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