1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 #undef __FUNCT__ 499 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 500 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 501 { 502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 504 PetscErrorCode ierr; 505 PetscInt l,*garray = mat->garray,diag; 506 507 PetscFunctionBegin; 508 /* code only works for square matrices A */ 509 510 /* find size of row to the left of the diagonal part */ 511 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 512 row = row - diag; 513 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 514 if (garray[b->j[b->i[row]+l]] > diag) break; 515 } 516 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 517 518 /* diagonal part */ 519 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 520 521 /* right of diagonal part */ 522 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 523 PetscFunctionReturn(0); 524 } 525 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatSetValues_MPIAIJ" 528 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 529 { 530 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 531 PetscScalar value; 532 PetscErrorCode ierr; 533 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 534 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 535 PetscBool roworiented = aij->roworiented; 536 537 /* Some Variables required in the macro */ 538 Mat A = aij->A; 539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 540 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 541 MatScalar *aa = a->a; 542 PetscBool ignorezeroentries = a->ignorezeroentries; 543 Mat B = aij->B; 544 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 545 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 546 MatScalar *ba = b->a; 547 548 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 549 PetscInt nonew; 550 MatScalar *ap1,*ap2; 551 552 PetscFunctionBegin; 553 for (i=0; i<m; i++) { 554 if (im[i] < 0) continue; 555 #if defined(PETSC_USE_DEBUG) 556 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 557 #endif 558 if (im[i] >= rstart && im[i] < rend) { 559 row = im[i] - rstart; 560 lastcol1 = -1; 561 rp1 = aj + ai[row]; 562 ap1 = aa + ai[row]; 563 rmax1 = aimax[row]; 564 nrow1 = ailen[row]; 565 low1 = 0; 566 high1 = nrow1; 567 lastcol2 = -1; 568 rp2 = bj + bi[row]; 569 ap2 = ba + bi[row]; 570 rmax2 = bimax[row]; 571 nrow2 = bilen[row]; 572 low2 = 0; 573 high2 = nrow2; 574 575 for (j=0; j<n; j++) { 576 if (roworiented) value = v[i*n+j]; 577 else value = v[i+j*m]; 578 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 579 if (in[j] >= cstart && in[j] < cend) { 580 col = in[j] - cstart; 581 nonew = a->nonew; 582 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 583 } else if (in[j] < 0) continue; 584 #if defined(PETSC_USE_DEBUG) 585 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 586 #endif 587 else { 588 if (mat->was_assembled) { 589 if (!aij->colmap) { 590 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 591 } 592 #if defined(PETSC_USE_CTABLE) 593 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 594 col--; 595 #else 596 col = aij->colmap[in[j]] - 1; 597 #endif 598 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 599 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 600 col = in[j]; 601 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 602 B = aij->B; 603 b = (Mat_SeqAIJ*)B->data; 604 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 605 rp2 = bj + bi[row]; 606 ap2 = ba + bi[row]; 607 rmax2 = bimax[row]; 608 nrow2 = bilen[row]; 609 low2 = 0; 610 high2 = nrow2; 611 bm = aij->B->rmap->n; 612 ba = b->a; 613 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 614 } else col = in[j]; 615 nonew = b->nonew; 616 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 617 } 618 } 619 } else { 620 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 621 if (!aij->donotstash) { 622 mat->assembled = PETSC_FALSE; 623 if (roworiented) { 624 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 625 } else { 626 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 627 } 628 } 629 } 630 } 631 PetscFunctionReturn(0); 632 } 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatGetValues_MPIAIJ" 636 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 641 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 642 643 PetscFunctionBegin; 644 for (i=0; i<m; i++) { 645 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 646 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 647 if (idxm[i] >= rstart && idxm[i] < rend) { 648 row = idxm[i] - rstart; 649 for (j=0; j<n; j++) { 650 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 651 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 652 if (idxn[j] >= cstart && idxn[j] < cend) { 653 col = idxn[j] - cstart; 654 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 655 } else { 656 if (!aij->colmap) { 657 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 658 } 659 #if defined(PETSC_USE_CTABLE) 660 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 661 col--; 662 #else 663 col = aij->colmap[idxn[j]] - 1; 664 #endif 665 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 666 else { 667 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 668 } 669 } 670 } 671 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 672 } 673 PetscFunctionReturn(0); 674 } 675 676 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 680 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 681 { 682 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 683 PetscErrorCode ierr; 684 PetscInt nstash,reallocs; 685 InsertMode addv; 686 687 PetscFunctionBegin; 688 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 689 690 /* make sure all processors are either in INSERTMODE or ADDMODE */ 691 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 692 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 693 mat->insertmode = addv; /* in case this processor had no cache */ 694 695 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 696 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 697 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 698 PetscFunctionReturn(0); 699 } 700 701 #undef __FUNCT__ 702 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 703 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 704 { 705 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 706 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 707 PetscErrorCode ierr; 708 PetscMPIInt n; 709 PetscInt i,j,rstart,ncols,flg; 710 PetscInt *row,*col; 711 PetscBool other_disassembled; 712 PetscScalar *val; 713 InsertMode addv = mat->insertmode; 714 715 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 716 717 PetscFunctionBegin; 718 if (!aij->donotstash && !mat->nooffprocentries) { 719 while (1) { 720 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 721 if (!flg) break; 722 723 for (i=0; i<n; ) { 724 /* Now identify the consecutive vals belonging to the same row */ 725 for (j=i,rstart=row[j]; j<n; j++) { 726 if (row[j] != rstart) break; 727 } 728 if (j < n) ncols = j-i; 729 else ncols = n-i; 730 /* Now assemble all these values with a single function call */ 731 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 732 733 i = j; 734 } 735 } 736 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 737 } 738 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 739 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 740 741 /* determine if any processor has disassembled, if so we must 742 also disassemble ourselfs, in order that we may reassemble. */ 743 /* 744 if nonzero structure of submatrix B cannot change then we know that 745 no processor disassembled thus we can skip this stuff 746 */ 747 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 748 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 749 if (mat->was_assembled && !other_disassembled) { 750 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 751 } 752 } 753 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 754 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 755 } 756 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 757 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 758 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 759 760 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 761 762 aij->rowvalues = 0; 763 764 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 765 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 766 767 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 768 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 769 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 770 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 771 } 772 PetscFunctionReturn(0); 773 } 774 775 #undef __FUNCT__ 776 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 777 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 778 { 779 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 780 PetscErrorCode ierr; 781 782 PetscFunctionBegin; 783 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 784 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 785 PetscFunctionReturn(0); 786 } 787 788 #undef __FUNCT__ 789 #define __FUNCT__ "MatZeroRows_MPIAIJ" 790 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 791 { 792 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 793 PetscInt *owners = A->rmap->range; 794 PetscInt n = A->rmap->n; 795 PetscSF sf; 796 PetscInt *lrows; 797 PetscSFNode *rrows; 798 PetscInt r, p = 0, len = 0; 799 PetscErrorCode ierr; 800 801 PetscFunctionBegin; 802 /* Create SF where leaves are input rows and roots are owned rows */ 803 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 804 for (r = 0; r < n; ++r) lrows[r] = -1; 805 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 806 for (r = 0; r < N; ++r) { 807 const PetscInt idx = rows[r]; 808 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 809 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 810 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 811 } 812 if (A->nooffproczerorows) { 813 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 814 lrows[len++] = idx - owners[p]; 815 } else { 816 rrows[r].rank = p; 817 rrows[r].index = rows[r] - owners[p]; 818 } 819 } 820 if (!A->nooffproczerorows) { 821 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 822 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 823 /* Collect flags for rows to be zeroed */ 824 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 825 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 826 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 827 /* Compress and put in row numbers */ 828 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 829 } 830 /* fix right hand side if needed */ 831 if (x && b) { 832 const PetscScalar *xx; 833 PetscScalar *bb; 834 835 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 836 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 837 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 838 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 839 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 840 } 841 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 842 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 843 if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) { 844 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 845 } else if (diag != 0.0) { 846 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 847 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 848 for (r = 0; r < len; ++r) { 849 const PetscInt row = lrows[r] + A->rmap->rstart; 850 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 851 } 852 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 853 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 854 } else { 855 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 856 } 857 ierr = PetscFree(lrows);CHKERRQ(ierr); 858 859 /* only change matrix nonzero state if pattern was allowed to be changed */ 860 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 861 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 862 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 863 } 864 PetscFunctionReturn(0); 865 } 866 867 #undef __FUNCT__ 868 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 869 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 870 { 871 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 872 PetscErrorCode ierr; 873 PetscMPIInt n = A->rmap->n; 874 PetscInt i,j,r,m,p = 0,len = 0; 875 PetscInt *lrows,*owners = A->rmap->range; 876 PetscSFNode *rrows; 877 PetscSF sf; 878 const PetscScalar *xx; 879 PetscScalar *bb,*mask; 880 Vec xmask,lmask; 881 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 882 const PetscInt *aj, *ii,*ridx; 883 PetscScalar *aa; 884 885 PetscFunctionBegin; 886 /* Create SF where leaves are input rows and roots are owned rows */ 887 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 888 for (r = 0; r < n; ++r) lrows[r] = -1; 889 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 890 for (r = 0; r < N; ++r) { 891 const PetscInt idx = rows[r]; 892 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 893 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 894 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 895 } 896 rrows[r].rank = p; 897 rrows[r].index = rows[r] - owners[p]; 898 } 899 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 900 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 901 /* Collect flags for rows to be zeroed */ 902 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 903 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 904 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 905 /* Compress and put in row numbers */ 906 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 907 /* zero diagonal part of matrix */ 908 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 909 /* handle off diagonal part of matrix */ 910 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 911 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 912 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 913 for (i=0; i<len; i++) bb[lrows[i]] = 1; 914 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 915 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 916 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 917 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 918 if (x) { 919 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 920 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 921 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 922 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 923 } 924 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 925 /* remove zeroed rows of off diagonal matrix */ 926 ii = aij->i; 927 for (i=0; i<len; i++) { 928 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 929 } 930 /* loop over all elements of off process part of matrix zeroing removed columns*/ 931 if (aij->compressedrow.use) { 932 m = aij->compressedrow.nrows; 933 ii = aij->compressedrow.i; 934 ridx = aij->compressedrow.rindex; 935 for (i=0; i<m; i++) { 936 n = ii[i+1] - ii[i]; 937 aj = aij->j + ii[i]; 938 aa = aij->a + ii[i]; 939 940 for (j=0; j<n; j++) { 941 if (PetscAbsScalar(mask[*aj])) { 942 if (b) bb[*ridx] -= *aa*xx[*aj]; 943 *aa = 0.0; 944 } 945 aa++; 946 aj++; 947 } 948 ridx++; 949 } 950 } else { /* do not use compressed row format */ 951 m = l->B->rmap->n; 952 for (i=0; i<m; i++) { 953 n = ii[i+1] - ii[i]; 954 aj = aij->j + ii[i]; 955 aa = aij->a + ii[i]; 956 for (j=0; j<n; j++) { 957 if (PetscAbsScalar(mask[*aj])) { 958 if (b) bb[i] -= *aa*xx[*aj]; 959 *aa = 0.0; 960 } 961 aa++; 962 aj++; 963 } 964 } 965 } 966 if (x) { 967 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 968 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 969 } 970 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 971 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 972 ierr = PetscFree(lrows);CHKERRQ(ierr); 973 974 /* only change matrix nonzero state if pattern was allowed to be changed */ 975 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 976 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 977 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 978 } 979 PetscFunctionReturn(0); 980 } 981 982 #undef __FUNCT__ 983 #define __FUNCT__ "MatMult_MPIAIJ" 984 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 985 { 986 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 987 PetscErrorCode ierr; 988 PetscInt nt; 989 990 PetscFunctionBegin; 991 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 992 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 993 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 994 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 995 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 996 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 997 PetscFunctionReturn(0); 998 } 999 1000 #undef __FUNCT__ 1001 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1002 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1003 { 1004 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1005 PetscErrorCode ierr; 1006 1007 PetscFunctionBegin; 1008 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1009 PetscFunctionReturn(0); 1010 } 1011 1012 #undef __FUNCT__ 1013 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1014 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1015 { 1016 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1017 PetscErrorCode ierr; 1018 1019 PetscFunctionBegin; 1020 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1021 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1022 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1023 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1024 PetscFunctionReturn(0); 1025 } 1026 1027 #undef __FUNCT__ 1028 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1029 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1030 { 1031 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1032 PetscErrorCode ierr; 1033 PetscBool merged; 1034 1035 PetscFunctionBegin; 1036 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1037 /* do nondiagonal part */ 1038 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1039 if (!merged) { 1040 /* send it on its way */ 1041 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1042 /* do local part */ 1043 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1044 /* receive remote parts: note this assumes the values are not actually */ 1045 /* added in yy until the next line, */ 1046 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1047 } else { 1048 /* do local part */ 1049 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1050 /* send it on its way */ 1051 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1052 /* values actually were received in the Begin() but we need to call this nop */ 1053 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1054 } 1055 PetscFunctionReturn(0); 1056 } 1057 1058 #undef __FUNCT__ 1059 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1060 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1061 { 1062 MPI_Comm comm; 1063 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1064 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1065 IS Me,Notme; 1066 PetscErrorCode ierr; 1067 PetscInt M,N,first,last,*notme,i; 1068 PetscMPIInt size; 1069 1070 PetscFunctionBegin; 1071 /* Easy test: symmetric diagonal block */ 1072 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1073 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1074 if (!*f) PetscFunctionReturn(0); 1075 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1076 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1077 if (size == 1) PetscFunctionReturn(0); 1078 1079 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1080 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1081 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1082 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1083 for (i=0; i<first; i++) notme[i] = i; 1084 for (i=last; i<M; i++) notme[i-last+first] = i; 1085 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1086 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1087 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1088 Aoff = Aoffs[0]; 1089 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1090 Boff = Boffs[0]; 1091 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1092 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1093 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1094 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1095 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1096 ierr = PetscFree(notme);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1102 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 1107 PetscFunctionBegin; 1108 /* do nondiagonal part */ 1109 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1110 /* send it on its way */ 1111 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1112 /* do local part */ 1113 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1114 /* receive remote parts */ 1115 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 /* 1120 This only works correctly for square matrices where the subblock A->A is the 1121 diagonal block 1122 */ 1123 #undef __FUNCT__ 1124 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1125 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1126 { 1127 PetscErrorCode ierr; 1128 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1129 1130 PetscFunctionBegin; 1131 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1132 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1133 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1134 PetscFunctionReturn(0); 1135 } 1136 1137 #undef __FUNCT__ 1138 #define __FUNCT__ "MatScale_MPIAIJ" 1139 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1140 { 1141 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1142 PetscErrorCode ierr; 1143 1144 PetscFunctionBegin; 1145 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1146 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1147 PetscFunctionReturn(0); 1148 } 1149 1150 #undef __FUNCT__ 1151 #define __FUNCT__ "MatDestroy_MPIAIJ" 1152 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1153 { 1154 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1155 PetscErrorCode ierr; 1156 1157 PetscFunctionBegin; 1158 #if defined(PETSC_USE_LOG) 1159 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1160 #endif 1161 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1162 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1163 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1164 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1165 #if defined(PETSC_USE_CTABLE) 1166 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1167 #else 1168 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1169 #endif 1170 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1171 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1172 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1173 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1174 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1175 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1176 1177 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1178 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1179 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1180 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1181 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1182 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1184 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1185 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1186 #if defined(PETSC_HAVE_ELEMENTAL) 1187 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1188 #endif 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1194 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1195 { 1196 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1197 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1198 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1199 PetscErrorCode ierr; 1200 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1201 int fd; 1202 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1203 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1204 PetscScalar *column_values; 1205 PetscInt message_count,flowcontrolcount; 1206 FILE *file; 1207 1208 PetscFunctionBegin; 1209 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1210 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1211 nz = A->nz + B->nz; 1212 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1213 if (!rank) { 1214 header[0] = MAT_FILE_CLASSID; 1215 header[1] = mat->rmap->N; 1216 header[2] = mat->cmap->N; 1217 1218 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1220 /* get largest number of rows any processor has */ 1221 rlen = mat->rmap->n; 1222 range = mat->rmap->range; 1223 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1224 } else { 1225 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1226 rlen = mat->rmap->n; 1227 } 1228 1229 /* load up the local row counts */ 1230 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1231 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1232 1233 /* store the row lengths to the file */ 1234 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1235 if (!rank) { 1236 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1237 for (i=1; i<size; i++) { 1238 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1239 rlen = range[i+1] - range[i]; 1240 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1241 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1242 } 1243 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1244 } else { 1245 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1246 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1247 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1248 } 1249 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1250 1251 /* load up the local column indices */ 1252 nzmax = nz; /* th processor needs space a largest processor needs */ 1253 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1254 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1255 cnt = 0; 1256 for (i=0; i<mat->rmap->n; i++) { 1257 for (j=B->i[i]; j<B->i[i+1]; j++) { 1258 if ((col = garray[B->j[j]]) > cstart) break; 1259 column_indices[cnt++] = col; 1260 } 1261 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1262 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1263 } 1264 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1265 1266 /* store the column indices to the file */ 1267 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1268 if (!rank) { 1269 MPI_Status status; 1270 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1271 for (i=1; i<size; i++) { 1272 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1273 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1274 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1275 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1276 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1277 } 1278 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1279 } else { 1280 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1281 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1282 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1283 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1284 } 1285 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1286 1287 /* load up the local column values */ 1288 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1289 cnt = 0; 1290 for (i=0; i<mat->rmap->n; i++) { 1291 for (j=B->i[i]; j<B->i[i+1]; j++) { 1292 if (garray[B->j[j]] > cstart) break; 1293 column_values[cnt++] = B->a[j]; 1294 } 1295 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1296 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1297 } 1298 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1299 1300 /* store the column values to the file */ 1301 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1302 if (!rank) { 1303 MPI_Status status; 1304 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1305 for (i=1; i<size; i++) { 1306 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1307 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1308 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1309 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1310 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1311 } 1312 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1313 } else { 1314 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1315 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1316 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1317 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1318 } 1319 ierr = PetscFree(column_values);CHKERRQ(ierr); 1320 1321 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1322 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1323 PetscFunctionReturn(0); 1324 } 1325 1326 #include <petscdraw.h> 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1329 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1330 { 1331 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1332 PetscErrorCode ierr; 1333 PetscMPIInt rank = aij->rank,size = aij->size; 1334 PetscBool isdraw,iascii,isbinary; 1335 PetscViewer sviewer; 1336 PetscViewerFormat format; 1337 1338 PetscFunctionBegin; 1339 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1340 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1341 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1342 if (iascii) { 1343 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1344 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1345 MatInfo info; 1346 PetscBool inodes; 1347 1348 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1349 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1350 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1351 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1352 if (!inodes) { 1353 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1354 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1355 } else { 1356 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1357 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1358 } 1359 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1360 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1361 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1362 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1363 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1364 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1365 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1366 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1367 PetscFunctionReturn(0); 1368 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1369 PetscInt inodecount,inodelimit,*inodes; 1370 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1371 if (inodes) { 1372 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1373 } else { 1374 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1375 } 1376 PetscFunctionReturn(0); 1377 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1378 PetscFunctionReturn(0); 1379 } 1380 } else if (isbinary) { 1381 if (size == 1) { 1382 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1383 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1384 } else { 1385 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1386 } 1387 PetscFunctionReturn(0); 1388 } else if (isdraw) { 1389 PetscDraw draw; 1390 PetscBool isnull; 1391 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1392 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1393 } 1394 1395 { 1396 /* assemble the entire matrix onto first processor. */ 1397 Mat A; 1398 Mat_SeqAIJ *Aloc; 1399 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1400 MatScalar *a; 1401 1402 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1403 if (!rank) { 1404 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1405 } else { 1406 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1407 } 1408 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1409 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1410 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1411 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1412 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1413 1414 /* copy over the A part */ 1415 Aloc = (Mat_SeqAIJ*)aij->A->data; 1416 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1417 row = mat->rmap->rstart; 1418 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1419 for (i=0; i<m; i++) { 1420 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1421 row++; 1422 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1423 } 1424 aj = Aloc->j; 1425 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1426 1427 /* copy over the B part */ 1428 Aloc = (Mat_SeqAIJ*)aij->B->data; 1429 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1430 row = mat->rmap->rstart; 1431 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1432 ct = cols; 1433 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1434 for (i=0; i<m; i++) { 1435 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1436 row++; 1437 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1438 } 1439 ierr = PetscFree(ct);CHKERRQ(ierr); 1440 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1441 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1442 /* 1443 Everyone has to call to draw the matrix since the graphics waits are 1444 synchronized across all processors that share the PetscDraw object 1445 */ 1446 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1447 if (!rank) { 1448 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1449 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1450 } 1451 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1452 ierr = MatDestroy(&A);CHKERRQ(ierr); 1453 } 1454 PetscFunctionReturn(0); 1455 } 1456 1457 #undef __FUNCT__ 1458 #define __FUNCT__ "MatView_MPIAIJ" 1459 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1460 { 1461 PetscErrorCode ierr; 1462 PetscBool iascii,isdraw,issocket,isbinary; 1463 1464 PetscFunctionBegin; 1465 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1466 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1467 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1468 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1469 if (iascii || isdraw || isbinary || issocket) { 1470 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1471 } 1472 PetscFunctionReturn(0); 1473 } 1474 1475 #undef __FUNCT__ 1476 #define __FUNCT__ "MatSOR_MPIAIJ" 1477 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1478 { 1479 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1480 PetscErrorCode ierr; 1481 Vec bb1 = 0; 1482 PetscBool hasop; 1483 1484 PetscFunctionBegin; 1485 if (flag == SOR_APPLY_UPPER) { 1486 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1487 PetscFunctionReturn(0); 1488 } 1489 1490 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1491 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1492 } 1493 1494 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1495 if (flag & SOR_ZERO_INITIAL_GUESS) { 1496 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1497 its--; 1498 } 1499 1500 while (its--) { 1501 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1502 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1503 1504 /* update rhs: bb1 = bb - B*x */ 1505 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1506 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1507 1508 /* local sweep */ 1509 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1510 } 1511 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1512 if (flag & SOR_ZERO_INITIAL_GUESS) { 1513 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1514 its--; 1515 } 1516 while (its--) { 1517 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1518 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1519 1520 /* update rhs: bb1 = bb - B*x */ 1521 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1522 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1523 1524 /* local sweep */ 1525 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1526 } 1527 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1528 if (flag & SOR_ZERO_INITIAL_GUESS) { 1529 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1530 its--; 1531 } 1532 while (its--) { 1533 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1534 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1535 1536 /* update rhs: bb1 = bb - B*x */ 1537 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1538 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1539 1540 /* local sweep */ 1541 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1542 } 1543 } else if (flag & SOR_EISENSTAT) { 1544 Vec xx1; 1545 1546 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1547 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1548 1549 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1550 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1551 if (!mat->diag) { 1552 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1553 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1554 } 1555 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1556 if (hasop) { 1557 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1558 } else { 1559 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1560 } 1561 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1562 1563 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1564 1565 /* local sweep */ 1566 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1567 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1568 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1569 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1570 1571 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1572 PetscFunctionReturn(0); 1573 } 1574 1575 #undef __FUNCT__ 1576 #define __FUNCT__ "MatPermute_MPIAIJ" 1577 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1578 { 1579 Mat aA,aB,Aperm; 1580 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1581 PetscScalar *aa,*ba; 1582 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1583 PetscSF rowsf,sf; 1584 IS parcolp = NULL; 1585 PetscBool done; 1586 PetscErrorCode ierr; 1587 1588 PetscFunctionBegin; 1589 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1590 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1591 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1592 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1593 1594 /* Invert row permutation to find out where my rows should go */ 1595 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1596 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1597 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1598 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1599 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1600 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1601 1602 /* Invert column permutation to find out where my columns should go */ 1603 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1604 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1605 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1606 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1607 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1608 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1609 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1610 1611 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1612 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1613 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1614 1615 /* Find out where my gcols should go */ 1616 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1617 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1618 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1619 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1620 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1621 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1622 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1623 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1624 1625 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1626 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1627 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1628 for (i=0; i<m; i++) { 1629 PetscInt row = rdest[i],rowner; 1630 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1631 for (j=ai[i]; j<ai[i+1]; j++) { 1632 PetscInt cowner,col = cdest[aj[j]]; 1633 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1634 if (rowner == cowner) dnnz[i]++; 1635 else onnz[i]++; 1636 } 1637 for (j=bi[i]; j<bi[i+1]; j++) { 1638 PetscInt cowner,col = gcdest[bj[j]]; 1639 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1640 if (rowner == cowner) dnnz[i]++; 1641 else onnz[i]++; 1642 } 1643 } 1644 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1645 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1646 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1647 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1648 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1649 1650 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1651 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1652 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1653 for (i=0; i<m; i++) { 1654 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1655 PetscInt j0,rowlen; 1656 rowlen = ai[i+1] - ai[i]; 1657 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1658 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1659 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1660 } 1661 rowlen = bi[i+1] - bi[i]; 1662 for (j0=j=0; j<rowlen; j0=j) { 1663 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1664 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1665 } 1666 } 1667 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1668 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1669 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1670 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1671 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1672 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1673 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1674 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1675 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1676 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1677 *B = Aperm; 1678 PetscFunctionReturn(0); 1679 } 1680 1681 #undef __FUNCT__ 1682 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1683 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1684 { 1685 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1686 Mat A = mat->A,B = mat->B; 1687 PetscErrorCode ierr; 1688 PetscReal isend[5],irecv[5]; 1689 1690 PetscFunctionBegin; 1691 info->block_size = 1.0; 1692 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1693 1694 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1695 isend[3] = info->memory; isend[4] = info->mallocs; 1696 1697 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1698 1699 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1700 isend[3] += info->memory; isend[4] += info->mallocs; 1701 if (flag == MAT_LOCAL) { 1702 info->nz_used = isend[0]; 1703 info->nz_allocated = isend[1]; 1704 info->nz_unneeded = isend[2]; 1705 info->memory = isend[3]; 1706 info->mallocs = isend[4]; 1707 } else if (flag == MAT_GLOBAL_MAX) { 1708 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1709 1710 info->nz_used = irecv[0]; 1711 info->nz_allocated = irecv[1]; 1712 info->nz_unneeded = irecv[2]; 1713 info->memory = irecv[3]; 1714 info->mallocs = irecv[4]; 1715 } else if (flag == MAT_GLOBAL_SUM) { 1716 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1717 1718 info->nz_used = irecv[0]; 1719 info->nz_allocated = irecv[1]; 1720 info->nz_unneeded = irecv[2]; 1721 info->memory = irecv[3]; 1722 info->mallocs = irecv[4]; 1723 } 1724 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1725 info->fill_ratio_needed = 0; 1726 info->factor_mallocs = 0; 1727 PetscFunctionReturn(0); 1728 } 1729 1730 #undef __FUNCT__ 1731 #define __FUNCT__ "MatSetOption_MPIAIJ" 1732 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1733 { 1734 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1735 PetscErrorCode ierr; 1736 1737 PetscFunctionBegin; 1738 switch (op) { 1739 case MAT_NEW_NONZERO_LOCATIONS: 1740 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1741 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1742 case MAT_KEEP_NONZERO_PATTERN: 1743 case MAT_NEW_NONZERO_LOCATION_ERR: 1744 case MAT_USE_INODES: 1745 case MAT_IGNORE_ZERO_ENTRIES: 1746 MatCheckPreallocated(A,1); 1747 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1748 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1749 break; 1750 case MAT_ROW_ORIENTED: 1751 a->roworiented = flg; 1752 1753 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1754 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1755 break; 1756 case MAT_NEW_DIAGONALS: 1757 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1758 break; 1759 case MAT_IGNORE_OFF_PROC_ENTRIES: 1760 a->donotstash = flg; 1761 break; 1762 case MAT_SPD: 1763 A->spd_set = PETSC_TRUE; 1764 A->spd = flg; 1765 if (flg) { 1766 A->symmetric = PETSC_TRUE; 1767 A->structurally_symmetric = PETSC_TRUE; 1768 A->symmetric_set = PETSC_TRUE; 1769 A->structurally_symmetric_set = PETSC_TRUE; 1770 } 1771 break; 1772 case MAT_SYMMETRIC: 1773 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1774 break; 1775 case MAT_STRUCTURALLY_SYMMETRIC: 1776 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1777 break; 1778 case MAT_HERMITIAN: 1779 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1780 break; 1781 case MAT_SYMMETRY_ETERNAL: 1782 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1783 break; 1784 default: 1785 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1786 } 1787 PetscFunctionReturn(0); 1788 } 1789 1790 #undef __FUNCT__ 1791 #define __FUNCT__ "MatGetRow_MPIAIJ" 1792 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1793 { 1794 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1795 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1796 PetscErrorCode ierr; 1797 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1798 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1799 PetscInt *cmap,*idx_p; 1800 1801 PetscFunctionBegin; 1802 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1803 mat->getrowactive = PETSC_TRUE; 1804 1805 if (!mat->rowvalues && (idx || v)) { 1806 /* 1807 allocate enough space to hold information from the longest row. 1808 */ 1809 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1810 PetscInt max = 1,tmp; 1811 for (i=0; i<matin->rmap->n; i++) { 1812 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1813 if (max < tmp) max = tmp; 1814 } 1815 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1816 } 1817 1818 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1819 lrow = row - rstart; 1820 1821 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1822 if (!v) {pvA = 0; pvB = 0;} 1823 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1824 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1825 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1826 nztot = nzA + nzB; 1827 1828 cmap = mat->garray; 1829 if (v || idx) { 1830 if (nztot) { 1831 /* Sort by increasing column numbers, assuming A and B already sorted */ 1832 PetscInt imark = -1; 1833 if (v) { 1834 *v = v_p = mat->rowvalues; 1835 for (i=0; i<nzB; i++) { 1836 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1837 else break; 1838 } 1839 imark = i; 1840 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1841 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1842 } 1843 if (idx) { 1844 *idx = idx_p = mat->rowindices; 1845 if (imark > -1) { 1846 for (i=0; i<imark; i++) { 1847 idx_p[i] = cmap[cworkB[i]]; 1848 } 1849 } else { 1850 for (i=0; i<nzB; i++) { 1851 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1852 else break; 1853 } 1854 imark = i; 1855 } 1856 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1857 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1858 } 1859 } else { 1860 if (idx) *idx = 0; 1861 if (v) *v = 0; 1862 } 1863 } 1864 *nz = nztot; 1865 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1866 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1867 PetscFunctionReturn(0); 1868 } 1869 1870 #undef __FUNCT__ 1871 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1872 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1873 { 1874 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1875 1876 PetscFunctionBegin; 1877 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1878 aij->getrowactive = PETSC_FALSE; 1879 PetscFunctionReturn(0); 1880 } 1881 1882 #undef __FUNCT__ 1883 #define __FUNCT__ "MatNorm_MPIAIJ" 1884 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1885 { 1886 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1887 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1888 PetscErrorCode ierr; 1889 PetscInt i,j,cstart = mat->cmap->rstart; 1890 PetscReal sum = 0.0; 1891 MatScalar *v; 1892 1893 PetscFunctionBegin; 1894 if (aij->size == 1) { 1895 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1896 } else { 1897 if (type == NORM_FROBENIUS) { 1898 v = amat->a; 1899 for (i=0; i<amat->nz; i++) { 1900 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1901 } 1902 v = bmat->a; 1903 for (i=0; i<bmat->nz; i++) { 1904 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1905 } 1906 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1907 *norm = PetscSqrtReal(*norm); 1908 } else if (type == NORM_1) { /* max column norm */ 1909 PetscReal *tmp,*tmp2; 1910 PetscInt *jj,*garray = aij->garray; 1911 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1912 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1913 *norm = 0.0; 1914 v = amat->a; jj = amat->j; 1915 for (j=0; j<amat->nz; j++) { 1916 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1917 } 1918 v = bmat->a; jj = bmat->j; 1919 for (j=0; j<bmat->nz; j++) { 1920 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1921 } 1922 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1923 for (j=0; j<mat->cmap->N; j++) { 1924 if (tmp2[j] > *norm) *norm = tmp2[j]; 1925 } 1926 ierr = PetscFree(tmp);CHKERRQ(ierr); 1927 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1928 } else if (type == NORM_INFINITY) { /* max row norm */ 1929 PetscReal ntemp = 0.0; 1930 for (j=0; j<aij->A->rmap->n; j++) { 1931 v = amat->a + amat->i[j]; 1932 sum = 0.0; 1933 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1934 sum += PetscAbsScalar(*v); v++; 1935 } 1936 v = bmat->a + bmat->i[j]; 1937 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1938 sum += PetscAbsScalar(*v); v++; 1939 } 1940 if (sum > ntemp) ntemp = sum; 1941 } 1942 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1943 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1944 } 1945 PetscFunctionReturn(0); 1946 } 1947 1948 #undef __FUNCT__ 1949 #define __FUNCT__ "MatTranspose_MPIAIJ" 1950 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1951 { 1952 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1953 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1954 PetscErrorCode ierr; 1955 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1956 PetscInt cstart = A->cmap->rstart,ncol; 1957 Mat B; 1958 MatScalar *array; 1959 1960 PetscFunctionBegin; 1961 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1962 1963 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1964 ai = Aloc->i; aj = Aloc->j; 1965 bi = Bloc->i; bj = Bloc->j; 1966 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1967 PetscInt *d_nnz,*g_nnz,*o_nnz; 1968 PetscSFNode *oloc; 1969 PETSC_UNUSED PetscSF sf; 1970 1971 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1972 /* compute d_nnz for preallocation */ 1973 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1974 for (i=0; i<ai[ma]; i++) { 1975 d_nnz[aj[i]]++; 1976 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1977 } 1978 /* compute local off-diagonal contributions */ 1979 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1980 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1981 /* map those to global */ 1982 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1983 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1984 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1985 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1986 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1987 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1988 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1989 1990 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1991 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1992 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1993 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1994 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1995 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1996 } else { 1997 B = *matout; 1998 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1999 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2000 } 2001 2002 /* copy over the A part */ 2003 array = Aloc->a; 2004 row = A->rmap->rstart; 2005 for (i=0; i<ma; i++) { 2006 ncol = ai[i+1]-ai[i]; 2007 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2008 row++; 2009 array += ncol; aj += ncol; 2010 } 2011 aj = Aloc->j; 2012 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2013 2014 /* copy over the B part */ 2015 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2016 array = Bloc->a; 2017 row = A->rmap->rstart; 2018 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2019 cols_tmp = cols; 2020 for (i=0; i<mb; i++) { 2021 ncol = bi[i+1]-bi[i]; 2022 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2023 row++; 2024 array += ncol; cols_tmp += ncol; 2025 } 2026 ierr = PetscFree(cols);CHKERRQ(ierr); 2027 2028 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2029 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2030 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2031 *matout = B; 2032 } else { 2033 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2034 } 2035 PetscFunctionReturn(0); 2036 } 2037 2038 #undef __FUNCT__ 2039 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2040 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2041 { 2042 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2043 Mat a = aij->A,b = aij->B; 2044 PetscErrorCode ierr; 2045 PetscInt s1,s2,s3; 2046 2047 PetscFunctionBegin; 2048 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2049 if (rr) { 2050 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2051 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2052 /* Overlap communication with computation. */ 2053 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2054 } 2055 if (ll) { 2056 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2057 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2058 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2059 } 2060 /* scale the diagonal block */ 2061 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2062 2063 if (rr) { 2064 /* Do a scatter end and then right scale the off-diagonal block */ 2065 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2066 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2067 } 2068 PetscFunctionReturn(0); 2069 } 2070 2071 #undef __FUNCT__ 2072 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2073 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2074 { 2075 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2076 PetscErrorCode ierr; 2077 2078 PetscFunctionBegin; 2079 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2080 PetscFunctionReturn(0); 2081 } 2082 2083 #undef __FUNCT__ 2084 #define __FUNCT__ "MatEqual_MPIAIJ" 2085 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2086 { 2087 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2088 Mat a,b,c,d; 2089 PetscBool flg; 2090 PetscErrorCode ierr; 2091 2092 PetscFunctionBegin; 2093 a = matA->A; b = matA->B; 2094 c = matB->A; d = matB->B; 2095 2096 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2097 if (flg) { 2098 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2099 } 2100 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2101 PetscFunctionReturn(0); 2102 } 2103 2104 #undef __FUNCT__ 2105 #define __FUNCT__ "MatCopy_MPIAIJ" 2106 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2107 { 2108 PetscErrorCode ierr; 2109 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2110 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2111 2112 PetscFunctionBegin; 2113 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2114 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2115 /* because of the column compression in the off-processor part of the matrix a->B, 2116 the number of columns in a->B and b->B may be different, hence we cannot call 2117 the MatCopy() directly on the two parts. If need be, we can provide a more 2118 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2119 then copying the submatrices */ 2120 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2121 } else { 2122 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2123 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2124 } 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatSetUp_MPIAIJ" 2130 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2131 { 2132 PetscErrorCode ierr; 2133 2134 PetscFunctionBegin; 2135 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2136 PetscFunctionReturn(0); 2137 } 2138 2139 /* 2140 Computes the number of nonzeros per row needed for preallocation when X and Y 2141 have different nonzero structure. 2142 */ 2143 #undef __FUNCT__ 2144 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2145 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2146 { 2147 PetscInt i,j,k,nzx,nzy; 2148 2149 PetscFunctionBegin; 2150 /* Set the number of nonzeros in the new matrix */ 2151 for (i=0; i<m; i++) { 2152 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2153 nzx = xi[i+1] - xi[i]; 2154 nzy = yi[i+1] - yi[i]; 2155 nnz[i] = 0; 2156 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2157 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2158 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2159 nnz[i]++; 2160 } 2161 for (; k<nzy; k++) nnz[i]++; 2162 } 2163 PetscFunctionReturn(0); 2164 } 2165 2166 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2169 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2170 { 2171 PetscErrorCode ierr; 2172 PetscInt m = Y->rmap->N; 2173 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2174 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2175 2176 PetscFunctionBegin; 2177 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2178 PetscFunctionReturn(0); 2179 } 2180 2181 #undef __FUNCT__ 2182 #define __FUNCT__ "MatAXPY_MPIAIJ" 2183 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2184 { 2185 PetscErrorCode ierr; 2186 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2187 PetscBLASInt bnz,one=1; 2188 Mat_SeqAIJ *x,*y; 2189 2190 PetscFunctionBegin; 2191 if (str == SAME_NONZERO_PATTERN) { 2192 PetscScalar alpha = a; 2193 x = (Mat_SeqAIJ*)xx->A->data; 2194 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2195 y = (Mat_SeqAIJ*)yy->A->data; 2196 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2197 x = (Mat_SeqAIJ*)xx->B->data; 2198 y = (Mat_SeqAIJ*)yy->B->data; 2199 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2200 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2201 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2202 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2203 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2204 } else { 2205 Mat B; 2206 PetscInt *nnz_d,*nnz_o; 2207 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2208 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2209 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2210 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2211 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2212 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2213 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2214 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2215 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2216 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2217 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2218 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2219 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2220 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2221 } 2222 PetscFunctionReturn(0); 2223 } 2224 2225 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2226 2227 #undef __FUNCT__ 2228 #define __FUNCT__ "MatConjugate_MPIAIJ" 2229 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2230 { 2231 #if defined(PETSC_USE_COMPLEX) 2232 PetscErrorCode ierr; 2233 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2234 2235 PetscFunctionBegin; 2236 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2237 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2238 #else 2239 PetscFunctionBegin; 2240 #endif 2241 PetscFunctionReturn(0); 2242 } 2243 2244 #undef __FUNCT__ 2245 #define __FUNCT__ "MatRealPart_MPIAIJ" 2246 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2247 { 2248 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2249 PetscErrorCode ierr; 2250 2251 PetscFunctionBegin; 2252 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2253 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2259 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2260 { 2261 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2262 PetscErrorCode ierr; 2263 2264 PetscFunctionBegin; 2265 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2266 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2267 PetscFunctionReturn(0); 2268 } 2269 2270 #if defined(PETSC_HAVE_PBGL) 2271 2272 #include <boost/parallel/mpi/bsp_process_group.hpp> 2273 #include <boost/graph/distributed/ilu_default_graph.hpp> 2274 #include <boost/graph/distributed/ilu_0_block.hpp> 2275 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2276 #include <boost/graph/distributed/petsc/interface.hpp> 2277 #include <boost/multi_array.hpp> 2278 #include <boost/parallel/distributed_property_map->hpp> 2279 2280 #undef __FUNCT__ 2281 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2282 /* 2283 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2284 */ 2285 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2286 { 2287 namespace petsc = boost::distributed::petsc; 2288 2289 namespace graph_dist = boost::graph::distributed; 2290 using boost::graph::distributed::ilu_default::process_group_type; 2291 using boost::graph::ilu_permuted; 2292 2293 PetscBool row_identity, col_identity; 2294 PetscContainer c; 2295 PetscInt m, n, M, N; 2296 PetscErrorCode ierr; 2297 2298 PetscFunctionBegin; 2299 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2300 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2301 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2302 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2303 2304 process_group_type pg; 2305 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2306 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2307 lgraph_type& level_graph = *lgraph_p; 2308 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2309 2310 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2311 ilu_permuted(level_graph); 2312 2313 /* put together the new matrix */ 2314 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2315 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2316 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2317 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2318 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2319 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2320 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2321 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2322 2323 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2324 ierr = PetscContainerSetPointer(c, lgraph_p); 2325 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2326 ierr = PetscContainerDestroy(&c); 2327 PetscFunctionReturn(0); 2328 } 2329 2330 #undef __FUNCT__ 2331 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2332 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2333 { 2334 PetscFunctionBegin; 2335 PetscFunctionReturn(0); 2336 } 2337 2338 #undef __FUNCT__ 2339 #define __FUNCT__ "MatSolve_MPIAIJ" 2340 /* 2341 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2342 */ 2343 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2344 { 2345 namespace graph_dist = boost::graph::distributed; 2346 2347 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2348 lgraph_type *lgraph_p; 2349 PetscContainer c; 2350 PetscErrorCode ierr; 2351 2352 PetscFunctionBegin; 2353 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2354 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2355 ierr = VecCopy(b, x);CHKERRQ(ierr); 2356 2357 PetscScalar *array_x; 2358 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2359 PetscInt sx; 2360 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2361 2362 PetscScalar *array_b; 2363 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2364 PetscInt sb; 2365 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2366 2367 lgraph_type& level_graph = *lgraph_p; 2368 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2369 2370 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2371 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2372 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2373 2374 typedef boost::iterator_property_map<array_ref_type::iterator, 2375 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2376 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2377 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2378 2379 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2380 PetscFunctionReturn(0); 2381 } 2382 #endif 2383 2384 #undef __FUNCT__ 2385 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2386 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2387 { 2388 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2389 PetscErrorCode ierr; 2390 PetscInt i,*idxb = 0; 2391 PetscScalar *va,*vb; 2392 Vec vtmp; 2393 2394 PetscFunctionBegin; 2395 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2396 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2397 if (idx) { 2398 for (i=0; i<A->rmap->n; i++) { 2399 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2400 } 2401 } 2402 2403 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2404 if (idx) { 2405 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2406 } 2407 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2408 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2409 2410 for (i=0; i<A->rmap->n; i++) { 2411 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2412 va[i] = vb[i]; 2413 if (idx) idx[i] = a->garray[idxb[i]]; 2414 } 2415 } 2416 2417 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2418 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2419 ierr = PetscFree(idxb);CHKERRQ(ierr); 2420 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 #undef __FUNCT__ 2425 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2426 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2427 { 2428 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2429 PetscErrorCode ierr; 2430 PetscInt i,*idxb = 0; 2431 PetscScalar *va,*vb; 2432 Vec vtmp; 2433 2434 PetscFunctionBegin; 2435 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2436 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2437 if (idx) { 2438 for (i=0; i<A->cmap->n; i++) { 2439 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2440 } 2441 } 2442 2443 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2444 if (idx) { 2445 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2446 } 2447 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2448 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2449 2450 for (i=0; i<A->rmap->n; i++) { 2451 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2452 va[i] = vb[i]; 2453 if (idx) idx[i] = a->garray[idxb[i]]; 2454 } 2455 } 2456 2457 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2458 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2459 ierr = PetscFree(idxb);CHKERRQ(ierr); 2460 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2466 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2467 { 2468 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2469 PetscInt n = A->rmap->n; 2470 PetscInt cstart = A->cmap->rstart; 2471 PetscInt *cmap = mat->garray; 2472 PetscInt *diagIdx, *offdiagIdx; 2473 Vec diagV, offdiagV; 2474 PetscScalar *a, *diagA, *offdiagA; 2475 PetscInt r; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2480 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2481 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2482 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2483 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2484 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2485 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2486 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2487 for (r = 0; r < n; ++r) { 2488 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2489 a[r] = diagA[r]; 2490 idx[r] = cstart + diagIdx[r]; 2491 } else { 2492 a[r] = offdiagA[r]; 2493 idx[r] = cmap[offdiagIdx[r]]; 2494 } 2495 } 2496 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2497 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2498 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2499 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2500 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2501 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2502 PetscFunctionReturn(0); 2503 } 2504 2505 #undef __FUNCT__ 2506 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2507 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2508 { 2509 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2510 PetscInt n = A->rmap->n; 2511 PetscInt cstart = A->cmap->rstart; 2512 PetscInt *cmap = mat->garray; 2513 PetscInt *diagIdx, *offdiagIdx; 2514 Vec diagV, offdiagV; 2515 PetscScalar *a, *diagA, *offdiagA; 2516 PetscInt r; 2517 PetscErrorCode ierr; 2518 2519 PetscFunctionBegin; 2520 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2521 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2522 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2523 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2524 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2525 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2526 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2527 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2528 for (r = 0; r < n; ++r) { 2529 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2530 a[r] = diagA[r]; 2531 idx[r] = cstart + diagIdx[r]; 2532 } else { 2533 a[r] = offdiagA[r]; 2534 idx[r] = cmap[offdiagIdx[r]]; 2535 } 2536 } 2537 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2538 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2539 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2540 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2541 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2542 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2543 PetscFunctionReturn(0); 2544 } 2545 2546 #undef __FUNCT__ 2547 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2548 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2549 { 2550 PetscErrorCode ierr; 2551 Mat *dummy; 2552 2553 PetscFunctionBegin; 2554 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2555 *newmat = *dummy; 2556 ierr = PetscFree(dummy);CHKERRQ(ierr); 2557 PetscFunctionReturn(0); 2558 } 2559 2560 #undef __FUNCT__ 2561 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2562 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2563 { 2564 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2565 PetscErrorCode ierr; 2566 2567 PetscFunctionBegin; 2568 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 #undef __FUNCT__ 2573 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2574 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2575 { 2576 PetscErrorCode ierr; 2577 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2578 2579 PetscFunctionBegin; 2580 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2581 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2582 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2583 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2584 PetscFunctionReturn(0); 2585 } 2586 2587 #undef __FUNCT__ 2588 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ" 2589 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2590 { 2591 PetscFunctionBegin; 2592 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2593 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2594 PetscFunctionReturn(0); 2595 } 2596 2597 #undef __FUNCT__ 2598 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap" 2599 /*@ 2600 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2601 2602 Collective on Mat 2603 2604 Input Parameters: 2605 + A - the matrix 2606 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2607 2608 @*/ 2609 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2610 { 2611 PetscErrorCode ierr; 2612 2613 PetscFunctionBegin; 2614 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2615 PetscFunctionReturn(0); 2616 } 2617 2618 #undef __FUNCT__ 2619 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2620 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptions *PetscOptionsObject,Mat A) 2621 { 2622 PetscErrorCode ierr; 2623 PetscBool sc = PETSC_FALSE,flg; 2624 2625 PetscFunctionBegin; 2626 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2627 ierr = PetscObjectOptionsBegin((PetscObject)A); 2628 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2629 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2630 if (flg) { 2631 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2632 } 2633 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2634 PetscFunctionReturn(0); 2635 } 2636 2637 #undef __FUNCT__ 2638 #define __FUNCT__ "MatShift_MPIAIJ" 2639 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2640 { 2641 PetscErrorCode ierr; 2642 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2643 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data,*bij = (Mat_SeqAIJ*)maij->B->data; 2644 2645 PetscFunctionBegin; 2646 if (!aij->nz && !bij->nz) { 2647 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2648 } 2649 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2650 PetscFunctionReturn(0); 2651 } 2652 2653 /* -------------------------------------------------------------------*/ 2654 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2655 MatGetRow_MPIAIJ, 2656 MatRestoreRow_MPIAIJ, 2657 MatMult_MPIAIJ, 2658 /* 4*/ MatMultAdd_MPIAIJ, 2659 MatMultTranspose_MPIAIJ, 2660 MatMultTransposeAdd_MPIAIJ, 2661 #if defined(PETSC_HAVE_PBGL) 2662 MatSolve_MPIAIJ, 2663 #else 2664 0, 2665 #endif 2666 0, 2667 0, 2668 /*10*/ 0, 2669 0, 2670 0, 2671 MatSOR_MPIAIJ, 2672 MatTranspose_MPIAIJ, 2673 /*15*/ MatGetInfo_MPIAIJ, 2674 MatEqual_MPIAIJ, 2675 MatGetDiagonal_MPIAIJ, 2676 MatDiagonalScale_MPIAIJ, 2677 MatNorm_MPIAIJ, 2678 /*20*/ MatAssemblyBegin_MPIAIJ, 2679 MatAssemblyEnd_MPIAIJ, 2680 MatSetOption_MPIAIJ, 2681 MatZeroEntries_MPIAIJ, 2682 /*24*/ MatZeroRows_MPIAIJ, 2683 0, 2684 #if defined(PETSC_HAVE_PBGL) 2685 0, 2686 #else 2687 0, 2688 #endif 2689 0, 2690 0, 2691 /*29*/ MatSetUp_MPIAIJ, 2692 #if defined(PETSC_HAVE_PBGL) 2693 0, 2694 #else 2695 0, 2696 #endif 2697 0, 2698 0, 2699 0, 2700 /*34*/ MatDuplicate_MPIAIJ, 2701 0, 2702 0, 2703 0, 2704 0, 2705 /*39*/ MatAXPY_MPIAIJ, 2706 MatGetSubMatrices_MPIAIJ, 2707 MatIncreaseOverlap_MPIAIJ, 2708 MatGetValues_MPIAIJ, 2709 MatCopy_MPIAIJ, 2710 /*44*/ MatGetRowMax_MPIAIJ, 2711 MatScale_MPIAIJ, 2712 MatShift_MPIAIJ, 2713 MatDiagonalSet_MPIAIJ, 2714 MatZeroRowsColumns_MPIAIJ, 2715 /*49*/ MatSetRandom_MPIAIJ, 2716 0, 2717 0, 2718 0, 2719 0, 2720 /*54*/ MatFDColoringCreate_MPIXAIJ, 2721 0, 2722 MatSetUnfactored_MPIAIJ, 2723 MatPermute_MPIAIJ, 2724 0, 2725 /*59*/ MatGetSubMatrix_MPIAIJ, 2726 MatDestroy_MPIAIJ, 2727 MatView_MPIAIJ, 2728 0, 2729 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2730 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2731 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2732 0, 2733 0, 2734 0, 2735 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2736 MatGetRowMinAbs_MPIAIJ, 2737 0, 2738 MatSetColoring_MPIAIJ, 2739 0, 2740 MatSetValuesAdifor_MPIAIJ, 2741 /*75*/ MatFDColoringApply_AIJ, 2742 MatSetFromOptions_MPIAIJ, 2743 0, 2744 0, 2745 MatFindZeroDiagonals_MPIAIJ, 2746 /*80*/ 0, 2747 0, 2748 0, 2749 /*83*/ MatLoad_MPIAIJ, 2750 0, 2751 0, 2752 0, 2753 0, 2754 0, 2755 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2756 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2757 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2758 MatPtAP_MPIAIJ_MPIAIJ, 2759 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2760 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2761 0, 2762 0, 2763 0, 2764 0, 2765 /*99*/ 0, 2766 0, 2767 0, 2768 MatConjugate_MPIAIJ, 2769 0, 2770 /*104*/MatSetValuesRow_MPIAIJ, 2771 MatRealPart_MPIAIJ, 2772 MatImaginaryPart_MPIAIJ, 2773 0, 2774 0, 2775 /*109*/0, 2776 0, 2777 MatGetRowMin_MPIAIJ, 2778 0, 2779 0, 2780 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2781 0, 2782 0, 2783 0, 2784 0, 2785 /*119*/0, 2786 0, 2787 0, 2788 0, 2789 MatGetMultiProcBlock_MPIAIJ, 2790 /*124*/MatFindNonzeroRows_MPIAIJ, 2791 MatGetColumnNorms_MPIAIJ, 2792 MatInvertBlockDiagonal_MPIAIJ, 2793 0, 2794 MatGetSubMatricesMPI_MPIAIJ, 2795 /*129*/0, 2796 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2797 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2798 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2799 0, 2800 /*134*/0, 2801 0, 2802 0, 2803 0, 2804 0, 2805 /*139*/0, 2806 0, 2807 0, 2808 MatFDColoringSetUp_MPIXAIJ, 2809 MatFindOffBlockDiagonalEntries_MPIAIJ, 2810 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2811 }; 2812 2813 /* ----------------------------------------------------------------------------------------*/ 2814 2815 #undef __FUNCT__ 2816 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2817 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2818 { 2819 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2820 PetscErrorCode ierr; 2821 2822 PetscFunctionBegin; 2823 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2824 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2825 PetscFunctionReturn(0); 2826 } 2827 2828 #undef __FUNCT__ 2829 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2830 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2831 { 2832 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2833 PetscErrorCode ierr; 2834 2835 PetscFunctionBegin; 2836 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2837 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2838 PetscFunctionReturn(0); 2839 } 2840 2841 #undef __FUNCT__ 2842 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2843 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2844 { 2845 Mat_MPIAIJ *b; 2846 PetscErrorCode ierr; 2847 2848 PetscFunctionBegin; 2849 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2850 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2851 b = (Mat_MPIAIJ*)B->data; 2852 2853 if (!B->preallocated) { 2854 /* Explicitly create 2 MATSEQAIJ matrices. */ 2855 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2856 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2857 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2858 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2859 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2860 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2861 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2862 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2863 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2864 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2865 } 2866 2867 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2868 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2869 B->preallocated = PETSC_TRUE; 2870 PetscFunctionReturn(0); 2871 } 2872 2873 #undef __FUNCT__ 2874 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2875 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2876 { 2877 Mat mat; 2878 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2879 PetscErrorCode ierr; 2880 2881 PetscFunctionBegin; 2882 *newmat = 0; 2883 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2884 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2885 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2886 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2887 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2888 a = (Mat_MPIAIJ*)mat->data; 2889 2890 mat->factortype = matin->factortype; 2891 mat->assembled = PETSC_TRUE; 2892 mat->insertmode = NOT_SET_VALUES; 2893 mat->preallocated = PETSC_TRUE; 2894 2895 a->size = oldmat->size; 2896 a->rank = oldmat->rank; 2897 a->donotstash = oldmat->donotstash; 2898 a->roworiented = oldmat->roworiented; 2899 a->rowindices = 0; 2900 a->rowvalues = 0; 2901 a->getrowactive = PETSC_FALSE; 2902 2903 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2904 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2905 2906 if (oldmat->colmap) { 2907 #if defined(PETSC_USE_CTABLE) 2908 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2909 #else 2910 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2911 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2912 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2913 #endif 2914 } else a->colmap = 0; 2915 if (oldmat->garray) { 2916 PetscInt len; 2917 len = oldmat->B->cmap->n; 2918 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2919 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2920 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2921 } else a->garray = 0; 2922 2923 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2924 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2925 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2926 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2927 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2928 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2929 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2930 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2931 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2932 *newmat = mat; 2933 PetscFunctionReturn(0); 2934 } 2935 2936 2937 2938 #undef __FUNCT__ 2939 #define __FUNCT__ "MatLoad_MPIAIJ" 2940 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2941 { 2942 PetscScalar *vals,*svals; 2943 MPI_Comm comm; 2944 PetscErrorCode ierr; 2945 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2946 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2947 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2948 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2949 PetscInt cend,cstart,n,*rowners; 2950 int fd; 2951 PetscInt bs = newMat->rmap->bs; 2952 2953 PetscFunctionBegin; 2954 /* force binary viewer to load .info file if it has not yet done so */ 2955 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2956 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2957 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2958 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2959 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2960 if (!rank) { 2961 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2962 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2963 } 2964 2965 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2966 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2967 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2968 if (bs < 0) bs = 1; 2969 2970 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2971 M = header[1]; N = header[2]; 2972 2973 /* If global sizes are set, check if they are consistent with that given in the file */ 2974 if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M); 2975 if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N); 2976 2977 /* determine ownership of all (block) rows */ 2978 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2979 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2980 else m = newMat->rmap->n; /* Set by user */ 2981 2982 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2983 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2984 2985 /* First process needs enough room for process with most rows */ 2986 if (!rank) { 2987 mmax = rowners[1]; 2988 for (i=2; i<=size; i++) { 2989 mmax = PetscMax(mmax, rowners[i]); 2990 } 2991 } else mmax = -1; /* unused, but compilers complain */ 2992 2993 rowners[0] = 0; 2994 for (i=2; i<=size; i++) { 2995 rowners[i] += rowners[i-1]; 2996 } 2997 rstart = rowners[rank]; 2998 rend = rowners[rank+1]; 2999 3000 /* distribute row lengths to all processors */ 3001 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 3002 if (!rank) { 3003 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3004 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3005 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3006 for (j=0; j<m; j++) { 3007 procsnz[0] += ourlens[j]; 3008 } 3009 for (i=1; i<size; i++) { 3010 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3011 /* calculate the number of nonzeros on each processor */ 3012 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3013 procsnz[i] += rowlengths[j]; 3014 } 3015 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3016 } 3017 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3018 } else { 3019 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3020 } 3021 3022 if (!rank) { 3023 /* determine max buffer needed and allocate it */ 3024 maxnz = 0; 3025 for (i=0; i<size; i++) { 3026 maxnz = PetscMax(maxnz,procsnz[i]); 3027 } 3028 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3029 3030 /* read in my part of the matrix column indices */ 3031 nz = procsnz[0]; 3032 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3033 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3034 3035 /* read in every one elses and ship off */ 3036 for (i=1; i<size; i++) { 3037 nz = procsnz[i]; 3038 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3039 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3040 } 3041 ierr = PetscFree(cols);CHKERRQ(ierr); 3042 } else { 3043 /* determine buffer space needed for message */ 3044 nz = 0; 3045 for (i=0; i<m; i++) { 3046 nz += ourlens[i]; 3047 } 3048 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3049 3050 /* receive message of column indices*/ 3051 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3052 } 3053 3054 /* determine column ownership if matrix is not square */ 3055 if (N != M) { 3056 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3057 else n = newMat->cmap->n; 3058 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3059 cstart = cend - n; 3060 } else { 3061 cstart = rstart; 3062 cend = rend; 3063 n = cend - cstart; 3064 } 3065 3066 /* loop over local rows, determining number of off diagonal entries */ 3067 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3068 jj = 0; 3069 for (i=0; i<m; i++) { 3070 for (j=0; j<ourlens[i]; j++) { 3071 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3072 jj++; 3073 } 3074 } 3075 3076 for (i=0; i<m; i++) { 3077 ourlens[i] -= offlens[i]; 3078 } 3079 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3080 3081 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3082 3083 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3084 3085 for (i=0; i<m; i++) { 3086 ourlens[i] += offlens[i]; 3087 } 3088 3089 if (!rank) { 3090 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3091 3092 /* read in my part of the matrix numerical values */ 3093 nz = procsnz[0]; 3094 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3095 3096 /* insert into matrix */ 3097 jj = rstart; 3098 smycols = mycols; 3099 svals = vals; 3100 for (i=0; i<m; i++) { 3101 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3102 smycols += ourlens[i]; 3103 svals += ourlens[i]; 3104 jj++; 3105 } 3106 3107 /* read in other processors and ship out */ 3108 for (i=1; i<size; i++) { 3109 nz = procsnz[i]; 3110 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3111 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3112 } 3113 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3114 } else { 3115 /* receive numeric values */ 3116 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3117 3118 /* receive message of values*/ 3119 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3120 3121 /* insert into matrix */ 3122 jj = rstart; 3123 smycols = mycols; 3124 svals = vals; 3125 for (i=0; i<m; i++) { 3126 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3127 smycols += ourlens[i]; 3128 svals += ourlens[i]; 3129 jj++; 3130 } 3131 } 3132 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3133 ierr = PetscFree(vals);CHKERRQ(ierr); 3134 ierr = PetscFree(mycols);CHKERRQ(ierr); 3135 ierr = PetscFree(rowners);CHKERRQ(ierr); 3136 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3137 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3138 PetscFunctionReturn(0); 3139 } 3140 3141 #undef __FUNCT__ 3142 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3143 /* TODO: Not scalable because of ISAllGather(). */ 3144 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3145 { 3146 PetscErrorCode ierr; 3147 IS iscol_local; 3148 PetscInt csize; 3149 3150 PetscFunctionBegin; 3151 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3152 if (call == MAT_REUSE_MATRIX) { 3153 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3154 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3155 } else { 3156 PetscInt cbs; 3157 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3158 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3159 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3160 } 3161 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3162 if (call == MAT_INITIAL_MATRIX) { 3163 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3164 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3165 } 3166 PetscFunctionReturn(0); 3167 } 3168 3169 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3170 #undef __FUNCT__ 3171 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3172 /* 3173 Not great since it makes two copies of the submatrix, first an SeqAIJ 3174 in local and then by concatenating the local matrices the end result. 3175 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3176 3177 Note: This requires a sequential iscol with all indices. 3178 */ 3179 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3180 { 3181 PetscErrorCode ierr; 3182 PetscMPIInt rank,size; 3183 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3184 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3185 PetscBool allcolumns, colflag; 3186 Mat M,Mreuse; 3187 MatScalar *vwork,*aa; 3188 MPI_Comm comm; 3189 Mat_SeqAIJ *aij; 3190 3191 PetscFunctionBegin; 3192 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3193 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3195 3196 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3197 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3198 if (colflag && ncol == mat->cmap->N) { 3199 allcolumns = PETSC_TRUE; 3200 } else { 3201 allcolumns = PETSC_FALSE; 3202 } 3203 if (call == MAT_REUSE_MATRIX) { 3204 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3205 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3206 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3207 } else { 3208 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3209 } 3210 3211 /* 3212 m - number of local rows 3213 n - number of columns (same on all processors) 3214 rstart - first row in new global matrix generated 3215 */ 3216 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3217 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3218 if (call == MAT_INITIAL_MATRIX) { 3219 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3220 ii = aij->i; 3221 jj = aij->j; 3222 3223 /* 3224 Determine the number of non-zeros in the diagonal and off-diagonal 3225 portions of the matrix in order to do correct preallocation 3226 */ 3227 3228 /* first get start and end of "diagonal" columns */ 3229 if (csize == PETSC_DECIDE) { 3230 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3231 if (mglobal == n) { /* square matrix */ 3232 nlocal = m; 3233 } else { 3234 nlocal = n/size + ((n % size) > rank); 3235 } 3236 } else { 3237 nlocal = csize; 3238 } 3239 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3240 rstart = rend - nlocal; 3241 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); 3242 3243 /* next, compute all the lengths */ 3244 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3245 olens = dlens + m; 3246 for (i=0; i<m; i++) { 3247 jend = ii[i+1] - ii[i]; 3248 olen = 0; 3249 dlen = 0; 3250 for (j=0; j<jend; j++) { 3251 if (*jj < rstart || *jj >= rend) olen++; 3252 else dlen++; 3253 jj++; 3254 } 3255 olens[i] = olen; 3256 dlens[i] = dlen; 3257 } 3258 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3259 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3260 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3261 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3262 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3263 ierr = PetscFree(dlens);CHKERRQ(ierr); 3264 } else { 3265 PetscInt ml,nl; 3266 3267 M = *newmat; 3268 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3269 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3270 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3271 /* 3272 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3273 rather than the slower MatSetValues(). 3274 */ 3275 M->was_assembled = PETSC_TRUE; 3276 M->assembled = PETSC_FALSE; 3277 } 3278 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3279 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3280 ii = aij->i; 3281 jj = aij->j; 3282 aa = aij->a; 3283 for (i=0; i<m; i++) { 3284 row = rstart + i; 3285 nz = ii[i+1] - ii[i]; 3286 cwork = jj; jj += nz; 3287 vwork = aa; aa += nz; 3288 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3289 } 3290 3291 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3292 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3293 *newmat = M; 3294 3295 /* save submatrix used in processor for next request */ 3296 if (call == MAT_INITIAL_MATRIX) { 3297 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3298 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3299 } 3300 PetscFunctionReturn(0); 3301 } 3302 3303 #undef __FUNCT__ 3304 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3305 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3306 { 3307 PetscInt m,cstart, cend,j,nnz,i,d; 3308 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3309 const PetscInt *JJ; 3310 PetscScalar *values; 3311 PetscErrorCode ierr; 3312 3313 PetscFunctionBegin; 3314 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3315 3316 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3317 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3318 m = B->rmap->n; 3319 cstart = B->cmap->rstart; 3320 cend = B->cmap->rend; 3321 rstart = B->rmap->rstart; 3322 3323 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3324 3325 #if defined(PETSC_USE_DEBUGGING) 3326 for (i=0; i<m; i++) { 3327 nnz = Ii[i+1]- Ii[i]; 3328 JJ = J + Ii[i]; 3329 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3330 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3331 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); 3332 } 3333 #endif 3334 3335 for (i=0; i<m; i++) { 3336 nnz = Ii[i+1]- Ii[i]; 3337 JJ = J + Ii[i]; 3338 nnz_max = PetscMax(nnz_max,nnz); 3339 d = 0; 3340 for (j=0; j<nnz; j++) { 3341 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3342 } 3343 d_nnz[i] = d; 3344 o_nnz[i] = nnz - d; 3345 } 3346 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3347 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3348 3349 if (v) values = (PetscScalar*)v; 3350 else { 3351 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3352 } 3353 3354 for (i=0; i<m; i++) { 3355 ii = i + rstart; 3356 nnz = Ii[i+1]- Ii[i]; 3357 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3358 } 3359 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3360 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3361 3362 if (!v) { 3363 ierr = PetscFree(values);CHKERRQ(ierr); 3364 } 3365 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3366 PetscFunctionReturn(0); 3367 } 3368 3369 #undef __FUNCT__ 3370 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3371 /*@ 3372 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3373 (the default parallel PETSc format). 3374 3375 Collective on MPI_Comm 3376 3377 Input Parameters: 3378 + B - the matrix 3379 . i - the indices into j for the start of each local row (starts with zero) 3380 . j - the column indices for each local row (starts with zero) 3381 - v - optional values in the matrix 3382 3383 Level: developer 3384 3385 Notes: 3386 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3387 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3388 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3389 3390 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3391 3392 The format which is used for the sparse matrix input, is equivalent to a 3393 row-major ordering.. i.e for the following matrix, the input data expected is 3394 as shown: 3395 3396 1 0 0 3397 2 0 3 P0 3398 ------- 3399 4 5 6 P1 3400 3401 Process0 [P0]: rows_owned=[0,1] 3402 i = {0,1,3} [size = nrow+1 = 2+1] 3403 j = {0,0,2} [size = nz = 6] 3404 v = {1,2,3} [size = nz = 6] 3405 3406 Process1 [P1]: rows_owned=[2] 3407 i = {0,3} [size = nrow+1 = 1+1] 3408 j = {0,1,2} [size = nz = 6] 3409 v = {4,5,6} [size = nz = 6] 3410 3411 .keywords: matrix, aij, compressed row, sparse, parallel 3412 3413 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3414 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3415 @*/ 3416 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3417 { 3418 PetscErrorCode ierr; 3419 3420 PetscFunctionBegin; 3421 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3422 PetscFunctionReturn(0); 3423 } 3424 3425 #undef __FUNCT__ 3426 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3427 /*@C 3428 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3429 (the default parallel PETSc format). For good matrix assembly performance 3430 the user should preallocate the matrix storage by setting the parameters 3431 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3432 performance can be increased by more than a factor of 50. 3433 3434 Collective on MPI_Comm 3435 3436 Input Parameters: 3437 + B - the matrix 3438 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3439 (same value is used for all local rows) 3440 . d_nnz - array containing the number of nonzeros in the various rows of the 3441 DIAGONAL portion of the local submatrix (possibly different for each row) 3442 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3443 The size of this array is equal to the number of local rows, i.e 'm'. 3444 For matrices that will be factored, you must leave room for (and set) 3445 the diagonal entry even if it is zero. 3446 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3447 submatrix (same value is used for all local rows). 3448 - o_nnz - array containing the number of nonzeros in the various rows of the 3449 OFF-DIAGONAL portion of the local submatrix (possibly different for 3450 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3451 structure. The size of this array is equal to the number 3452 of local rows, i.e 'm'. 3453 3454 If the *_nnz parameter is given then the *_nz parameter is ignored 3455 3456 The AIJ format (also called the Yale sparse matrix format or 3457 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3458 storage. The stored row and column indices begin with zero. 3459 See Users-Manual: ch_mat for details. 3460 3461 The parallel matrix is partitioned such that the first m0 rows belong to 3462 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3463 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3464 3465 The DIAGONAL portion of the local submatrix of a processor can be defined 3466 as the submatrix which is obtained by extraction the part corresponding to 3467 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3468 first row that belongs to the processor, r2 is the last row belonging to 3469 the this processor, and c1-c2 is range of indices of the local part of a 3470 vector suitable for applying the matrix to. This is an mxn matrix. In the 3471 common case of a square matrix, the row and column ranges are the same and 3472 the DIAGONAL part is also square. The remaining portion of the local 3473 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3474 3475 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3476 3477 You can call MatGetInfo() to get information on how effective the preallocation was; 3478 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3479 You can also run with the option -info and look for messages with the string 3480 malloc in them to see if additional memory allocation was needed. 3481 3482 Example usage: 3483 3484 Consider the following 8x8 matrix with 34 non-zero values, that is 3485 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3486 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3487 as follows: 3488 3489 .vb 3490 1 2 0 | 0 3 0 | 0 4 3491 Proc0 0 5 6 | 7 0 0 | 8 0 3492 9 0 10 | 11 0 0 | 12 0 3493 ------------------------------------- 3494 13 0 14 | 15 16 17 | 0 0 3495 Proc1 0 18 0 | 19 20 21 | 0 0 3496 0 0 0 | 22 23 0 | 24 0 3497 ------------------------------------- 3498 Proc2 25 26 27 | 0 0 28 | 29 0 3499 30 0 0 | 31 32 33 | 0 34 3500 .ve 3501 3502 This can be represented as a collection of submatrices as: 3503 3504 .vb 3505 A B C 3506 D E F 3507 G H I 3508 .ve 3509 3510 Where the submatrices A,B,C are owned by proc0, D,E,F are 3511 owned by proc1, G,H,I are owned by proc2. 3512 3513 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3514 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3515 The 'M','N' parameters are 8,8, and have the same values on all procs. 3516 3517 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3518 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3519 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3520 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3521 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3522 matrix, ans [DF] as another SeqAIJ matrix. 3523 3524 When d_nz, o_nz parameters are specified, d_nz storage elements are 3525 allocated for every row of the local diagonal submatrix, and o_nz 3526 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3527 One way to choose d_nz and o_nz is to use the max nonzerors per local 3528 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3529 In this case, the values of d_nz,o_nz are: 3530 .vb 3531 proc0 : dnz = 2, o_nz = 2 3532 proc1 : dnz = 3, o_nz = 2 3533 proc2 : dnz = 1, o_nz = 4 3534 .ve 3535 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3536 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3537 for proc3. i.e we are using 12+15+10=37 storage locations to store 3538 34 values. 3539 3540 When d_nnz, o_nnz parameters are specified, the storage is specified 3541 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3542 In the above case the values for d_nnz,o_nnz are: 3543 .vb 3544 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3545 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3546 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3547 .ve 3548 Here the space allocated is sum of all the above values i.e 34, and 3549 hence pre-allocation is perfect. 3550 3551 Level: intermediate 3552 3553 .keywords: matrix, aij, compressed row, sparse, parallel 3554 3555 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3556 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3557 @*/ 3558 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3559 { 3560 PetscErrorCode ierr; 3561 3562 PetscFunctionBegin; 3563 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3564 PetscValidType(B,1); 3565 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3566 PetscFunctionReturn(0); 3567 } 3568 3569 #undef __FUNCT__ 3570 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3571 /*@ 3572 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3573 CSR format the local rows. 3574 3575 Collective on MPI_Comm 3576 3577 Input Parameters: 3578 + comm - MPI communicator 3579 . m - number of local rows (Cannot be PETSC_DECIDE) 3580 . n - This value should be the same as the local size used in creating the 3581 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3582 calculated if N is given) For square matrices n is almost always m. 3583 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3584 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3585 . i - row indices 3586 . j - column indices 3587 - a - matrix values 3588 3589 Output Parameter: 3590 . mat - the matrix 3591 3592 Level: intermediate 3593 3594 Notes: 3595 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3596 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3597 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3598 3599 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3600 3601 The format which is used for the sparse matrix input, is equivalent to a 3602 row-major ordering.. i.e for the following matrix, the input data expected is 3603 as shown: 3604 3605 1 0 0 3606 2 0 3 P0 3607 ------- 3608 4 5 6 P1 3609 3610 Process0 [P0]: rows_owned=[0,1] 3611 i = {0,1,3} [size = nrow+1 = 2+1] 3612 j = {0,0,2} [size = nz = 6] 3613 v = {1,2,3} [size = nz = 6] 3614 3615 Process1 [P1]: rows_owned=[2] 3616 i = {0,3} [size = nrow+1 = 1+1] 3617 j = {0,1,2} [size = nz = 6] 3618 v = {4,5,6} [size = nz = 6] 3619 3620 .keywords: matrix, aij, compressed row, sparse, parallel 3621 3622 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3623 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3624 @*/ 3625 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3626 { 3627 PetscErrorCode ierr; 3628 3629 PetscFunctionBegin; 3630 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3631 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3632 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3633 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3634 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3635 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3636 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3637 PetscFunctionReturn(0); 3638 } 3639 3640 #undef __FUNCT__ 3641 #define __FUNCT__ "MatCreateAIJ" 3642 /*@C 3643 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3644 (the default parallel PETSc format). For good matrix assembly performance 3645 the user should preallocate the matrix storage by setting the parameters 3646 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3647 performance can be increased by more than a factor of 50. 3648 3649 Collective on MPI_Comm 3650 3651 Input Parameters: 3652 + comm - MPI communicator 3653 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3654 This value should be the same as the local size used in creating the 3655 y vector for the matrix-vector product y = Ax. 3656 . n - This value should be the same as the local size used in creating the 3657 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3658 calculated if N is given) For square matrices n is almost always m. 3659 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3660 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3661 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3662 (same value is used for all local rows) 3663 . d_nnz - array containing the number of nonzeros in the various rows of the 3664 DIAGONAL portion of the local submatrix (possibly different for each row) 3665 or NULL, if d_nz is used to specify the nonzero structure. 3666 The size of this array is equal to the number of local rows, i.e 'm'. 3667 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3668 submatrix (same value is used for all local rows). 3669 - o_nnz - array containing the number of nonzeros in the various rows of the 3670 OFF-DIAGONAL portion of the local submatrix (possibly different for 3671 each row) or NULL, if o_nz is used to specify the nonzero 3672 structure. The size of this array is equal to the number 3673 of local rows, i.e 'm'. 3674 3675 Output Parameter: 3676 . A - the matrix 3677 3678 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3679 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3680 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3681 3682 Notes: 3683 If the *_nnz parameter is given then the *_nz parameter is ignored 3684 3685 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3686 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3687 storage requirements for this matrix. 3688 3689 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3690 processor than it must be used on all processors that share the object for 3691 that argument. 3692 3693 The user MUST specify either the local or global matrix dimensions 3694 (possibly both). 3695 3696 The parallel matrix is partitioned across processors such that the 3697 first m0 rows belong to process 0, the next m1 rows belong to 3698 process 1, the next m2 rows belong to process 2 etc.. where 3699 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3700 values corresponding to [m x N] submatrix. 3701 3702 The columns are logically partitioned with the n0 columns belonging 3703 to 0th partition, the next n1 columns belonging to the next 3704 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3705 3706 The DIAGONAL portion of the local submatrix on any given processor 3707 is the submatrix corresponding to the rows and columns m,n 3708 corresponding to the given processor. i.e diagonal matrix on 3709 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3710 etc. The remaining portion of the local submatrix [m x (N-n)] 3711 constitute the OFF-DIAGONAL portion. The example below better 3712 illustrates this concept. 3713 3714 For a square global matrix we define each processor's diagonal portion 3715 to be its local rows and the corresponding columns (a square submatrix); 3716 each processor's off-diagonal portion encompasses the remainder of the 3717 local matrix (a rectangular submatrix). 3718 3719 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3720 3721 When calling this routine with a single process communicator, a matrix of 3722 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3723 type of communicator, use the construction mechanism: 3724 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3725 3726 By default, this format uses inodes (identical nodes) when possible. 3727 We search for consecutive rows with the same nonzero structure, thereby 3728 reusing matrix information to achieve increased efficiency. 3729 3730 Options Database Keys: 3731 + -mat_no_inode - Do not use inodes 3732 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3733 - -mat_aij_oneindex - Internally use indexing starting at 1 3734 rather than 0. Note that when calling MatSetValues(), 3735 the user still MUST index entries starting at 0! 3736 3737 3738 Example usage: 3739 3740 Consider the following 8x8 matrix with 34 non-zero values, that is 3741 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3742 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3743 as follows: 3744 3745 .vb 3746 1 2 0 | 0 3 0 | 0 4 3747 Proc0 0 5 6 | 7 0 0 | 8 0 3748 9 0 10 | 11 0 0 | 12 0 3749 ------------------------------------- 3750 13 0 14 | 15 16 17 | 0 0 3751 Proc1 0 18 0 | 19 20 21 | 0 0 3752 0 0 0 | 22 23 0 | 24 0 3753 ------------------------------------- 3754 Proc2 25 26 27 | 0 0 28 | 29 0 3755 30 0 0 | 31 32 33 | 0 34 3756 .ve 3757 3758 This can be represented as a collection of submatrices as: 3759 3760 .vb 3761 A B C 3762 D E F 3763 G H I 3764 .ve 3765 3766 Where the submatrices A,B,C are owned by proc0, D,E,F are 3767 owned by proc1, G,H,I are owned by proc2. 3768 3769 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3770 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3771 The 'M','N' parameters are 8,8, and have the same values on all procs. 3772 3773 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3774 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3775 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3776 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3777 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3778 matrix, ans [DF] as another SeqAIJ matrix. 3779 3780 When d_nz, o_nz parameters are specified, d_nz storage elements are 3781 allocated for every row of the local diagonal submatrix, and o_nz 3782 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3783 One way to choose d_nz and o_nz is to use the max nonzerors per local 3784 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3785 In this case, the values of d_nz,o_nz are: 3786 .vb 3787 proc0 : dnz = 2, o_nz = 2 3788 proc1 : dnz = 3, o_nz = 2 3789 proc2 : dnz = 1, o_nz = 4 3790 .ve 3791 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3792 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3793 for proc3. i.e we are using 12+15+10=37 storage locations to store 3794 34 values. 3795 3796 When d_nnz, o_nnz parameters are specified, the storage is specified 3797 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3798 In the above case the values for d_nnz,o_nnz are: 3799 .vb 3800 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3801 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3802 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3803 .ve 3804 Here the space allocated is sum of all the above values i.e 34, and 3805 hence pre-allocation is perfect. 3806 3807 Level: intermediate 3808 3809 .keywords: matrix, aij, compressed row, sparse, parallel 3810 3811 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3812 MPIAIJ, MatCreateMPIAIJWithArrays() 3813 @*/ 3814 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) 3815 { 3816 PetscErrorCode ierr; 3817 PetscMPIInt size; 3818 3819 PetscFunctionBegin; 3820 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3821 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3822 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3823 if (size > 1) { 3824 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3825 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3826 } else { 3827 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3828 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3829 } 3830 PetscFunctionReturn(0); 3831 } 3832 3833 #undef __FUNCT__ 3834 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3835 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3836 { 3837 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3838 3839 PetscFunctionBegin; 3840 if (Ad) *Ad = a->A; 3841 if (Ao) *Ao = a->B; 3842 if (colmap) *colmap = a->garray; 3843 PetscFunctionReturn(0); 3844 } 3845 3846 #undef __FUNCT__ 3847 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3848 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3849 { 3850 PetscErrorCode ierr; 3851 PetscInt i; 3852 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3853 3854 PetscFunctionBegin; 3855 if (coloring->ctype == IS_COLORING_GLOBAL) { 3856 ISColoringValue *allcolors,*colors; 3857 ISColoring ocoloring; 3858 3859 /* set coloring for diagonal portion */ 3860 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3861 3862 /* set coloring for off-diagonal portion */ 3863 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3864 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3865 for (i=0; i<a->B->cmap->n; i++) { 3866 colors[i] = allcolors[a->garray[i]]; 3867 } 3868 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3869 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3870 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3871 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3872 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3873 ISColoringValue *colors; 3874 PetscInt *larray; 3875 ISColoring ocoloring; 3876 3877 /* set coloring for diagonal portion */ 3878 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3879 for (i=0; i<a->A->cmap->n; i++) { 3880 larray[i] = i + A->cmap->rstart; 3881 } 3882 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3883 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3884 for (i=0; i<a->A->cmap->n; i++) { 3885 colors[i] = coloring->colors[larray[i]]; 3886 } 3887 ierr = PetscFree(larray);CHKERRQ(ierr); 3888 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3889 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3890 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3891 3892 /* set coloring for off-diagonal portion */ 3893 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3894 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3895 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3896 for (i=0; i<a->B->cmap->n; i++) { 3897 colors[i] = coloring->colors[larray[i]]; 3898 } 3899 ierr = PetscFree(larray);CHKERRQ(ierr); 3900 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3901 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3902 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3903 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3904 PetscFunctionReturn(0); 3905 } 3906 3907 #undef __FUNCT__ 3908 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3909 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3910 { 3911 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3912 PetscErrorCode ierr; 3913 3914 PetscFunctionBegin; 3915 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3916 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3917 PetscFunctionReturn(0); 3918 } 3919 3920 #undef __FUNCT__ 3921 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3922 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3923 { 3924 PetscErrorCode ierr; 3925 PetscInt m,N,i,rstart,nnz,Ii; 3926 PetscInt *indx; 3927 PetscScalar *values; 3928 3929 PetscFunctionBegin; 3930 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3931 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3932 PetscInt *dnz,*onz,sum,bs,cbs; 3933 3934 if (n == PETSC_DECIDE) { 3935 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3936 } 3937 /* Check sum(n) = N */ 3938 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3939 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3940 3941 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3942 rstart -= m; 3943 3944 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3945 for (i=0; i<m; i++) { 3946 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3947 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3948 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3949 } 3950 3951 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3952 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3953 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3954 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3955 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3956 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3957 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3958 } 3959 3960 /* numeric phase */ 3961 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3962 for (i=0; i<m; i++) { 3963 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3964 Ii = i + rstart; 3965 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3966 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3967 } 3968 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3969 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3970 PetscFunctionReturn(0); 3971 } 3972 3973 #undef __FUNCT__ 3974 #define __FUNCT__ "MatFileSplit" 3975 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3976 { 3977 PetscErrorCode ierr; 3978 PetscMPIInt rank; 3979 PetscInt m,N,i,rstart,nnz; 3980 size_t len; 3981 const PetscInt *indx; 3982 PetscViewer out; 3983 char *name; 3984 Mat B; 3985 const PetscScalar *values; 3986 3987 PetscFunctionBegin; 3988 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3989 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3990 /* Should this be the type of the diagonal block of A? */ 3991 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3992 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3993 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3994 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3995 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3996 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3997 for (i=0; i<m; i++) { 3998 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3999 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4000 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4001 } 4002 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4003 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4004 4005 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4006 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4007 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4008 sprintf(name,"%s.%d",outfile,rank); 4009 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4010 ierr = PetscFree(name);CHKERRQ(ierr); 4011 ierr = MatView(B,out);CHKERRQ(ierr); 4012 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4013 ierr = MatDestroy(&B);CHKERRQ(ierr); 4014 PetscFunctionReturn(0); 4015 } 4016 4017 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4018 #undef __FUNCT__ 4019 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4020 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4021 { 4022 PetscErrorCode ierr; 4023 Mat_Merge_SeqsToMPI *merge; 4024 PetscContainer container; 4025 4026 PetscFunctionBegin; 4027 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4028 if (container) { 4029 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4030 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4031 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4032 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4033 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4034 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4035 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4036 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4037 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4038 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4039 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4040 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4041 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4042 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4043 ierr = PetscFree(merge);CHKERRQ(ierr); 4044 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4045 } 4046 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4047 PetscFunctionReturn(0); 4048 } 4049 4050 #include <../src/mat/utils/freespace.h> 4051 #include <petscbt.h> 4052 4053 #undef __FUNCT__ 4054 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4055 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4056 { 4057 PetscErrorCode ierr; 4058 MPI_Comm comm; 4059 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4060 PetscMPIInt size,rank,taga,*len_s; 4061 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4062 PetscInt proc,m; 4063 PetscInt **buf_ri,**buf_rj; 4064 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4065 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4066 MPI_Request *s_waits,*r_waits; 4067 MPI_Status *status; 4068 MatScalar *aa=a->a; 4069 MatScalar **abuf_r,*ba_i; 4070 Mat_Merge_SeqsToMPI *merge; 4071 PetscContainer container; 4072 4073 PetscFunctionBegin; 4074 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4075 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4076 4077 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4078 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4079 4080 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4081 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4082 4083 bi = merge->bi; 4084 bj = merge->bj; 4085 buf_ri = merge->buf_ri; 4086 buf_rj = merge->buf_rj; 4087 4088 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4089 owners = merge->rowmap->range; 4090 len_s = merge->len_s; 4091 4092 /* send and recv matrix values */ 4093 /*-----------------------------*/ 4094 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4095 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4096 4097 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4098 for (proc=0,k=0; proc<size; proc++) { 4099 if (!len_s[proc]) continue; 4100 i = owners[proc]; 4101 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4102 k++; 4103 } 4104 4105 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4106 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4107 ierr = PetscFree(status);CHKERRQ(ierr); 4108 4109 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4110 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4111 4112 /* insert mat values of mpimat */ 4113 /*----------------------------*/ 4114 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4115 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4116 4117 for (k=0; k<merge->nrecv; k++) { 4118 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4119 nrows = *(buf_ri_k[k]); 4120 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4121 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4122 } 4123 4124 /* set values of ba */ 4125 m = merge->rowmap->n; 4126 for (i=0; i<m; i++) { 4127 arow = owners[rank] + i; 4128 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4129 bnzi = bi[i+1] - bi[i]; 4130 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4131 4132 /* add local non-zero vals of this proc's seqmat into ba */ 4133 anzi = ai[arow+1] - ai[arow]; 4134 aj = a->j + ai[arow]; 4135 aa = a->a + ai[arow]; 4136 nextaj = 0; 4137 for (j=0; nextaj<anzi; j++) { 4138 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4139 ba_i[j] += aa[nextaj++]; 4140 } 4141 } 4142 4143 /* add received vals into ba */ 4144 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4145 /* i-th row */ 4146 if (i == *nextrow[k]) { 4147 anzi = *(nextai[k]+1) - *nextai[k]; 4148 aj = buf_rj[k] + *(nextai[k]); 4149 aa = abuf_r[k] + *(nextai[k]); 4150 nextaj = 0; 4151 for (j=0; nextaj<anzi; j++) { 4152 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4153 ba_i[j] += aa[nextaj++]; 4154 } 4155 } 4156 nextrow[k]++; nextai[k]++; 4157 } 4158 } 4159 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4160 } 4161 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4162 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4163 4164 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4165 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4166 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4167 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4168 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4169 PetscFunctionReturn(0); 4170 } 4171 4172 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4173 4174 #undef __FUNCT__ 4175 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4176 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4177 { 4178 PetscErrorCode ierr; 4179 Mat B_mpi; 4180 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4181 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4182 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4183 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4184 PetscInt len,proc,*dnz,*onz,bs,cbs; 4185 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4186 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4187 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4188 MPI_Status *status; 4189 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4190 PetscBT lnkbt; 4191 Mat_Merge_SeqsToMPI *merge; 4192 PetscContainer container; 4193 4194 PetscFunctionBegin; 4195 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4196 4197 /* make sure it is a PETSc comm */ 4198 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4199 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4200 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4201 4202 ierr = PetscNew(&merge);CHKERRQ(ierr); 4203 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4204 4205 /* determine row ownership */ 4206 /*---------------------------------------------------------*/ 4207 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4208 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4209 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4210 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4211 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4212 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4213 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4214 4215 m = merge->rowmap->n; 4216 owners = merge->rowmap->range; 4217 4218 /* determine the number of messages to send, their lengths */ 4219 /*---------------------------------------------------------*/ 4220 len_s = merge->len_s; 4221 4222 len = 0; /* length of buf_si[] */ 4223 merge->nsend = 0; 4224 for (proc=0; proc<size; proc++) { 4225 len_si[proc] = 0; 4226 if (proc == rank) { 4227 len_s[proc] = 0; 4228 } else { 4229 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4230 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4231 } 4232 if (len_s[proc]) { 4233 merge->nsend++; 4234 nrows = 0; 4235 for (i=owners[proc]; i<owners[proc+1]; i++) { 4236 if (ai[i+1] > ai[i]) nrows++; 4237 } 4238 len_si[proc] = 2*(nrows+1); 4239 len += len_si[proc]; 4240 } 4241 } 4242 4243 /* determine the number and length of messages to receive for ij-structure */ 4244 /*-------------------------------------------------------------------------*/ 4245 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4246 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4247 4248 /* post the Irecv of j-structure */ 4249 /*-------------------------------*/ 4250 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4251 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4252 4253 /* post the Isend of j-structure */ 4254 /*--------------------------------*/ 4255 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4256 4257 for (proc=0, k=0; proc<size; proc++) { 4258 if (!len_s[proc]) continue; 4259 i = owners[proc]; 4260 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4261 k++; 4262 } 4263 4264 /* receives and sends of j-structure are complete */ 4265 /*------------------------------------------------*/ 4266 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4267 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4268 4269 /* send and recv i-structure */ 4270 /*---------------------------*/ 4271 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4272 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4273 4274 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4275 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4276 for (proc=0,k=0; proc<size; proc++) { 4277 if (!len_s[proc]) continue; 4278 /* form outgoing message for i-structure: 4279 buf_si[0]: nrows to be sent 4280 [1:nrows]: row index (global) 4281 [nrows+1:2*nrows+1]: i-structure index 4282 */ 4283 /*-------------------------------------------*/ 4284 nrows = len_si[proc]/2 - 1; 4285 buf_si_i = buf_si + nrows+1; 4286 buf_si[0] = nrows; 4287 buf_si_i[0] = 0; 4288 nrows = 0; 4289 for (i=owners[proc]; i<owners[proc+1]; i++) { 4290 anzi = ai[i+1] - ai[i]; 4291 if (anzi) { 4292 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4293 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4294 nrows++; 4295 } 4296 } 4297 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4298 k++; 4299 buf_si += len_si[proc]; 4300 } 4301 4302 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4303 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4304 4305 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4306 for (i=0; i<merge->nrecv; i++) { 4307 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); 4308 } 4309 4310 ierr = PetscFree(len_si);CHKERRQ(ierr); 4311 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4312 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4313 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4314 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4315 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4316 ierr = PetscFree(status);CHKERRQ(ierr); 4317 4318 /* compute a local seq matrix in each processor */ 4319 /*----------------------------------------------*/ 4320 /* allocate bi array and free space for accumulating nonzero column info */ 4321 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4322 bi[0] = 0; 4323 4324 /* create and initialize a linked list */ 4325 nlnk = N+1; 4326 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4327 4328 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4329 len = ai[owners[rank+1]] - ai[owners[rank]]; 4330 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4331 4332 current_space = free_space; 4333 4334 /* determine symbolic info for each local row */ 4335 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4336 4337 for (k=0; k<merge->nrecv; k++) { 4338 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4339 nrows = *buf_ri_k[k]; 4340 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4341 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4342 } 4343 4344 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4345 len = 0; 4346 for (i=0; i<m; i++) { 4347 bnzi = 0; 4348 /* add local non-zero cols of this proc's seqmat into lnk */ 4349 arow = owners[rank] + i; 4350 anzi = ai[arow+1] - ai[arow]; 4351 aj = a->j + ai[arow]; 4352 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4353 bnzi += nlnk; 4354 /* add received col data into lnk */ 4355 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4356 if (i == *nextrow[k]) { /* i-th row */ 4357 anzi = *(nextai[k]+1) - *nextai[k]; 4358 aj = buf_rj[k] + *nextai[k]; 4359 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4360 bnzi += nlnk; 4361 nextrow[k]++; nextai[k]++; 4362 } 4363 } 4364 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4365 4366 /* if free space is not available, make more free space */ 4367 if (current_space->local_remaining<bnzi) { 4368 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4369 nspacedouble++; 4370 } 4371 /* copy data into free space, then initialize lnk */ 4372 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4373 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4374 4375 current_space->array += bnzi; 4376 current_space->local_used += bnzi; 4377 current_space->local_remaining -= bnzi; 4378 4379 bi[i+1] = bi[i] + bnzi; 4380 } 4381 4382 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4383 4384 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4385 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4386 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4387 4388 /* create symbolic parallel matrix B_mpi */ 4389 /*---------------------------------------*/ 4390 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4391 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4392 if (n==PETSC_DECIDE) { 4393 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4394 } else { 4395 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4396 } 4397 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4398 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4399 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4400 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4401 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4402 4403 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4404 B_mpi->assembled = PETSC_FALSE; 4405 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4406 merge->bi = bi; 4407 merge->bj = bj; 4408 merge->buf_ri = buf_ri; 4409 merge->buf_rj = buf_rj; 4410 merge->coi = NULL; 4411 merge->coj = NULL; 4412 merge->owners_co = NULL; 4413 4414 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4415 4416 /* attach the supporting struct to B_mpi for reuse */ 4417 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4418 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4419 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4420 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4421 *mpimat = B_mpi; 4422 4423 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4424 PetscFunctionReturn(0); 4425 } 4426 4427 #undef __FUNCT__ 4428 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4429 /*@C 4430 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4431 matrices from each processor 4432 4433 Collective on MPI_Comm 4434 4435 Input Parameters: 4436 + comm - the communicators the parallel matrix will live on 4437 . seqmat - the input sequential matrices 4438 . m - number of local rows (or PETSC_DECIDE) 4439 . n - number of local columns (or PETSC_DECIDE) 4440 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4441 4442 Output Parameter: 4443 . mpimat - the parallel matrix generated 4444 4445 Level: advanced 4446 4447 Notes: 4448 The dimensions of the sequential matrix in each processor MUST be the same. 4449 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4450 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4451 @*/ 4452 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4453 { 4454 PetscErrorCode ierr; 4455 PetscMPIInt size; 4456 4457 PetscFunctionBegin; 4458 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4459 if (size == 1) { 4460 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4461 if (scall == MAT_INITIAL_MATRIX) { 4462 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4463 } else { 4464 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4465 } 4466 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4467 PetscFunctionReturn(0); 4468 } 4469 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4470 if (scall == MAT_INITIAL_MATRIX) { 4471 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4472 } 4473 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4474 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4475 PetscFunctionReturn(0); 4476 } 4477 4478 #undef __FUNCT__ 4479 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4480 /*@ 4481 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4482 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4483 with MatGetSize() 4484 4485 Not Collective 4486 4487 Input Parameters: 4488 + A - the matrix 4489 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4490 4491 Output Parameter: 4492 . A_loc - the local sequential matrix generated 4493 4494 Level: developer 4495 4496 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4497 4498 @*/ 4499 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4500 { 4501 PetscErrorCode ierr; 4502 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4503 Mat_SeqAIJ *mat,*a,*b; 4504 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4505 MatScalar *aa,*ba,*cam; 4506 PetscScalar *ca; 4507 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4508 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4509 PetscBool match; 4510 MPI_Comm comm; 4511 PetscMPIInt size; 4512 4513 PetscFunctionBegin; 4514 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4515 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4516 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4517 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4518 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4519 4520 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4521 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4522 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4523 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4524 aa = a->a; ba = b->a; 4525 if (scall == MAT_INITIAL_MATRIX) { 4526 if (size == 1) { 4527 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4528 PetscFunctionReturn(0); 4529 } 4530 4531 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4532 ci[0] = 0; 4533 for (i=0; i<am; i++) { 4534 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4535 } 4536 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4537 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4538 k = 0; 4539 for (i=0; i<am; i++) { 4540 ncols_o = bi[i+1] - bi[i]; 4541 ncols_d = ai[i+1] - ai[i]; 4542 /* off-diagonal portion of A */ 4543 for (jo=0; jo<ncols_o; jo++) { 4544 col = cmap[*bj]; 4545 if (col >= cstart) break; 4546 cj[k] = col; bj++; 4547 ca[k++] = *ba++; 4548 } 4549 /* diagonal portion of A */ 4550 for (j=0; j<ncols_d; j++) { 4551 cj[k] = cstart + *aj++; 4552 ca[k++] = *aa++; 4553 } 4554 /* off-diagonal portion of A */ 4555 for (j=jo; j<ncols_o; j++) { 4556 cj[k] = cmap[*bj++]; 4557 ca[k++] = *ba++; 4558 } 4559 } 4560 /* put together the new matrix */ 4561 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4562 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4563 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4564 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4565 mat->free_a = PETSC_TRUE; 4566 mat->free_ij = PETSC_TRUE; 4567 mat->nonew = 0; 4568 } else if (scall == MAT_REUSE_MATRIX) { 4569 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4570 ci = mat->i; cj = mat->j; cam = mat->a; 4571 for (i=0; i<am; i++) { 4572 /* off-diagonal portion of A */ 4573 ncols_o = bi[i+1] - bi[i]; 4574 for (jo=0; jo<ncols_o; jo++) { 4575 col = cmap[*bj]; 4576 if (col >= cstart) break; 4577 *cam++ = *ba++; bj++; 4578 } 4579 /* diagonal portion of A */ 4580 ncols_d = ai[i+1] - ai[i]; 4581 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4582 /* off-diagonal portion of A */ 4583 for (j=jo; j<ncols_o; j++) { 4584 *cam++ = *ba++; bj++; 4585 } 4586 } 4587 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4588 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4589 PetscFunctionReturn(0); 4590 } 4591 4592 #undef __FUNCT__ 4593 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4594 /*@C 4595 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4596 4597 Not Collective 4598 4599 Input Parameters: 4600 + A - the matrix 4601 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4602 - row, col - index sets of rows and columns to extract (or NULL) 4603 4604 Output Parameter: 4605 . A_loc - the local sequential matrix generated 4606 4607 Level: developer 4608 4609 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4610 4611 @*/ 4612 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4613 { 4614 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4615 PetscErrorCode ierr; 4616 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4617 IS isrowa,iscola; 4618 Mat *aloc; 4619 PetscBool match; 4620 4621 PetscFunctionBegin; 4622 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4623 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4624 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4625 if (!row) { 4626 start = A->rmap->rstart; end = A->rmap->rend; 4627 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4628 } else { 4629 isrowa = *row; 4630 } 4631 if (!col) { 4632 start = A->cmap->rstart; 4633 cmap = a->garray; 4634 nzA = a->A->cmap->n; 4635 nzB = a->B->cmap->n; 4636 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4637 ncols = 0; 4638 for (i=0; i<nzB; i++) { 4639 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4640 else break; 4641 } 4642 imark = i; 4643 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4644 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4645 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4646 } else { 4647 iscola = *col; 4648 } 4649 if (scall != MAT_INITIAL_MATRIX) { 4650 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4651 aloc[0] = *A_loc; 4652 } 4653 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4654 *A_loc = aloc[0]; 4655 ierr = PetscFree(aloc);CHKERRQ(ierr); 4656 if (!row) { 4657 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4658 } 4659 if (!col) { 4660 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4661 } 4662 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4663 PetscFunctionReturn(0); 4664 } 4665 4666 #undef __FUNCT__ 4667 #define __FUNCT__ "MatGetBrowsOfAcols" 4668 /*@C 4669 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4670 4671 Collective on Mat 4672 4673 Input Parameters: 4674 + A,B - the matrices in mpiaij format 4675 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4676 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4677 4678 Output Parameter: 4679 + rowb, colb - index sets of rows and columns of B to extract 4680 - B_seq - the sequential matrix generated 4681 4682 Level: developer 4683 4684 @*/ 4685 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4686 { 4687 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4688 PetscErrorCode ierr; 4689 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4690 IS isrowb,iscolb; 4691 Mat *bseq=NULL; 4692 4693 PetscFunctionBegin; 4694 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4695 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); 4696 } 4697 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4698 4699 if (scall == MAT_INITIAL_MATRIX) { 4700 start = A->cmap->rstart; 4701 cmap = a->garray; 4702 nzA = a->A->cmap->n; 4703 nzB = a->B->cmap->n; 4704 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4705 ncols = 0; 4706 for (i=0; i<nzB; i++) { /* row < local row index */ 4707 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4708 else break; 4709 } 4710 imark = i; 4711 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4712 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4713 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4714 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4715 } else { 4716 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4717 isrowb = *rowb; iscolb = *colb; 4718 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4719 bseq[0] = *B_seq; 4720 } 4721 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4722 *B_seq = bseq[0]; 4723 ierr = PetscFree(bseq);CHKERRQ(ierr); 4724 if (!rowb) { 4725 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4726 } else { 4727 *rowb = isrowb; 4728 } 4729 if (!colb) { 4730 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4731 } else { 4732 *colb = iscolb; 4733 } 4734 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4735 PetscFunctionReturn(0); 4736 } 4737 4738 #undef __FUNCT__ 4739 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4740 /* 4741 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4742 of the OFF-DIAGONAL portion of local A 4743 4744 Collective on Mat 4745 4746 Input Parameters: 4747 + A,B - the matrices in mpiaij format 4748 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4749 4750 Output Parameter: 4751 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4752 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4753 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4754 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4755 4756 Level: developer 4757 4758 */ 4759 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4760 { 4761 VecScatter_MPI_General *gen_to,*gen_from; 4762 PetscErrorCode ierr; 4763 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4764 Mat_SeqAIJ *b_oth; 4765 VecScatter ctx =a->Mvctx; 4766 MPI_Comm comm; 4767 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4768 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4769 PetscScalar *rvalues,*svalues; 4770 MatScalar *b_otha,*bufa,*bufA; 4771 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4772 MPI_Request *rwaits = NULL,*swaits = NULL; 4773 MPI_Status *sstatus,rstatus; 4774 PetscMPIInt jj,size; 4775 PetscInt *cols,sbs,rbs; 4776 PetscScalar *vals; 4777 4778 PetscFunctionBegin; 4779 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4780 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4781 4782 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4783 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); 4784 } 4785 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4786 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4787 4788 gen_to = (VecScatter_MPI_General*)ctx->todata; 4789 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4790 rvalues = gen_from->values; /* holds the length of receiving row */ 4791 svalues = gen_to->values; /* holds the length of sending row */ 4792 nrecvs = gen_from->n; 4793 nsends = gen_to->n; 4794 4795 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4796 srow = gen_to->indices; /* local row index to be sent */ 4797 sstarts = gen_to->starts; 4798 sprocs = gen_to->procs; 4799 sstatus = gen_to->sstatus; 4800 sbs = gen_to->bs; 4801 rstarts = gen_from->starts; 4802 rprocs = gen_from->procs; 4803 rbs = gen_from->bs; 4804 4805 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4806 if (scall == MAT_INITIAL_MATRIX) { 4807 /* i-array */ 4808 /*---------*/ 4809 /* post receives */ 4810 for (i=0; i<nrecvs; i++) { 4811 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4812 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4813 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4814 } 4815 4816 /* pack the outgoing message */ 4817 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4818 4819 sstartsj[0] = 0; 4820 rstartsj[0] = 0; 4821 len = 0; /* total length of j or a array to be sent */ 4822 k = 0; 4823 for (i=0; i<nsends; i++) { 4824 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4825 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4826 for (j=0; j<nrows; j++) { 4827 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4828 for (l=0; l<sbs; l++) { 4829 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4830 4831 rowlen[j*sbs+l] = ncols; 4832 4833 len += ncols; 4834 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4835 } 4836 k++; 4837 } 4838 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4839 4840 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4841 } 4842 /* recvs and sends of i-array are completed */ 4843 i = nrecvs; 4844 while (i--) { 4845 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4846 } 4847 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4848 4849 /* allocate buffers for sending j and a arrays */ 4850 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4851 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4852 4853 /* create i-array of B_oth */ 4854 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4855 4856 b_othi[0] = 0; 4857 len = 0; /* total length of j or a array to be received */ 4858 k = 0; 4859 for (i=0; i<nrecvs; i++) { 4860 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4861 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4862 for (j=0; j<nrows; j++) { 4863 b_othi[k+1] = b_othi[k] + rowlen[j]; 4864 len += rowlen[j]; k++; 4865 } 4866 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4867 } 4868 4869 /* allocate space for j and a arrrays of B_oth */ 4870 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4871 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4872 4873 /* j-array */ 4874 /*---------*/ 4875 /* post receives of j-array */ 4876 for (i=0; i<nrecvs; i++) { 4877 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4878 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4879 } 4880 4881 /* pack the outgoing message j-array */ 4882 k = 0; 4883 for (i=0; i<nsends; i++) { 4884 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4885 bufJ = bufj+sstartsj[i]; 4886 for (j=0; j<nrows; j++) { 4887 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4888 for (ll=0; ll<sbs; ll++) { 4889 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4890 for (l=0; l<ncols; l++) { 4891 *bufJ++ = cols[l]; 4892 } 4893 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4894 } 4895 } 4896 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4897 } 4898 4899 /* recvs and sends of j-array are completed */ 4900 i = nrecvs; 4901 while (i--) { 4902 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4903 } 4904 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4905 } else if (scall == MAT_REUSE_MATRIX) { 4906 sstartsj = *startsj_s; 4907 rstartsj = *startsj_r; 4908 bufa = *bufa_ptr; 4909 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4910 b_otha = b_oth->a; 4911 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4912 4913 /* a-array */ 4914 /*---------*/ 4915 /* post receives of a-array */ 4916 for (i=0; i<nrecvs; i++) { 4917 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4918 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4919 } 4920 4921 /* pack the outgoing message a-array */ 4922 k = 0; 4923 for (i=0; i<nsends; i++) { 4924 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4925 bufA = bufa+sstartsj[i]; 4926 for (j=0; j<nrows; j++) { 4927 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4928 for (ll=0; ll<sbs; ll++) { 4929 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4930 for (l=0; l<ncols; l++) { 4931 *bufA++ = vals[l]; 4932 } 4933 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4934 } 4935 } 4936 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4937 } 4938 /* recvs and sends of a-array are completed */ 4939 i = nrecvs; 4940 while (i--) { 4941 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4942 } 4943 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4944 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4945 4946 if (scall == MAT_INITIAL_MATRIX) { 4947 /* put together the new matrix */ 4948 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4949 4950 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4951 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4952 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4953 b_oth->free_a = PETSC_TRUE; 4954 b_oth->free_ij = PETSC_TRUE; 4955 b_oth->nonew = 0; 4956 4957 ierr = PetscFree(bufj);CHKERRQ(ierr); 4958 if (!startsj_s || !bufa_ptr) { 4959 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4960 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4961 } else { 4962 *startsj_s = sstartsj; 4963 *startsj_r = rstartsj; 4964 *bufa_ptr = bufa; 4965 } 4966 } 4967 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4968 PetscFunctionReturn(0); 4969 } 4970 4971 #undef __FUNCT__ 4972 #define __FUNCT__ "MatGetCommunicationStructs" 4973 /*@C 4974 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4975 4976 Not Collective 4977 4978 Input Parameters: 4979 . A - The matrix in mpiaij format 4980 4981 Output Parameter: 4982 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4983 . colmap - A map from global column index to local index into lvec 4984 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4985 4986 Level: developer 4987 4988 @*/ 4989 #if defined(PETSC_USE_CTABLE) 4990 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4991 #else 4992 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4993 #endif 4994 { 4995 Mat_MPIAIJ *a; 4996 4997 PetscFunctionBegin; 4998 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4999 PetscValidPointer(lvec, 2); 5000 PetscValidPointer(colmap, 3); 5001 PetscValidPointer(multScatter, 4); 5002 a = (Mat_MPIAIJ*) A->data; 5003 if (lvec) *lvec = a->lvec; 5004 if (colmap) *colmap = a->colmap; 5005 if (multScatter) *multScatter = a->Mvctx; 5006 PetscFunctionReturn(0); 5007 } 5008 5009 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5010 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5011 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5012 #if defined(PETSC_HAVE_ELEMENTAL) 5013 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5014 #endif 5015 5016 #undef __FUNCT__ 5017 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5018 /* 5019 Computes (B'*A')' since computing B*A directly is untenable 5020 5021 n p p 5022 ( ) ( ) ( ) 5023 m ( A ) * n ( B ) = m ( C ) 5024 ( ) ( ) ( ) 5025 5026 */ 5027 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5028 { 5029 PetscErrorCode ierr; 5030 Mat At,Bt,Ct; 5031 5032 PetscFunctionBegin; 5033 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5034 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5035 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5036 ierr = MatDestroy(&At);CHKERRQ(ierr); 5037 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5038 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5039 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5040 PetscFunctionReturn(0); 5041 } 5042 5043 #undef __FUNCT__ 5044 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5045 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5046 { 5047 PetscErrorCode ierr; 5048 PetscInt m=A->rmap->n,n=B->cmap->n; 5049 Mat Cmat; 5050 5051 PetscFunctionBegin; 5052 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); 5053 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5054 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5055 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5056 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5057 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5058 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5059 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5060 5061 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5062 5063 *C = Cmat; 5064 PetscFunctionReturn(0); 5065 } 5066 5067 /* ----------------------------------------------------------------*/ 5068 #undef __FUNCT__ 5069 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5070 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5071 { 5072 PetscErrorCode ierr; 5073 5074 PetscFunctionBegin; 5075 if (scall == MAT_INITIAL_MATRIX) { 5076 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5077 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5078 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5079 } 5080 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5081 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5082 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5083 PetscFunctionReturn(0); 5084 } 5085 5086 /*MC 5087 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5088 5089 Options Database Keys: 5090 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5091 5092 Level: beginner 5093 5094 .seealso: MatCreateAIJ() 5095 M*/ 5096 5097 #undef __FUNCT__ 5098 #define __FUNCT__ "MatCreate_MPIAIJ" 5099 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5100 { 5101 Mat_MPIAIJ *b; 5102 PetscErrorCode ierr; 5103 PetscMPIInt size; 5104 5105 PetscFunctionBegin; 5106 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5107 5108 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5109 B->data = (void*)b; 5110 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5111 B->assembled = PETSC_FALSE; 5112 B->insertmode = NOT_SET_VALUES; 5113 b->size = size; 5114 5115 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5116 5117 /* build cache for off array entries formed */ 5118 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5119 5120 b->donotstash = PETSC_FALSE; 5121 b->colmap = 0; 5122 b->garray = 0; 5123 b->roworiented = PETSC_TRUE; 5124 5125 /* stuff used for matrix vector multiply */ 5126 b->lvec = NULL; 5127 b->Mvctx = NULL; 5128 5129 /* stuff for MatGetRow() */ 5130 b->rowindices = 0; 5131 b->rowvalues = 0; 5132 b->getrowactive = PETSC_FALSE; 5133 5134 /* flexible pointer used in CUSP/CUSPARSE classes */ 5135 b->spptr = NULL; 5136 5137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5138 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5139 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5141 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5142 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5143 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5144 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5145 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5146 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5147 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5148 #if defined(PETSC_HAVE_ELEMENTAL) 5149 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5150 #endif 5151 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5152 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5153 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5154 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5155 PetscFunctionReturn(0); 5156 } 5157 5158 #undef __FUNCT__ 5159 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5160 /*@C 5161 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5162 and "off-diagonal" part of the matrix in CSR format. 5163 5164 Collective on MPI_Comm 5165 5166 Input Parameters: 5167 + comm - MPI communicator 5168 . m - number of local rows (Cannot be PETSC_DECIDE) 5169 . n - This value should be the same as the local size used in creating the 5170 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5171 calculated if N is given) For square matrices n is almost always m. 5172 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5173 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5174 . i - row indices for "diagonal" portion of matrix 5175 . j - column indices 5176 . a - matrix values 5177 . oi - row indices for "off-diagonal" portion of matrix 5178 . oj - column indices 5179 - oa - matrix values 5180 5181 Output Parameter: 5182 . mat - the matrix 5183 5184 Level: advanced 5185 5186 Notes: 5187 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5188 must free the arrays once the matrix has been destroyed and not before. 5189 5190 The i and j indices are 0 based 5191 5192 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5193 5194 This sets local rows and cannot be used to set off-processor values. 5195 5196 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5197 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5198 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5199 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5200 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5201 communication if it is known that only local entries will be set. 5202 5203 .keywords: matrix, aij, compressed row, sparse, parallel 5204 5205 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5206 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5207 @*/ 5208 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) 5209 { 5210 PetscErrorCode ierr; 5211 Mat_MPIAIJ *maij; 5212 5213 PetscFunctionBegin; 5214 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5215 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5216 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5217 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5218 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5219 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5220 maij = (Mat_MPIAIJ*) (*mat)->data; 5221 5222 (*mat)->preallocated = PETSC_TRUE; 5223 5224 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5225 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5226 5227 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5228 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5229 5230 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5231 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5232 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5233 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5234 5235 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5236 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5237 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5238 PetscFunctionReturn(0); 5239 } 5240 5241 /* 5242 Special version for direct calls from Fortran 5243 */ 5244 #include <petsc/private/fortranimpl.h> 5245 5246 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5247 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5248 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5249 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5250 #endif 5251 5252 /* Change these macros so can be used in void function */ 5253 #undef CHKERRQ 5254 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5255 #undef SETERRQ2 5256 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5257 #undef SETERRQ3 5258 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5259 #undef SETERRQ 5260 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5261 5262 #undef __FUNCT__ 5263 #define __FUNCT__ "matsetvaluesmpiaij_" 5264 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) 5265 { 5266 Mat mat = *mmat; 5267 PetscInt m = *mm, n = *mn; 5268 InsertMode addv = *maddv; 5269 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5270 PetscScalar value; 5271 PetscErrorCode ierr; 5272 5273 MatCheckPreallocated(mat,1); 5274 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5275 5276 #if defined(PETSC_USE_DEBUG) 5277 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5278 #endif 5279 { 5280 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5281 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5282 PetscBool roworiented = aij->roworiented; 5283 5284 /* Some Variables required in the macro */ 5285 Mat A = aij->A; 5286 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5287 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5288 MatScalar *aa = a->a; 5289 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5290 Mat B = aij->B; 5291 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5292 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5293 MatScalar *ba = b->a; 5294 5295 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5296 PetscInt nonew = a->nonew; 5297 MatScalar *ap1,*ap2; 5298 5299 PetscFunctionBegin; 5300 for (i=0; i<m; i++) { 5301 if (im[i] < 0) continue; 5302 #if defined(PETSC_USE_DEBUG) 5303 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); 5304 #endif 5305 if (im[i] >= rstart && im[i] < rend) { 5306 row = im[i] - rstart; 5307 lastcol1 = -1; 5308 rp1 = aj + ai[row]; 5309 ap1 = aa + ai[row]; 5310 rmax1 = aimax[row]; 5311 nrow1 = ailen[row]; 5312 low1 = 0; 5313 high1 = nrow1; 5314 lastcol2 = -1; 5315 rp2 = bj + bi[row]; 5316 ap2 = ba + bi[row]; 5317 rmax2 = bimax[row]; 5318 nrow2 = bilen[row]; 5319 low2 = 0; 5320 high2 = nrow2; 5321 5322 for (j=0; j<n; j++) { 5323 if (roworiented) value = v[i*n+j]; 5324 else value = v[i+j*m]; 5325 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5326 if (in[j] >= cstart && in[j] < cend) { 5327 col = in[j] - cstart; 5328 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5329 } else if (in[j] < 0) continue; 5330 #if defined(PETSC_USE_DEBUG) 5331 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); 5332 #endif 5333 else { 5334 if (mat->was_assembled) { 5335 if (!aij->colmap) { 5336 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5337 } 5338 #if defined(PETSC_USE_CTABLE) 5339 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5340 col--; 5341 #else 5342 col = aij->colmap[in[j]] - 1; 5343 #endif 5344 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5345 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5346 col = in[j]; 5347 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5348 B = aij->B; 5349 b = (Mat_SeqAIJ*)B->data; 5350 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5351 rp2 = bj + bi[row]; 5352 ap2 = ba + bi[row]; 5353 rmax2 = bimax[row]; 5354 nrow2 = bilen[row]; 5355 low2 = 0; 5356 high2 = nrow2; 5357 bm = aij->B->rmap->n; 5358 ba = b->a; 5359 } 5360 } else col = in[j]; 5361 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5362 } 5363 } 5364 } else if (!aij->donotstash) { 5365 if (roworiented) { 5366 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5367 } else { 5368 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5369 } 5370 } 5371 } 5372 } 5373 PetscFunctionReturnVoid(); 5374 } 5375 5376