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,MPIU_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) \ 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 (%D, %D) into matrix", row, col); \ 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) \ 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 (%D, %D) into matrix", row, col); \ 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); 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 (%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); 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 const char *matname; 1402 1403 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1404 if (!rank) { 1405 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1406 } else { 1407 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1408 } 1409 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1410 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1411 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1412 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1413 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1414 1415 /* copy over the A part */ 1416 Aloc = (Mat_SeqAIJ*)aij->A->data; 1417 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1418 row = mat->rmap->rstart; 1419 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1420 for (i=0; i<m; i++) { 1421 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1422 row++; 1423 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1424 } 1425 aj = Aloc->j; 1426 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1427 1428 /* copy over the B part */ 1429 Aloc = (Mat_SeqAIJ*)aij->B->data; 1430 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1431 row = mat->rmap->rstart; 1432 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1433 ct = cols; 1434 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1435 for (i=0; i<m; i++) { 1436 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1437 row++; 1438 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1439 } 1440 ierr = PetscFree(ct);CHKERRQ(ierr); 1441 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1442 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1443 /* 1444 Everyone has to call to draw the matrix since the graphics waits are 1445 synchronized across all processors that share the PetscDraw object 1446 */ 1447 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1448 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1449 if (!rank) { 1450 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1451 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1452 } 1453 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1454 ierr = MatDestroy(&A);CHKERRQ(ierr); 1455 } 1456 PetscFunctionReturn(0); 1457 } 1458 1459 #undef __FUNCT__ 1460 #define __FUNCT__ "MatView_MPIAIJ" 1461 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1462 { 1463 PetscErrorCode ierr; 1464 PetscBool iascii,isdraw,issocket,isbinary; 1465 1466 PetscFunctionBegin; 1467 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1468 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1469 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1470 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1471 if (iascii || isdraw || isbinary || issocket) { 1472 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1473 } 1474 PetscFunctionReturn(0); 1475 } 1476 1477 #undef __FUNCT__ 1478 #define __FUNCT__ "MatSOR_MPIAIJ" 1479 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1480 { 1481 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1482 PetscErrorCode ierr; 1483 Vec bb1 = 0; 1484 PetscBool hasop; 1485 1486 PetscFunctionBegin; 1487 if (flag == SOR_APPLY_UPPER) { 1488 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1489 PetscFunctionReturn(0); 1490 } 1491 1492 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1493 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1494 } 1495 1496 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1497 if (flag & SOR_ZERO_INITIAL_GUESS) { 1498 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1499 its--; 1500 } 1501 1502 while (its--) { 1503 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1504 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1505 1506 /* update rhs: bb1 = bb - B*x */ 1507 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1508 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1509 1510 /* local sweep */ 1511 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1512 } 1513 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1514 if (flag & SOR_ZERO_INITIAL_GUESS) { 1515 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1516 its--; 1517 } 1518 while (its--) { 1519 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1520 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1521 1522 /* update rhs: bb1 = bb - B*x */ 1523 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1524 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1525 1526 /* local sweep */ 1527 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1528 } 1529 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1530 if (flag & SOR_ZERO_INITIAL_GUESS) { 1531 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1532 its--; 1533 } 1534 while (its--) { 1535 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1536 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1537 1538 /* update rhs: bb1 = bb - B*x */ 1539 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1540 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1541 1542 /* local sweep */ 1543 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1544 } 1545 } else if (flag & SOR_EISENSTAT) { 1546 Vec xx1; 1547 1548 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1549 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1550 1551 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1552 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1553 if (!mat->diag) { 1554 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1555 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1556 } 1557 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1558 if (hasop) { 1559 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1560 } else { 1561 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1562 } 1563 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1564 1565 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1566 1567 /* local sweep */ 1568 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1569 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1570 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1571 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1572 1573 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1574 PetscFunctionReturn(0); 1575 } 1576 1577 #undef __FUNCT__ 1578 #define __FUNCT__ "MatPermute_MPIAIJ" 1579 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1580 { 1581 Mat aA,aB,Aperm; 1582 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1583 PetscScalar *aa,*ba; 1584 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1585 PetscSF rowsf,sf; 1586 IS parcolp = NULL; 1587 PetscBool done; 1588 PetscErrorCode ierr; 1589 1590 PetscFunctionBegin; 1591 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1592 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1593 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1594 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1595 1596 /* Invert row permutation to find out where my rows should go */ 1597 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1598 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1599 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1600 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1601 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1602 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1603 1604 /* Invert column permutation to find out where my columns should go */ 1605 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1606 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1607 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1608 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1609 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1610 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1611 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1612 1613 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1614 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1615 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1616 1617 /* Find out where my gcols should go */ 1618 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1619 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1620 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1621 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1622 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1623 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1624 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1625 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1626 1627 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1628 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1629 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1630 for (i=0; i<m; i++) { 1631 PetscInt row = rdest[i],rowner; 1632 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1633 for (j=ai[i]; j<ai[i+1]; j++) { 1634 PetscInt cowner,col = cdest[aj[j]]; 1635 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1636 if (rowner == cowner) dnnz[i]++; 1637 else onnz[i]++; 1638 } 1639 for (j=bi[i]; j<bi[i+1]; j++) { 1640 PetscInt cowner,col = gcdest[bj[j]]; 1641 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1642 if (rowner == cowner) dnnz[i]++; 1643 else onnz[i]++; 1644 } 1645 } 1646 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1647 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1648 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1649 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1650 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1651 1652 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1653 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1654 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1655 for (i=0; i<m; i++) { 1656 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1657 PetscInt j0,rowlen; 1658 rowlen = ai[i+1] - ai[i]; 1659 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1660 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1661 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1662 } 1663 rowlen = bi[i+1] - bi[i]; 1664 for (j0=j=0; j<rowlen; j0=j) { 1665 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1666 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1667 } 1668 } 1669 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1670 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1671 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1672 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1673 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1674 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1675 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1676 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1677 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1678 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1679 *B = Aperm; 1680 PetscFunctionReturn(0); 1681 } 1682 1683 #undef __FUNCT__ 1684 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1685 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1686 { 1687 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1688 Mat A = mat->A,B = mat->B; 1689 PetscErrorCode ierr; 1690 PetscReal isend[5],irecv[5]; 1691 1692 PetscFunctionBegin; 1693 info->block_size = 1.0; 1694 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1695 1696 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1697 isend[3] = info->memory; isend[4] = info->mallocs; 1698 1699 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1700 1701 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1702 isend[3] += info->memory; isend[4] += info->mallocs; 1703 if (flag == MAT_LOCAL) { 1704 info->nz_used = isend[0]; 1705 info->nz_allocated = isend[1]; 1706 info->nz_unneeded = isend[2]; 1707 info->memory = isend[3]; 1708 info->mallocs = isend[4]; 1709 } else if (flag == MAT_GLOBAL_MAX) { 1710 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1711 1712 info->nz_used = irecv[0]; 1713 info->nz_allocated = irecv[1]; 1714 info->nz_unneeded = irecv[2]; 1715 info->memory = irecv[3]; 1716 info->mallocs = irecv[4]; 1717 } else if (flag == MAT_GLOBAL_SUM) { 1718 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1719 1720 info->nz_used = irecv[0]; 1721 info->nz_allocated = irecv[1]; 1722 info->nz_unneeded = irecv[2]; 1723 info->memory = irecv[3]; 1724 info->mallocs = irecv[4]; 1725 } 1726 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1727 info->fill_ratio_needed = 0; 1728 info->factor_mallocs = 0; 1729 PetscFunctionReturn(0); 1730 } 1731 1732 #undef __FUNCT__ 1733 #define __FUNCT__ "MatSetOption_MPIAIJ" 1734 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1735 { 1736 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1737 PetscErrorCode ierr; 1738 1739 PetscFunctionBegin; 1740 switch (op) { 1741 case MAT_NEW_NONZERO_LOCATIONS: 1742 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1743 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1744 case MAT_KEEP_NONZERO_PATTERN: 1745 case MAT_NEW_NONZERO_LOCATION_ERR: 1746 case MAT_USE_INODES: 1747 case MAT_IGNORE_ZERO_ENTRIES: 1748 MatCheckPreallocated(A,1); 1749 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1750 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1751 break; 1752 case MAT_ROW_ORIENTED: 1753 a->roworiented = flg; 1754 1755 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1756 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1757 break; 1758 case MAT_NEW_DIAGONALS: 1759 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1760 break; 1761 case MAT_IGNORE_OFF_PROC_ENTRIES: 1762 a->donotstash = flg; 1763 break; 1764 case MAT_SPD: 1765 A->spd_set = PETSC_TRUE; 1766 A->spd = flg; 1767 if (flg) { 1768 A->symmetric = PETSC_TRUE; 1769 A->structurally_symmetric = PETSC_TRUE; 1770 A->symmetric_set = PETSC_TRUE; 1771 A->structurally_symmetric_set = PETSC_TRUE; 1772 } 1773 break; 1774 case MAT_SYMMETRIC: 1775 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1776 break; 1777 case MAT_STRUCTURALLY_SYMMETRIC: 1778 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1779 break; 1780 case MAT_HERMITIAN: 1781 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1782 break; 1783 case MAT_SYMMETRY_ETERNAL: 1784 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1785 break; 1786 default: 1787 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1788 } 1789 PetscFunctionReturn(0); 1790 } 1791 1792 #undef __FUNCT__ 1793 #define __FUNCT__ "MatGetRow_MPIAIJ" 1794 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1795 { 1796 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1797 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1798 PetscErrorCode ierr; 1799 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1800 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1801 PetscInt *cmap,*idx_p; 1802 1803 PetscFunctionBegin; 1804 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1805 mat->getrowactive = PETSC_TRUE; 1806 1807 if (!mat->rowvalues && (idx || v)) { 1808 /* 1809 allocate enough space to hold information from the longest row. 1810 */ 1811 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1812 PetscInt max = 1,tmp; 1813 for (i=0; i<matin->rmap->n; i++) { 1814 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1815 if (max < tmp) max = tmp; 1816 } 1817 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1818 } 1819 1820 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1821 lrow = row - rstart; 1822 1823 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1824 if (!v) {pvA = 0; pvB = 0;} 1825 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1826 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1827 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1828 nztot = nzA + nzB; 1829 1830 cmap = mat->garray; 1831 if (v || idx) { 1832 if (nztot) { 1833 /* Sort by increasing column numbers, assuming A and B already sorted */ 1834 PetscInt imark = -1; 1835 if (v) { 1836 *v = v_p = mat->rowvalues; 1837 for (i=0; i<nzB; i++) { 1838 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1839 else break; 1840 } 1841 imark = i; 1842 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1843 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1844 } 1845 if (idx) { 1846 *idx = idx_p = mat->rowindices; 1847 if (imark > -1) { 1848 for (i=0; i<imark; i++) { 1849 idx_p[i] = cmap[cworkB[i]]; 1850 } 1851 } else { 1852 for (i=0; i<nzB; i++) { 1853 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1854 else break; 1855 } 1856 imark = i; 1857 } 1858 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1859 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1860 } 1861 } else { 1862 if (idx) *idx = 0; 1863 if (v) *v = 0; 1864 } 1865 } 1866 *nz = nztot; 1867 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1868 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1869 PetscFunctionReturn(0); 1870 } 1871 1872 #undef __FUNCT__ 1873 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1874 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1875 { 1876 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1877 1878 PetscFunctionBegin; 1879 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1880 aij->getrowactive = PETSC_FALSE; 1881 PetscFunctionReturn(0); 1882 } 1883 1884 #undef __FUNCT__ 1885 #define __FUNCT__ "MatNorm_MPIAIJ" 1886 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1887 { 1888 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1889 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1890 PetscErrorCode ierr; 1891 PetscInt i,j,cstart = mat->cmap->rstart; 1892 PetscReal sum = 0.0; 1893 MatScalar *v; 1894 1895 PetscFunctionBegin; 1896 if (aij->size == 1) { 1897 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1898 } else { 1899 if (type == NORM_FROBENIUS) { 1900 v = amat->a; 1901 for (i=0; i<amat->nz; i++) { 1902 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1903 } 1904 v = bmat->a; 1905 for (i=0; i<bmat->nz; i++) { 1906 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1907 } 1908 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1909 *norm = PetscSqrtReal(*norm); 1910 } else if (type == NORM_1) { /* max column norm */ 1911 PetscReal *tmp,*tmp2; 1912 PetscInt *jj,*garray = aij->garray; 1913 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1914 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1915 *norm = 0.0; 1916 v = amat->a; jj = amat->j; 1917 for (j=0; j<amat->nz; j++) { 1918 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1919 } 1920 v = bmat->a; jj = bmat->j; 1921 for (j=0; j<bmat->nz; j++) { 1922 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1923 } 1924 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1925 for (j=0; j<mat->cmap->N; j++) { 1926 if (tmp2[j] > *norm) *norm = tmp2[j]; 1927 } 1928 ierr = PetscFree(tmp);CHKERRQ(ierr); 1929 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1930 } else if (type == NORM_INFINITY) { /* max row norm */ 1931 PetscReal ntemp = 0.0; 1932 for (j=0; j<aij->A->rmap->n; j++) { 1933 v = amat->a + amat->i[j]; 1934 sum = 0.0; 1935 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1936 sum += PetscAbsScalar(*v); v++; 1937 } 1938 v = bmat->a + bmat->i[j]; 1939 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1940 sum += PetscAbsScalar(*v); v++; 1941 } 1942 if (sum > ntemp) ntemp = sum; 1943 } 1944 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1945 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1946 } 1947 PetscFunctionReturn(0); 1948 } 1949 1950 #undef __FUNCT__ 1951 #define __FUNCT__ "MatTranspose_MPIAIJ" 1952 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1953 { 1954 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1955 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1956 PetscErrorCode ierr; 1957 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1958 PetscInt cstart = A->cmap->rstart,ncol; 1959 Mat B; 1960 MatScalar *array; 1961 1962 PetscFunctionBegin; 1963 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1964 1965 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1966 ai = Aloc->i; aj = Aloc->j; 1967 bi = Bloc->i; bj = Bloc->j; 1968 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1969 PetscInt *d_nnz,*g_nnz,*o_nnz; 1970 PetscSFNode *oloc; 1971 PETSC_UNUSED PetscSF sf; 1972 1973 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1974 /* compute d_nnz for preallocation */ 1975 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1976 for (i=0; i<ai[ma]; i++) { 1977 d_nnz[aj[i]]++; 1978 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1979 } 1980 /* compute local off-diagonal contributions */ 1981 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1982 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1983 /* map those to global */ 1984 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1985 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1986 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1987 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1988 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1989 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1990 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1991 1992 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1993 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1994 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1995 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1996 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1997 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1998 } else { 1999 B = *matout; 2000 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2001 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2002 } 2003 2004 /* copy over the A part */ 2005 array = Aloc->a; 2006 row = A->rmap->rstart; 2007 for (i=0; i<ma; i++) { 2008 ncol = ai[i+1]-ai[i]; 2009 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2010 row++; 2011 array += ncol; aj += ncol; 2012 } 2013 aj = Aloc->j; 2014 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2015 2016 /* copy over the B part */ 2017 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2018 array = Bloc->a; 2019 row = A->rmap->rstart; 2020 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2021 cols_tmp = cols; 2022 for (i=0; i<mb; i++) { 2023 ncol = bi[i+1]-bi[i]; 2024 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2025 row++; 2026 array += ncol; cols_tmp += ncol; 2027 } 2028 ierr = PetscFree(cols);CHKERRQ(ierr); 2029 2030 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2031 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2032 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2033 *matout = B; 2034 } else { 2035 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2036 } 2037 PetscFunctionReturn(0); 2038 } 2039 2040 #undef __FUNCT__ 2041 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2042 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2043 { 2044 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2045 Mat a = aij->A,b = aij->B; 2046 PetscErrorCode ierr; 2047 PetscInt s1,s2,s3; 2048 2049 PetscFunctionBegin; 2050 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2051 if (rr) { 2052 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2053 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2054 /* Overlap communication with computation. */ 2055 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2056 } 2057 if (ll) { 2058 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2059 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2060 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2061 } 2062 /* scale the diagonal block */ 2063 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2064 2065 if (rr) { 2066 /* Do a scatter end and then right scale the off-diagonal block */ 2067 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2068 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2069 } 2070 PetscFunctionReturn(0); 2071 } 2072 2073 #undef __FUNCT__ 2074 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2075 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2076 { 2077 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2078 PetscErrorCode ierr; 2079 2080 PetscFunctionBegin; 2081 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2082 PetscFunctionReturn(0); 2083 } 2084 2085 #undef __FUNCT__ 2086 #define __FUNCT__ "MatEqual_MPIAIJ" 2087 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2088 { 2089 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2090 Mat a,b,c,d; 2091 PetscBool flg; 2092 PetscErrorCode ierr; 2093 2094 PetscFunctionBegin; 2095 a = matA->A; b = matA->B; 2096 c = matB->A; d = matB->B; 2097 2098 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2099 if (flg) { 2100 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2101 } 2102 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2103 PetscFunctionReturn(0); 2104 } 2105 2106 #undef __FUNCT__ 2107 #define __FUNCT__ "MatCopy_MPIAIJ" 2108 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2109 { 2110 PetscErrorCode ierr; 2111 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2112 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2113 2114 PetscFunctionBegin; 2115 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2116 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2117 /* because of the column compression in the off-processor part of the matrix a->B, 2118 the number of columns in a->B and b->B may be different, hence we cannot call 2119 the MatCopy() directly on the two parts. If need be, we can provide a more 2120 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2121 then copying the submatrices */ 2122 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2123 } else { 2124 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2125 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2126 } 2127 PetscFunctionReturn(0); 2128 } 2129 2130 #undef __FUNCT__ 2131 #define __FUNCT__ "MatSetUp_MPIAIJ" 2132 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2133 { 2134 PetscErrorCode ierr; 2135 2136 PetscFunctionBegin; 2137 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2138 PetscFunctionReturn(0); 2139 } 2140 2141 /* 2142 Computes the number of nonzeros per row needed for preallocation when X and Y 2143 have different nonzero structure. 2144 */ 2145 #undef __FUNCT__ 2146 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2147 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) 2148 { 2149 PetscInt i,j,k,nzx,nzy; 2150 2151 PetscFunctionBegin; 2152 /* Set the number of nonzeros in the new matrix */ 2153 for (i=0; i<m; i++) { 2154 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2155 nzx = xi[i+1] - xi[i]; 2156 nzy = yi[i+1] - yi[i]; 2157 nnz[i] = 0; 2158 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2159 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2160 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2161 nnz[i]++; 2162 } 2163 for (; k<nzy; k++) nnz[i]++; 2164 } 2165 PetscFunctionReturn(0); 2166 } 2167 2168 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2169 #undef __FUNCT__ 2170 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2171 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2172 { 2173 PetscErrorCode ierr; 2174 PetscInt m = Y->rmap->N; 2175 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2176 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2177 2178 PetscFunctionBegin; 2179 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2180 PetscFunctionReturn(0); 2181 } 2182 2183 #undef __FUNCT__ 2184 #define __FUNCT__ "MatAXPY_MPIAIJ" 2185 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2186 { 2187 PetscErrorCode ierr; 2188 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2189 PetscBLASInt bnz,one=1; 2190 Mat_SeqAIJ *x,*y; 2191 2192 PetscFunctionBegin; 2193 if (str == SAME_NONZERO_PATTERN) { 2194 PetscScalar alpha = a; 2195 x = (Mat_SeqAIJ*)xx->A->data; 2196 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2197 y = (Mat_SeqAIJ*)yy->A->data; 2198 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2199 x = (Mat_SeqAIJ*)xx->B->data; 2200 y = (Mat_SeqAIJ*)yy->B->data; 2201 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2202 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2203 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2204 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2205 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2206 } else { 2207 Mat B; 2208 PetscInt *nnz_d,*nnz_o; 2209 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2210 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2211 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2212 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2213 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2214 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2215 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2216 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2217 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2218 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2219 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2220 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2221 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2222 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2223 } 2224 PetscFunctionReturn(0); 2225 } 2226 2227 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2228 2229 #undef __FUNCT__ 2230 #define __FUNCT__ "MatConjugate_MPIAIJ" 2231 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2232 { 2233 #if defined(PETSC_USE_COMPLEX) 2234 PetscErrorCode ierr; 2235 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2236 2237 PetscFunctionBegin; 2238 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2239 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2240 #else 2241 PetscFunctionBegin; 2242 #endif 2243 PetscFunctionReturn(0); 2244 } 2245 2246 #undef __FUNCT__ 2247 #define __FUNCT__ "MatRealPart_MPIAIJ" 2248 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2249 { 2250 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2251 PetscErrorCode ierr; 2252 2253 PetscFunctionBegin; 2254 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2255 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2256 PetscFunctionReturn(0); 2257 } 2258 2259 #undef __FUNCT__ 2260 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2261 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2262 { 2263 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2264 PetscErrorCode ierr; 2265 2266 PetscFunctionBegin; 2267 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2268 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2269 PetscFunctionReturn(0); 2270 } 2271 2272 #if defined(PETSC_HAVE_PBGL) 2273 2274 #include <boost/parallel/mpi/bsp_process_group.hpp> 2275 #include <boost/graph/distributed/ilu_default_graph.hpp> 2276 #include <boost/graph/distributed/ilu_0_block.hpp> 2277 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2278 #include <boost/graph/distributed/petsc/interface.hpp> 2279 #include <boost/multi_array.hpp> 2280 #include <boost/parallel/distributed_property_map->hpp> 2281 2282 #undef __FUNCT__ 2283 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2284 /* 2285 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2286 */ 2287 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2288 { 2289 namespace petsc = boost::distributed::petsc; 2290 2291 namespace graph_dist = boost::graph::distributed; 2292 using boost::graph::distributed::ilu_default::process_group_type; 2293 using boost::graph::ilu_permuted; 2294 2295 PetscBool row_identity, col_identity; 2296 PetscContainer c; 2297 PetscInt m, n, M, N; 2298 PetscErrorCode ierr; 2299 2300 PetscFunctionBegin; 2301 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2302 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2303 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2304 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2305 2306 process_group_type pg; 2307 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2308 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2309 lgraph_type& level_graph = *lgraph_p; 2310 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2311 2312 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2313 ilu_permuted(level_graph); 2314 2315 /* put together the new matrix */ 2316 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2317 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2318 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2319 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2320 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2321 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2322 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2323 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2324 2325 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2326 ierr = PetscContainerSetPointer(c, lgraph_p); 2327 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2328 ierr = PetscContainerDestroy(&c); 2329 PetscFunctionReturn(0); 2330 } 2331 2332 #undef __FUNCT__ 2333 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2334 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2335 { 2336 PetscFunctionBegin; 2337 PetscFunctionReturn(0); 2338 } 2339 2340 #undef __FUNCT__ 2341 #define __FUNCT__ "MatSolve_MPIAIJ" 2342 /* 2343 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2344 */ 2345 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2346 { 2347 namespace graph_dist = boost::graph::distributed; 2348 2349 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2350 lgraph_type *lgraph_p; 2351 PetscContainer c; 2352 PetscErrorCode ierr; 2353 2354 PetscFunctionBegin; 2355 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2356 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2357 ierr = VecCopy(b, x);CHKERRQ(ierr); 2358 2359 PetscScalar *array_x; 2360 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2361 PetscInt sx; 2362 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2363 2364 PetscScalar *array_b; 2365 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2366 PetscInt sb; 2367 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2368 2369 lgraph_type& level_graph = *lgraph_p; 2370 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2371 2372 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2373 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2374 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2375 2376 typedef boost::iterator_property_map<array_ref_type::iterator, 2377 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2378 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2379 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2380 2381 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2382 PetscFunctionReturn(0); 2383 } 2384 #endif 2385 2386 #undef __FUNCT__ 2387 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2388 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2389 { 2390 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2391 PetscErrorCode ierr; 2392 PetscInt i,*idxb = 0; 2393 PetscScalar *va,*vb; 2394 Vec vtmp; 2395 2396 PetscFunctionBegin; 2397 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2398 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2399 if (idx) { 2400 for (i=0; i<A->rmap->n; i++) { 2401 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2402 } 2403 } 2404 2405 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2406 if (idx) { 2407 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2408 } 2409 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2410 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2411 2412 for (i=0; i<A->rmap->n; i++) { 2413 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2414 va[i] = vb[i]; 2415 if (idx) idx[i] = a->garray[idxb[i]]; 2416 } 2417 } 2418 2419 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2420 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2421 ierr = PetscFree(idxb);CHKERRQ(ierr); 2422 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2423 PetscFunctionReturn(0); 2424 } 2425 2426 #undef __FUNCT__ 2427 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2428 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2429 { 2430 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2431 PetscErrorCode ierr; 2432 PetscInt i,*idxb = 0; 2433 PetscScalar *va,*vb; 2434 Vec vtmp; 2435 2436 PetscFunctionBegin; 2437 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2438 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2439 if (idx) { 2440 for (i=0; i<A->cmap->n; i++) { 2441 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2442 } 2443 } 2444 2445 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2446 if (idx) { 2447 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2448 } 2449 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2450 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2451 2452 for (i=0; i<A->rmap->n; i++) { 2453 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2454 va[i] = vb[i]; 2455 if (idx) idx[i] = a->garray[idxb[i]]; 2456 } 2457 } 2458 2459 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2460 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2461 ierr = PetscFree(idxb);CHKERRQ(ierr); 2462 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2463 PetscFunctionReturn(0); 2464 } 2465 2466 #undef __FUNCT__ 2467 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2468 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2469 { 2470 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2471 PetscInt n = A->rmap->n; 2472 PetscInt cstart = A->cmap->rstart; 2473 PetscInt *cmap = mat->garray; 2474 PetscInt *diagIdx, *offdiagIdx; 2475 Vec diagV, offdiagV; 2476 PetscScalar *a, *diagA, *offdiagA; 2477 PetscInt r; 2478 PetscErrorCode ierr; 2479 2480 PetscFunctionBegin; 2481 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2482 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2483 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2484 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2485 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2486 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2487 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2488 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2489 for (r = 0; r < n; ++r) { 2490 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2491 a[r] = diagA[r]; 2492 idx[r] = cstart + diagIdx[r]; 2493 } else { 2494 a[r] = offdiagA[r]; 2495 idx[r] = cmap[offdiagIdx[r]]; 2496 } 2497 } 2498 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2499 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2500 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2501 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2502 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2503 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2504 PetscFunctionReturn(0); 2505 } 2506 2507 #undef __FUNCT__ 2508 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2509 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2510 { 2511 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2512 PetscInt n = A->rmap->n; 2513 PetscInt cstart = A->cmap->rstart; 2514 PetscInt *cmap = mat->garray; 2515 PetscInt *diagIdx, *offdiagIdx; 2516 Vec diagV, offdiagV; 2517 PetscScalar *a, *diagA, *offdiagA; 2518 PetscInt r; 2519 PetscErrorCode ierr; 2520 2521 PetscFunctionBegin; 2522 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2523 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2524 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2525 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2526 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2527 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2528 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2529 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2530 for (r = 0; r < n; ++r) { 2531 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2532 a[r] = diagA[r]; 2533 idx[r] = cstart + diagIdx[r]; 2534 } else { 2535 a[r] = offdiagA[r]; 2536 idx[r] = cmap[offdiagIdx[r]]; 2537 } 2538 } 2539 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2540 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2541 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2542 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2543 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2544 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2545 PetscFunctionReturn(0); 2546 } 2547 2548 #undef __FUNCT__ 2549 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2550 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2551 { 2552 PetscErrorCode ierr; 2553 Mat *dummy; 2554 2555 PetscFunctionBegin; 2556 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2557 *newmat = *dummy; 2558 ierr = PetscFree(dummy);CHKERRQ(ierr); 2559 PetscFunctionReturn(0); 2560 } 2561 2562 #undef __FUNCT__ 2563 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2564 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2565 { 2566 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2567 PetscErrorCode ierr; 2568 2569 PetscFunctionBegin; 2570 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2571 PetscFunctionReturn(0); 2572 } 2573 2574 #undef __FUNCT__ 2575 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2576 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2577 { 2578 PetscErrorCode ierr; 2579 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2580 2581 PetscFunctionBegin; 2582 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2583 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2584 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2585 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2586 PetscFunctionReturn(0); 2587 } 2588 2589 /* -------------------------------------------------------------------*/ 2590 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2591 MatGetRow_MPIAIJ, 2592 MatRestoreRow_MPIAIJ, 2593 MatMult_MPIAIJ, 2594 /* 4*/ MatMultAdd_MPIAIJ, 2595 MatMultTranspose_MPIAIJ, 2596 MatMultTransposeAdd_MPIAIJ, 2597 #if defined(PETSC_HAVE_PBGL) 2598 MatSolve_MPIAIJ, 2599 #else 2600 0, 2601 #endif 2602 0, 2603 0, 2604 /*10*/ 0, 2605 0, 2606 0, 2607 MatSOR_MPIAIJ, 2608 MatTranspose_MPIAIJ, 2609 /*15*/ MatGetInfo_MPIAIJ, 2610 MatEqual_MPIAIJ, 2611 MatGetDiagonal_MPIAIJ, 2612 MatDiagonalScale_MPIAIJ, 2613 MatNorm_MPIAIJ, 2614 /*20*/ MatAssemblyBegin_MPIAIJ, 2615 MatAssemblyEnd_MPIAIJ, 2616 MatSetOption_MPIAIJ, 2617 MatZeroEntries_MPIAIJ, 2618 /*24*/ MatZeroRows_MPIAIJ, 2619 0, 2620 #if defined(PETSC_HAVE_PBGL) 2621 0, 2622 #else 2623 0, 2624 #endif 2625 0, 2626 0, 2627 /*29*/ MatSetUp_MPIAIJ, 2628 #if defined(PETSC_HAVE_PBGL) 2629 0, 2630 #else 2631 0, 2632 #endif 2633 0, 2634 0, 2635 0, 2636 /*34*/ MatDuplicate_MPIAIJ, 2637 0, 2638 0, 2639 0, 2640 0, 2641 /*39*/ MatAXPY_MPIAIJ, 2642 MatGetSubMatrices_MPIAIJ, 2643 MatIncreaseOverlap_MPIAIJ, 2644 MatGetValues_MPIAIJ, 2645 MatCopy_MPIAIJ, 2646 /*44*/ MatGetRowMax_MPIAIJ, 2647 MatScale_MPIAIJ, 2648 0, 2649 MatDiagonalSet_MPIAIJ, 2650 MatZeroRowsColumns_MPIAIJ, 2651 /*49*/ MatSetRandom_MPIAIJ, 2652 0, 2653 0, 2654 0, 2655 0, 2656 /*54*/ MatFDColoringCreate_MPIXAIJ, 2657 0, 2658 MatSetUnfactored_MPIAIJ, 2659 MatPermute_MPIAIJ, 2660 0, 2661 /*59*/ MatGetSubMatrix_MPIAIJ, 2662 MatDestroy_MPIAIJ, 2663 MatView_MPIAIJ, 2664 0, 2665 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2666 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2667 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2668 0, 2669 0, 2670 0, 2671 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2672 MatGetRowMinAbs_MPIAIJ, 2673 0, 2674 MatSetColoring_MPIAIJ, 2675 0, 2676 MatSetValuesAdifor_MPIAIJ, 2677 /*75*/ MatFDColoringApply_AIJ, 2678 0, 2679 0, 2680 0, 2681 MatFindZeroDiagonals_MPIAIJ, 2682 /*80*/ 0, 2683 0, 2684 0, 2685 /*83*/ MatLoad_MPIAIJ, 2686 0, 2687 0, 2688 0, 2689 0, 2690 0, 2691 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2692 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2693 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2694 MatPtAP_MPIAIJ_MPIAIJ, 2695 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2696 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2697 0, 2698 0, 2699 0, 2700 0, 2701 /*99*/ 0, 2702 0, 2703 0, 2704 MatConjugate_MPIAIJ, 2705 0, 2706 /*104*/MatSetValuesRow_MPIAIJ, 2707 MatRealPart_MPIAIJ, 2708 MatImaginaryPart_MPIAIJ, 2709 0, 2710 0, 2711 /*109*/0, 2712 0, 2713 MatGetRowMin_MPIAIJ, 2714 0, 2715 0, 2716 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2717 0, 2718 0, 2719 0, 2720 0, 2721 /*119*/0, 2722 0, 2723 0, 2724 0, 2725 MatGetMultiProcBlock_MPIAIJ, 2726 /*124*/MatFindNonzeroRows_MPIAIJ, 2727 MatGetColumnNorms_MPIAIJ, 2728 MatInvertBlockDiagonal_MPIAIJ, 2729 0, 2730 MatGetSubMatricesParallel_MPIAIJ, 2731 /*129*/0, 2732 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2733 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2734 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2735 0, 2736 /*134*/0, 2737 0, 2738 0, 2739 0, 2740 0, 2741 /*139*/0, 2742 0, 2743 0, 2744 MatFDColoringSetUp_MPIXAIJ, 2745 MatFindOffBlockDiagonalEntries_MPIAIJ, 2746 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2747 }; 2748 2749 /* ----------------------------------------------------------------------------------------*/ 2750 2751 #undef __FUNCT__ 2752 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2753 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2754 { 2755 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2756 PetscErrorCode ierr; 2757 2758 PetscFunctionBegin; 2759 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2760 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2761 PetscFunctionReturn(0); 2762 } 2763 2764 #undef __FUNCT__ 2765 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2766 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2767 { 2768 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2769 PetscErrorCode ierr; 2770 2771 PetscFunctionBegin; 2772 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2773 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2774 PetscFunctionReturn(0); 2775 } 2776 2777 #undef __FUNCT__ 2778 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2779 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2780 { 2781 Mat_MPIAIJ *b; 2782 PetscErrorCode ierr; 2783 2784 PetscFunctionBegin; 2785 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2786 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2787 b = (Mat_MPIAIJ*)B->data; 2788 2789 if (!B->preallocated) { 2790 /* Explicitly create 2 MATSEQAIJ matrices. */ 2791 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2792 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2793 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2794 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2795 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2796 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2797 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2798 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2799 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2800 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2801 } 2802 2803 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2804 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2805 B->preallocated = PETSC_TRUE; 2806 PetscFunctionReturn(0); 2807 } 2808 2809 #undef __FUNCT__ 2810 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2811 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2812 { 2813 Mat mat; 2814 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2815 PetscErrorCode ierr; 2816 2817 PetscFunctionBegin; 2818 *newmat = 0; 2819 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2820 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2821 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2822 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2823 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2824 a = (Mat_MPIAIJ*)mat->data; 2825 2826 mat->factortype = matin->factortype; 2827 mat->assembled = PETSC_TRUE; 2828 mat->insertmode = NOT_SET_VALUES; 2829 mat->preallocated = PETSC_TRUE; 2830 2831 a->size = oldmat->size; 2832 a->rank = oldmat->rank; 2833 a->donotstash = oldmat->donotstash; 2834 a->roworiented = oldmat->roworiented; 2835 a->rowindices = 0; 2836 a->rowvalues = 0; 2837 a->getrowactive = PETSC_FALSE; 2838 2839 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2840 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2841 2842 if (oldmat->colmap) { 2843 #if defined(PETSC_USE_CTABLE) 2844 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2845 #else 2846 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2847 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2848 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2849 #endif 2850 } else a->colmap = 0; 2851 if (oldmat->garray) { 2852 PetscInt len; 2853 len = oldmat->B->cmap->n; 2854 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2855 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2856 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2857 } else a->garray = 0; 2858 2859 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2860 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2861 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2862 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2863 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2864 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2865 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2866 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2867 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2868 *newmat = mat; 2869 PetscFunctionReturn(0); 2870 } 2871 2872 2873 2874 #undef __FUNCT__ 2875 #define __FUNCT__ "MatLoad_MPIAIJ" 2876 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2877 { 2878 PetscScalar *vals,*svals; 2879 MPI_Comm comm; 2880 PetscErrorCode ierr; 2881 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2882 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 2883 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2884 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2885 PetscInt cend,cstart,n,*rowners,sizesset=1; 2886 int fd; 2887 PetscInt bs = newMat->rmap->bs; 2888 2889 PetscFunctionBegin; 2890 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2891 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2892 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2893 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2894 if (!rank) { 2895 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2896 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2897 } 2898 2899 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 2900 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2901 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2902 if (bs < 0) bs = 1; 2903 2904 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 2905 2906 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2907 M = header[1]; N = header[2]; 2908 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2909 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 2910 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 2911 2912 /* If global sizes are set, check if they are consistent with that given in the file */ 2913 if (sizesset) { 2914 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 2915 } 2916 if (sizesset && newMat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 2917 if (sizesset && newMat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 2918 2919 /* determine ownership of all (block) rows */ 2920 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2921 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2922 else m = newMat->rmap->n; /* Set by user */ 2923 2924 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2925 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2926 2927 /* First process needs enough room for process with most rows */ 2928 if (!rank) { 2929 mmax = rowners[1]; 2930 for (i=2; i<=size; i++) { 2931 mmax = PetscMax(mmax, rowners[i]); 2932 } 2933 } else mmax = -1; /* unused, but compilers complain */ 2934 2935 rowners[0] = 0; 2936 for (i=2; i<=size; i++) { 2937 rowners[i] += rowners[i-1]; 2938 } 2939 rstart = rowners[rank]; 2940 rend = rowners[rank+1]; 2941 2942 /* distribute row lengths to all processors */ 2943 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2944 if (!rank) { 2945 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2946 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2947 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2948 for (j=0; j<m; j++) { 2949 procsnz[0] += ourlens[j]; 2950 } 2951 for (i=1; i<size; i++) { 2952 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2953 /* calculate the number of nonzeros on each processor */ 2954 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2955 procsnz[i] += rowlengths[j]; 2956 } 2957 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2958 } 2959 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2960 } else { 2961 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2962 } 2963 2964 if (!rank) { 2965 /* determine max buffer needed and allocate it */ 2966 maxnz = 0; 2967 for (i=0; i<size; i++) { 2968 maxnz = PetscMax(maxnz,procsnz[i]); 2969 } 2970 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2971 2972 /* read in my part of the matrix column indices */ 2973 nz = procsnz[0]; 2974 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2975 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2976 2977 /* read in every one elses and ship off */ 2978 for (i=1; i<size; i++) { 2979 nz = procsnz[i]; 2980 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2981 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2982 } 2983 ierr = PetscFree(cols);CHKERRQ(ierr); 2984 } else { 2985 /* determine buffer space needed for message */ 2986 nz = 0; 2987 for (i=0; i<m; i++) { 2988 nz += ourlens[i]; 2989 } 2990 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2991 2992 /* receive message of column indices*/ 2993 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2994 } 2995 2996 /* determine column ownership if matrix is not square */ 2997 if (N != M) { 2998 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2999 else n = newMat->cmap->n; 3000 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3001 cstart = cend - n; 3002 } else { 3003 cstart = rstart; 3004 cend = rend; 3005 n = cend - cstart; 3006 } 3007 3008 /* loop over local rows, determining number of off diagonal entries */ 3009 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3010 jj = 0; 3011 for (i=0; i<m; i++) { 3012 for (j=0; j<ourlens[i]; j++) { 3013 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3014 jj++; 3015 } 3016 } 3017 3018 for (i=0; i<m; i++) { 3019 ourlens[i] -= offlens[i]; 3020 } 3021 if (!sizesset) { 3022 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3023 } 3024 3025 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3026 3027 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3028 3029 for (i=0; i<m; i++) { 3030 ourlens[i] += offlens[i]; 3031 } 3032 3033 if (!rank) { 3034 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3035 3036 /* read in my part of the matrix numerical values */ 3037 nz = procsnz[0]; 3038 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3039 3040 /* insert into matrix */ 3041 jj = rstart; 3042 smycols = mycols; 3043 svals = vals; 3044 for (i=0; i<m; i++) { 3045 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3046 smycols += ourlens[i]; 3047 svals += ourlens[i]; 3048 jj++; 3049 } 3050 3051 /* read in other processors and ship out */ 3052 for (i=1; i<size; i++) { 3053 nz = procsnz[i]; 3054 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3055 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3056 } 3057 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3058 } else { 3059 /* receive numeric values */ 3060 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3061 3062 /* receive message of values*/ 3063 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3064 3065 /* insert into matrix */ 3066 jj = rstart; 3067 smycols = mycols; 3068 svals = vals; 3069 for (i=0; i<m; i++) { 3070 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3071 smycols += ourlens[i]; 3072 svals += ourlens[i]; 3073 jj++; 3074 } 3075 } 3076 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3077 ierr = PetscFree(vals);CHKERRQ(ierr); 3078 ierr = PetscFree(mycols);CHKERRQ(ierr); 3079 ierr = PetscFree(rowners);CHKERRQ(ierr); 3080 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3081 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3082 PetscFunctionReturn(0); 3083 } 3084 3085 #undef __FUNCT__ 3086 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3087 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3088 { 3089 PetscErrorCode ierr; 3090 IS iscol_local; 3091 PetscInt csize; 3092 3093 PetscFunctionBegin; 3094 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3095 if (call == MAT_REUSE_MATRIX) { 3096 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3097 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3098 } else { 3099 PetscInt cbs; 3100 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3101 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3102 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3103 } 3104 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3105 if (call == MAT_INITIAL_MATRIX) { 3106 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3107 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3108 } 3109 PetscFunctionReturn(0); 3110 } 3111 3112 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3113 #undef __FUNCT__ 3114 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3115 /* 3116 Not great since it makes two copies of the submatrix, first an SeqAIJ 3117 in local and then by concatenating the local matrices the end result. 3118 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3119 3120 Note: This requires a sequential iscol with all indices. 3121 */ 3122 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3123 { 3124 PetscErrorCode ierr; 3125 PetscMPIInt rank,size; 3126 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3127 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3128 PetscBool allcolumns, colflag; 3129 Mat M,Mreuse; 3130 MatScalar *vwork,*aa; 3131 MPI_Comm comm; 3132 Mat_SeqAIJ *aij; 3133 3134 PetscFunctionBegin; 3135 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3136 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3137 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3138 3139 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3140 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3141 if (colflag && ncol == mat->cmap->N) { 3142 allcolumns = PETSC_TRUE; 3143 } else { 3144 allcolumns = PETSC_FALSE; 3145 } 3146 if (call == MAT_REUSE_MATRIX) { 3147 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3148 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3149 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3150 } else { 3151 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3152 } 3153 3154 /* 3155 m - number of local rows 3156 n - number of columns (same on all processors) 3157 rstart - first row in new global matrix generated 3158 */ 3159 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3160 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3161 if (call == MAT_INITIAL_MATRIX) { 3162 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3163 ii = aij->i; 3164 jj = aij->j; 3165 3166 /* 3167 Determine the number of non-zeros in the diagonal and off-diagonal 3168 portions of the matrix in order to do correct preallocation 3169 */ 3170 3171 /* first get start and end of "diagonal" columns */ 3172 if (csize == PETSC_DECIDE) { 3173 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3174 if (mglobal == n) { /* square matrix */ 3175 nlocal = m; 3176 } else { 3177 nlocal = n/size + ((n % size) > rank); 3178 } 3179 } else { 3180 nlocal = csize; 3181 } 3182 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3183 rstart = rend - nlocal; 3184 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); 3185 3186 /* next, compute all the lengths */ 3187 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3188 olens = dlens + m; 3189 for (i=0; i<m; i++) { 3190 jend = ii[i+1] - ii[i]; 3191 olen = 0; 3192 dlen = 0; 3193 for (j=0; j<jend; j++) { 3194 if (*jj < rstart || *jj >= rend) olen++; 3195 else dlen++; 3196 jj++; 3197 } 3198 olens[i] = olen; 3199 dlens[i] = dlen; 3200 } 3201 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3202 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3203 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3204 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3205 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3206 ierr = PetscFree(dlens);CHKERRQ(ierr); 3207 } else { 3208 PetscInt ml,nl; 3209 3210 M = *newmat; 3211 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3212 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3213 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3214 /* 3215 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3216 rather than the slower MatSetValues(). 3217 */ 3218 M->was_assembled = PETSC_TRUE; 3219 M->assembled = PETSC_FALSE; 3220 } 3221 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3222 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3223 ii = aij->i; 3224 jj = aij->j; 3225 aa = aij->a; 3226 for (i=0; i<m; i++) { 3227 row = rstart + i; 3228 nz = ii[i+1] - ii[i]; 3229 cwork = jj; jj += nz; 3230 vwork = aa; aa += nz; 3231 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3232 } 3233 3234 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3235 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3236 *newmat = M; 3237 3238 /* save submatrix used in processor for next request */ 3239 if (call == MAT_INITIAL_MATRIX) { 3240 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3241 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3242 } 3243 PetscFunctionReturn(0); 3244 } 3245 3246 #undef __FUNCT__ 3247 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3248 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3249 { 3250 PetscInt m,cstart, cend,j,nnz,i,d; 3251 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3252 const PetscInt *JJ; 3253 PetscScalar *values; 3254 PetscErrorCode ierr; 3255 3256 PetscFunctionBegin; 3257 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3258 3259 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3260 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3261 m = B->rmap->n; 3262 cstart = B->cmap->rstart; 3263 cend = B->cmap->rend; 3264 rstart = B->rmap->rstart; 3265 3266 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3267 3268 #if defined(PETSC_USE_DEBUGGING) 3269 for (i=0; i<m; i++) { 3270 nnz = Ii[i+1]- Ii[i]; 3271 JJ = J + Ii[i]; 3272 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3273 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3274 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); 3275 } 3276 #endif 3277 3278 for (i=0; i<m; i++) { 3279 nnz = Ii[i+1]- Ii[i]; 3280 JJ = J + Ii[i]; 3281 nnz_max = PetscMax(nnz_max,nnz); 3282 d = 0; 3283 for (j=0; j<nnz; j++) { 3284 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3285 } 3286 d_nnz[i] = d; 3287 o_nnz[i] = nnz - d; 3288 } 3289 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3290 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3291 3292 if (v) values = (PetscScalar*)v; 3293 else { 3294 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3295 } 3296 3297 for (i=0; i<m; i++) { 3298 ii = i + rstart; 3299 nnz = Ii[i+1]- Ii[i]; 3300 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3301 } 3302 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3303 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3304 3305 if (!v) { 3306 ierr = PetscFree(values);CHKERRQ(ierr); 3307 } 3308 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3309 PetscFunctionReturn(0); 3310 } 3311 3312 #undef __FUNCT__ 3313 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3314 /*@ 3315 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3316 (the default parallel PETSc format). 3317 3318 Collective on MPI_Comm 3319 3320 Input Parameters: 3321 + B - the matrix 3322 . i - the indices into j for the start of each local row (starts with zero) 3323 . j - the column indices for each local row (starts with zero) 3324 - v - optional values in the matrix 3325 3326 Level: developer 3327 3328 Notes: 3329 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3330 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3331 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3332 3333 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3334 3335 The format which is used for the sparse matrix input, is equivalent to a 3336 row-major ordering.. i.e for the following matrix, the input data expected is 3337 as shown: 3338 3339 1 0 0 3340 2 0 3 P0 3341 ------- 3342 4 5 6 P1 3343 3344 Process0 [P0]: rows_owned=[0,1] 3345 i = {0,1,3} [size = nrow+1 = 2+1] 3346 j = {0,0,2} [size = nz = 6] 3347 v = {1,2,3} [size = nz = 6] 3348 3349 Process1 [P1]: rows_owned=[2] 3350 i = {0,3} [size = nrow+1 = 1+1] 3351 j = {0,1,2} [size = nz = 6] 3352 v = {4,5,6} [size = nz = 6] 3353 3354 .keywords: matrix, aij, compressed row, sparse, parallel 3355 3356 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3357 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3358 @*/ 3359 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3360 { 3361 PetscErrorCode ierr; 3362 3363 PetscFunctionBegin; 3364 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3365 PetscFunctionReturn(0); 3366 } 3367 3368 #undef __FUNCT__ 3369 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3370 /*@C 3371 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3372 (the default parallel PETSc format). For good matrix assembly performance 3373 the user should preallocate the matrix storage by setting the parameters 3374 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3375 performance can be increased by more than a factor of 50. 3376 3377 Collective on MPI_Comm 3378 3379 Input Parameters: 3380 + B - the matrix 3381 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3382 (same value is used for all local rows) 3383 . d_nnz - array containing the number of nonzeros in the various rows of the 3384 DIAGONAL portion of the local submatrix (possibly different for each row) 3385 or NULL, if d_nz is used to specify the nonzero structure. 3386 The size of this array is equal to the number of local rows, i.e 'm'. 3387 For matrices that will be factored, you must leave room for (and set) 3388 the diagonal entry even if it is zero. 3389 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3390 submatrix (same value is used for all local rows). 3391 - o_nnz - array containing the number of nonzeros in the various rows of the 3392 OFF-DIAGONAL portion of the local submatrix (possibly different for 3393 each row) or NULL, if o_nz is used to specify the nonzero 3394 structure. The size of this array is equal to the number 3395 of local rows, i.e 'm'. 3396 3397 If the *_nnz parameter is given then the *_nz parameter is ignored 3398 3399 The AIJ format (also called the Yale sparse matrix format or 3400 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3401 storage. The stored row and column indices begin with zero. 3402 See Users-Manual: ch_mat for details. 3403 3404 The parallel matrix is partitioned such that the first m0 rows belong to 3405 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3406 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3407 3408 The DIAGONAL portion of the local submatrix of a processor can be defined 3409 as the submatrix which is obtained by extraction the part corresponding to 3410 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3411 first row that belongs to the processor, r2 is the last row belonging to 3412 the this processor, and c1-c2 is range of indices of the local part of a 3413 vector suitable for applying the matrix to. This is an mxn matrix. In the 3414 common case of a square matrix, the row and column ranges are the same and 3415 the DIAGONAL part is also square. The remaining portion of the local 3416 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3417 3418 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3419 3420 You can call MatGetInfo() to get information on how effective the preallocation was; 3421 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3422 You can also run with the option -info and look for messages with the string 3423 malloc in them to see if additional memory allocation was needed. 3424 3425 Example usage: 3426 3427 Consider the following 8x8 matrix with 34 non-zero values, that is 3428 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3429 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3430 as follows: 3431 3432 .vb 3433 1 2 0 | 0 3 0 | 0 4 3434 Proc0 0 5 6 | 7 0 0 | 8 0 3435 9 0 10 | 11 0 0 | 12 0 3436 ------------------------------------- 3437 13 0 14 | 15 16 17 | 0 0 3438 Proc1 0 18 0 | 19 20 21 | 0 0 3439 0 0 0 | 22 23 0 | 24 0 3440 ------------------------------------- 3441 Proc2 25 26 27 | 0 0 28 | 29 0 3442 30 0 0 | 31 32 33 | 0 34 3443 .ve 3444 3445 This can be represented as a collection of submatrices as: 3446 3447 .vb 3448 A B C 3449 D E F 3450 G H I 3451 .ve 3452 3453 Where the submatrices A,B,C are owned by proc0, D,E,F are 3454 owned by proc1, G,H,I are owned by proc2. 3455 3456 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3457 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3458 The 'M','N' parameters are 8,8, and have the same values on all procs. 3459 3460 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3461 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3462 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3463 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3464 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3465 matrix, ans [DF] as another SeqAIJ matrix. 3466 3467 When d_nz, o_nz parameters are specified, d_nz storage elements are 3468 allocated for every row of the local diagonal submatrix, and o_nz 3469 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3470 One way to choose d_nz and o_nz is to use the max nonzerors per local 3471 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3472 In this case, the values of d_nz,o_nz are: 3473 .vb 3474 proc0 : dnz = 2, o_nz = 2 3475 proc1 : dnz = 3, o_nz = 2 3476 proc2 : dnz = 1, o_nz = 4 3477 .ve 3478 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3479 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3480 for proc3. i.e we are using 12+15+10=37 storage locations to store 3481 34 values. 3482 3483 When d_nnz, o_nnz parameters are specified, the storage is specified 3484 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3485 In the above case the values for d_nnz,o_nnz are: 3486 .vb 3487 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3488 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3489 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3490 .ve 3491 Here the space allocated is sum of all the above values i.e 34, and 3492 hence pre-allocation is perfect. 3493 3494 Level: intermediate 3495 3496 .keywords: matrix, aij, compressed row, sparse, parallel 3497 3498 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3499 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3500 @*/ 3501 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3502 { 3503 PetscErrorCode ierr; 3504 3505 PetscFunctionBegin; 3506 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3507 PetscValidType(B,1); 3508 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3509 PetscFunctionReturn(0); 3510 } 3511 3512 #undef __FUNCT__ 3513 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3514 /*@ 3515 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3516 CSR format the local rows. 3517 3518 Collective on MPI_Comm 3519 3520 Input Parameters: 3521 + comm - MPI communicator 3522 . m - number of local rows (Cannot be PETSC_DECIDE) 3523 . n - This value should be the same as the local size used in creating the 3524 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3525 calculated if N is given) For square matrices n is almost always m. 3526 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3527 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3528 . i - row indices 3529 . j - column indices 3530 - a - matrix values 3531 3532 Output Parameter: 3533 . mat - the matrix 3534 3535 Level: intermediate 3536 3537 Notes: 3538 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3539 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3540 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3541 3542 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3543 3544 The format which is used for the sparse matrix input, is equivalent to a 3545 row-major ordering.. i.e for the following matrix, the input data expected is 3546 as shown: 3547 3548 1 0 0 3549 2 0 3 P0 3550 ------- 3551 4 5 6 P1 3552 3553 Process0 [P0]: rows_owned=[0,1] 3554 i = {0,1,3} [size = nrow+1 = 2+1] 3555 j = {0,0,2} [size = nz = 6] 3556 v = {1,2,3} [size = nz = 6] 3557 3558 Process1 [P1]: rows_owned=[2] 3559 i = {0,3} [size = nrow+1 = 1+1] 3560 j = {0,1,2} [size = nz = 6] 3561 v = {4,5,6} [size = nz = 6] 3562 3563 .keywords: matrix, aij, compressed row, sparse, parallel 3564 3565 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3566 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3567 @*/ 3568 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3569 { 3570 PetscErrorCode ierr; 3571 3572 PetscFunctionBegin; 3573 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3574 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3575 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3576 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3577 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3578 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3579 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3580 PetscFunctionReturn(0); 3581 } 3582 3583 #undef __FUNCT__ 3584 #define __FUNCT__ "MatCreateAIJ" 3585 /*@C 3586 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3587 (the default parallel PETSc format). For good matrix assembly performance 3588 the user should preallocate the matrix storage by setting the parameters 3589 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3590 performance can be increased by more than a factor of 50. 3591 3592 Collective on MPI_Comm 3593 3594 Input Parameters: 3595 + comm - MPI communicator 3596 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3597 This value should be the same as the local size used in creating the 3598 y vector for the matrix-vector product y = Ax. 3599 . n - This value should be the same as the local size used in creating the 3600 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3601 calculated if N is given) For square matrices n is almost always m. 3602 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3603 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3604 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3605 (same value is used for all local rows) 3606 . d_nnz - array containing the number of nonzeros in the various rows of the 3607 DIAGONAL portion of the local submatrix (possibly different for each row) 3608 or NULL, if d_nz is used to specify the nonzero structure. 3609 The size of this array is equal to the number of local rows, i.e 'm'. 3610 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3611 submatrix (same value is used for all local rows). 3612 - o_nnz - array containing the number of nonzeros in the various rows of the 3613 OFF-DIAGONAL portion of the local submatrix (possibly different for 3614 each row) or NULL, if o_nz is used to specify the nonzero 3615 structure. The size of this array is equal to the number 3616 of local rows, i.e 'm'. 3617 3618 Output Parameter: 3619 . A - the matrix 3620 3621 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3622 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3623 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3624 3625 Notes: 3626 If the *_nnz parameter is given then the *_nz parameter is ignored 3627 3628 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3629 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3630 storage requirements for this matrix. 3631 3632 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3633 processor than it must be used on all processors that share the object for 3634 that argument. 3635 3636 The user MUST specify either the local or global matrix dimensions 3637 (possibly both). 3638 3639 The parallel matrix is partitioned across processors such that the 3640 first m0 rows belong to process 0, the next m1 rows belong to 3641 process 1, the next m2 rows belong to process 2 etc.. where 3642 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3643 values corresponding to [m x N] submatrix. 3644 3645 The columns are logically partitioned with the n0 columns belonging 3646 to 0th partition, the next n1 columns belonging to the next 3647 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3648 3649 The DIAGONAL portion of the local submatrix on any given processor 3650 is the submatrix corresponding to the rows and columns m,n 3651 corresponding to the given processor. i.e diagonal matrix on 3652 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3653 etc. The remaining portion of the local submatrix [m x (N-n)] 3654 constitute the OFF-DIAGONAL portion. The example below better 3655 illustrates this concept. 3656 3657 For a square global matrix we define each processor's diagonal portion 3658 to be its local rows and the corresponding columns (a square submatrix); 3659 each processor's off-diagonal portion encompasses the remainder of the 3660 local matrix (a rectangular submatrix). 3661 3662 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3663 3664 When calling this routine with a single process communicator, a matrix of 3665 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3666 type of communicator, use the construction mechanism: 3667 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3668 3669 By default, this format uses inodes (identical nodes) when possible. 3670 We search for consecutive rows with the same nonzero structure, thereby 3671 reusing matrix information to achieve increased efficiency. 3672 3673 Options Database Keys: 3674 + -mat_no_inode - Do not use inodes 3675 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3676 - -mat_aij_oneindex - Internally use indexing starting at 1 3677 rather than 0. Note that when calling MatSetValues(), 3678 the user still MUST index entries starting at 0! 3679 3680 3681 Example usage: 3682 3683 Consider the following 8x8 matrix with 34 non-zero values, that is 3684 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3685 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3686 as follows: 3687 3688 .vb 3689 1 2 0 | 0 3 0 | 0 4 3690 Proc0 0 5 6 | 7 0 0 | 8 0 3691 9 0 10 | 11 0 0 | 12 0 3692 ------------------------------------- 3693 13 0 14 | 15 16 17 | 0 0 3694 Proc1 0 18 0 | 19 20 21 | 0 0 3695 0 0 0 | 22 23 0 | 24 0 3696 ------------------------------------- 3697 Proc2 25 26 27 | 0 0 28 | 29 0 3698 30 0 0 | 31 32 33 | 0 34 3699 .ve 3700 3701 This can be represented as a collection of submatrices as: 3702 3703 .vb 3704 A B C 3705 D E F 3706 G H I 3707 .ve 3708 3709 Where the submatrices A,B,C are owned by proc0, D,E,F are 3710 owned by proc1, G,H,I are owned by proc2. 3711 3712 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3713 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3714 The 'M','N' parameters are 8,8, and have the same values on all procs. 3715 3716 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3717 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3718 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3719 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3720 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3721 matrix, ans [DF] as another SeqAIJ matrix. 3722 3723 When d_nz, o_nz parameters are specified, d_nz storage elements are 3724 allocated for every row of the local diagonal submatrix, and o_nz 3725 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3726 One way to choose d_nz and o_nz is to use the max nonzerors per local 3727 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3728 In this case, the values of d_nz,o_nz are: 3729 .vb 3730 proc0 : dnz = 2, o_nz = 2 3731 proc1 : dnz = 3, o_nz = 2 3732 proc2 : dnz = 1, o_nz = 4 3733 .ve 3734 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3735 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3736 for proc3. i.e we are using 12+15+10=37 storage locations to store 3737 34 values. 3738 3739 When d_nnz, o_nnz parameters are specified, the storage is specified 3740 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3741 In the above case the values for d_nnz,o_nnz are: 3742 .vb 3743 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3744 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3745 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3746 .ve 3747 Here the space allocated is sum of all the above values i.e 34, and 3748 hence pre-allocation is perfect. 3749 3750 Level: intermediate 3751 3752 .keywords: matrix, aij, compressed row, sparse, parallel 3753 3754 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3755 MPIAIJ, MatCreateMPIAIJWithArrays() 3756 @*/ 3757 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) 3758 { 3759 PetscErrorCode ierr; 3760 PetscMPIInt size; 3761 3762 PetscFunctionBegin; 3763 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3764 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3765 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3766 if (size > 1) { 3767 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3768 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3769 } else { 3770 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3771 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3772 } 3773 PetscFunctionReturn(0); 3774 } 3775 3776 #undef __FUNCT__ 3777 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3778 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3779 { 3780 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3781 3782 PetscFunctionBegin; 3783 if (Ad) *Ad = a->A; 3784 if (Ao) *Ao = a->B; 3785 if (colmap) *colmap = a->garray; 3786 PetscFunctionReturn(0); 3787 } 3788 3789 #undef __FUNCT__ 3790 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3791 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3792 { 3793 PetscErrorCode ierr; 3794 PetscInt i; 3795 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3796 3797 PetscFunctionBegin; 3798 if (coloring->ctype == IS_COLORING_GLOBAL) { 3799 ISColoringValue *allcolors,*colors; 3800 ISColoring ocoloring; 3801 3802 /* set coloring for diagonal portion */ 3803 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3804 3805 /* set coloring for off-diagonal portion */ 3806 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3807 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3808 for (i=0; i<a->B->cmap->n; i++) { 3809 colors[i] = allcolors[a->garray[i]]; 3810 } 3811 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3812 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3813 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3814 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3815 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3816 ISColoringValue *colors; 3817 PetscInt *larray; 3818 ISColoring ocoloring; 3819 3820 /* set coloring for diagonal portion */ 3821 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3822 for (i=0; i<a->A->cmap->n; i++) { 3823 larray[i] = i + A->cmap->rstart; 3824 } 3825 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3826 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3827 for (i=0; i<a->A->cmap->n; i++) { 3828 colors[i] = coloring->colors[larray[i]]; 3829 } 3830 ierr = PetscFree(larray);CHKERRQ(ierr); 3831 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3832 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3833 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3834 3835 /* set coloring for off-diagonal portion */ 3836 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3837 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3838 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3839 for (i=0; i<a->B->cmap->n; i++) { 3840 colors[i] = coloring->colors[larray[i]]; 3841 } 3842 ierr = PetscFree(larray);CHKERRQ(ierr); 3843 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3844 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3845 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3846 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3847 PetscFunctionReturn(0); 3848 } 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3852 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3853 { 3854 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3855 PetscErrorCode ierr; 3856 3857 PetscFunctionBegin; 3858 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3859 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3860 PetscFunctionReturn(0); 3861 } 3862 3863 #undef __FUNCT__ 3864 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3865 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3866 { 3867 PetscErrorCode ierr; 3868 PetscInt m,N,i,rstart,nnz,Ii; 3869 PetscInt *indx; 3870 PetscScalar *values; 3871 3872 PetscFunctionBegin; 3873 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3874 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3875 PetscInt *dnz,*onz,sum,bs,cbs; 3876 3877 if (n == PETSC_DECIDE) { 3878 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3879 } 3880 /* Check sum(n) = N */ 3881 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3882 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3883 3884 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3885 rstart -= m; 3886 3887 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3888 for (i=0; i<m; i++) { 3889 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3890 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3891 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3892 } 3893 3894 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3895 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3896 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3897 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3898 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3899 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3900 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3901 } 3902 3903 /* numeric phase */ 3904 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3905 for (i=0; i<m; i++) { 3906 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3907 Ii = i + rstart; 3908 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3909 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3910 } 3911 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3912 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3913 PetscFunctionReturn(0); 3914 } 3915 3916 #undef __FUNCT__ 3917 #define __FUNCT__ "MatFileSplit" 3918 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3919 { 3920 PetscErrorCode ierr; 3921 PetscMPIInt rank; 3922 PetscInt m,N,i,rstart,nnz; 3923 size_t len; 3924 const PetscInt *indx; 3925 PetscViewer out; 3926 char *name; 3927 Mat B; 3928 const PetscScalar *values; 3929 3930 PetscFunctionBegin; 3931 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3932 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3933 /* Should this be the type of the diagonal block of A? */ 3934 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3935 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3936 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3937 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3938 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3939 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3940 for (i=0; i<m; i++) { 3941 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3942 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3943 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3944 } 3945 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3946 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3947 3948 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3949 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3950 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3951 sprintf(name,"%s.%d",outfile,rank); 3952 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3953 ierr = PetscFree(name);CHKERRQ(ierr); 3954 ierr = MatView(B,out);CHKERRQ(ierr); 3955 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3956 ierr = MatDestroy(&B);CHKERRQ(ierr); 3957 PetscFunctionReturn(0); 3958 } 3959 3960 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3961 #undef __FUNCT__ 3962 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3963 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3964 { 3965 PetscErrorCode ierr; 3966 Mat_Merge_SeqsToMPI *merge; 3967 PetscContainer container; 3968 3969 PetscFunctionBegin; 3970 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3971 if (container) { 3972 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3973 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3974 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3975 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3976 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3977 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3978 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3979 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3980 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3981 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3982 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3983 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3984 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3985 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3986 ierr = PetscFree(merge);CHKERRQ(ierr); 3987 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3988 } 3989 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3990 PetscFunctionReturn(0); 3991 } 3992 3993 #include <../src/mat/utils/freespace.h> 3994 #include <petscbt.h> 3995 3996 #undef __FUNCT__ 3997 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 3998 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3999 { 4000 PetscErrorCode ierr; 4001 MPI_Comm comm; 4002 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4003 PetscMPIInt size,rank,taga,*len_s; 4004 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4005 PetscInt proc,m; 4006 PetscInt **buf_ri,**buf_rj; 4007 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4008 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4009 MPI_Request *s_waits,*r_waits; 4010 MPI_Status *status; 4011 MatScalar *aa=a->a; 4012 MatScalar **abuf_r,*ba_i; 4013 Mat_Merge_SeqsToMPI *merge; 4014 PetscContainer container; 4015 4016 PetscFunctionBegin; 4017 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4018 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4019 4020 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4021 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4022 4023 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4024 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4025 4026 bi = merge->bi; 4027 bj = merge->bj; 4028 buf_ri = merge->buf_ri; 4029 buf_rj = merge->buf_rj; 4030 4031 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4032 owners = merge->rowmap->range; 4033 len_s = merge->len_s; 4034 4035 /* send and recv matrix values */ 4036 /*-----------------------------*/ 4037 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4038 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4039 4040 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4041 for (proc=0,k=0; proc<size; proc++) { 4042 if (!len_s[proc]) continue; 4043 i = owners[proc]; 4044 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4045 k++; 4046 } 4047 4048 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4049 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4050 ierr = PetscFree(status);CHKERRQ(ierr); 4051 4052 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4053 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4054 4055 /* insert mat values of mpimat */ 4056 /*----------------------------*/ 4057 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4058 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4059 4060 for (k=0; k<merge->nrecv; k++) { 4061 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4062 nrows = *(buf_ri_k[k]); 4063 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4064 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4065 } 4066 4067 /* set values of ba */ 4068 m = merge->rowmap->n; 4069 for (i=0; i<m; i++) { 4070 arow = owners[rank] + i; 4071 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4072 bnzi = bi[i+1] - bi[i]; 4073 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4074 4075 /* add local non-zero vals of this proc's seqmat into ba */ 4076 anzi = ai[arow+1] - ai[arow]; 4077 aj = a->j + ai[arow]; 4078 aa = a->a + ai[arow]; 4079 nextaj = 0; 4080 for (j=0; nextaj<anzi; j++) { 4081 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4082 ba_i[j] += aa[nextaj++]; 4083 } 4084 } 4085 4086 /* add received vals into ba */ 4087 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4088 /* i-th row */ 4089 if (i == *nextrow[k]) { 4090 anzi = *(nextai[k]+1) - *nextai[k]; 4091 aj = buf_rj[k] + *(nextai[k]); 4092 aa = abuf_r[k] + *(nextai[k]); 4093 nextaj = 0; 4094 for (j=0; nextaj<anzi; j++) { 4095 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4096 ba_i[j] += aa[nextaj++]; 4097 } 4098 } 4099 nextrow[k]++; nextai[k]++; 4100 } 4101 } 4102 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4103 } 4104 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4105 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4106 4107 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4108 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4109 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4110 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4111 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4112 PetscFunctionReturn(0); 4113 } 4114 4115 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4116 4117 #undef __FUNCT__ 4118 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4119 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4120 { 4121 PetscErrorCode ierr; 4122 Mat B_mpi; 4123 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4124 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4125 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4126 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4127 PetscInt len,proc,*dnz,*onz,bs,cbs; 4128 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4129 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4130 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4131 MPI_Status *status; 4132 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4133 PetscBT lnkbt; 4134 Mat_Merge_SeqsToMPI *merge; 4135 PetscContainer container; 4136 4137 PetscFunctionBegin; 4138 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4139 4140 /* make sure it is a PETSc comm */ 4141 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4142 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4143 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4144 4145 ierr = PetscNew(&merge);CHKERRQ(ierr); 4146 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4147 4148 /* determine row ownership */ 4149 /*---------------------------------------------------------*/ 4150 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4151 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4152 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4153 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4154 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4155 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4156 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4157 4158 m = merge->rowmap->n; 4159 owners = merge->rowmap->range; 4160 4161 /* determine the number of messages to send, their lengths */ 4162 /*---------------------------------------------------------*/ 4163 len_s = merge->len_s; 4164 4165 len = 0; /* length of buf_si[] */ 4166 merge->nsend = 0; 4167 for (proc=0; proc<size; proc++) { 4168 len_si[proc] = 0; 4169 if (proc == rank) { 4170 len_s[proc] = 0; 4171 } else { 4172 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4173 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4174 } 4175 if (len_s[proc]) { 4176 merge->nsend++; 4177 nrows = 0; 4178 for (i=owners[proc]; i<owners[proc+1]; i++) { 4179 if (ai[i+1] > ai[i]) nrows++; 4180 } 4181 len_si[proc] = 2*(nrows+1); 4182 len += len_si[proc]; 4183 } 4184 } 4185 4186 /* determine the number and length of messages to receive for ij-structure */ 4187 /*-------------------------------------------------------------------------*/ 4188 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4189 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4190 4191 /* post the Irecv of j-structure */ 4192 /*-------------------------------*/ 4193 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4194 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4195 4196 /* post the Isend of j-structure */ 4197 /*--------------------------------*/ 4198 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4199 4200 for (proc=0, k=0; proc<size; proc++) { 4201 if (!len_s[proc]) continue; 4202 i = owners[proc]; 4203 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4204 k++; 4205 } 4206 4207 /* receives and sends of j-structure are complete */ 4208 /*------------------------------------------------*/ 4209 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4210 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4211 4212 /* send and recv i-structure */ 4213 /*---------------------------*/ 4214 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4215 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4216 4217 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4218 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4219 for (proc=0,k=0; proc<size; proc++) { 4220 if (!len_s[proc]) continue; 4221 /* form outgoing message for i-structure: 4222 buf_si[0]: nrows to be sent 4223 [1:nrows]: row index (global) 4224 [nrows+1:2*nrows+1]: i-structure index 4225 */ 4226 /*-------------------------------------------*/ 4227 nrows = len_si[proc]/2 - 1; 4228 buf_si_i = buf_si + nrows+1; 4229 buf_si[0] = nrows; 4230 buf_si_i[0] = 0; 4231 nrows = 0; 4232 for (i=owners[proc]; i<owners[proc+1]; i++) { 4233 anzi = ai[i+1] - ai[i]; 4234 if (anzi) { 4235 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4236 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4237 nrows++; 4238 } 4239 } 4240 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4241 k++; 4242 buf_si += len_si[proc]; 4243 } 4244 4245 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4246 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4247 4248 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4249 for (i=0; i<merge->nrecv; i++) { 4250 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); 4251 } 4252 4253 ierr = PetscFree(len_si);CHKERRQ(ierr); 4254 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4255 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4256 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4257 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4258 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4259 ierr = PetscFree(status);CHKERRQ(ierr); 4260 4261 /* compute a local seq matrix in each processor */ 4262 /*----------------------------------------------*/ 4263 /* allocate bi array and free space for accumulating nonzero column info */ 4264 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4265 bi[0] = 0; 4266 4267 /* create and initialize a linked list */ 4268 nlnk = N+1; 4269 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4270 4271 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4272 len = ai[owners[rank+1]] - ai[owners[rank]]; 4273 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4274 4275 current_space = free_space; 4276 4277 /* determine symbolic info for each local row */ 4278 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4279 4280 for (k=0; k<merge->nrecv; k++) { 4281 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4282 nrows = *buf_ri_k[k]; 4283 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4284 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4285 } 4286 4287 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4288 len = 0; 4289 for (i=0; i<m; i++) { 4290 bnzi = 0; 4291 /* add local non-zero cols of this proc's seqmat into lnk */ 4292 arow = owners[rank] + i; 4293 anzi = ai[arow+1] - ai[arow]; 4294 aj = a->j + ai[arow]; 4295 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4296 bnzi += nlnk; 4297 /* add received col data into lnk */ 4298 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4299 if (i == *nextrow[k]) { /* i-th row */ 4300 anzi = *(nextai[k]+1) - *nextai[k]; 4301 aj = buf_rj[k] + *nextai[k]; 4302 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4303 bnzi += nlnk; 4304 nextrow[k]++; nextai[k]++; 4305 } 4306 } 4307 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4308 4309 /* if free space is not available, make more free space */ 4310 if (current_space->local_remaining<bnzi) { 4311 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4312 nspacedouble++; 4313 } 4314 /* copy data into free space, then initialize lnk */ 4315 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4316 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4317 4318 current_space->array += bnzi; 4319 current_space->local_used += bnzi; 4320 current_space->local_remaining -= bnzi; 4321 4322 bi[i+1] = bi[i] + bnzi; 4323 } 4324 4325 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4326 4327 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4328 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4329 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4330 4331 /* create symbolic parallel matrix B_mpi */ 4332 /*---------------------------------------*/ 4333 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4334 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4335 if (n==PETSC_DECIDE) { 4336 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4337 } else { 4338 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4339 } 4340 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4341 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4342 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4343 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4344 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4345 4346 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4347 B_mpi->assembled = PETSC_FALSE; 4348 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4349 merge->bi = bi; 4350 merge->bj = bj; 4351 merge->buf_ri = buf_ri; 4352 merge->buf_rj = buf_rj; 4353 merge->coi = NULL; 4354 merge->coj = NULL; 4355 merge->owners_co = NULL; 4356 4357 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4358 4359 /* attach the supporting struct to B_mpi for reuse */ 4360 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4361 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4362 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4363 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4364 *mpimat = B_mpi; 4365 4366 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4367 PetscFunctionReturn(0); 4368 } 4369 4370 #undef __FUNCT__ 4371 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4372 /*@C 4373 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4374 matrices from each processor 4375 4376 Collective on MPI_Comm 4377 4378 Input Parameters: 4379 + comm - the communicators the parallel matrix will live on 4380 . seqmat - the input sequential matrices 4381 . m - number of local rows (or PETSC_DECIDE) 4382 . n - number of local columns (or PETSC_DECIDE) 4383 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4384 4385 Output Parameter: 4386 . mpimat - the parallel matrix generated 4387 4388 Level: advanced 4389 4390 Notes: 4391 The dimensions of the sequential matrix in each processor MUST be the same. 4392 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4393 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4394 @*/ 4395 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4396 { 4397 PetscErrorCode ierr; 4398 PetscMPIInt size; 4399 4400 PetscFunctionBegin; 4401 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4402 if (size == 1) { 4403 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4404 if (scall == MAT_INITIAL_MATRIX) { 4405 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4406 } else { 4407 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4408 } 4409 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4410 PetscFunctionReturn(0); 4411 } 4412 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4413 if (scall == MAT_INITIAL_MATRIX) { 4414 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4415 } 4416 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4417 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4418 PetscFunctionReturn(0); 4419 } 4420 4421 #undef __FUNCT__ 4422 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4423 /*@ 4424 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4425 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4426 with MatGetSize() 4427 4428 Not Collective 4429 4430 Input Parameters: 4431 + A - the matrix 4432 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4433 4434 Output Parameter: 4435 . A_loc - the local sequential matrix generated 4436 4437 Level: developer 4438 4439 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4440 4441 @*/ 4442 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4443 { 4444 PetscErrorCode ierr; 4445 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4446 Mat_SeqAIJ *mat,*a,*b; 4447 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4448 MatScalar *aa,*ba,*cam; 4449 PetscScalar *ca; 4450 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4451 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4452 PetscBool match; 4453 MPI_Comm comm; 4454 PetscMPIInt size; 4455 4456 PetscFunctionBegin; 4457 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4458 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4459 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4460 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4461 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4462 4463 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4464 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4465 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4466 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4467 aa = a->a; ba = b->a; 4468 if (scall == MAT_INITIAL_MATRIX) { 4469 if (size == 1) { 4470 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4471 PetscFunctionReturn(0); 4472 } 4473 4474 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4475 ci[0] = 0; 4476 for (i=0; i<am; i++) { 4477 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4478 } 4479 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4480 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4481 k = 0; 4482 for (i=0; i<am; i++) { 4483 ncols_o = bi[i+1] - bi[i]; 4484 ncols_d = ai[i+1] - ai[i]; 4485 /* off-diagonal portion of A */ 4486 for (jo=0; jo<ncols_o; jo++) { 4487 col = cmap[*bj]; 4488 if (col >= cstart) break; 4489 cj[k] = col; bj++; 4490 ca[k++] = *ba++; 4491 } 4492 /* diagonal portion of A */ 4493 for (j=0; j<ncols_d; j++) { 4494 cj[k] = cstart + *aj++; 4495 ca[k++] = *aa++; 4496 } 4497 /* off-diagonal portion of A */ 4498 for (j=jo; j<ncols_o; j++) { 4499 cj[k] = cmap[*bj++]; 4500 ca[k++] = *ba++; 4501 } 4502 } 4503 /* put together the new matrix */ 4504 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4505 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4506 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4507 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4508 mat->free_a = PETSC_TRUE; 4509 mat->free_ij = PETSC_TRUE; 4510 mat->nonew = 0; 4511 } else if (scall == MAT_REUSE_MATRIX) { 4512 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4513 ci = mat->i; cj = mat->j; cam = mat->a; 4514 for (i=0; i<am; i++) { 4515 /* off-diagonal portion of A */ 4516 ncols_o = bi[i+1] - bi[i]; 4517 for (jo=0; jo<ncols_o; jo++) { 4518 col = cmap[*bj]; 4519 if (col >= cstart) break; 4520 *cam++ = *ba++; bj++; 4521 } 4522 /* diagonal portion of A */ 4523 ncols_d = ai[i+1] - ai[i]; 4524 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4525 /* off-diagonal portion of A */ 4526 for (j=jo; j<ncols_o; j++) { 4527 *cam++ = *ba++; bj++; 4528 } 4529 } 4530 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4531 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4532 PetscFunctionReturn(0); 4533 } 4534 4535 #undef __FUNCT__ 4536 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4537 /*@C 4538 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4539 4540 Not Collective 4541 4542 Input Parameters: 4543 + A - the matrix 4544 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4545 - row, col - index sets of rows and columns to extract (or NULL) 4546 4547 Output Parameter: 4548 . A_loc - the local sequential matrix generated 4549 4550 Level: developer 4551 4552 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4553 4554 @*/ 4555 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4556 { 4557 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4558 PetscErrorCode ierr; 4559 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4560 IS isrowa,iscola; 4561 Mat *aloc; 4562 PetscBool match; 4563 4564 PetscFunctionBegin; 4565 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4566 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4567 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4568 if (!row) { 4569 start = A->rmap->rstart; end = A->rmap->rend; 4570 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4571 } else { 4572 isrowa = *row; 4573 } 4574 if (!col) { 4575 start = A->cmap->rstart; 4576 cmap = a->garray; 4577 nzA = a->A->cmap->n; 4578 nzB = a->B->cmap->n; 4579 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4580 ncols = 0; 4581 for (i=0; i<nzB; i++) { 4582 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4583 else break; 4584 } 4585 imark = i; 4586 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4587 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4588 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4589 } else { 4590 iscola = *col; 4591 } 4592 if (scall != MAT_INITIAL_MATRIX) { 4593 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4594 aloc[0] = *A_loc; 4595 } 4596 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4597 *A_loc = aloc[0]; 4598 ierr = PetscFree(aloc);CHKERRQ(ierr); 4599 if (!row) { 4600 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4601 } 4602 if (!col) { 4603 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4604 } 4605 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4606 PetscFunctionReturn(0); 4607 } 4608 4609 #undef __FUNCT__ 4610 #define __FUNCT__ "MatGetBrowsOfAcols" 4611 /*@C 4612 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4613 4614 Collective on Mat 4615 4616 Input Parameters: 4617 + A,B - the matrices in mpiaij format 4618 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4619 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4620 4621 Output Parameter: 4622 + rowb, colb - index sets of rows and columns of B to extract 4623 - B_seq - the sequential matrix generated 4624 4625 Level: developer 4626 4627 @*/ 4628 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4629 { 4630 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4631 PetscErrorCode ierr; 4632 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4633 IS isrowb,iscolb; 4634 Mat *bseq=NULL; 4635 4636 PetscFunctionBegin; 4637 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4638 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); 4639 } 4640 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4641 4642 if (scall == MAT_INITIAL_MATRIX) { 4643 start = A->cmap->rstart; 4644 cmap = a->garray; 4645 nzA = a->A->cmap->n; 4646 nzB = a->B->cmap->n; 4647 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4648 ncols = 0; 4649 for (i=0; i<nzB; i++) { /* row < local row index */ 4650 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4651 else break; 4652 } 4653 imark = i; 4654 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4655 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4656 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4657 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4658 } else { 4659 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4660 isrowb = *rowb; iscolb = *colb; 4661 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4662 bseq[0] = *B_seq; 4663 } 4664 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4665 *B_seq = bseq[0]; 4666 ierr = PetscFree(bseq);CHKERRQ(ierr); 4667 if (!rowb) { 4668 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4669 } else { 4670 *rowb = isrowb; 4671 } 4672 if (!colb) { 4673 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4674 } else { 4675 *colb = iscolb; 4676 } 4677 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4678 PetscFunctionReturn(0); 4679 } 4680 4681 #undef __FUNCT__ 4682 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4683 /* 4684 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4685 of the OFF-DIAGONAL portion of local A 4686 4687 Collective on Mat 4688 4689 Input Parameters: 4690 + A,B - the matrices in mpiaij format 4691 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4692 4693 Output Parameter: 4694 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4695 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4696 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4697 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4698 4699 Level: developer 4700 4701 */ 4702 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4703 { 4704 VecScatter_MPI_General *gen_to,*gen_from; 4705 PetscErrorCode ierr; 4706 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4707 Mat_SeqAIJ *b_oth; 4708 VecScatter ctx =a->Mvctx; 4709 MPI_Comm comm; 4710 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4711 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4712 PetscScalar *rvalues,*svalues; 4713 MatScalar *b_otha,*bufa,*bufA; 4714 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4715 MPI_Request *rwaits = NULL,*swaits = NULL; 4716 MPI_Status *sstatus,rstatus; 4717 PetscMPIInt jj,size; 4718 PetscInt *cols,sbs,rbs; 4719 PetscScalar *vals; 4720 4721 PetscFunctionBegin; 4722 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4723 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4724 if (size == 1) PetscFunctionReturn(0); 4725 4726 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4727 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); 4728 } 4729 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4730 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4731 4732 gen_to = (VecScatter_MPI_General*)ctx->todata; 4733 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4734 rvalues = gen_from->values; /* holds the length of receiving row */ 4735 svalues = gen_to->values; /* holds the length of sending row */ 4736 nrecvs = gen_from->n; 4737 nsends = gen_to->n; 4738 4739 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4740 srow = gen_to->indices; /* local row index to be sent */ 4741 sstarts = gen_to->starts; 4742 sprocs = gen_to->procs; 4743 sstatus = gen_to->sstatus; 4744 sbs = gen_to->bs; 4745 rstarts = gen_from->starts; 4746 rprocs = gen_from->procs; 4747 rbs = gen_from->bs; 4748 4749 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4750 if (scall == MAT_INITIAL_MATRIX) { 4751 /* i-array */ 4752 /*---------*/ 4753 /* post receives */ 4754 for (i=0; i<nrecvs; i++) { 4755 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4756 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4757 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4758 } 4759 4760 /* pack the outgoing message */ 4761 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4762 4763 sstartsj[0] = 0; 4764 rstartsj[0] = 0; 4765 len = 0; /* total length of j or a array to be sent */ 4766 k = 0; 4767 for (i=0; i<nsends; i++) { 4768 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4769 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4770 for (j=0; j<nrows; j++) { 4771 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4772 for (l=0; l<sbs; l++) { 4773 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4774 4775 rowlen[j*sbs+l] = ncols; 4776 4777 len += ncols; 4778 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4779 } 4780 k++; 4781 } 4782 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4783 4784 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4785 } 4786 /* recvs and sends of i-array are completed */ 4787 i = nrecvs; 4788 while (i--) { 4789 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4790 } 4791 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4792 4793 /* allocate buffers for sending j and a arrays */ 4794 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4795 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4796 4797 /* create i-array of B_oth */ 4798 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4799 4800 b_othi[0] = 0; 4801 len = 0; /* total length of j or a array to be received */ 4802 k = 0; 4803 for (i=0; i<nrecvs; i++) { 4804 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4805 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4806 for (j=0; j<nrows; j++) { 4807 b_othi[k+1] = b_othi[k] + rowlen[j]; 4808 len += rowlen[j]; k++; 4809 } 4810 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4811 } 4812 4813 /* allocate space for j and a arrrays of B_oth */ 4814 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4815 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4816 4817 /* j-array */ 4818 /*---------*/ 4819 /* post receives of j-array */ 4820 for (i=0; i<nrecvs; i++) { 4821 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4822 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4823 } 4824 4825 /* pack the outgoing message j-array */ 4826 k = 0; 4827 for (i=0; i<nsends; i++) { 4828 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4829 bufJ = bufj+sstartsj[i]; 4830 for (j=0; j<nrows; j++) { 4831 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4832 for (ll=0; ll<sbs; ll++) { 4833 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4834 for (l=0; l<ncols; l++) { 4835 *bufJ++ = cols[l]; 4836 } 4837 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4838 } 4839 } 4840 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4841 } 4842 4843 /* recvs and sends of j-array are completed */ 4844 i = nrecvs; 4845 while (i--) { 4846 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4847 } 4848 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4849 } else if (scall == MAT_REUSE_MATRIX) { 4850 sstartsj = *startsj_s; 4851 rstartsj = *startsj_r; 4852 bufa = *bufa_ptr; 4853 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4854 b_otha = b_oth->a; 4855 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4856 4857 /* a-array */ 4858 /*---------*/ 4859 /* post receives of a-array */ 4860 for (i=0; i<nrecvs; i++) { 4861 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4862 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4863 } 4864 4865 /* pack the outgoing message a-array */ 4866 k = 0; 4867 for (i=0; i<nsends; i++) { 4868 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4869 bufA = bufa+sstartsj[i]; 4870 for (j=0; j<nrows; j++) { 4871 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4872 for (ll=0; ll<sbs; ll++) { 4873 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4874 for (l=0; l<ncols; l++) { 4875 *bufA++ = vals[l]; 4876 } 4877 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4878 } 4879 } 4880 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4881 } 4882 /* recvs and sends of a-array are completed */ 4883 i = nrecvs; 4884 while (i--) { 4885 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4886 } 4887 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4888 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4889 4890 if (scall == MAT_INITIAL_MATRIX) { 4891 /* put together the new matrix */ 4892 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4893 4894 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4895 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4896 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4897 b_oth->free_a = PETSC_TRUE; 4898 b_oth->free_ij = PETSC_TRUE; 4899 b_oth->nonew = 0; 4900 4901 ierr = PetscFree(bufj);CHKERRQ(ierr); 4902 if (!startsj_s || !bufa_ptr) { 4903 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4904 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4905 } else { 4906 *startsj_s = sstartsj; 4907 *startsj_r = rstartsj; 4908 *bufa_ptr = bufa; 4909 } 4910 } 4911 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4912 PetscFunctionReturn(0); 4913 } 4914 4915 #undef __FUNCT__ 4916 #define __FUNCT__ "MatGetCommunicationStructs" 4917 /*@C 4918 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4919 4920 Not Collective 4921 4922 Input Parameters: 4923 . A - The matrix in mpiaij format 4924 4925 Output Parameter: 4926 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4927 . colmap - A map from global column index to local index into lvec 4928 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4929 4930 Level: developer 4931 4932 @*/ 4933 #if defined(PETSC_USE_CTABLE) 4934 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4935 #else 4936 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4937 #endif 4938 { 4939 Mat_MPIAIJ *a; 4940 4941 PetscFunctionBegin; 4942 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4943 PetscValidPointer(lvec, 2); 4944 PetscValidPointer(colmap, 3); 4945 PetscValidPointer(multScatter, 4); 4946 a = (Mat_MPIAIJ*) A->data; 4947 if (lvec) *lvec = a->lvec; 4948 if (colmap) *colmap = a->colmap; 4949 if (multScatter) *multScatter = a->Mvctx; 4950 PetscFunctionReturn(0); 4951 } 4952 4953 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4954 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4955 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4956 #if defined(PETSC_HAVE_ELEMENTAL) 4957 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4958 #endif 4959 4960 #undef __FUNCT__ 4961 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4962 /* 4963 Computes (B'*A')' since computing B*A directly is untenable 4964 4965 n p p 4966 ( ) ( ) ( ) 4967 m ( A ) * n ( B ) = m ( C ) 4968 ( ) ( ) ( ) 4969 4970 */ 4971 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4972 { 4973 PetscErrorCode ierr; 4974 Mat At,Bt,Ct; 4975 4976 PetscFunctionBegin; 4977 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4978 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4979 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4980 ierr = MatDestroy(&At);CHKERRQ(ierr); 4981 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4982 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4983 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4984 PetscFunctionReturn(0); 4985 } 4986 4987 #undef __FUNCT__ 4988 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4989 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4990 { 4991 PetscErrorCode ierr; 4992 PetscInt m=A->rmap->n,n=B->cmap->n; 4993 Mat Cmat; 4994 4995 PetscFunctionBegin; 4996 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); 4997 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4998 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4999 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5000 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5001 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5002 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5003 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5004 5005 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5006 5007 *C = Cmat; 5008 PetscFunctionReturn(0); 5009 } 5010 5011 /* ----------------------------------------------------------------*/ 5012 #undef __FUNCT__ 5013 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5014 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5015 { 5016 PetscErrorCode ierr; 5017 5018 PetscFunctionBegin; 5019 if (scall == MAT_INITIAL_MATRIX) { 5020 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5021 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5022 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5023 } 5024 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5025 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5026 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5027 PetscFunctionReturn(0); 5028 } 5029 5030 /*MC 5031 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5032 5033 Options Database Keys: 5034 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5035 5036 Level: beginner 5037 5038 .seealso: MatCreateAIJ() 5039 M*/ 5040 5041 #undef __FUNCT__ 5042 #define __FUNCT__ "MatCreate_MPIAIJ" 5043 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5044 { 5045 Mat_MPIAIJ *b; 5046 PetscErrorCode ierr; 5047 PetscMPIInt size; 5048 5049 PetscFunctionBegin; 5050 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5051 5052 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5053 B->data = (void*)b; 5054 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5055 B->assembled = PETSC_FALSE; 5056 B->insertmode = NOT_SET_VALUES; 5057 b->size = size; 5058 5059 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5060 5061 /* build cache for off array entries formed */ 5062 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5063 5064 b->donotstash = PETSC_FALSE; 5065 b->colmap = 0; 5066 b->garray = 0; 5067 b->roworiented = PETSC_TRUE; 5068 5069 /* stuff used for matrix vector multiply */ 5070 b->lvec = NULL; 5071 b->Mvctx = NULL; 5072 5073 /* stuff for MatGetRow() */ 5074 b->rowindices = 0; 5075 b->rowvalues = 0; 5076 b->getrowactive = PETSC_FALSE; 5077 5078 /* flexible pointer used in CUSP/CUSPARSE classes */ 5079 b->spptr = NULL; 5080 5081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5086 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5091 #if defined(PETSC_HAVE_ELEMENTAL) 5092 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5093 #endif 5094 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5095 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5096 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5097 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5098 PetscFunctionReturn(0); 5099 } 5100 5101 #undef __FUNCT__ 5102 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5103 /*@C 5104 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5105 and "off-diagonal" part of the matrix in CSR format. 5106 5107 Collective on MPI_Comm 5108 5109 Input Parameters: 5110 + comm - MPI communicator 5111 . m - number of local rows (Cannot be PETSC_DECIDE) 5112 . n - This value should be the same as the local size used in creating the 5113 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5114 calculated if N is given) For square matrices n is almost always m. 5115 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5116 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5117 . i - row indices for "diagonal" portion of matrix 5118 . j - column indices 5119 . a - matrix values 5120 . oi - row indices for "off-diagonal" portion of matrix 5121 . oj - column indices 5122 - oa - matrix values 5123 5124 Output Parameter: 5125 . mat - the matrix 5126 5127 Level: advanced 5128 5129 Notes: 5130 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5131 must free the arrays once the matrix has been destroyed and not before. 5132 5133 The i and j indices are 0 based 5134 5135 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5136 5137 This sets local rows and cannot be used to set off-processor values. 5138 5139 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5140 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5141 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5142 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5143 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5144 communication if it is known that only local entries will be set. 5145 5146 .keywords: matrix, aij, compressed row, sparse, parallel 5147 5148 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5149 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5150 @*/ 5151 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) 5152 { 5153 PetscErrorCode ierr; 5154 Mat_MPIAIJ *maij; 5155 5156 PetscFunctionBegin; 5157 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5158 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5159 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5160 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5161 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5162 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5163 maij = (Mat_MPIAIJ*) (*mat)->data; 5164 5165 (*mat)->preallocated = PETSC_TRUE; 5166 5167 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5168 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5169 5170 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5171 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5172 5173 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5174 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5175 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5176 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5177 5178 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5179 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5180 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5181 PetscFunctionReturn(0); 5182 } 5183 5184 /* 5185 Special version for direct calls from Fortran 5186 */ 5187 #include <petsc-private/fortranimpl.h> 5188 5189 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5190 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5191 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5192 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5193 #endif 5194 5195 /* Change these macros so can be used in void function */ 5196 #undef CHKERRQ 5197 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5198 #undef SETERRQ2 5199 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5200 #undef SETERRQ3 5201 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5202 #undef SETERRQ 5203 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5204 5205 #undef __FUNCT__ 5206 #define __FUNCT__ "matsetvaluesmpiaij_" 5207 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) 5208 { 5209 Mat mat = *mmat; 5210 PetscInt m = *mm, n = *mn; 5211 InsertMode addv = *maddv; 5212 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5213 PetscScalar value; 5214 PetscErrorCode ierr; 5215 5216 MatCheckPreallocated(mat,1); 5217 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5218 5219 #if defined(PETSC_USE_DEBUG) 5220 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5221 #endif 5222 { 5223 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5224 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5225 PetscBool roworiented = aij->roworiented; 5226 5227 /* Some Variables required in the macro */ 5228 Mat A = aij->A; 5229 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5230 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5231 MatScalar *aa = a->a; 5232 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5233 Mat B = aij->B; 5234 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5235 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5236 MatScalar *ba = b->a; 5237 5238 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5239 PetscInt nonew = a->nonew; 5240 MatScalar *ap1,*ap2; 5241 5242 PetscFunctionBegin; 5243 for (i=0; i<m; i++) { 5244 if (im[i] < 0) continue; 5245 #if defined(PETSC_USE_DEBUG) 5246 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); 5247 #endif 5248 if (im[i] >= rstart && im[i] < rend) { 5249 row = im[i] - rstart; 5250 lastcol1 = -1; 5251 rp1 = aj + ai[row]; 5252 ap1 = aa + ai[row]; 5253 rmax1 = aimax[row]; 5254 nrow1 = ailen[row]; 5255 low1 = 0; 5256 high1 = nrow1; 5257 lastcol2 = -1; 5258 rp2 = bj + bi[row]; 5259 ap2 = ba + bi[row]; 5260 rmax2 = bimax[row]; 5261 nrow2 = bilen[row]; 5262 low2 = 0; 5263 high2 = nrow2; 5264 5265 for (j=0; j<n; j++) { 5266 if (roworiented) value = v[i*n+j]; 5267 else value = v[i+j*m]; 5268 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5269 if (in[j] >= cstart && in[j] < cend) { 5270 col = in[j] - cstart; 5271 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5272 } else if (in[j] < 0) continue; 5273 #if defined(PETSC_USE_DEBUG) 5274 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); 5275 #endif 5276 else { 5277 if (mat->was_assembled) { 5278 if (!aij->colmap) { 5279 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5280 } 5281 #if defined(PETSC_USE_CTABLE) 5282 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5283 col--; 5284 #else 5285 col = aij->colmap[in[j]] - 1; 5286 #endif 5287 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5288 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5289 col = in[j]; 5290 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5291 B = aij->B; 5292 b = (Mat_SeqAIJ*)B->data; 5293 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5294 rp2 = bj + bi[row]; 5295 ap2 = ba + bi[row]; 5296 rmax2 = bimax[row]; 5297 nrow2 = bilen[row]; 5298 low2 = 0; 5299 high2 = nrow2; 5300 bm = aij->B->rmap->n; 5301 ba = b->a; 5302 } 5303 } else col = in[j]; 5304 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5305 } 5306 } 5307 } else if (!aij->donotstash) { 5308 if (roworiented) { 5309 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5310 } else { 5311 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5312 } 5313 } 5314 } 5315 } 5316 PetscFunctionReturnVoid(); 5317 } 5318 5319