReturn(0); 786 } 787 788 #undef __FUNCT__ 789 #define __FUNCT__ "MatZeroRows_MPIAIJ" 790 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 791 { 792 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 793 PetscInt *owners = A->rmap->range; 794 PetscInt n = A->rmap->n; 795 PetscSF sf; 796 PetscInt *lrows; 797 PetscSFNode *rrows; 798 PetscInt r, p = 0, len = 0; 799 PetscErrorCode ierr; 800 801 PetscFunctionBegin; 802 /* Create SF where leaves are input rows and roots are owned rows */ 803 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 804 for (r = 0; r < n; ++r) lrows[r] = -1; 805 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 806 for (r = 0; r < N; ++r) { 807 const PetscInt idx = rows[r]; 808 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); 809 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 810 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 811 } 812 if (A->nooffproczerorows) { 813 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 814 lrows[len++] = idx - owners[p]; 815 } else { 816 rrows[r].rank = p; 817 rrows[r].index = rows[r] - owners[p]; 818 } 819 } 820 if (!A->nooffproczerorows) { 821 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 822 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 823 /* Collect flags for rows to be zeroed */ 824 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 825 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 826 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 827 /* Compress and put in row numbers */ 828 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 829 } 830 /* fix right hand side if needed */ 831 if (x && b) { 832 const PetscScalar *xx; 833 PetscScalar *bb; 834 835 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 836 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 837 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 838 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 839 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 840 } 841 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 842 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 843 if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) { 844 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 845 } else if (diag != 0.0) { 846 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 847 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"); 848 for (r = 0; r < len; ++r) { 849 const PetscInt row = lrows[r] + A->rmap->rstart; 850 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 851 } 852 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 853 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 854 } else { 855 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 856 } 857 ierr = PetscFree(lrows);CHKERRQ(ierr); 858 859 /* only change matrix nonzero state if pattern was allowed to be changed */ 860 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 861 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 862 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 863 } 864 PetscFunctionReturn(0); 865 } 866 867 #undef __FUNCT__ 868 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 869 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 870 { 871 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 872 PetscErrorCode ierr; 873 PetscMPIInt n = A->rmap->n; 874 PetscInt i,j,r,m,p = 0,len = 0; 875 PetscInt *lrows,*owners = A->rmap->range; 876 PetscSFNode *rrows; 877 PetscSF sf; 878 const PetscScalar *xx; 879 PetscScalar *bb,*mask; 880 Vec xmask,lmask; 881 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 882 const PetscInt *aj, *ii,*ridx; 883 PetscScalar *aa; 884 885 PetscFunctionBegin; 886 /* Create SF where leaves are input rows and roots are owned rows */ 887 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 888 for (r = 0; r < n; ++r) lrows[r] = -1; 889 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 890 for (r = 0; r < N; ++r) { 891 const PetscInt idx = rows[r]; 892 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); 893 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 894 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 895 } 896 rrows[r].rank = p; 897 rrows[r].index = rows[r] - owners[p]; 898 } 899 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 900 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 901 /* Collect flags for rows to be zeroed */ 902 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 903 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 904 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 905 /* Compress and put in row numbers */ 906 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 907 /* zero diagonal part of matrix */ 908 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 909 /* handle off diagonal part of matrix */ 910 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 911 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 912 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 913 for (i=0; i<len; i++) bb[lrows[i]] = 1; 914 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 915 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 916 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 917 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 918 if (x) { 919 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 920 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 921 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 922 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 923 } 924 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 925 /* remove zeroed rows of off diagonal matrix */ 926 ii = aij->i; 927 for (i=0; i<len; i++) { 928 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 929 } 930 /* loop over all elements of off process part of matrix zeroing removed columns*/ 931 if (aij->compressedrow.use) { 932 m = aij->compressedrow.nrows; 933 ii = aij->compressedrow.i; 934 ridx = aij->compressedrow.rindex; 935 for (i=0; i<m; i++) { 936 n = ii[i+1] - ii[i]; 937 aj = aij->j + ii[i]; 938 aa = aij->a + ii[i]; 939 940 for (j=0; j<n; j++) { 941 if (PetscAbsScalar(mask[*aj])) { 942 if (b) bb[*ridx] -= *aa*xx[*aj]; 943 *aa = 0.0; 944 } 945 aa++; 946 aj++; 947 } 948 ridx++; 949 } 950 } else { /* do not use compressed row format */ 951 m = l->B->rmap->n; 952 for (i=0; i<m; i++) { 953 n = ii[i+1] - ii[i]; 954 aj = aij->j + ii[i]; 955 aa = aij->a + ii[i]; 956 for (j=0; j<n; j++) { 957 if (PetscAbsScalar(mask[*aj])) { 958 if (b) bb[i] -= *aa*xx[*aj]; 959 *aa = 0.0; 960 } 961 aa++; 962 aj++; 963 } 964 } 965 } 966 if (x) { 967 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 968 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 969 } 970 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 971 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 972 ierr = PetscFree(lrows);CHKERRQ(ierr); 973 974 /* only change matrix nonzero state if pattern was allowed to be changed */ 975 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 976 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 977 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 978 } 979 PetscFunctionReturn(0); 980 } 981 982 #undef __FUNCT__ 983 #define __FUNCT__ "MatMult_MPIAIJ" 984 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 985 { 986 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 987 PetscErrorCode ierr; 988 PetscInt nt; 989 990 PetscFunctionBegin; 991 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 992 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); 993 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 994 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 995 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 996 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 997 PetscFunctionReturn(0); 998 } 999 1000 #undef __FUNCT__ 1001 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1002 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1003 { 1004 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1005 PetscErrorCode ierr; 1006 1007 PetscFunctionBegin; 1008 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1009 PetscFunctionReturn(0); 1010 } 1011 1012 #undef __FUNCT__ 1013 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1014 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1015 { 1016 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1017 PetscErrorCode ierr; 1018 1019 PetscFunctionBegin; 1020 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1021 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1022 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1023 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1024 PetscFunctionReturn(0); 1025 } 1026 1027 #undef __FUNCT__ 1028 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1029 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1030 { 1031 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1032 PetscErrorCode ierr; 1033 PetscBool merged; 1034 1035 PetscFunctionBegin; 1036 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1037 /* do nondiagonal part */ 1038 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1039 if (!merged) { 1040 /* send it on its way */ 1041 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1042 /* do local part */ 1043 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1044 /* receive remote parts: note this assumes the values are not actually */ 1045 /* added in yy until the next line, */ 1046 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1047 } else { 1048 /* do local part */ 1049 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1050 /* send it on its way */ 1051 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1052 /* values actually were received in the Begin() but we need to call this nop */ 1053 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1054 } 1055 PetscFunctionReturn(0); 1056 } 1057 1058 #undef __FUNCT__ 1059 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1060 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1061 { 1062 MPI_Comm comm; 1063 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1064 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1065 IS Me,Notme; 1066 PetscErrorCode ierr; 1067 PetscInt M,N,first,last,*notme,i; 1068 PetscMPIInt size; 1069 1070 PetscFunctionBegin; 1071 /* Easy test: symmetric diagonal block */ 1072 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1073 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1074 if (!*f) PetscFunctionReturn(0); 1075 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1076 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1077 if (size == 1) PetscFunctionReturn(0); 1078 1079 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1080 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1081 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1082 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1083 for (i=0; i<first; i++) notme[i] = i; 1084 for (i=last; i<M; i++) notme[i-last+first] = i; 1085 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1086 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1087 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1088 Aoff = Aoffs[0]; 1089 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1090 Boff = Boffs[0]; 1091 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1092 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1093 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1094 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1095 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1096 ierr = PetscFree(notme);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1102 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 1107 PetscFunctionBegin; 1108 /* do nondiagonal part */ 1109 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1110 /* send it on its way */ 1111 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1112 /* do local part */ 1113 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1114 /* receive remote parts */ 1115 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 /* 1120 This only works correctly for square matrices where the subblock A->A is the 1121 diagonal block 1122 */ 1123 #undef __FUNCT__ 1124 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1125 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1126 { 1127 PetscErrorCode ierr; 1128 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1129 1130 PetscFunctionBegin; 1131 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1132 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"); 1133 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1134 PetscFunctionReturn(0); 1135 } 1136 1137 #undef __FUNCT__ 1138 #define __FUNCT__ "MatScale_MPIAIJ" 1139 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1140 { 1141 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1142 PetscErrorCode ierr; 1143 1144 PetscFunctionBegin; 1145 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1146 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1147 PetscFunctionReturn(0); 1148 } 1149 1150 #undef __FUNCT__ 1151 #define __FUNCT__ "MatDestroy_MPIAIJ" 1152 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1153 { 1154 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1155 PetscErrorCode ierr; 1156 1157 PetscFunctionBegin; 1158 #if defined(PETSC_USE_LOG) 1159 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1160 #endif 1161 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1162 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1163 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1164 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1165 #if defined(PETSC_USE_CTABLE) 1166 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1167 #else 1168 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1169 #endif 1170 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1171 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1172 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1173 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1174 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1175 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1176 1177 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1178 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1179 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1180 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1181 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1182 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1184 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1185 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1186 #if defined(PETSC_HAVE_ELEMENTAL) 1187 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1188 #endif 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1194 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1195 { 1196 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1197 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1198 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1199 PetscErrorCode ierr; 1200 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1201 int fd; 1202 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1203 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1204 PetscScalar *column_values; 1205 PetscInt message_count,flowcontrolcount; 1206 FILE *file; 1207 1208 PetscFunctionBegin; 1209 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1210 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1211 nz = A->nz + B->nz; 1212 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1213 if (!rank) { 1214 header[0] = MAT_FILE_CLASSID; 1215 header[1] = mat->rmap->N; 1216 header[2] = mat->cmap->N; 1217 1218 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1220 /* get largest number of rows any processor has */ 1221 rlen = mat->rmap->n; 1222 range = mat->rmap->range; 1223 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1224 } else { 1225 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1226 rlen = mat->rmap->n; 1227 } 1228 1229 /* load up the local row counts */ 1230 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1231 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]; 1232 1233 /* store the row lengths to the file */ 1234 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1235 if (!rank) { 1236 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1237 for (i=1; i<size; i++) { 1238 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1239 rlen = range[i+1] - range[i]; 1240 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1241 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1242 } 1243 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1244 } else { 1245 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1246 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1247 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1248 } 1249 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1250 1251 /* load up the local column indices */ 1252 nzmax = nz; /* th processor needs space a largest processor needs */ 1253 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1254 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1255 cnt = 0; 1256 for (i=0; i<mat->rmap->n; i++) { 1257 for (j=B->i[i]; j<B->i[i+1]; j++) { 1258 if ((col = garray[B->j[j]]) > cstart) break; 1259 column_indices[cnt++] = col; 1260 } 1261 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1262 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1263 } 1264 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); 1265 1266 /* store the column indices to the file */ 1267 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1268 if (!rank) { 1269 MPI_Status status; 1270 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1271 for (i=1; i<size; i++) { 1272 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1273 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1274 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1275 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1276 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1277 } 1278 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1279 } else { 1280 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1281 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1282 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1283 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1284 } 1285 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1286 1287 /* load up the local column values */ 1288 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1289 cnt = 0; 1290 for (i=0; i<mat->rmap->n; i++) { 1291 for (j=B->i[i]; j<B->i[i+1]; j++) { 1292 if (garray[B->j[j]] > cstart) break; 1293 column_values[cnt++] = B->a[j]; 1294 } 1295 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1296 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1297 } 1298 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); 1299 1300 /* store the column values to the file */ 1301 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1302 if (!rank) { 1303 MPI_Status status; 1304 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1305 for (i=1; i<size; i++) { 1306 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1307 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1308 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1309 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1310 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1311 } 1312 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1313 } else { 1314 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1315 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1316 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1317 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1318 } 1319 ierr = PetscFree(column_values);CHKERRQ(ierr); 1320 1321 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1322 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 #include <petscdraw.h> 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1329 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1330 { 1331 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1332 PetscErrorCode ierr; 1333 PetscMPIInt rank = aij->rank,size = aij->size; 1334 PetscBool isdraw,iascii,isbinary; 1335 PetscViewer sviewer; 1336 PetscViewerFormat format; 1337 1338 PetscFunctionBegin; 1339 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1340 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1341 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1342 if (iascii) { 1343 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1344 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1345 MatInfo info; 1346 PetscBool inodes; 1347 1348 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1349 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1350 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1351 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1352 if (!inodes) { 1353 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1354 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1355 } else { 1356 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1357 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1358 } 1359 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1360 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1361 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1362 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1363 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1364 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1365 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1366 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1367 PetscFunctionReturn(0); 1368 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1369 PetscInt inodecount,inodelimit,*inodes; 1370 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1371 if (inodes) { 1372 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1373 } else { 1374 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1375 } 1376 PetscFunctionReturn(0); 1377 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1378 PetscFunctionReturn(0); 1379 } 1380 } else if (isbinary) { 1381 if (size == 1) { 1382 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1383 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1384 } else { 1385 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1386 } 1387 PetscFunctionReturn(0); 1388 } else if (isdraw) { 1389 PetscDraw draw; 1390 PetscBool isnull; 1391 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1392 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1393 } 1394 1395 { 1396 /* assemble the entire matrix onto first processor. */ 1397 Mat A; 1398 Mat_SeqAIJ *Aloc; 1399 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1400 MatScalar *a; 1401 1402 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1403 if (!rank) { 1404 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1405 } else { 1406 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1407 } 1408 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1409 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1410 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1411 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1412 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1413 1414 /* copy over the A part */ 1415 Aloc = (Mat_SeqAIJ*)aij->A->data; 1416 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1417 row = mat->rmap->rstart; 1418 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1419 for (i=0; i<m; i++) { 1420 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1421 row++; 1422 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1423 } 1424 aj = Aloc->j; 1425 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1426 1427 /* copy over the B part */ 1428 Aloc = (Mat_SeqAIJ*)aij->B->data; 1429 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1430 row = mat->rmap->rstart; 1431 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1432 ct = cols; 1433 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1434 for (i=0; i<m; i++) { 1435 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1436 row++; 1437 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1438 } 1439 ierr = PetscFree(ct);CHKERRQ(ierr); 1440 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1441 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1442 /* 1443 Everyone has to call to draw the matrix since the graphics waits are 1444 synchronized across all processors that share the PetscDraw object 1445 */ 1446 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1447 if (!rank) { 1448 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1449 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1450 } 1451 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1452 ierr = MatDestroy(&A);CHKERRQ(ierr); 1453 } 1454 PetscFunctionReturn(0); 1455 } 1456 1457 #undef __FUNCT__ 1458 #define __FUNCT__ "MatView_MPIAIJ" 1459 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1460 { 1461 PetscErrorCode ierr; 1462 PetscBool iascii,isdraw,issocket,isbinary; 1463 1464 PetscFunctionBegin; 1465 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1466 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1467 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1468 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1469 if (iascii || isdraw || isbinary || issocket) { 1470 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1471 } 1472 PetscFunctionReturn(0); 1473 } 1474 1475 #undef __FUNCT__ 1476 #define __FUNCT__ "MatSOR_MPIAIJ" 1477 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1478 { 1479 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1480 PetscErrorCode ierr; 1481 Vec bb1 = 0; 1482 PetscBool hasop; 1483 1484 PetscFunctionBegin; 1485 if (flag == SOR_APPLY_UPPER) { 1486 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1487 PetscFunctionReturn(0); 1488 } 1489 1490 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1491 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1492 } 1493 1494 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1495 if (flag & SOR_ZERO_INITIAL_GUESS) { 1496 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1497 its--; 1498 } 1499 1500 while (its--) { 1501 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1502 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1503 1504 /* update rhs: bb1 = bb - B*x */ 1505 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1506 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1507 1508 /* local sweep */ 1509 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1510 } 1511 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1512 if (flag & SOR_ZERO_INITIAL_GUESS) { 1513 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1514 its--; 1515 } 1516 while (its--) { 1517 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1518 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1519 1520 /* update rhs: bb1 = bb - B*x */ 1521 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1522 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1523 1524 /* local sweep */ 1525 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1526 } 1527 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1528 if (flag & SOR_ZERO_INITIAL_GUESS) { 1529 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1530 its--; 1531 } 1532 while (its--) { 1533 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1534 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1535 1536 /* update rhs: bb1 = bb - B*x */ 1537 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1538 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1539 1540 /* local sweep */ 1541 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1542 } 1543 } else if (flag & SOR_EISENSTAT) { 1544 Vec xx1; 1545 1546 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1547 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1548 1549 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1550 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1551 if (!mat->diag) { 1552 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1553 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1554 } 1555 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1556 if (hasop) { 1557 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1558 } else { 1559 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1560 } 1561 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1562 1563 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1564 1565 /* local sweep */ 1566 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1567 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1568 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1569 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1570 1571 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1572 PetscFunctionReturn(0); 1573 } 1574 1575 #undef __FUNCT__ 1576 #define __FUNCT__ "MatPermute_MPIAIJ" 1577 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1578 { 1579 Mat aA,aB,Aperm; 1580 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1581 PetscScalar *aa,*ba; 1582 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1583 PetscSF rowsf,sf; 1584 IS parcolp = NULL; 1585 PetscBool done; 1586 PetscErrorCode ierr; 1587 1588 PetscFunctionBegin; 1589 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1590 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1591 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1592 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1593 1594 /* Invert row permutation to find out where my rows should go */ 1595 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1596 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1597 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1598 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1599 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1600 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1601 1602 /* Invert column permutation to find out where my columns should go */ 1603 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1604 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1605 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1606 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1607 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1608 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1609 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1610 1611 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1612 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1613 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1614 1615 /* Find out where my gcols should go */ 1616 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1617 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1618 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1619 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1620 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1621 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1622 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1623 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1624 1625 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1626 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1627 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1628 for (i=0; i<m; i++) { 1629 PetscInt row = rdest[i],rowner; 1630 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1631 for (j=ai[i]; j<ai[i+1]; j++) { 1632 PetscInt cowner,col = cdest[aj[j]]; 1633 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1634 if (rowner == cowner) dnnz[i]++; 1635 else onnz[i]++; 1636 } 1637 for (j=bi[i]; j<bi[i+1]; j++) { 1638 PetscInt cowner,col = gcdest[bj[j]]; 1639 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1640 if (rowner == cowner) dnnz[i]++; 1641 else onnz[i]++; 1642 } 1643 } 1644 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1645 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1646 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1647 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1648 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1649 1650 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1651 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1652 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1653 for (i=0; i<m; i++) { 1654 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1655 PetscInt j0,rowlen; 1656 rowlen = ai[i+1] - ai[i]; 1657 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1658 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1659 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1660 } 1661 rowlen = bi[i+1] - bi[i]; 1662 for (j0=j=0; j<rowlen; j0=j) { 1663 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1664 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1665 } 1666 } 1667 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1668 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1669 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1670 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1671 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1672 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1673 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1674 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1675 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1676 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1677 *B = Aperm; 1678 PetscFunctionReturn(0); 1679 } 1680 1681 #undef __FUNCT__ 1682 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1683 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1684 { 1685 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1686 Mat A = mat->A,B = mat->B; 1687 PetscErrorCode ierr; 1688 PetscReal isend[5],irecv[5]; 1689 1690 PetscFunctionBegin; 1691 info->block_size = 1.0; 1692 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1693 1694 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1695 isend[3] = info->memory; isend[4] = info->mallocs; 1696 1697 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1698 1699 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1700 isend[3] += info->memory; isend[4] += info->mallocs; 1701 if (flag == MAT_LOCAL) { 1702 info->nz_used = isend[0]; 1703 info->nz_allocated = isend[1]; 1704 info->nz_unneeded = isend[2]; 1705 info->memory = isend[3]; 1706 info->mallocs = isend[4]; 1707 } else if (flag == MAT_GLOBAL_MAX) { 1708 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1709 1710 info->nz_used = irecv[0]; 1711 info->nz_allocated = irecv[1]; 1712 info->nz_unneeded = irecv[2]; 1713 info->memory = irecv[3]; 1714 info->mallocs = irecv[4]; 1715 } else if (flag == MAT_GLOBAL_SUM) { 1716 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1717 1718 info->nz_used = irecv[0]; 1719 info->nz_allocated = irecv[1]; 1720 info->nz_unneeded = irecv[2]; 1721 info->memory = irecv[3]; 1722 info->mallocs = irecv[4]; 1723 } 1724 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1725 info->fill_ratio_needed = 0; 1726 info->factor_mallocs = 0; 1727 PetscFunctionReturn(0); 1728 } 1729 1730 #undef __FUNCT__ 1731 #define __FUNCT__ "MatSetOption_MPIAIJ" 1732 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1733 { 1734 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1735 PetscErrorCode ierr; 1736 1737 PetscFunctionBegin; 1738 switch (op) { 1739 case MAT_NEW_NONZERO_LOCATIONS: 1740 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1741 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1742 case MAT_KEEP_NONZERO_PATTERN: 1743 case MAT_NEW_NONZERO_LOCATION_ERR: 1744 case MAT_USE_INODES: 1745 case MAT_IGNORE_ZERO_ENTRIES: 1746 MatCheckPreallocated(A,1); 1747 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1748 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1749 break; 1750 case MAT_ROW_ORIENTED: 1751 a->roworiented = flg; 1752 1753 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1754 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1755 break; 1756 case MAT_NEW_DIAGONALS: 1757 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1758 break; 1759 case MAT_IGNORE_OFF_PROC_ENTRIES: 1760 a->donotstash = flg; 1761 break; 1762 case MAT_SPD: 1763 A->spd_set = PETSC_TRUE; 1764 A->spd = flg; 1765 if (flg) { 1766 A->symmetric = PETSC_TRUE; 1767 A->structurally_symmetric = PETSC_TRUE; 1768 A->symmetric_set = PETSC_TRUE; 1769 A->structurally_symmetric_set = PETSC_TRUE; 1770 } 1771 break; 1772 case MAT_SYMMETRIC: 1773 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1774 break; 1775 case MAT_STRUCTURALLY_SYMMETRIC: 1776 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1777 break; 1778 case MAT_HERMITIAN: 1779 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1780 break; 1781 case MAT_SYMMETRY_ETERNAL: 1782 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1783 break; 1784 default: 1785 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1786 } 1787 PetscFunctionReturn(0); 1788 } 1789 1790 #undef __FUNCT__ 1791 #define __FUNCT__ "MatGetRow_MPIAIJ" 1792 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1793 { 1794 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1795 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1796 PetscErrorCode ierr; 1797 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1798 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1799 PetscInt *cmap,*idx_p; 1800 1801 PetscFunctionBegin; 1802 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1803 mat->getrowactive = PETSC_TRUE; 1804 1805 if (!mat->rowvalues && (idx || v)) { 1806 /* 1807 allocate enough space to hold information from the longest row. 1808 */ 1809 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1810 PetscInt max = 1,tmp; 1811 for (i=0; i<matin->rmap->n; i++) { 1812 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1813 if (max < tmp) max = tmp; 1814 } 1815 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1816 } 1817 1818 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1819 lrow = row - rstart; 1820 1821 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1822 if (!v) {pvA = 0; pvB = 0;} 1823 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1824 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1825 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1826 nztot = nzA + nzB; 1827 1828 cmap = mat->garray; 1829 if (v || idx) { 1830 if (nztot) { 1831 /* Sort by increasing column numbers, assuming A and B already sorted */ 1832 PetscInt imark = -1; 1833 if (v) { 1834 *v = v_p = mat->rowvalues; 1835 for (i=0; i<nzB; i++) { 1836 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1837 else break; 1838 } 1839 imark = i; 1840 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1841 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1842 } 1843 if (idx) { 1844 *idx = idx_p = mat->rowindices; 1845 if (imark > -1) { 1846 for (i=0; i<imark; i++) { 1847 idx_p[i] = cmap[cworkB[i]]; 1848 } 1849 } else { 1850 for (i=0; i<nzB; i++) { 1851 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1852 else break; 1853 } 1854 imark = i; 1855 } 1856 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1857 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1858 } 1859 } else { 1860 if (idx) *idx = 0; 1861 if (v) *v = 0; 1862 } 1863 } 1864 *nz = nztot; 1865 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1866 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1867 PetscFunctionReturn(0); 1868 } 1869 1870 #undef __FUNCT__ 1871 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1872 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1873 { 1874 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1875 1876 PetscFunctionBegin; 1877 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1878 aij->getrowactive = PETSC_FALSE; 1879 PetscFunctionReturn(0); 1880 } 1881 1882 #undef __FUNCT__ 1883 #define __FUNCT__ "MatNorm_MPIAIJ" 1884 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1885 { 1886 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1887 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1888 PetscErrorCode ierr; 1889 PetscInt i,j,cstart = mat->cmap->rstart; 1890 PetscReal sum = 0.0; 1891 MatScalar *v; 1892 1893 PetscFunctionBegin; 1894 if (aij->size == 1) { 1895 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1896 } else { 1897 if (type == NORM_FROBENIUS) { 1898 v = amat->a; 1899 for (i=0; i<amat->nz; i++) { 1900 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1901 } 1902 v = bmat->a; 1903 for (i=0; i<bmat->nz; i++) { 1904 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1905 } 1906 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1907 *norm = PetscSqrtReal(*norm); 1908 } else if (type == NORM_1) { /* max column norm */ 1909 PetscReal *tmp,*tmp2; 1910 PetscInt *jj,*garray = aij->garray; 1911 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1912 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1913 *norm = 0.0; 1914 v = amat->a; jj = amat->j; 1915 for (j=0; j<amat->nz; j++) { 1916 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1917 } 1918 v = bmat->a; jj = bmat->j; 1919 for (j=0; j<bmat->nz; j++) { 1920 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1921 } 1922 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1923 for (j=0; j<mat->cmap->N; j++) { 1924 if (tmp2[j] > *norm) *norm = tmp2[j]; 1925 } 1926 ierr = PetscFree(tmp);CHKERRQ(ierr); 1927 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1928 } else if (type == NORM_INFINITY) { /* max row norm */ 1929 PetscReal ntemp = 0.0; 1930 for (j=0; j<aij->A->rmap->n; j++) { 1931 v = amat->a + amat->i[j]; 1932 sum = 0.0; 1933 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1934 sum += PetscAbsScalar(*v); v++; 1935 } 1936 v = bmat->a + bmat->i[j]; 1937 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1938 sum += PetscAbsScalar(*v); v++; 1939 } 1940 if (sum > ntemp) ntemp = sum; 1941 } 1942 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1943 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1944 } 1945 PetscFunctionReturn(0); 1946 } 1947 1948 #undef __FUNCT__ 1949 #define __FUNCT__ "MatTranspose_MPIAIJ" 1950 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1951 { 1952 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1953 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1954 PetscErrorCode ierr; 1955 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1956 PetscInt cstart = A->cmap->rstart,ncol; 1957 Mat B; 1958 MatScalar *array; 1959 1960 PetscFunctionBegin; 1961 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1962 1963 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1964 ai = Aloc->i; aj = Aloc->j; 1965 bi = Bloc->i; bj = Bloc->j; 1966 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1967 PetscInt *d_nnz,*g_nnz,*o_nnz; 1968 PetscSFNode *oloc; 1969 PETSC_UNUSED PetscSF sf; 1970 1971 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1972 /* compute d_nnz for preallocation */ 1973 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1974 for (i=0; i<ai[ma]; i++) { 1975 d_nnz[aj[i]]++; 1976 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1977 } 1978 /* compute local off-diagonal contributions */ 1979 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1980 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1981 /* map those to global */ 1982 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1983 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1984 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1985 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1986 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1987 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1988 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1989 1990 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1991 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1992 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1993 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1994 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1995 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1996 } else { 1997 B = *matout; 1998 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1999 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2000 } 2001 2002 /* copy over the A part */ 2003 array = Aloc->a; 2004 row = A->rmap->rstart; 2005 for (i=0; i<ma; i++) { 2006 ncol = ai[i+1]-ai[i]; 2007 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2008 row++; 2009 array += ncol; aj += ncol; 2010 } 2011 aj = Aloc->j; 2012 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2013 2014 /* copy over the B part */ 2015 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2016 array = Bloc->a; 2017 row = A->rmap->rstart; 2018 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2019 cols_tmp = cols; 2020 for (i=0; i<mb; i++) { 2021 ncol = bi[i+1]-bi[i]; 2022 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2023 row++; 2024 array += ncol; cols_tmp += ncol; 2025 } 2026 ierr = PetscFree(cols);CHKERRQ(ierr); 2027 2028 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2029 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2030 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2031 *matout = B; 2032 } else { 2033 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2034 } 2035 PetscFunctionReturn(0); 2036 } 2037 2038 #undef __FUNCT__ 2039 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2040 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2041 { 2042 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2043 Mat a = aij->A,b = aij->B; 2044 PetscErrorCode ierr; 2045 PetscInt s1,s2,s3; 2046 2047 PetscFunctionBegin; 2048 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2049 if (rr) { 2050 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2051 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2052 /* Overlap communication with computation. */ 2053 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2054 } 2055 if (ll) { 2056 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2057 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2058 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2059 } 2060 /* scale the diagonal block */ 2061 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2062 2063 if (rr) { 2064 /* Do a scatter end and then right scale the off-diagonal block */ 2065 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2066 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2067 } 2068 PetscFunctionReturn(0); 2069 } 2070 2071 #undef __FUNCT__ 2072 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2073 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2074 { 2075 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2076 PetscErrorCode ierr; 2077 2078 PetscFunctionBegin; 2079 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2080 PetscFunctionReturn(0); 2081 } 2082 2083 #undef __FUNCT__ 2084 #define __FUNCT__ "MatEqual_MPIAIJ" 2085 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2086 { 2087 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2088 Mat a,b,c,d; 2089 PetscBool flg; 2090 PetscErrorCode ierr; 2091 2092 PetscFunctionBegin; 2093 a = matA->A; b = matA->B; 2094 c = matB->A; d = matB->B; 2095 2096 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2097 if (flg) { 2098 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2099 } 2100 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2101 PetscFunctionReturn(0); 2102 } 2103 2104 #undef __FUNCT__ 2105 #define __FUNCT__ "MatCopy_MPIAIJ" 2106 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2107 { 2108 PetscErrorCode ierr; 2109 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2110 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2111 2112 PetscFunctionBegin; 2113 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2114 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2115 /* because of the column compression in the off-processor part of the matrix a->B, 2116 the number of columns in a->B and b->B may be different, hence we cannot call 2117 the MatCopy() directly on the two parts. If need be, we can provide a more 2118 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2119 then copying the submatrices */ 2120 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2121 } else { 2122 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2123 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2124 } 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatSetUp_MPIAIJ" 2130 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2131 { 2132 PetscErrorCode ierr; 2133 2134 PetscFunctionBegin; 2135 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2136 PetscFunctionReturn(0); 2137 } 2138 2139 /* 2140 Computes the number of nonzeros per row needed for preallocation when X and Y 2141 have different nonzero structure. 2142 */ 2143 #undef __FUNCT__ 2144 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2145 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) 2146 { 2147 PetscInt i,j,k,nzx,nzy; 2148 2149 PetscFunctionBegin; 2150 /* Set the number of nonzeros in the new matrix */ 2151 for (i=0; i<m; i++) { 2152 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2153 nzx = xi[i+1] - xi[i]; 2154 nzy = yi[i+1] - yi[i]; 2155 nnz[i] = 0; 2156 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2157 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2158 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2159 nnz[i]++; 2160 } 2161 for (; k<nzy; k++) nnz[i]++; 2162 } 2163 PetscFunctionReturn(0); 2164 } 2165 2166 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2169 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2170 { 2171 PetscErrorCode ierr; 2172 PetscInt m = Y->rmap->N; 2173 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2174 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2175 2176 PetscFunctionBegin; 2177 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2178 PetscFunctionReturn(0); 2179 } 2180 2181 #undef __FUNCT__ 2182 #define __FUNCT__ "MatAXPY_MPIAIJ" 2183 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2184 { 2185 PetscErrorCode ierr; 2186 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2187 PetscBLASInt bnz,one=1; 2188 Mat_SeqAIJ *x,*y; 2189 2190 PetscFunctionBegin; 2191 if (str == SAME_NONZERO_PATTERN) { 2192 PetscScalar alpha = a; 2193 x = (Mat_SeqAIJ*)xx->A->data; 2194 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2195 y = (Mat_SeqAIJ*)yy->A->data; 2196 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2197 x = (Mat_SeqAIJ*)xx->B->data; 2198 y = (Mat_SeqAIJ*)yy->B->data; 2199 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2200 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2201 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2202 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2203 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2204 } else { 2205 Mat B; 2206 PetscInt *nnz_d,*nnz_o; 2207 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2208 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2209 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2210 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2211 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2212 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2213 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2214 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2215 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2216 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2217 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2218 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2219 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2220 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2221 } 2222 PetscFunctionReturn(0); 2223 } 2224 2225 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2226 2227 #undef __FUNCT__ 2228 #define __FUNCT__ "MatConjugate_MPIAIJ" 2229 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2230 { 2231 #if defined(PETSC_USE_COMPLEX) 2232 PetscErrorCode ierr; 2233 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2234 2235 PetscFunctionBegin; 2236 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2237 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2238 #else 2239 PetscFunctionBegin; 2240 #endif 2241 PetscFunctionReturn(0); 2242 } 2243 2244 #undef __FUNCT__ 2245 #define __FUNCT__ "MatRealPart_MPIAIJ" 2246 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2247 { 2248 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2249 PetscErrorCode ierr; 2250 2251 PetscFunctionBegin; 2252 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2253 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2259 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2260 { 2261 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2262 PetscErrorCode ierr; 2263 2264 PetscFunctionBegin; 2265 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2266 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2267 PetscFunctionReturn(0); 2268 } 2269 2270 #if defined(PETSC_HAVE_PBGL) 2271 2272 #include <boost/parallel/mpi/bsp_process_group.hpp> 2273 #include <boost/graph/distributed/ilu_default_graph.hpp> 2274 #include <boost/graph/distributed/ilu_0_block.hpp> 2275 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2276 #include <boost/graph/distributed/petsc/interface.hpp> 2277 #include <boost/multi_array.hpp> 2278 #include <boost/parallel/distributed_property_map->hpp> 2279 2280 #undef __FUNCT__ 2281 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2282 /* 2283 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2284 */ 2285 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2286 { 2287 namespace petsc = boost::distributed::petsc; 2288 2289 namespace graph_dist = boost::graph::distributed; 2290 using boost::graph::distributed::ilu_default::process_group_type; 2291 using boost::graph::ilu_permuted; 2292 2293 PetscBool row_identity, col_identity; 2294 PetscContainer c; 2295 PetscInt m, n, M, N; 2296 PetscErrorCode ierr; 2297 2298 PetscFunctionBegin; 2299 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2300 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2301 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2302 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2303 2304 process_group_type pg; 2305 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2306 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2307 lgraph_type& level_graph = *lgraph_p; 2308 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2309 2310 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2311 ilu_permuted(level_graph); 2312 2313 /* put together the new matrix */ 2314 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2315 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2316 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2317 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2318 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2319 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2320 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2321 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2322 2323 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2324 ierr = PetscContainerSetPointer(c, lgraph_p); 2325 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2326 ierr = PetscContainerDestroy(&c); 2327 PetscFunctionReturn(0); 2328 } 2329 2330 #undef __FUNCT__ 2331 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2332 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2333 { 2334 PetscFunctionBegin; 2335 PetscFunctionReturn(0); 2336 } 2337 2338 #undef __FUNCT__ 2339 #define __FUNCT__ "MatSolve_MPIAIJ" 2340 /* 2341 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2342 */ 2343 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2344 { 2345 namespace graph_dist = boost::graph::distributed; 2346 2347 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2348 lgraph_type *lgraph_p; 2349 PetscContainer c; 2350 PetscErrorCode ierr; 2351 2352 PetscFunctionBegin; 2353 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2354 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2355 ierr = VecCopy(b, x);CHKERRQ(ierr); 2356 2357 PetscScalar *array_x; 2358 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2359 PetscInt sx; 2360 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2361 2362 PetscScalar *array_b; 2363 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2364 PetscInt sb; 2365 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2366 2367 lgraph_type& level_graph = *lgraph_p; 2368 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2369 2370 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2371 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2372 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2373 2374 typedef boost::iterator_property_map<array_ref_type::iterator, 2375 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2376 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2377 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2378 2379 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2380 PetscFunctionReturn(0); 2381 } 2382 #endif 2383 2384 #undef __FUNCT__ 2385 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2386 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2387 { 2388 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2389 PetscErrorCode ierr; 2390 PetscInt i,*idxb = 0; 2391 PetscScalar *va,*vb; 2392 Vec vtmp; 2393 2394 PetscFunctionBegin; 2395 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2396 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2397 if (idx) { 2398 for (i=0; i<A->rmap->n; i++) { 2399 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2400 } 2401 } 2402 2403 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2404 if (idx) { 2405 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2406 } 2407 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2408 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2409 2410 for (i=0; i<A->rmap->n; i++) { 2411 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2412 va[i] = vb[i]; 2413 if (idx) idx[i] = a->garray[idxb[i]]; 2414 } 2415 } 2416 2417 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2418 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2419 ierr = PetscFree(idxb);CHKERRQ(ierr); 2420 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 #undef __FUNCT__ 2425 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2426 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2427 { 2428 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2429 PetscErrorCode ierr; 2430 PetscInt i,*idxb = 0; 2431 PetscScalar *va,*vb; 2432 Vec vtmp; 2433 2434 PetscFunctionBegin; 2435 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2436 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2437 if (idx) { 2438 for (i=0; i<A->cmap->n; i++) { 2439 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2440 } 2441 } 2442 2443 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2444 if (idx) { 2445 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2446 } 2447 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2448 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2449 2450 for (i=0; i<A->rmap->n; i++) { 2451 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2452 va[i] = vb[i]; 2453 if (idx) idx[i] = a->garray[idxb[i]]; 2454 } 2455 } 2456 2457 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2458 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2459 ierr = PetscFree(idxb);CHKERRQ(ierr); 2460 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2466 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2467 { 2468 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2469 PetscInt n = A->rmap->n; 2470 PetscInt cstart = A->cmap->rstart; 2471 PetscInt *cmap = mat->garray; 2472 PetscInt *diagIdx, *offdiagIdx; 2473 Vec diagV, offdiagV; 2474 PetscScalar *a, *diagA, *offdiagA; 2475 PetscInt r; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2480 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2481 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2482 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2483 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2484 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2485 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2486 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2487 for (r = 0; r < n; ++r) { 2488 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2489 a[r] = diagA[r]; 2490 idx[r] = cstart + diagIdx[r]; 2491 } else { 2492 a[r] = offdiagA[r]; 2493 idx[r] = cmap[offdiagIdx[r]]; 2494 } 2495 } 2496 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2497 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2498 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2499 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2500 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2501 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2502 PetscFunctionReturn(0); 2503 } 2504 2505 #undef __FUNCT__ 2506 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2507 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2508 { 2509 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2510 PetscInt n = A->rmap->n; 2511 PetscInt cstart = A->cmap->rstart; 2512 PetscInt *cmap = mat->garray; 2513 PetscInt *diagIdx, *offdiagIdx; 2514 Vec diagV, offdiagV; 2515 PetscScalar *a, *diagA, *offdiagA; 2516 PetscInt r; 2517 PetscErrorCode ierr; 2518 2519 PetscFunctionBegin; 2520 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2521 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2522 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2523 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2524 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2525 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2526 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2527 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2528 for (r = 0; r < n; ++r) { 2529 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2530 a[r] = diagA[r]; 2531 idx[r] = cstart + diagIdx[r]; 2532 } else { 2533 a[r] = offdiagA[r]; 2534 idx[r] = cmap[offdiagIdx[r]]; 2535 } 2536 } 2537 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2538 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2539 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2540 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2541 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2542 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2543 PetscFunctionReturn(0); 2544 } 2545 2546 #undef __FUNCT__ 2547 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2548 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2549 { 2550 PetscErrorCode ierr; 2551 Mat *dummy; 2552 2553 PetscFunctionBegin; 2554 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2555 *newmat = *dummy; 2556 ierr = PetscFree(dummy);CHKERRQ(ierr); 2557 PetscFunctionReturn(0); 2558 } 2559 2560 #undef __FUNCT__ 2561 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2562 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2563 { 2564 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2565 PetscErrorCode ierr; 2566 2567 PetscFunctionBegin; 2568 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 #undef __FUNCT__ 2573 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2574 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2575 { 2576 PetscErrorCode ierr; 2577 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2578 2579 PetscFunctionBegin; 2580 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2581 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2582 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2583 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2584 PetscFunctionReturn(0); 2585 } 2586 2587 #undef __FUNCT__ 2588 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ" 2589 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2590 { 2591 PetscFunctionBegin; 2592 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2593 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2594 PetscFunctionReturn(0); 2595 } 2596 2597 #undef __FUNCT__ 2598 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap" 2599 /*@ 2600 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2601 2602 Collective on Mat 2603 2604 Input Parameters: 2605 + A - the matrix 2606 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2607 2608 @*/ 2609 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2610 { 2611 PetscErrorCode ierr; 2612 2613 PetscFunctionBegin; 2614 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2615 PetscFunctionReturn(0); 2616 } 2617 2618 #undef __FUNCT__ 2619 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2620 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptions *PetscOptionsObject,Mat A) 2621 { 2622 PetscErrorCode ierr; 2623 PetscBool sc = PETSC_FALSE,flg; 2624 2625 PetscFunctionBegin; 2626 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2627 ierr = PetscObjectOptionsBegin((PetscObject)A); 2628 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2629 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2630 if (flg) { 2631 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2632 } 2633 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2634 PetscFunctionReturn(0); 2635 } 2636 2637 #undef __FUNCT__ 2638 #define __FUNCT__ "MatShift_MPIAIJ" 2639 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2640 { 2641 PetscErrorCode ierr; 2642 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2643 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data,*bij = (Mat_SeqAIJ*)maij->B->data; 2644 2645 PetscFunctionBegin; 2646 if (!aij->nz && !bij->nz) { 2647 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2648 } 2649 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2650 PetscFunctionReturn(0); 2651 } 2652 2653 /* -------------------------------------------------------------------*/ 2654 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2655 MatGetRow_MPIAIJ, 2656 MatRestoreRow_MPIAIJ, 2657 MatMult_MPIAIJ, 2658 /* 4*/ MatMultAdd_MPIAIJ, 2659 MatMultTranspose_MPIAIJ, 2660 MatMultTransposeAdd_MPIAIJ, 2661 #if defined(PETSC_HAVE_PBGL) 2662 MatSolve_MPIAIJ, 2663 #else 2664 0, 2665 #endif 2666 0, 2667 0, 2668 /*10*/ 0, 2669 0, 2670 0, 2671 MatSOR_MPIAIJ, 2672 MatTranspose_MPIAIJ, 2673 /*15*/ MatGetInfo_MPIAIJ, 2674 MatEqual_MPIAIJ, 2675 MatGetDiagonal_MPIAIJ, 2676 MatDiagonalScale_MPIAIJ, 2677 MatNorm_MPIAIJ, 2678 /*20*/ MatAssemblyBegin_MPIAIJ, 2679 MatAssemblyEnd_MPIAIJ, 2680 MatSetOption_MPIAIJ, 2681 MatZeroEntries_MPIAIJ, 2682 /*24*/ MatZeroRows_MPIAIJ, 2683 0, 2684 #if defined(PETSC_HAVE_PBGL) 2685 0, 2686 #else 2687 0, 2688 #endif 2689 0, 2690 0, 2691 /*29*/ MatSetUp_MPIAIJ, 2692 #if defined(PETSC_HAVE_PBGL) 2693 0, 2694 #else 2695 0, 2696 #endif 2697 0, 2698 0, 2699 0, 2700 /*34*/ MatDuplicate_MPIAIJ, 2701 0, 2702 0, 2703 0, 2704 0, 2705 /*39*/ MatAXPY_MPIAIJ, 2706 MatGetSubMatrices_MPIAIJ, 2707 MatIncreaseOverlap_MPIAIJ, 2708 MatGetValues_MPIAIJ, 2709 MatCopy_MPIAIJ, 2710 /*44*/ MatGetRowMax_MPIAIJ, 2711 MatScale_MPIAIJ, 2712 MatShift_MPIAIJ, 2713 MatDiagonalSet_MPIAIJ, 2714 MatZeroRowsColumns_MPIAIJ, 2715 /*49*/ MatSetRandom_MPIAIJ, 2716 0, 2717 0, 2718 0, 2719 0, 2720 /*54*/ MatFDColoringCreate_MPIXAIJ, 2721 0, 2722 MatSetUnfactored_MPIAIJ, 2723 MatPermute_MPIAIJ, 2724 0, 2725 /*59*/ MatGetSubMatrix_MPIAIJ, 2726 MatDestroy_MPIAIJ, 2727 MatView_MPIAIJ, 2728 0, 2729 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2730 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2731 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2732 0, 2733 0, 2734 0, 2735 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2736 MatGetRowMinAbs_MPIAIJ, 2737 0, 2738 MatSetColoring_MPIAIJ, 2739 0, 2740 MatSetValuesAdifor_MPIAIJ, 2741 /*75*/ MatFDColoringApply_AIJ, 2742 MatSetFromOptions_MPIAIJ, 2743 0, 2744 0, 2745 MatFindZeroDiagonals_MPIAIJ, 2746 /*80*/ 0, 2747 0, 2748 0, 2749 /*83*/ MatLoad_MPIAIJ, 2750 0, 2751 0, 2752 0, 2753 0, 2754 0, 2755 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2756 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2757 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2758 MatPtAP_MPIAIJ_MPIAIJ, 2759 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2760 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2761 0, 2762 0, 2763 0, 2764 0, 2765 /*99*/ 0, 2766 0, 2767 0, 2768 MatConjugate_MPIAIJ, 2769 0, 2770 /*104*/MatSetValuesRow_MPIAIJ, 2771 MatRealPart_MPIAIJ, 2772 MatImaginaryPart_MPIAIJ, 2773 0, 2774 0, 2775 /*109*/0, 2776 0, 2777 MatGetRowMin_MPIAIJ, 2778 0, 2779 0, 2780 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2781 0, 2782 0, 2783 0, 2784 0, 2785 /*119*/0, 2786 0, 2787 0, 2788 0, 2789 MatGetMultiProcBlock_MPIAIJ, 2790 /*124*/MatFindNonzeroRows_MPIAIJ, 2791 MatGetColumnNorms_MPIAIJ, 2792 MatInvertBlockDiagonal_MPIAIJ, 2793 0, 2794 MatGetSubMatricesParallel_MPIAIJ, 2795 /*129*/0, 2796 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2797 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2798 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2799 0, 2800 /*134*/0, 2801 0, 2802 0, 2803 0, 2804 0, 2805 /*139*/0, 2806 0, 2807 0, 2808 MatFDColoringSetUp_MPIXAIJ, 2809 MatFindOffBlockDiagonalEntries_MPIAIJ, 2810 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2811 }; 2812 2813 /* ----------------------------------------------------------------------------------------*/ 2814 2815 #undef __FUNCT__ 2816 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2817 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2818 { 2819 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2820 PetscErrorCode ierr; 2821 2822 PetscFunctionBegin; 2823 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2824 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2825 PetscFunctionReturn(0); 2826 } 2827 2828 #undef __FUNCT__ 2829 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2830 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2831 { 2832 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2833 PetscErrorCode ierr; 2834 2835 PetscFunctionBegin; 2836 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2837 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2838 PetscFunctionReturn(0); 2839 } 2840 2841 #undef __FUNCT__ 2842 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2843 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2844 { 2845 Mat_MPIAIJ *b; 2846 PetscErrorCode ierr; 2847 2848 PetscFunctionBegin; 2849 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2850 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2851 b = (Mat_MPIAIJ*)B->data; 2852 2853 if (!B->preallocated) { 2854 /* Explicitly create 2 MATSEQAIJ matrices. */ 2855 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2856 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2857 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2858 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2859 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2860 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2861 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2862 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2863 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2864 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2865 } 2866 2867 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2868 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2869 B->preallocated = PETSC_TRUE; 2870 PetscFunctionReturn(0); 2871 } 2872 2873 #undef __FUNCT__ 2874 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2875 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2876 { 2877 Mat mat; 2878 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2879 PetscErrorCode ierr; 2880 2881 PetscFunctionBegin; 2882 *newmat = 0; 2883 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2884 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2885 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2886 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2887 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2888 a = (Mat_MPIAIJ*)mat->data; 2889 2890 mat->factortype = matin->factortype; 2891 mat->assembled = PETSC_TRUE; 2892 mat->insertmode = NOT_SET_VALUES; 2893 mat->preallocated = PETSC_TRUE; 2894 2895 a->size = oldmat->size; 2896 a->rank = oldmat->rank; 2897 a->donotstash = oldmat->donotstash; 2898 a->roworiented = oldmat->roworiented; 2899 a->rowindices = 0; 2900 a->rowvalues = 0; 2901 a->getrowactive = PETSC_FALSE; 2902 2903 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2904 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2905 2906 if (oldmat->colmap) { 2907 #if defined(PETSC_USE_CTABLE) 2908 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2909 #else 2910 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2911 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2912 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2913 #endif 2914 } else a->colmap = 0; 2915 if (oldmat->garray) { 2916 PetscInt len; 2917 len = oldmat->B->cmap->n; 2918 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2919 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2920 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2921 } else a->garray = 0; 2922 2923 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2924 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2925 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2926 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2927 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2928 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2929 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2930 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2931 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2932 *newmat = mat; 2933 PetscFunctionReturn(0); 2934 } 2935 2936 2937 2938 #undef __FUNCT__ 2939 #define __FUNCT__ "MatLoad_MPIAIJ" 2940 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2941 { 2942 PetscScalar *vals,*svals; 2943 MPI_Comm comm; 2944 PetscErrorCode ierr; 2945 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2946 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2947 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2948 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2949 PetscInt cend,cstart,n,*rowners; 2950 int fd; 2951 PetscInt bs = newMat->rmap->bs; 2952 2953 PetscFunctionBegin; 2954 /* force binary viewer to load .info file if it has not yet done so */ 2955 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2956 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2957 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2958 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2959 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2960 if (!rank) { 2961 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2962 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2963 } 2964 2965 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2966 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2967 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2968 if (bs < 0) bs = 1; 2969 2970 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2971 M = header[1]; N = header[2]; 2972 2973 /* If global sizes are set, check if they are consistent with that given in the file */ 2974 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); 2975 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); 2976 2977 /* determine ownership of all (block) rows */ 2978 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2979 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2980 else m = newMat->rmap->n; /* Set by user */ 2981 2982 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2983 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2984 2985 /* First process needs enough room for process with most rows */ 2986 if (!rank) { 2987 mmax = rowners[1]; 2988 for (i=2; i<=size; i++) { 2989 mmax = PetscMax(mmax, rowners[i]); 2990 } 2991 } else mmax = -1; /* unused, but compilers complain */ 2992 2993 rowners[0] = 0; 2994 for (i=2; i<=size; i++) { 2995 rowners[i] += rowners[i-1]; 2996 } 2997 rstart = rowners[rank]; 2998 rend = rowners[rank+1]; 2999 3000 /* distribute row lengths to all processors */ 3001 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 3002 if (!rank) { 3003 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3004 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3005 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3006 for (j=0; j<m; j++) { 3007 procsnz[0] += ourlens[j]; 3008 } 3009 for (i=1; i<size; i++) { 3010 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3011 /* calculate the number of nonzeros on each processor */ 3012 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3013 procsnz[i] += rowlengths[j]; 3014 } 3015 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3016 } 3017 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3018 } else { 3019 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3020 } 3021 3022 if (!rank) { 3023 /* determine max buffer needed and allocate it */ 3024 maxnz = 0; 3025 for (i=0; i<size; i++) { 3026 maxnz = PetscMax(maxnz,procsnz[i]); 3027 } 3028 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3029 3030 /* read in my part of the matrix column indices */ 3031 nz = procsnz[0]; 3032 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3033 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3034 3035 /* read in every one elses and ship off */ 3036 for (i=1; i<size; i++) { 3037 nz = procsnz[i]; 3038 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3039 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3040 } 3041 ierr = PetscFree(cols);CHKERRQ(ierr); 3042 } else { 3043 /* determine buffer space needed for message */ 3044 nz = 0; 3045 for (i=0; i<m; i++) { 3046 nz += ourlens[i]; 3047 } 3048 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3049 3050 /* receive message of column indices*/ 3051 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3052 } 3053 3054 /* determine column ownership if matrix is not square */ 3055 if (N != M) { 3056 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3057 else n = newMat->cmap->n; 3058 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3059 cstart = cend - n; 3060 } else { 3061 cstart = rstart; 3062 cend = rend; 3063 n = cend - cstart; 3064 } 3065 3066 /* loop over local rows, determining number of off diagonal entries */ 3067 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3068 jj = 0; 3069 for (i=0; i<m; i++) { 3070 for (j=0; j<ourlens[i]; j++) { 3071 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3072 jj++; 3073 } 3074 } 3075 3076 for (i=0; i<m; i++) { 3077 ourlens[i] -= offlens[i]; 3078 } 3079 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3080 3081 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3082 3083 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3084 3085 for (i=0; i<m; i++) { 3086 ourlens[i] += offlens[i]; 3087 } 3088 3089 if (!rank) { 3090 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3091 3092 /* read in my part of the matrix numerical values */ 3093 nz = procsnz[0]; 3094 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3095 3096 /* insert into matrix */ 3097 jj = rstart; 3098 smycols = mycols; 3099 svals = vals; 3100 for (i=0; i<m; i++) { 3101 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3102 smycols += ourlens[i]; 3103 svals += ourlens[i]; 3104 jj++; 3105 } 3106 3107 /* read in other processors and ship out */ 3108 for (i=1; i<size; i++) { 3109 nz = procsnz[i]; 3110 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3111 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3112 } 3113 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3114 } else { 3115 /* receive numeric values */ 3116 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3117 3118 /* receive message of values*/ 3119 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3120 3121 /* insert into matrix */ 3122 jj = rstart; 3123 smycols = mycols; 3124 svals = vals; 3125 for (i=0; i<m; i++) { 3126 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3127 smycols += ourlens[i]; 3128 svals += ourlens[i]; 3129 jj++; 3130 } 3131 } 3132 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3133 ierr = PetscFree(vals);CHKERRQ(ierr); 3134 ierr = PetscFree(mycols);CHKERRQ(ierr); 3135 ierr = PetscFree(rowners);CHKERRQ(ierr); 3136 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3137 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3138 PetscFunctionReturn(0); 3139 } 3140 3141 #undef __FUNCT__ 3142 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3143 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3144 { 3145 PetscErrorCode ierr; 3146 IS iscol_local; 3147 PetscInt csize; 3148 3149 PetscFunctionBegin; 3150 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3151 if (call == MAT_REUSE_MATRIX) { 3152 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3153 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3154 } else { 3155 PetscInt cbs; 3156 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3157 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3158 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3159 } 3160 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3161 if (call == MAT_INITIAL_MATRIX) { 3162 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3163 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3164 } 3165 PetscFunctionReturn(0); 3166 } 3167 3168 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3169 #undef __FUNCT__ 3170 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3171 /* 3172 Not great since it makes two copies of the submatrix, first an SeqAIJ 3173 in local and then by concatenating the local matrices the end result. 3174 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3175 3176 Note: This requires a sequential iscol with all indices. 3177 */ 3178 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3179 { 3180 PetscErrorCode ierr; 3181 PetscMPIInt rank,size; 3182 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3183 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3184 PetscBool allcolumns, colflag; 3185 Mat M,Mreuse; 3186 MatScalar *vwork,*aa; 3187 MPI_Comm comm; 3188 Mat_SeqAIJ *aij; 3189 3190 PetscFunctionBegin; 3191 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3192 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3193 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3194 3195 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3196 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3197 if (colflag && ncol == mat->cmap->N) { 3198 allcolumns = PETSC_TRUE; 3199 } else { 3200 allcolumns = PETSC_FALSE; 3201 } 3202 if (call == MAT_REUSE_MATRIX) { 3203 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3204 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3205 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3206 } else { 3207 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3208 } 3209 3210 /* 3211 m - number of local rows 3212 n - number of columns (same on all processors) 3213 rstart - first row in new global matrix generated 3214 */ 3215 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3216 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3217 if (call == MAT_INITIAL_MATRIX) { 3218 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3219 ii = aij->i; 3220 jj = aij->j; 3221 3222 /* 3223 Determine the number of non-zeros in the diagonal and off-diagonal 3224 portions of the matrix in order to do correct preallocation 3225 */ 3226 3227 /* first get start and end of "diagonal" columns */ 3228 if (csize == PETSC_DECIDE) { 3229 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3230 if (mglobal == n) { /* square matrix */ 3231 nlocal = m; 3232 } else { 3233 nlocal = n/size + ((n % size) > rank); 3234 } 3235 } else { 3236 nlocal = csize; 3237 } 3238 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3239 rstart = rend - nlocal; 3240 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); 3241 3242 /* next, compute all the lengths */ 3243 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3244 olens = dlens + m; 3245 for (i=0; i<m; i++) { 3246 jend = ii[i+1] - ii[i]; 3247 olen = 0; 3248 dlen = 0; 3249 for (j=0; j<jend; j++) { 3250 if (*jj < rstart || *jj >= rend) olen++; 3251 else dlen++; 3252 jj++; 3253 } 3254 olens[i] = olen; 3255 dlens[i] = dlen; 3256 } 3257 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3258 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3259 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3260 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3261 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3262 ierr = PetscFree(dlens);CHKERRQ(ierr); 3263 } else { 3264 PetscInt ml,nl; 3265 3266 M = *newmat; 3267 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3268 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3269 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3270 /* 3271 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3272 rather than the slower MatSetValues(). 3273 */ 3274 M->was_assembled = PETSC_TRUE; 3275 M->assembled = PETSC_FALSE; 3276 } 3277 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3278 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3279 ii = aij->i; 3280 jj = aij->j; 3281 aa = aij->a; 3282 for (i=0; i<m; i++) { 3283 row = rstart + i; 3284 nz = ii[i+1] - ii[i]; 3285 cwork = jj; jj += nz; 3286 vwork = aa; aa += nz; 3287 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3288 } 3289 3290 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3291 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3292 *newmat = M; 3293 3294 /* save submatrix used in processor for next request */ 3295 if (call == MAT_INITIAL_MATRIX) { 3296 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3297 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3298 } 3299 PetscFunctionReturn(0); 3300 } 3301 3302 #undef __FUNCT__ 3303 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3304 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3305 { 3306 PetscInt m,cstart, cend,j,nnz,i,d; 3307 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3308 const PetscInt *JJ; 3309 PetscScalar *values; 3310 PetscErrorCode ierr; 3311 3312 PetscFunctionBegin; 3313 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3314 3315 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3316 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3317 m = B->rmap->n; 3318 cstart = B->cmap->rstart; 3319 cend = B->cmap->rend; 3320 rstart = B->rmap->rstart; 3321 3322 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3323 3324 #if defined(PETSC_USE_DEBUGGING) 3325 for (i=0; i<m; i++) { 3326 nnz = Ii[i+1]- Ii[i]; 3327 JJ = J + Ii[i]; 3328 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3329 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3330 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); 3331 } 3332 #endif 3333 3334 for (i=0; i<m; i++) { 3335 nnz = Ii[i+1]- Ii[i]; 3336 JJ = J + Ii[i]; 3337 nnz_max = PetscMax(nnz_max,nnz); 3338 d = 0; 3339 for (j=0; j<nnz; j++) { 3340 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3341 } 3342 d_nnz[i] = d; 3343 o_nnz[i] = nnz - d; 3344 } 3345 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3346 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3347 3348 if (v) values = (PetscScalar*)v; 3349 else { 3350 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3351 } 3352 3353 for (i=0; i<m; i++) { 3354 ii = i + rstart; 3355 nnz = Ii[i+1]- Ii[i]; 3356 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3357 } 3358 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3359 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3360 3361 if (!v) { 3362 ierr = PetscFree(values);CHKERRQ(ierr); 3363 } 3364 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3365 PetscFunctionReturn(0); 3366 } 3367 3368 #undef __FUNCT__ 3369 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3370 /*@ 3371 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3372 (the default parallel PETSc format). 3373 3374 Collective on MPI_Comm 3375 3376 Input Parameters: 3377 + B - the matrix 3378 . i - the indices into j for the start of each local row (starts with zero) 3379 . j - the column indices for each local row (starts with zero) 3380 - v - optional values in the matrix 3381 3382 Level: developer 3383 3384 Notes: 3385 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3386 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3387 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3388 3389 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3390 3391 The format which is used for the sparse matrix input, is equivalent to a 3392 row-major ordering.. i.e for the following matrix, the input data expected is 3393 as shown: 3394 3395 1 0 0 3396 2 0 3 P0 3397 ------- 3398 4 5 6 P1 3399 3400 Process0 [P0]: rows_owned=[0,1] 3401 i = {0,1,3} [size = nrow+1 = 2+1] 3402 j = {0,0,2} [size = nz = 6] 3403 v = {1,2,3} [size = nz = 6] 3404 3405 Process1 [P1]: rows_owned=[2] 3406 i = {0,3} [size = nrow+1 = 1+1] 3407 j = {0,1,2} [size = nz = 6] 3408 v = {4,5,6} [size = nz = 6] 3409 3410 .keywords: matrix, aij, compressed row, sparse, parallel 3411 3412 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3413 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3414 @*/ 3415 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3416 { 3417 PetscErrorCode ierr; 3418 3419 PetscFunctionBegin; 3420 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3421 PetscFunctionReturn(0); 3422 } 3423 3424 #undef __FUNCT__ 3425 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3426 /*@C 3427 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3428 (the default parallel PETSc format). For good matrix assembly performance 3429 the user should preallocate the matrix storage by setting the parameters 3430 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3431 performance can be increased by more than a factor of 50. 3432 3433 Collective on MPI_Comm 3434 3435 Input Parameters: 3436 + B - the matrix 3437 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3438 (same value is used for all local rows) 3439 . d_nnz - array containing the number of nonzeros in the various rows of the 3440 DIAGONAL portion of the local submatrix (possibly different for each row) 3441 or NULL, if d_nz is used to specify the nonzero structure. 3442 The size of this array is equal to the number of local rows, i.e 'm'. 3443 For matrices that will be factored, you must leave room for (and set) 3444 the diagonal entry even if it is zero. 3445 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3446 submatrix (same value is used for all local rows). 3447 - o_nnz - array containing the number of nonzeros in the various rows of the 3448 OFF-DIAGONAL portion of the local submatrix (possibly different for 3449 each row) or NULL, if o_nz is used to specify the nonzero 3450 structure. The size of this array is equal to the number 3451 of local rows, i.e 'm'. 3452 3453 If the *_nnz parameter is given then the *_nz parameter is ignored 3454 3455 The AIJ format (also called the Yale sparse matrix format or 3456 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3457 storage. The stored row and column indices begin with zero. 3458 See Users-Manual: ch_mat for details. 3459 3460 The parallel matrix is partitioned such that the first m0 rows belong to 3461 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3462 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3463 3464 The DIAGONAL portion of the local submatrix of a processor can be defined 3465 as the submatrix which is obtained by extraction the part corresponding to 3466 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3467 first row that belongs to the processor, r2 is the last row belonging to 3468 the this processor, and c1-c2 is range of indices of the local part of a 3469 vector suitable for applying the matrix to. This is an mxn matrix. In the 3470 common case of a square matrix, the row and column ranges are the same and 3471 the DIAGONAL part is also square. The remaining portion of the local 3472 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3473 3474 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3475 3476 You can call MatGetInfo() to get information on how effective the preallocation was; 3477 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3478 You can also run with the option -info and look for messages with the string 3479 malloc in them to see if additional memory allocation was needed. 3480 3481 Example usage: 3482 3483 Consider the following 8x8 matrix with 34 non-zero values, that is 3484 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3485 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3486 as follows: 3487 3488 .vb 3489 1 2 0 | 0 3 0 | 0 4 3490 Proc0 0 5 6 | 7 0 0 | 8 0 3491 9 0 10 | 11 0 0 | 12 0 3492 ------------------------------------- 3493 13 0 14 | 15 16 17 | 0 0 3494 Proc1 0 18 0 | 19 20 21 | 0 0 3495 0 0 0 | 22 23 0 | 24 0 3496 ------------------------------------- 3497 Proc2 25 26 27 | 0 0 28 | 29 0 3498 30 0 0 | 31 32 33 | 0 34 3499 .ve 3500 3501 This can be represented as a collection of submatrices as: 3502 3503 .vb 3504 A B C 3505 D E F 3506 G H I 3507 .ve 3508 3509 Where the submatrices A,B,C are owned by proc0, D,E,F are 3510 owned by proc1, G,H,I are owned by proc2. 3511 3512 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3513 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3514 The 'M','N' parameters are 8,8, and have the same values on all procs. 3515 3516 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3517 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3518 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3519 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3520 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3521 matrix, ans [DF] as another SeqAIJ matrix. 3522 3523 When d_nz, o_nz parameters are specified, d_nz storage elements are 3524 allocated for every row of the local diagonal submatrix, and o_nz 3525 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3526 One way to choose d_nz and o_nz is to use the max nonzerors per local 3527 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3528 In this case, the values of d_nz,o_nz are: 3529 .vb 3530 proc0 : dnz = 2, o_nz = 2 3531 proc1 : dnz = 3, o_nz = 2 3532 proc2 : dnz = 1, o_nz = 4 3533 .ve 3534 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3535 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3536 for proc3. i.e we are using 12+15+10=37 storage locations to store 3537 34 values. 3538 3539 When d_nnz, o_nnz parameters are specified, the storage is specified 3540 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3541 In the above case the values for d_nnz,o_nnz are: 3542 .vb 3543 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3544 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3545 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3546 .ve 3547 Here the space allocated is sum of all the above values i.e 34, and 3548 hence pre-allocation is perfect. 3549 3550 Level: intermediate 3551 3552 .keywords: matrix, aij, compressed row, sparse, parallel 3553 3554 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3555 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3556 @*/ 3557 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3558 { 3559 PetscErrorCode ierr; 3560 3561 PetscFunctionBegin; 3562 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3563 PetscValidType(B,1); 3564 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3565 PetscFunctionReturn(0); 3566 } 3567 3568 #undef __FUNCT__ 3569 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3570 /*@ 3571 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3572 CSR format the local rows. 3573 3574 Collective on MPI_Comm 3575 3576 Input Parameters: 3577 + comm - MPI communicator 3578 . m - number of local rows (Cannot be PETSC_DECIDE) 3579 . n - This value should be the same as the local size used in creating the 3580 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3581 calculated if N is given) For square matrices n is almost always m. 3582 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3583 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3584 . i - row indices 3585 . j - column indices 3586 - a - matrix values 3587 3588 Output Parameter: 3589 . mat - the matrix 3590 3591 Level: intermediate 3592 3593 Notes: 3594 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3595 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3596 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3597 3598 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3599 3600 The format which is used for the sparse matrix input, is equivalent to a 3601 row-major ordering.. i.e for the following matrix, the input data expected is 3602 as shown: 3603 3604 1 0 0 3605 2 0 3 P0 3606 ------- 3607 4 5 6 P1 3608 3609 Process0 [P0]: rows_owned=[0,1] 3610 i = {0,1,3} [size = nrow+1 = 2+1] 3611 j = {0,0,2} [size = nz = 6] 3612 v = {1,2,3} [size = nz = 6] 3613 3614 Process1 [P1]: rows_owned=[2] 3615 i = {0,3} [size = nrow+1 = 1+1] 3616 j = {0,1,2} [size = nz = 6] 3617 v = {4,5,6} [size = nz = 6] 3618 3619 .keywords: matrix, aij, compressed row, sparse, parallel 3620 3621 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3622 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3623 @*/ 3624 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3625 { 3626 PetscErrorCode ierr; 3627 3628 PetscFunctionBegin; 3629 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3630 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3631 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3632 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3633 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3634 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3635 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3636 PetscFunctionReturn(0); 3637 } 3638 3639 #undef __FUNCT__ 3640 #define __FUNCT__ "MatCreateAIJ" 3641 /*@C 3642 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3643 (the default parallel PETSc format). For good matrix assembly performance 3644 the user should preallocate the matrix storage by setting the parameters 3645 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3646 performance can be increased by more than a factor of 50. 3647 3648 Collective on MPI_Comm 3649 3650 Input Parameters: 3651 + comm - MPI communicator 3652 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3653 This value should be the same as the local size used in creating the 3654 y vector for the matrix-vector product y = Ax. 3655 . n - This value should be the same as the local size used in creating the 3656 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3657 calculated if N is given) For square matrices n is almost always m. 3658 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3659 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3660 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3661 (same value is used for all local rows) 3662 . d_nnz - array containing the number of nonzeros in the various rows of the 3663 DIAGONAL portion of the local submatrix (possibly different for each row) 3664 or NULL, if d_nz is used to specify the nonzero structure. 3665 The size of this array is equal to the number of local rows, i.e 'm'. 3666 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3667 submatrix (same value is used for all local rows). 3668 - o_nnz - array containing the number of nonzeros in the various rows of the 3669 OFF-DIAGONAL portion of the local submatrix (possibly different for 3670 each row) or NULL, if o_nz is used to specify the nonzero 3671 structure. The size of this array is equal to the number 3672 of local rows, i.e 'm'. 3673 3674 Output Parameter: 3675 . A - the matrix 3676 3677 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3678 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3679 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3680 3681 Notes: 3682 If the *_nnz parameter is given then the *_nz parameter is ignored 3683 3684 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3685 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3686 storage requirements for this matrix. 3687 3688 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3689 processor than it must be used on all processors that share the object for 3690 that argument. 3691 3692 The user MUST specify either the local or global matrix dimensions 3693 (possibly both). 3694 3695 The parallel matrix is partitioned across processors such that the 3696 first m0 rows belong to process 0, the next m1 rows belong to 3697 process 1, the next m2 rows belong to process 2 etc.. where 3698 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3699 values corresponding to [m x N] submatrix. 3700 3701 The columns are logically partitioned with the n0 columns belonging 3702 to 0th partition, the next n1 columns belonging to the next 3703 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3704 3705 The DIAGONAL portion of the local submatrix on any given processor 3706 is the submatrix corresponding to the rows and columns m,n 3707 corresponding to the given processor. i.e diagonal matrix on 3708 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3709 etc. The remaining portion of the local submatrix [m x (N-n)] 3710 constitute the OFF-DIAGONAL portion. The example below better 3711 illustrates this concept. 3712 3713 For a square global matrix we define each processor's diagonal portion 3714 to be its local rows and the corresponding columns (a square submatrix); 3715 each processor's off-diagonal portion encompasses the remainder of the 3716 local matrix (a rectangular submatrix). 3717 3718 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3719 3720 When calling this routine with a single process communicator, a matrix of 3721 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3722 type of communicator, use the construction mechanism: 3723 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3724 3725 By default, this format uses inodes (identical nodes) when possible. 3726 We search for consecutive rows with the same nonzero structure, thereby 3727 reusing matrix information to achieve increased efficiency. 3728 3729 Options Database Keys: 3730 + -mat_no_inode - Do not use inodes 3731 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3732 - -mat_aij_oneindex - Internally use indexing starting at 1 3733 rather than 0. Note that when calling MatSetValues(), 3734 the user still MUST index entries starting at 0! 3735 3736 3737 Example usage: 3738 3739 Consider the following 8x8 matrix with 34 non-zero values, that is 3740 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3741 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3742 as follows: 3743 3744 .vb 3745 1 2 0 | 0 3 0 | 0 4 3746 Proc0 0 5 6 | 7 0 0 | 8 0 3747 9 0 10 | 11 0 0 | 12 0 3748 ------------------------------------- 3749 13 0 14 | 15 16 17 | 0 0 3750 Proc1 0 18 0 | 19 20 21 | 0 0 3751 0 0 0 | 22 23 0 | 24 0 3752 ------------------------------------- 3753 Proc2 25 26 27 | 0 0 28 | 29 0 3754 30 0 0 | 31 32 33 | 0 34 3755 .ve 3756 3757 This can be represented as a collection of submatrices as: 3758 3759 .vb 3760 A B C 3761 D E F 3762 G H I 3763 .ve 3764 3765 Where the submatrices A,B,C are owned by proc0, D,E,F are 3766 owned by proc1, G,H,I are owned by proc2. 3767 3768 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3769 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3770 The 'M','N' parameters are 8,8, and have the same values on all procs. 3771 3772 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3773 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3774 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3775 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3776 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3777 matrix, ans [DF] as another SeqAIJ matrix. 3778 3779 When d_nz, o_nz parameters are specified, d_nz storage elements are 3780 allocated for every row of the local diagonal submatrix, and o_nz 3781 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3782 One way to choose d_nz and o_nz is to use the max nonzerors per local 3783 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3784 In this case, the values of d_nz,o_nz are: 3785 .vb 3786 proc0 : dnz = 2, o_nz = 2 3787 proc1 : dnz = 3, o_nz = 2 3788 proc2 : dnz = 1, o_nz = 4 3789 .ve 3790 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3791 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3792 for proc3. i.e we are using 12+15+10=37 storage locations to store 3793 34 values. 3794 3795 When d_nnz, o_nnz parameters are specified, the storage is specified 3796 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3797 In the above case the values for d_nnz,o_nnz are: 3798 .vb 3799 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3800 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3801 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3802 .ve 3803 Here the space allocated is sum of all the above values i.e 34, and 3804 hence pre-allocation is perfect. 3805 3806 Level: intermediate 3807 3808 .keywords: matrix, aij, compressed row, sparse, parallel 3809 3810 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3811 MPIAIJ, MatCreateMPIAIJWithArrays() 3812 @*/ 3813 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) 3814 { 3815 PetscErrorCode ierr; 3816 PetscMPIInt size; 3817 3818 PetscFunctionBegin; 3819 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3820 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3821 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3822 if (size > 1) { 3823 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3824 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3825 } else { 3826 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3827 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3828 } 3829 PetscFunctionReturn(0); 3830 } 3831 3832 #undef __FUNCT__ 3833 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3834 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3835 { 3836 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3837 3838 PetscFunctionBegin; 3839 if (Ad) *Ad = a->A; 3840 if (Ao) *Ao = a->B; 3841 if (colmap) *colmap = a->garray; 3842 PetscFunctionReturn(0); 3843 } 3844 3845 #undef __FUNCT__ 3846 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3847 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3848 { 3849 PetscErrorCode ierr; 3850 PetscInt i; 3851 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3852 3853 PetscFunctionBegin; 3854 if (coloring->ctype == IS_COLORING_GLOBAL) { 3855 ISColoringValue *allcolors,*colors; 3856 ISColoring ocoloring; 3857 3858 /* set coloring for diagonal portion */ 3859 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3860 3861 /* set coloring for off-diagonal portion */ 3862 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3863 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3864 for (i=0; i<a->B->cmap->n; i++) { 3865 colors[i] = allcolors[a->garray[i]]; 3866 } 3867 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3868 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3869 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3870 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3871 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3872 ISColoringValue *colors; 3873 PetscInt *larray; 3874 ISColoring ocoloring; 3875 3876 /* set coloring for diagonal portion */ 3877 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3878 for (i=0; i<a->A->cmap->n; i++) { 3879 larray[i] = i + A->cmap->rstart; 3880 } 3881 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3882 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3883 for (i=0; i<a->A->cmap->n; i++) { 3884 colors[i] = coloring->colors[larray[i]]; 3885 } 3886 ierr = PetscFree(larray);CHKERRQ(ierr); 3887 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3888 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3889 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3890 3891 /* set coloring for off-diagonal portion */ 3892 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3893 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3894 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3895 for (i=0; i<a->B->cmap->n; i++) { 3896 colors[i] = coloring->colors[larray[i]]; 3897 } 3898 ierr = PetscFree(larray);CHKERRQ(ierr); 3899 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3900 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3901 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3902 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3903 PetscFunctionReturn(0); 3904 } 3905 3906 #undef __FUNCT__ 3907 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3908 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3909 { 3910 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3911 PetscErrorCode ierr; 3912 3913 PetscFunctionBegin; 3914 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3915 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3916 PetscFunctionReturn(0); 3917 } 3918 3919 #undef __FUNCT__ 3920 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3921 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3922 { 3923 PetscErrorCode ierr; 3924 PetscInt m,N,i,rstart,nnz,Ii; 3925 PetscInt *indx; 3926 PetscScalar *values; 3927 3928 PetscFunctionBegin; 3929 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3930 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3931 PetscInt *dnz,*onz,sum,bs,cbs; 3932 3933 if (n == PETSC_DECIDE) { 3934 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3935 } 3936 /* Check sum(n) = N */ 3937 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3938 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3939 3940 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3941 rstart -= m; 3942 3943 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3944 for (i=0; i<m; i++) { 3945 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3946 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3947 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3948 } 3949 3950 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3951 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3952 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3953 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3954 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3955 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3956 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3957 } 3958 3959 /* numeric phase */ 3960 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3961 for (i=0; i<m; i++) { 3962 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3963 Ii = i + rstart; 3964 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3965 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3966 } 3967 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3968 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3969 PetscFunctionReturn(0); 3970 } 3971 3972 #undef __FUNCT__ 3973 #define __FUNCT__ "MatFileSplit" 3974 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3975 { 3976 PetscErrorCode ierr; 3977 PetscMPIInt rank; 3978 PetscInt m,N,i,rstart,nnz; 3979 size_t len; 3980 const PetscInt *indx; 3981 PetscViewer out; 3982 char *name; 3983 Mat B; 3984 const PetscScalar *values; 3985 3986 PetscFunctionBegin; 3987 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3988 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3989 /* Should this be the type of the diagonal block of A? */ 3990 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3991 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3992 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3993 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3994 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3995 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3996 for (i=0; i<m; i++) { 3997 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3998 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3999 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4000 } 4001 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4002 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4003 4004 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4005 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4006 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4007 sprintf(name,"%s.%d",outfile,rank); 4008 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4009 ierr = PetscFree(name);CHKERRQ(ierr); 4010 ierr = MatView(B,out);CHKERRQ(ierr); 4011 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4012 ierr = MatDestroy(&B);CHKERRQ(ierr); 4013 PetscFunctionReturn(0); 4014 } 4015 4016 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4017 #undef __FUNCT__ 4018 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4019 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4020 { 4021 PetscErrorCode ierr; 4022 Mat_Merge_SeqsToMPI *merge; 4023 PetscContainer container; 4024 4025 PetscFunctionBegin; 4026 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4027 if (container) { 4028 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4029 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4030 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4031 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4032 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4033 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4034 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4035 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4036 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4037 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4038 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4039 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4040 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4041 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4042 ierr = PetscFree(merge);CHKERRQ(ierr); 4043 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4044 } 4045 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4046 PetscFunctionReturn(0); 4047 } 4048 4049 #include <../src/mat/utils/freespace.h> 4050 #include <petscbt.h> 4051 4052 #undef __FUNCT__ 4053 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4054 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4055 { 4056 PetscErrorCode ierr; 4057 MPI_Comm comm; 4058 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4059 PetscMPIInt size,rank,taga,*len_s; 4060 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4061 PetscInt proc,m; 4062 PetscInt **buf_ri,**buf_rj; 4063 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4064 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4065 MPI_Request *s_waits,*r_waits; 4066 MPI_Status *status; 4067 MatScalar *aa=a->a; 4068 MatScalar **abuf_r,*ba_i; 4069 Mat_Merge_SeqsToMPI *merge; 4070 PetscContainer container; 4071 4072 PetscFunctionBegin; 4073 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4074 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4075 4076 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4077 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4078 4079 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4080 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4081 4082 bi = merge->bi; 4083 bj = merge->bj; 4084 buf_ri = merge->buf_ri; 4085 buf_rj = merge->buf_rj; 4086 4087 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4088 owners = merge->rowmap->range; 4089 len_s = merge->len_s; 4090 4091 /* send and recv matrix values */ 4092 /*-----------------------------*/ 4093 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4094 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4095 4096 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4097 for (proc=0,k=0; proc<size; proc++) { 4098 if (!len_s[proc]) continue; 4099 i = owners[proc]; 4100 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4101 k++; 4102 } 4103 4104 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4105 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4106 ierr = PetscFree(status);CHKERRQ(ierr); 4107 4108 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4109 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4110 4111 /* insert mat values of mpimat */ 4112 /*----------------------------*/ 4113 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4114 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4115 4116 for (k=0; k<merge->nrecv; k++) { 4117 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4118 nrows = *(buf_ri_k[k]); 4119 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4120 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4121 } 4122 4123 /* set values of ba */ 4124 m = merge->rowmap->n; 4125 for (i=0; i<m; i++) { 4126 arow = owners[rank] + i; 4127 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4128 bnzi = bi[i+1] - bi[i]; 4129 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4130 4131 /* add local non-zero vals of this proc's seqmat into ba */ 4132 anzi = ai[arow+1] - ai[arow]; 4133 aj = a->j + ai[arow]; 4134 aa = a->a + ai[arow]; 4135 nextaj = 0; 4136 for (j=0; nextaj<anzi; j++) { 4137 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4138 ba_i[j] += aa[nextaj++]; 4139 } 4140 } 4141 4142 /* add received vals into ba */ 4143 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4144 /* i-th row */ 4145 if (i == *nextrow[k]) { 4146 anzi = *(nextai[k]+1) - *nextai[k]; 4147 aj = buf_rj[k] + *(nextai[k]); 4148 aa = abuf_r[k] + *(nextai[k]); 4149 nextaj = 0; 4150 for (j=0; nextaj<anzi; j++) { 4151 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4152 ba_i[j] += aa[nextaj++]; 4153 } 4154 } 4155 nextrow[k]++; nextai[k]++; 4156 } 4157 } 4158 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4159 } 4160 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4161 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4162 4163 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4164 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4165 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4166 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4167 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4168 PetscFunctionReturn(0); 4169 } 4170 4171 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4172 4173 #undef __FUNCT__ 4174 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4175 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4176 { 4177 PetscErrorCode ierr; 4178 Mat B_mpi; 4179 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4180 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4181 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4182 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4183 PetscInt len,proc,*dnz,*onz,bs,cbs; 4184 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4185 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4186 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4187 MPI_Status *status; 4188 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4189 PetscBT lnkbt; 4190 Mat_Merge_SeqsToMPI *merge; 4191 PetscContainer container; 4192 4193 PetscFunctionBegin; 4194 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4195 4196 /* make sure it is a PETSc comm */ 4197 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4199 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4200 4201 ierr = PetscNew(&merge);CHKERRQ(ierr); 4202 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4203 4204 /* determine row ownership */ 4205 /*---------------------------------------------------------*/ 4206 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4207 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4208 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4209 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4210 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4211 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4212 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4213 4214 m = merge->rowmap->n; 4215 owners = merge->rowmap->range; 4216 4217 /* determine the number of messages to send, their lengths */ 4218 /*---------------------------------------------------------*/ 4219 len_s = merge->len_s; 4220 4221 len = 0; /* length of buf_si[] */ 4222 merge->nsend = 0; 4223 for (proc=0; proc<size; proc++) { 4224 len_si[proc] = 0; 4225 if (proc == rank) { 4226 len_s[proc] = 0; 4227 } else { 4228 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4229 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4230 } 4231 if (len_s[proc]) { 4232 merge->nsend++; 4233 nrows = 0; 4234 for (i=owners[proc]; i<owners[proc+1]; i++) { 4235 if (ai[i+1] > ai[i]) nrows++; 4236 } 4237 len_si[proc] = 2*(nrows+1); 4238 len += len_si[proc]; 4239 } 4240 } 4241 4242 /* determine the number and length of messages to receive for ij-structure */ 4243 /*-------------------------------------------------------------------------*/ 4244 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4245 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4246 4247 /* post the Irecv of j-structure */ 4248 /*-------------------------------*/ 4249 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4250 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4251 4252 /* post the Isend of j-structure */ 4253 /*--------------------------------*/ 4254 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4255 4256 for (proc=0, k=0; proc<size; proc++) { 4257 if (!len_s[proc]) continue; 4258 i = owners[proc]; 4259 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4260 k++; 4261 } 4262 4263 /* receives and sends of j-structure are complete */ 4264 /*------------------------------------------------*/ 4265 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4266 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4267 4268 /* send and recv i-structure */ 4269 /*---------------------------*/ 4270 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4271 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4272 4273 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4274 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4275 for (proc=0,k=0; proc<size; proc++) { 4276 if (!len_s[proc]) continue; 4277 /* form outgoing message for i-structure: 4278 buf_si[0]: nrows to be sent 4279 [1:nrows]: row index (global) 4280 [nrows+1:2*nrows+1]: i-structure index 4281 */ 4282 /*-------------------------------------------*/ 4283 nrows = len_si[proc]/2 - 1; 4284 buf_si_i = buf_si + nrows+1; 4285 buf_si[0] = nrows; 4286 buf_si_i[0] = 0; 4287 nrows = 0; 4288 for (i=owners[proc]; i<owners[proc+1]; i++) { 4289 anzi = ai[i+1] - ai[i]; 4290 if (anzi) { 4291 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4292 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4293 nrows++; 4294 } 4295 } 4296 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4297 k++; 4298 buf_si += len_si[proc]; 4299 } 4300 4301 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4302 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4303 4304 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4305 for (i=0; i<merge->nrecv; i++) { 4306 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); 4307 } 4308 4309 ierr = PetscFree(len_si);CHKERRQ(ierr); 4310 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4311 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4312 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4313 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4314 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4315 ierr = PetscFree(status);CHKERRQ(ierr); 4316 4317 /* compute a local seq matrix in each processor */ 4318 /*----------------------------------------------*/ 4319 /* allocate bi array and free space for accumulating nonzero column info */ 4320 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4321 bi[0] = 0; 4322 4323 /* create and initialize a linked list */ 4324 nlnk = N+1; 4325 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4326 4327 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4328 len = ai[owners[rank+1]] - ai[owners[rank]]; 4329 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4330 4331 current_space = free_space; 4332 4333 /* determine symbolic info for each local row */ 4334 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4335 4336 for (k=0; k<merge->nrecv; k++) { 4337 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4338 nrows = *buf_ri_k[k]; 4339 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4340 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4341 } 4342 4343 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4344 len = 0; 4345 for (i=0; i<m; i++) { 4346 bnzi = 0; 4347 /* add local non-zero cols of this proc's seqmat into lnk */ 4348 arow = owners[rank] + i; 4349 anzi = ai[arow+1] - ai[arow]; 4350 aj = a->j + ai[arow]; 4351 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4352 bnzi += nlnk; 4353 /* add received col data into lnk */ 4354 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4355 if (i == *nextrow[k]) { /* i-th row */ 4356 anzi = *(nextai[k]+1) - *nextai[k]; 4357 aj = buf_rj[k] + *nextai[k]; 4358 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4359 bnzi += nlnk; 4360 nextrow[k]++; nextai[k]++; 4361 } 4362 } 4363 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4364 4365 /* if free space is not available, make more free space */ 4366 if (current_space->local_remaining<bnzi) { 4367 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4368 nspacedouble++; 4369 } 4370 /* copy data into free space, then initialize lnk */ 4371 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4372 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4373 4374 current_space->array += bnzi; 4375 current_space->local_used += bnzi; 4376 current_space->local_remaining -= bnzi; 4377 4378 bi[i+1] = bi[i] + bnzi; 4379 } 4380 4381 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4382 4383 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4384 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4385 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4386 4387 /* create symbolic parallel matrix B_mpi */ 4388 /*---------------------------------------*/ 4389 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4390 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4391 if (n==PETSC_DECIDE) { 4392 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4393 } else { 4394 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4395 } 4396 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4397 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4398 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4399 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4400 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4401 4402 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4403 B_mpi->assembled = PETSC_FALSE; 4404 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4405 merge->bi = bi; 4406 merge->bj = bj; 4407 merge->buf_ri = buf_ri; 4408 merge->buf_rj = buf_rj; 4409 merge->coi = NULL; 4410 merge->coj = NULL; 4411 merge->owners_co = NULL; 4412 4413 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4414 4415 /* attach the supporting struct to B_mpi for reuse */ 4416 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4417 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4418 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4419 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4420 *mpimat = B_mpi; 4421 4422 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4423 PetscFunctionReturn(0); 4424 } 4425 4426 #undef __FUNCT__ 4427 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4428 /*@C 4429 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4430 matrices from each processor 4431 4432 Collective on MPI_Comm 4433 4434 Input Parameters: 4435 + comm - the communicators the parallel matrix will live on 4436 . seqmat - the input sequential matrices 4437 . m - number of local rows (or PETSC_DECIDE) 4438 . n - number of local columns (or PETSC_DECIDE) 4439 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4440 4441 Output Parameter: 4442 . mpimat - the parallel matrix generated 4443 4444 Level: advanced 4445 4446 Notes: 4447 The dimensions of the sequential matrix in each processor MUST be the same. 4448 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4449 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4450 @*/ 4451 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4452 { 4453 PetscErrorCode ierr; 4454 PetscMPIInt size; 4455 4456 PetscFunctionBegin; 4457 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4458 if (size == 1) { 4459 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4460 if (scall == MAT_INITIAL_MATRIX) { 4461 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4462 } else { 4463 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4464 } 4465 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4466 PetscFunctionReturn(0); 4467 } 4468 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4469 if (scall == MAT_INITIAL_MATRIX) { 4470 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4471 } 4472 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4473 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4474 PetscFunctionReturn(0); 4475 } 4476 4477 #undef __FUNCT__ 4478 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4479 /*@ 4480 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4481 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4482 with MatGetSize() 4483 4484 Not Collective 4485 4486 Input Parameters: 4487 + A - the matrix 4488 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4489 4490 Output Parameter: 4491 . A_loc - the local sequential matrix generated 4492 4493 Level: developer 4494 4495 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4496 4497 @*/ 4498 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4499 { 4500 PetscErrorCode ierr; 4501 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4502 Mat_SeqAIJ *mat,*a,*b; 4503 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4504 MatScalar *aa,*ba,*cam; 4505 PetscScalar *ca; 4506 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4507 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4508 PetscBool match; 4509 MPI_Comm comm; 4510 PetscMPIInt size; 4511 4512 PetscFunctionBegin; 4513 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4514 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4515 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4516 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4517 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4518 4519 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4520 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4521 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4522 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4523 aa = a->a; ba = b->a; 4524 if (scall == MAT_INITIAL_MATRIX) { 4525 if (size == 1) { 4526 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4527 PetscFunctionReturn(0); 4528 } 4529 4530 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4531 ci[0] = 0; 4532 for (i=0; i<am; i++) { 4533 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4534 } 4535 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4536 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4537 k = 0; 4538 for (i=0; i<am; i++) { 4539 ncols_o = bi[i+1] - bi[i]; 4540 ncols_d = ai[i+1] - ai[i]; 4541 /* off-diagonal portion of A */ 4542 for (jo=0; jo<ncols_o; jo++) { 4543 col = cmap[*bj]; 4544 if (col >= cstart) break; 4545 cj[k] = col; bj++; 4546 ca[k++] = *ba++; 4547 } 4548 /* diagonal portion of A */ 4549 for (j=0; j<ncols_d; j++) { 4550 cj[k] = cstart + *aj++; 4551 ca[k++] = *aa++; 4552 } 4553 /* off-diagonal portion of A */ 4554 for (j=jo; j<ncols_o; j++) { 4555 cj[k] = cmap[*bj++]; 4556 ca[k++] = *ba++; 4557 } 4558 } 4559 /* put together the new matrix */ 4560 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4561 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4562 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4563 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4564 mat->free_a = PETSC_TRUE; 4565 mat->free_ij = PETSC_TRUE; 4566 mat->nonew = 0; 4567 } else if (scall == MAT_REUSE_MATRIX) { 4568 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4569 ci = mat->i; cj = mat->j; cam = mat->a; 4570 for (i=0; i<am; i++) { 4571 /* off-diagonal portion of A */ 4572 ncols_o = bi[i+1] - bi[i]; 4573 for (jo=0; jo<ncols_o; jo++) { 4574 col = cmap[*bj]; 4575 if (col >= cstart) break; 4576 *cam++ = *ba++; bj++; 4577 } 4578 /* diagonal portion of A */ 4579 ncols_d = ai[i+1] - ai[i]; 4580 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4581 /* off-diagonal portion of A */ 4582 for (j=jo; j<ncols_o; j++) { 4583 *cam++ = *ba++; bj++; 4584 } 4585 } 4586 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4587 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4588 PetscFunctionReturn(0); 4589 } 4590 4591 #undef __FUNCT__ 4592 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4593 /*@C 4594 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4595 4596 Not Collective 4597 4598 Input Parameters: 4599 + A - the matrix 4600 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4601 - row, col - index sets of rows and columns to extract (or NULL) 4602 4603 Output Parameter: 4604 . A_loc - the local sequential matrix generated 4605 4606 Level: developer 4607 4608 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4609 4610 @*/ 4611 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4612 { 4613 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4614 PetscErrorCode ierr; 4615 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4616 IS isrowa,iscola; 4617 Mat *aloc; 4618 PetscBool match; 4619 4620 PetscFunctionBegin; 4621 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4622 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4623 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4624 if (!row) { 4625 start = A->rmap->rstart; end = A->rmap->rend; 4626 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4627 } else { 4628 isrowa = *row; 4629 } 4630 if (!col) { 4631 start = A->cmap->rstart; 4632 cmap = a->garray; 4633 nzA = a->A->cmap->n; 4634 nzB = a->B->cmap->n; 4635 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4636 ncols = 0; 4637 for (i=0; i<nzB; i++) { 4638 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4639 else break; 4640 } 4641 imark = i; 4642 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4643 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4644 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4645 } else { 4646 iscola = *col; 4647 } 4648 if (scall != MAT_INITIAL_MATRIX) { 4649 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4650 aloc[0] = *A_loc; 4651 } 4652 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4653 *A_loc = aloc[0]; 4654 ierr = PetscFree(aloc);CHKERRQ(ierr); 4655 if (!row) { 4656 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4657 } 4658 if (!col) { 4659 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4660 } 4661 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4662 PetscFunctionReturn(0); 4663 } 4664 4665 #undef __FUNCT__ 4666 #define __FUNCT__ "MatGetBrowsOfAcols" 4667 /*@C 4668 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4669 4670 Collective on Mat 4671 4672 Input Parameters: 4673 + A,B - the matrices in mpiaij format 4674 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4675 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4676 4677 Output Parameter: 4678 + rowb, colb - index sets of rows and columns of B to extract 4679 - B_seq - the sequential matrix generated 4680 4681 Level: developer 4682 4683 @*/ 4684 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4685 { 4686 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4687 PetscErrorCode ierr; 4688 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4689 IS isrowb,iscolb; 4690 Mat *bseq=NULL; 4691 4692 PetscFunctionBegin; 4693 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4694 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); 4695 } 4696 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4697 4698 if (scall == MAT_INITIAL_MATRIX) { 4699 start = A->cmap->rstart; 4700 cmap = a->garray; 4701 nzA = a->A->cmap->n; 4702 nzB = a->B->cmap->n; 4703 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4704 ncols = 0; 4705 for (i=0; i<nzB; i++) { /* row < local row index */ 4706 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4707 else break; 4708 } 4709 imark = i; 4710 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4711 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4712 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4713 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4714 } else { 4715 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4716 isrowb = *rowb; iscolb = *colb; 4717 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4718 bseq[0] = *B_seq; 4719 } 4720 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4721 *B_seq = bseq[0]; 4722 ierr = PetscFree(bseq);CHKERRQ(ierr); 4723 if (!rowb) { 4724 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4725 } else { 4726 *rowb = isrowb; 4727 } 4728 if (!colb) { 4729 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4730 } else { 4731 *colb = iscolb; 4732 } 4733 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4734 PetscFunctionReturn(0); 4735 } 4736 4737 #undef __FUNCT__ 4738 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4739 /* 4740 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4741 of the OFF-DIAGONAL portion of local A 4742 4743 Collective on Mat 4744 4745 Input Parameters: 4746 + A,B - the matrices in mpiaij format 4747 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4748 4749 Output Parameter: 4750 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4751 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4752 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4753 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4754 4755 Level: developer 4756 4757 */ 4758 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4759 { 4760 VecScatter_MPI_General *gen_to,*gen_from; 4761 PetscErrorCode ierr; 4762 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4763 Mat_SeqAIJ *b_oth; 4764 VecScatter ctx =a->Mvctx; 4765 MPI_Comm comm; 4766 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4767 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4768 PetscScalar *rvalues,*svalues; 4769 MatScalar *b_otha,*bufa,*bufA; 4770 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4771 MPI_Request *rwaits = NULL,*swaits = NULL; 4772 MPI_Status *sstatus,rstatus; 4773 PetscMPIInt jj,size; 4774 PetscInt *cols,sbs,rbs; 4775 PetscScalar *vals; 4776 4777 PetscFunctionBegin; 4778 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4779 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4780 4781 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4782 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); 4783 } 4784 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4785 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4786 4787 gen_to = (VecScatter_MPI_General*)ctx->todata; 4788 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4789 rvalues = gen_from->values; /* holds the length of receiving row */ 4790 svalues = gen_to->values; /* holds the length of sending row */ 4791 nrecvs = gen_from->n; 4792 nsends = gen_to->n; 4793 4794 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4795 srow = gen_to->indices; /* local row index to be sent */ 4796 sstarts = gen_to->starts; 4797 sprocs = gen_to->procs; 4798 sstatus = gen_to->sstatus; 4799 sbs = gen_to->bs; 4800 rstarts = gen_from->starts; 4801 rprocs = gen_from->procs; 4802 rbs = gen_from->bs; 4803 4804 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4805 if (scall == MAT_INITIAL_MATRIX) { 4806 /* i-array */ 4807 /*---------*/ 4808 /* post receives */ 4809 for (i=0; i<nrecvs; i++) { 4810 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4811 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4812 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4813 } 4814 4815 /* pack the outgoing message */ 4816 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4817 4818 sstartsj[0] = 0; 4819 rstartsj[0] = 0; 4820 len = 0; /* total length of j or a array to be sent */ 4821 k = 0; 4822 for (i=0; i<nsends; i++) { 4823 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4824 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4825 for (j=0; j<nrows; j++) { 4826 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4827 for (l=0; l<sbs; l++) { 4828 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4829 4830 rowlen[j*sbs+l] = ncols; 4831 4832 len += ncols; 4833 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4834 } 4835 k++; 4836 } 4837 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4838 4839 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4840 } 4841 /* recvs and sends of i-array are completed */ 4842 i = nrecvs; 4843 while (i--) { 4844 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4845 } 4846 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4847 4848 /* allocate buffers for sending j and a arrays */ 4849 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4850 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4851 4852 /* create i-array of B_oth */ 4853 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4854 4855 b_othi[0] = 0; 4856 len = 0; /* total length of j or a array to be received */ 4857 k = 0; 4858 for (i=0; i<nrecvs; i++) { 4859 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4860 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4861 for (j=0; j<nrows; j++) { 4862 b_othi[k+1] = b_othi[k] + rowlen[j]; 4863 len += rowlen[j]; k++; 4864 } 4865 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4866 } 4867 4868 /* allocate space for j and a arrrays of B_oth */ 4869 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4870 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4871 4872 /* j-array */ 4873 /*---------*/ 4874 /* post receives of j-array */ 4875 for (i=0; i<nrecvs; i++) { 4876 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4877 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4878 } 4879 4880 /* pack the outgoing message j-array */ 4881 k = 0; 4882 for (i=0; i<nsends; i++) { 4883 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4884 bufJ = bufj+sstartsj[i]; 4885 for (j=0; j<nrows; j++) { 4886 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4887 for (ll=0; ll<sbs; ll++) { 4888 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4889 for (l=0; l<ncols; l++) { 4890 *bufJ++ = cols[l]; 4891 } 4892 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4893 } 4894 } 4895 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4896 } 4897 4898 /* recvs and sends of j-array are completed */ 4899 i = nrecvs; 4900 while (i--) { 4901 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4902 } 4903 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4904 } else if (scall == MAT_REUSE_MATRIX) { 4905 sstartsj = *startsj_s; 4906 rstartsj = *startsj_r; 4907 bufa = *bufa_ptr; 4908 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4909 b_otha = b_oth->a; 4910 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4911 4912 /* a-array */ 4913 /*---------*/ 4914 /* post receives of a-array */ 4915 for (i=0; i<nrecvs; i++) { 4916 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4917 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4918 } 4919 4920 /* pack the outgoing message a-array */ 4921 k = 0; 4922 for (i=0; i<nsends; i++) { 4923 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4924 bufA = bufa+sstartsj[i]; 4925 for (j=0; j<nrows; j++) { 4926 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4927 for (ll=0; ll<sbs; ll++) { 4928 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4929 for (l=0; l<ncols; l++) { 4930 *bufA++ = vals[l]; 4931 } 4932 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4933 } 4934 } 4935 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4936 } 4937 /* recvs and sends of a-array are completed */ 4938 i = nrecvs; 4939 while (i--) { 4940 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4941 } 4942 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4943 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4944 4945 if (scall == MAT_INITIAL_MATRIX) { 4946 /* put together the new matrix */ 4947 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4948 4949 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4950 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4951 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4952 b_oth->free_a = PETSC_TRUE; 4953 b_oth->free_ij = PETSC_TRUE; 4954 b_oth->nonew = 0; 4955 4956 ierr = PetscFree(bufj);CHKERRQ(ierr); 4957 if (!startsj_s || !bufa_ptr) { 4958 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4959 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4960 } else { 4961 *startsj_s = sstartsj; 4962 *startsj_r = rstartsj; 4963 *bufa_ptr = bufa; 4964 } 4965 } 4966 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4967 PetscFunctionReturn(0); 4968 } 4969 4970 #undef __FUNCT__ 4971 #define __FUNCT__ "MatGetCommunicationStructs" 4972 /*@C 4973 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4974 4975 Not Collective 4976 4977 Input Parameters: 4978 . A - The matrix in mpiaij format 4979 4980 Output Parameter: 4981 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4982 . colmap - A map from global column index to local index into lvec 4983 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4984 4985 Level: developer 4986 4987 @*/ 4988 #if defined(PETSC_USE_CTABLE) 4989 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4990 #else 4991 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4992 #endif 4993 { 4994 Mat_MPIAIJ *a; 4995 4996 PetscFunctionBegin; 4997 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4998 PetscValidPointer(lvec, 2); 4999 PetscValidPointer(colmap, 3); 5000 PetscValidPointer(multScatter, 4); 5001 a = (Mat_MPIAIJ*) A->data; 5002 if (lvec) *lvec = a->lvec; 5003 if (colmap) *colmap = a->colmap; 5004 if (multScatter) *multScatter = a->Mvctx; 5005 PetscFunctionReturn(0); 5006 } 5007 5008 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5009 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5010 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5011 #if defined(PETSC_HAVE_ELEMENTAL) 5012 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5013 #endif 5014 5015 #undef __FUNCT__ 5016 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5017 /* 5018 Computes (B'*A')' since computing B*A directly is untenable 5019 5020 n p p 5021 ( ) ( ) ( ) 5022 m ( A ) * n ( B ) = m ( C ) 5023 ( ) ( ) ( ) 5024 5025 */ 5026 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5027 { 5028 PetscErrorCode ierr; 5029 Mat At,Bt,Ct; 5030 5031 PetscFunctionBegin; 5032 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5033 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5034 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5035 ierr = MatDestroy(&At);CHKERRQ(ierr); 5036 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5037 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5038 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5039 PetscFunctionReturn(0); 5040 } 5041 5042 #undef __FUNCT__ 5043 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5044 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5045 { 5046 PetscErrorCode ierr; 5047 PetscInt m=A->rmap->n,n=B->cmap->n; 5048 Mat Cmat; 5049 5050 PetscFunctionBegin; 5051 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); 5052 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5053 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5054 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5055 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5056 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5057 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5058 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5059 5060 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5061 5062 *C = Cmat; 5063 PetscFunctionReturn(0); 5064 } 5065 5066 /* ----------------------------------------------------------------*/ 5067 #undef __FUNCT__ 5068 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5069 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5070 { 5071 PetscErrorCode ierr; 5072 5073 PetscFunctionBegin; 5074 if (scall == MAT_INITIAL_MATRIX) { 5075 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5076 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5077 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5078 } 5079 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5080 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5081 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5082 PetscFunctionReturn(0); 5083 } 5084 5085 /*MC 5086 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5087 5088 Options Database Keys: 5089 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5090 5091 Level: beginner 5092 5093 .seealso: MatCreateAIJ() 5094 M*/ 5095 5096 #undef __FUNCT__ 5097 #define __FUNCT__ "MatCreate_MPIAIJ" 5098 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5099 { 5100 Mat_MPIAIJ *b; 5101 PetscErrorCode ierr; 5102 PetscMPIInt size; 5103 5104 PetscFunctionBegin; 5105 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5106 5107 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5108 B->data = (void*)b; 5109 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5110 B->assembled = PETSC_FALSE; 5111 B->insertmode = NOT_SET_VALUES; 5112 b->size = size; 5113 5114 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5115 5116 /* build cache for off array entries formed */ 5117 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5118 5119 b->donotstash = PETSC_FALSE; 5120 b->colmap = 0; 5121 b->garray = 0; 5122 b->roworiented = PETSC_TRUE; 5123 5124 /* stuff used for matrix vector multiply */ 5125 b->lvec = NULL; 5126 b->Mvctx = NULL; 5127 5128 /* stuff for MatGetRow() */ 5129 b->rowindices = 0; 5130 b->rowvalues = 0; 5131 b->getrowactive = PETSC_FALSE; 5132 5133 /* flexible pointer used in CUSP/CUSPARSE classes */ 5134 b->spptr = NULL; 5135 5136 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5138 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5139 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5141 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5142 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5143 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5144 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5145 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5146 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5147 #if defined(PETSC_HAVE_ELEMENTAL) 5148 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5149 #endif 5150 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5151 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5152 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5153 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5154 PetscFunctionReturn(0); 5155 } 5156 5157 #undef __FUNCT__ 5158 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5159 /*@C 5160 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5161 and "off-diagonal" part of the matrix in CSR format. 5162 5163 Collective on MPI_Comm 5164 5165 Input Parameters: 5166 + comm - MPI communicator 5167 . m - number of local rows (Cannot be PETSC_DECIDE) 5168 . n - This value should be the same as the local size used in creating the 5169 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5170 calculated if N is given) For square matrices n is almost always m. 5171 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5172 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5173 . i - row indices for "diagonal" portion of matrix 5174 . j - column indices 5175 . a - matrix values 5176 . oi - row indices for "off-diagonal" portion of matrix 5177 . oj - column indices 5178 - oa - matrix values 5179 5180 Output Parameter: 5181 . mat - the matrix 5182 5183 Level: advanced 5184 5185 Notes: 5186 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5187 must free the arrays once the matrix has been destroyed and not before. 5188 5189 The i and j indices are 0 based 5190 5191 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5192 5193 This sets local rows and cannot be used to set off-processor values. 5194 5195 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5196 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5197 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5198 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5199 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5200 communication if it is known that only local entries will be set. 5201 5202 .keywords: matrix, aij, compressed row, sparse, parallel 5203 5204 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5205 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5206 @*/ 5207 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) 5208 { 5209 PetscErrorCode ierr; 5210 Mat_MPIAIJ *maij; 5211 5212 PetscFunctionBegin; 5213 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5214 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5215 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5216 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5217 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5218 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5219 maij = (Mat_MPIAIJ*) (*mat)->data; 5220 5221 (*mat)->preallocated = PETSC_TRUE; 5222 5223 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5224 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5225 5226 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5227 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5228 5229 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5230 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5231 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5232 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5233 5234 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5235 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5236 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5237 PetscFunctionReturn(0); 5238 } 5239 5240 /* 5241 Special version for direct calls from Fortran 5242 */ 5243 #include <petsc/private/fortranimpl.h> 5244 5245 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5246 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5247 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5248 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5249 #endif 5250 5251 /* Change these macros so can be used in void function */ 5252 #undef CHKERRQ 5253 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5254 #undef SETERRQ2 5255 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5256 #undef SETERRQ3 5257 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5258 #undef SETERRQ 5259 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5260 5261 #undef __FUNCT__ 5262 #define __FUNCT__ "matsetvaluesmpiaij_" 5263 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) 5264 { 5265 Mat mat = *mmat; 5266 PetscInt m = *mm, n = *mn; 5267 InsertMode addv = *maddv; 5268 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5269 PetscScalar value; 5270 PetscErrorCode ierr; 5271 5272 MatCheckPreallocated(mat,1); 5273 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5274 5275 #if defined(PETSC_USE_DEBUG) 5276 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5277 #endif 5278 { 5279 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5280 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5281 PetscBool roworiented = aij->roworiented; 5282 5283 /* Some Variables required in the macro */ 5284 Mat A = aij->A; 5285 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5286 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5287 MatScalar *aa = a->a; 5288 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5289 Mat B = aij->B; 5290 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5291 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5292 MatScalar *ba = b->a; 5293 5294 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5295 PetscInt nonew = a->nonew; 5296 MatScalar *ap1,*ap2; 5297 5298 PetscFunctionBegin; 5299 for (i=0; i<m; i++) { 5300 if (im[i] < 0) continue; 5301 #if defined(PETSC_USE_DEBUG) 5302 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); 5303 #endif 5304 if (im[i] >= rstart && im[i] < rend) { 5305 row = im[i] - rstart; 5306 lastcol1 = -1; 5307 rp1 = aj + ai[row]; 5308 ap1 = aa + ai[row]; 5309 rmax1 = aimax[row]; 5310 nrow1 = ailen[row]; 5311 low1 = 0; 5312 high1 = nrow1; 5313 lastcol2 = -1; 5314 rp2 = bj + bi[row]; 5315 ap2 = ba + bi[row]; 5316 rmax2 = bimax[row]; 5317 nrow2 = bilen[row]; 5318 low2 = 0; 5319 high2 = nrow2; 5320 5321 for (j=0; j<n; j++) { 5322 if (roworiented) value = v[i*n+j]; 5323 else value = v[i+j*m]; 5324 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5325 if (in[j] >= cstart && in[j] < cend) { 5326 col = in[j] - cstart; 5327 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5328 } else if (in[j] < 0) continue; 5329 #if defined(PETSC_USE_DEBUG) 5330 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); 5331 #endif 5332 else { 5333 if (mat->was_assembled) { 5334 if (!aij->colmap) { 5335 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5336 } 5337 #if defined(PETSC_USE_CTABLE) 5338 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5339 col--; 5340 #else 5341 col = aij->colmap[in[j]] - 1; 5342 #endif 5343 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5344 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5345 col = in[j]; 5346 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5347 B = aij->B; 5348 b = (Mat_SeqAIJ*)B->data; 5349 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5350 rp2 = bj + bi[row]; 5351 ap2 = ba + bi[row]; 5352 rmax2 = bimax[row]; 5353 nrow2 = bilen[row]; 5354 low2 = 0; 5355 high2 = nrow2; 5356 bm = aij->B->rmap->n; 5357 ba = b->a; 5358 } 5359 } else col = in[j]; 5360 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5361 } 5362 } 5363 } else if (!aij->donotstash) { 5364 if (roworiented) { 5365 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5366 } else { 5367 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5368 } 5369 } 5370 } 5371 } 5372 PetscFunctionReturnVoid(); 5373 } 5374 5375