1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petsc-private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPIU_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,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 /* -------------------------------------------------------------------*/ 2638 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2639 MatGetRow_MPIAIJ, 2640 MatRestoreRow_MPIAIJ, 2641 MatMult_MPIAIJ, 2642 /* 4*/ MatMultAdd_MPIAIJ, 2643 MatMultTranspose_MPIAIJ, 2644 MatMultTransposeAdd_MPIAIJ, 2645 #if defined(PETSC_HAVE_PBGL) 2646 MatSolve_MPIAIJ, 2647 #else 2648 0, 2649 #endif 2650 0, 2651 0, 2652 /*10*/ 0, 2653 0, 2654 0, 2655 MatSOR_MPIAIJ, 2656 MatTranspose_MPIAIJ, 2657 /*15*/ MatGetInfo_MPIAIJ, 2658 MatEqual_MPIAIJ, 2659 MatGetDiagonal_MPIAIJ, 2660 MatDiagonalScale_MPIAIJ, 2661 MatNorm_MPIAIJ, 2662 /*20*/ MatAssemblyBegin_MPIAIJ, 2663 MatAssemblyEnd_MPIAIJ, 2664 MatSetOption_MPIAIJ, 2665 MatZeroEntries_MPIAIJ, 2666 /*24*/ MatZeroRows_MPIAIJ, 2667 0, 2668 #if defined(PETSC_HAVE_PBGL) 2669 0, 2670 #else 2671 0, 2672 #endif 2673 0, 2674 0, 2675 /*29*/ MatSetUp_MPIAIJ, 2676 #if defined(PETSC_HAVE_PBGL) 2677 0, 2678 #else 2679 0, 2680 #endif 2681 0, 2682 0, 2683 0, 2684 /*34*/ MatDuplicate_MPIAIJ, 2685 0, 2686 0, 2687 0, 2688 0, 2689 /*39*/ MatAXPY_MPIAIJ, 2690 MatGetSubMatrices_MPIAIJ, 2691 MatIncreaseOverlap_MPIAIJ, 2692 MatGetValues_MPIAIJ, 2693 MatCopy_MPIAIJ, 2694 /*44*/ MatGetRowMax_MPIAIJ, 2695 MatScale_MPIAIJ, 2696 0, 2697 MatDiagonalSet_MPIAIJ, 2698 MatZeroRowsColumns_MPIAIJ, 2699 /*49*/ MatSetRandom_MPIAIJ, 2700 0, 2701 0, 2702 0, 2703 0, 2704 /*54*/ MatFDColoringCreate_MPIXAIJ, 2705 0, 2706 MatSetUnfactored_MPIAIJ, 2707 MatPermute_MPIAIJ, 2708 0, 2709 /*59*/ MatGetSubMatrix_MPIAIJ, 2710 MatDestroy_MPIAIJ, 2711 MatView_MPIAIJ, 2712 0, 2713 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2714 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2715 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2716 0, 2717 0, 2718 0, 2719 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2720 MatGetRowMinAbs_MPIAIJ, 2721 0, 2722 MatSetColoring_MPIAIJ, 2723 0, 2724 MatSetValuesAdifor_MPIAIJ, 2725 /*75*/ MatFDColoringApply_AIJ, 2726 MatSetFromOptions_MPIAIJ, 2727 0, 2728 0, 2729 MatFindZeroDiagonals_MPIAIJ, 2730 /*80*/ 0, 2731 0, 2732 0, 2733 /*83*/ MatLoad_MPIAIJ, 2734 0, 2735 0, 2736 0, 2737 0, 2738 0, 2739 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2740 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2741 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2742 MatPtAP_MPIAIJ_MPIAIJ, 2743 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2744 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2745 0, 2746 0, 2747 0, 2748 0, 2749 /*99*/ 0, 2750 0, 2751 0, 2752 MatConjugate_MPIAIJ, 2753 0, 2754 /*104*/MatSetValuesRow_MPIAIJ, 2755 MatRealPart_MPIAIJ, 2756 MatImaginaryPart_MPIAIJ, 2757 0, 2758 0, 2759 /*109*/0, 2760 0, 2761 MatGetRowMin_MPIAIJ, 2762 0, 2763 0, 2764 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2765 0, 2766 0, 2767 0, 2768 0, 2769 /*119*/0, 2770 0, 2771 0, 2772 0, 2773 MatGetMultiProcBlock_MPIAIJ, 2774 /*124*/MatFindNonzeroRows_MPIAIJ, 2775 MatGetColumnNorms_MPIAIJ, 2776 MatInvertBlockDiagonal_MPIAIJ, 2777 0, 2778 MatGetSubMatricesParallel_MPIAIJ, 2779 /*129*/0, 2780 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2781 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2782 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2783 0, 2784 /*134*/0, 2785 0, 2786 0, 2787 0, 2788 0, 2789 /*139*/0, 2790 0, 2791 0, 2792 MatFDColoringSetUp_MPIXAIJ, 2793 MatFindOffBlockDiagonalEntries_MPIAIJ, 2794 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2795 }; 2796 2797 /* ----------------------------------------------------------------------------------------*/ 2798 2799 #undef __FUNCT__ 2800 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2801 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2802 { 2803 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2804 PetscErrorCode ierr; 2805 2806 PetscFunctionBegin; 2807 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2808 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2809 PetscFunctionReturn(0); 2810 } 2811 2812 #undef __FUNCT__ 2813 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2814 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2815 { 2816 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2817 PetscErrorCode ierr; 2818 2819 PetscFunctionBegin; 2820 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2821 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2822 PetscFunctionReturn(0); 2823 } 2824 2825 #undef __FUNCT__ 2826 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2827 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2828 { 2829 Mat_MPIAIJ *b; 2830 PetscErrorCode ierr; 2831 2832 PetscFunctionBegin; 2833 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2834 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2835 b = (Mat_MPIAIJ*)B->data; 2836 2837 if (!B->preallocated) { 2838 /* Explicitly create 2 MATSEQAIJ matrices. */ 2839 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2840 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2841 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2842 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2843 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2844 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2845 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2846 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2847 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2848 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2849 } 2850 2851 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2852 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2853 B->preallocated = PETSC_TRUE; 2854 PetscFunctionReturn(0); 2855 } 2856 2857 #undef __FUNCT__ 2858 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2859 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2860 { 2861 Mat mat; 2862 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2863 PetscErrorCode ierr; 2864 2865 PetscFunctionBegin; 2866 *newmat = 0; 2867 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2868 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2869 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2870 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2871 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2872 a = (Mat_MPIAIJ*)mat->data; 2873 2874 mat->factortype = matin->factortype; 2875 mat->assembled = PETSC_TRUE; 2876 mat->insertmode = NOT_SET_VALUES; 2877 mat->preallocated = PETSC_TRUE; 2878 2879 a->size = oldmat->size; 2880 a->rank = oldmat->rank; 2881 a->donotstash = oldmat->donotstash; 2882 a->roworiented = oldmat->roworiented; 2883 a->rowindices = 0; 2884 a->rowvalues = 0; 2885 a->getrowactive = PETSC_FALSE; 2886 2887 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2888 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2889 2890 if (oldmat->colmap) { 2891 #if defined(PETSC_USE_CTABLE) 2892 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2893 #else 2894 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2895 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2896 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2897 #endif 2898 } else a->colmap = 0; 2899 if (oldmat->garray) { 2900 PetscInt len; 2901 len = oldmat->B->cmap->n; 2902 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2903 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2904 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2905 } else a->garray = 0; 2906 2907 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2908 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2909 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2910 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2911 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2912 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2913 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2914 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2915 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2916 *newmat = mat; 2917 PetscFunctionReturn(0); 2918 } 2919 2920 2921 2922 #undef __FUNCT__ 2923 #define __FUNCT__ "MatLoad_MPIAIJ" 2924 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2925 { 2926 PetscScalar *vals,*svals; 2927 MPI_Comm comm; 2928 PetscErrorCode ierr; 2929 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2930 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 2931 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2932 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2933 PetscInt cend,cstart,n,*rowners,sizesset=1; 2934 int fd; 2935 PetscInt bs = newMat->rmap->bs; 2936 2937 PetscFunctionBegin; 2938 /* force binary viewer to load .info file if it has not yet done so */ 2939 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2940 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2941 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2942 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2943 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2944 if (!rank) { 2945 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2946 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2947 } 2948 2949 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2950 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2951 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2952 if (bs < 0) bs = 1; 2953 2954 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 2955 2956 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2957 M = header[1]; N = header[2]; 2958 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2959 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 2960 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 2961 2962 /* If global sizes are set, check if they are consistent with that given in the file */ 2963 if (sizesset) { 2964 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 2965 } 2966 if (sizesset && newMat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 2967 if (sizesset && newMat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 2968 2969 /* determine ownership of all (block) rows */ 2970 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2971 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2972 else m = newMat->rmap->n; /* Set by user */ 2973 2974 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2975 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2976 2977 /* First process needs enough room for process with most rows */ 2978 if (!rank) { 2979 mmax = rowners[1]; 2980 for (i=2; i<=size; i++) { 2981 mmax = PetscMax(mmax, rowners[i]); 2982 } 2983 } else mmax = -1; /* unused, but compilers complain */ 2984 2985 rowners[0] = 0; 2986 for (i=2; i<=size; i++) { 2987 rowners[i] += rowners[i-1]; 2988 } 2989 rstart = rowners[rank]; 2990 rend = rowners[rank+1]; 2991 2992 /* distribute row lengths to all processors */ 2993 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2994 if (!rank) { 2995 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2996 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2997 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2998 for (j=0; j<m; j++) { 2999 procsnz[0] += ourlens[j]; 3000 } 3001 for (i=1; i<size; i++) { 3002 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3003 /* calculate the number of nonzeros on each processor */ 3004 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3005 procsnz[i] += rowlengths[j]; 3006 } 3007 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3008 } 3009 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3010 } else { 3011 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3012 } 3013 3014 if (!rank) { 3015 /* determine max buffer needed and allocate it */ 3016 maxnz = 0; 3017 for (i=0; i<size; i++) { 3018 maxnz = PetscMax(maxnz,procsnz[i]); 3019 } 3020 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3021 3022 /* read in my part of the matrix column indices */ 3023 nz = procsnz[0]; 3024 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3025 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3026 3027 /* read in every one elses and ship off */ 3028 for (i=1; i<size; i++) { 3029 nz = procsnz[i]; 3030 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3031 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3032 } 3033 ierr = PetscFree(cols);CHKERRQ(ierr); 3034 } else { 3035 /* determine buffer space needed for message */ 3036 nz = 0; 3037 for (i=0; i<m; i++) { 3038 nz += ourlens[i]; 3039 } 3040 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3041 3042 /* receive message of column indices*/ 3043 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3044 } 3045 3046 /* determine column ownership if matrix is not square */ 3047 if (N != M) { 3048 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3049 else n = newMat->cmap->n; 3050 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3051 cstart = cend - n; 3052 } else { 3053 cstart = rstart; 3054 cend = rend; 3055 n = cend - cstart; 3056 } 3057 3058 /* loop over local rows, determining number of off diagonal entries */ 3059 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3060 jj = 0; 3061 for (i=0; i<m; i++) { 3062 for (j=0; j<ourlens[i]; j++) { 3063 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3064 jj++; 3065 } 3066 } 3067 3068 for (i=0; i<m; i++) { 3069 ourlens[i] -= offlens[i]; 3070 } 3071 if (!sizesset) { 3072 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3073 } 3074 3075 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3076 3077 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3078 3079 for (i=0; i<m; i++) { 3080 ourlens[i] += offlens[i]; 3081 } 3082 3083 if (!rank) { 3084 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3085 3086 /* read in my part of the matrix numerical values */ 3087 nz = procsnz[0]; 3088 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3089 3090 /* insert into matrix */ 3091 jj = rstart; 3092 smycols = mycols; 3093 svals = vals; 3094 for (i=0; i<m; i++) { 3095 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3096 smycols += ourlens[i]; 3097 svals += ourlens[i]; 3098 jj++; 3099 } 3100 3101 /* read in other processors and ship out */ 3102 for (i=1; i<size; i++) { 3103 nz = procsnz[i]; 3104 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3105 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3106 } 3107 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3108 } else { 3109 /* receive numeric values */ 3110 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3111 3112 /* receive message of values*/ 3113 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3114 3115 /* insert into matrix */ 3116 jj = rstart; 3117 smycols = mycols; 3118 svals = vals; 3119 for (i=0; i<m; i++) { 3120 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3121 smycols += ourlens[i]; 3122 svals += ourlens[i]; 3123 jj++; 3124 } 3125 } 3126 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3127 ierr = PetscFree(vals);CHKERRQ(ierr); 3128 ierr = PetscFree(mycols);CHKERRQ(ierr); 3129 ierr = PetscFree(rowners);CHKERRQ(ierr); 3130 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3131 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3132 PetscFunctionReturn(0); 3133 } 3134 3135 #undef __FUNCT__ 3136 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3137 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3138 { 3139 PetscErrorCode ierr; 3140 IS iscol_local; 3141 PetscInt csize; 3142 3143 PetscFunctionBegin; 3144 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3145 if (call == MAT_REUSE_MATRIX) { 3146 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3147 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3148 } else { 3149 PetscInt cbs; 3150 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3151 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3152 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3153 } 3154 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3155 if (call == MAT_INITIAL_MATRIX) { 3156 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3157 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3158 } 3159 PetscFunctionReturn(0); 3160 } 3161 3162 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3163 #undef __FUNCT__ 3164 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3165 /* 3166 Not great since it makes two copies of the submatrix, first an SeqAIJ 3167 in local and then by concatenating the local matrices the end result. 3168 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3169 3170 Note: This requires a sequential iscol with all indices. 3171 */ 3172 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3173 { 3174 PetscErrorCode ierr; 3175 PetscMPIInt rank,size; 3176 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3177 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3178 PetscBool allcolumns, colflag; 3179 Mat M,Mreuse; 3180 MatScalar *vwork,*aa; 3181 MPI_Comm comm; 3182 Mat_SeqAIJ *aij; 3183 3184 PetscFunctionBegin; 3185 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3186 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3187 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3188 3189 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3190 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3191 if (colflag && ncol == mat->cmap->N) { 3192 allcolumns = PETSC_TRUE; 3193 } else { 3194 allcolumns = PETSC_FALSE; 3195 } 3196 if (call == MAT_REUSE_MATRIX) { 3197 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3198 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3199 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3200 } else { 3201 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3202 } 3203 3204 /* 3205 m - number of local rows 3206 n - number of columns (same on all processors) 3207 rstart - first row in new global matrix generated 3208 */ 3209 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3210 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3211 if (call == MAT_INITIAL_MATRIX) { 3212 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3213 ii = aij->i; 3214 jj = aij->j; 3215 3216 /* 3217 Determine the number of non-zeros in the diagonal and off-diagonal 3218 portions of the matrix in order to do correct preallocation 3219 */ 3220 3221 /* first get start and end of "diagonal" columns */ 3222 if (csize == PETSC_DECIDE) { 3223 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3224 if (mglobal == n) { /* square matrix */ 3225 nlocal = m; 3226 } else { 3227 nlocal = n/size + ((n % size) > rank); 3228 } 3229 } else { 3230 nlocal = csize; 3231 } 3232 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3233 rstart = rend - nlocal; 3234 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); 3235 3236 /* next, compute all the lengths */ 3237 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3238 olens = dlens + m; 3239 for (i=0; i<m; i++) { 3240 jend = ii[i+1] - ii[i]; 3241 olen = 0; 3242 dlen = 0; 3243 for (j=0; j<jend; j++) { 3244 if (*jj < rstart || *jj >= rend) olen++; 3245 else dlen++; 3246 jj++; 3247 } 3248 olens[i] = olen; 3249 dlens[i] = dlen; 3250 } 3251 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3252 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3253 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3254 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3255 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3256 ierr = PetscFree(dlens);CHKERRQ(ierr); 3257 } else { 3258 PetscInt ml,nl; 3259 3260 M = *newmat; 3261 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3262 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3263 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3264 /* 3265 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3266 rather than the slower MatSetValues(). 3267 */ 3268 M->was_assembled = PETSC_TRUE; 3269 M->assembled = PETSC_FALSE; 3270 } 3271 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3272 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3273 ii = aij->i; 3274 jj = aij->j; 3275 aa = aij->a; 3276 for (i=0; i<m; i++) { 3277 row = rstart + i; 3278 nz = ii[i+1] - ii[i]; 3279 cwork = jj; jj += nz; 3280 vwork = aa; aa += nz; 3281 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3282 } 3283 3284 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3285 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3286 *newmat = M; 3287 3288 /* save submatrix used in processor for next request */ 3289 if (call == MAT_INITIAL_MATRIX) { 3290 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3291 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3292 } 3293 PetscFunctionReturn(0); 3294 } 3295 3296 #undef __FUNCT__ 3297 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3298 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3299 { 3300 PetscInt m,cstart, cend,j,nnz,i,d; 3301 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3302 const PetscInt *JJ; 3303 PetscScalar *values; 3304 PetscErrorCode ierr; 3305 3306 PetscFunctionBegin; 3307 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3308 3309 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3310 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3311 m = B->rmap->n; 3312 cstart = B->cmap->rstart; 3313 cend = B->cmap->rend; 3314 rstart = B->rmap->rstart; 3315 3316 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3317 3318 #if defined(PETSC_USE_DEBUGGING) 3319 for (i=0; i<m; i++) { 3320 nnz = Ii[i+1]- Ii[i]; 3321 JJ = J + Ii[i]; 3322 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3323 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3324 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); 3325 } 3326 #endif 3327 3328 for (i=0; i<m; i++) { 3329 nnz = Ii[i+1]- Ii[i]; 3330 JJ = J + Ii[i]; 3331 nnz_max = PetscMax(nnz_max,nnz); 3332 d = 0; 3333 for (j=0; j<nnz; j++) { 3334 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3335 } 3336 d_nnz[i] = d; 3337 o_nnz[i] = nnz - d; 3338 } 3339 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3340 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3341 3342 if (v) values = (PetscScalar*)v; 3343 else { 3344 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3345 } 3346 3347 for (i=0; i<m; i++) { 3348 ii = i + rstart; 3349 nnz = Ii[i+1]- Ii[i]; 3350 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3351 } 3352 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3353 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3354 3355 if (!v) { 3356 ierr = PetscFree(values);CHKERRQ(ierr); 3357 } 3358 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3359 PetscFunctionReturn(0); 3360 } 3361 3362 #undef __FUNCT__ 3363 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3364 /*@ 3365 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3366 (the default parallel PETSc format). 3367 3368 Collective on MPI_Comm 3369 3370 Input Parameters: 3371 + B - the matrix 3372 . i - the indices into j for the start of each local row (starts with zero) 3373 . j - the column indices for each local row (starts with zero) 3374 - v - optional values in the matrix 3375 3376 Level: developer 3377 3378 Notes: 3379 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3380 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3381 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3382 3383 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3384 3385 The format which is used for the sparse matrix input, is equivalent to a 3386 row-major ordering.. i.e for the following matrix, the input data expected is 3387 as shown: 3388 3389 1 0 0 3390 2 0 3 P0 3391 ------- 3392 4 5 6 P1 3393 3394 Process0 [P0]: rows_owned=[0,1] 3395 i = {0,1,3} [size = nrow+1 = 2+1] 3396 j = {0,0,2} [size = nz = 6] 3397 v = {1,2,3} [size = nz = 6] 3398 3399 Process1 [P1]: rows_owned=[2] 3400 i = {0,3} [size = nrow+1 = 1+1] 3401 j = {0,1,2} [size = nz = 6] 3402 v = {4,5,6} [size = nz = 6] 3403 3404 .keywords: matrix, aij, compressed row, sparse, parallel 3405 3406 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3407 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3408 @*/ 3409 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3410 { 3411 PetscErrorCode ierr; 3412 3413 PetscFunctionBegin; 3414 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3415 PetscFunctionReturn(0); 3416 } 3417 3418 #undef __FUNCT__ 3419 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3420 /*@C 3421 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3422 (the default parallel PETSc format). For good matrix assembly performance 3423 the user should preallocate the matrix storage by setting the parameters 3424 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3425 performance can be increased by more than a factor of 50. 3426 3427 Collective on MPI_Comm 3428 3429 Input Parameters: 3430 + B - the matrix 3431 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3432 (same value is used for all local rows) 3433 . d_nnz - array containing the number of nonzeros in the various rows of the 3434 DIAGONAL portion of the local submatrix (possibly different for each row) 3435 or NULL, if d_nz is used to specify the nonzero structure. 3436 The size of this array is equal to the number of local rows, i.e 'm'. 3437 For matrices that will be factored, you must leave room for (and set) 3438 the diagonal entry even if it is zero. 3439 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3440 submatrix (same value is used for all local rows). 3441 - o_nnz - array containing the number of nonzeros in the various rows of the 3442 OFF-DIAGONAL portion of the local submatrix (possibly different for 3443 each row) or NULL, if o_nz is used to specify the nonzero 3444 structure. The size of this array is equal to the number 3445 of local rows, i.e 'm'. 3446 3447 If the *_nnz parameter is given then the *_nz parameter is ignored 3448 3449 The AIJ format (also called the Yale sparse matrix format or 3450 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3451 storage. The stored row and column indices begin with zero. 3452 See Users-Manual: ch_mat for details. 3453 3454 The parallel matrix is partitioned such that the first m0 rows belong to 3455 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3456 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3457 3458 The DIAGONAL portion of the local submatrix of a processor can be defined 3459 as the submatrix which is obtained by extraction the part corresponding to 3460 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3461 first row that belongs to the processor, r2 is the last row belonging to 3462 the this processor, and c1-c2 is range of indices of the local part of a 3463 vector suitable for applying the matrix to. This is an mxn matrix. In the 3464 common case of a square matrix, the row and column ranges are the same and 3465 the DIAGONAL part is also square. The remaining portion of the local 3466 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3467 3468 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3469 3470 You can call MatGetInfo() to get information on how effective the preallocation was; 3471 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3472 You can also run with the option -info and look for messages with the string 3473 malloc in them to see if additional memory allocation was needed. 3474 3475 Example usage: 3476 3477 Consider the following 8x8 matrix with 34 non-zero values, that is 3478 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3479 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3480 as follows: 3481 3482 .vb 3483 1 2 0 | 0 3 0 | 0 4 3484 Proc0 0 5 6 | 7 0 0 | 8 0 3485 9 0 10 | 11 0 0 | 12 0 3486 ------------------------------------- 3487 13 0 14 | 15 16 17 | 0 0 3488 Proc1 0 18 0 | 19 20 21 | 0 0 3489 0 0 0 | 22 23 0 | 24 0 3490 ------------------------------------- 3491 Proc2 25 26 27 | 0 0 28 | 29 0 3492 30 0 0 | 31 32 33 | 0 34 3493 .ve 3494 3495 This can be represented as a collection of submatrices as: 3496 3497 .vb 3498 A B C 3499 D E F 3500 G H I 3501 .ve 3502 3503 Where the submatrices A,B,C are owned by proc0, D,E,F are 3504 owned by proc1, G,H,I are owned by proc2. 3505 3506 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3507 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3508 The 'M','N' parameters are 8,8, and have the same values on all procs. 3509 3510 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3511 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3512 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3513 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3514 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3515 matrix, ans [DF] as another SeqAIJ matrix. 3516 3517 When d_nz, o_nz parameters are specified, d_nz storage elements are 3518 allocated for every row of the local diagonal submatrix, and o_nz 3519 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3520 One way to choose d_nz and o_nz is to use the max nonzerors per local 3521 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3522 In this case, the values of d_nz,o_nz are: 3523 .vb 3524 proc0 : dnz = 2, o_nz = 2 3525 proc1 : dnz = 3, o_nz = 2 3526 proc2 : dnz = 1, o_nz = 4 3527 .ve 3528 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3529 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3530 for proc3. i.e we are using 12+15+10=37 storage locations to store 3531 34 values. 3532 3533 When d_nnz, o_nnz parameters are specified, the storage is specified 3534 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3535 In the above case the values for d_nnz,o_nnz are: 3536 .vb 3537 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3538 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3539 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3540 .ve 3541 Here the space allocated is sum of all the above values i.e 34, and 3542 hence pre-allocation is perfect. 3543 3544 Level: intermediate 3545 3546 .keywords: matrix, aij, compressed row, sparse, parallel 3547 3548 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3549 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3550 @*/ 3551 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3552 { 3553 PetscErrorCode ierr; 3554 3555 PetscFunctionBegin; 3556 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3557 PetscValidType(B,1); 3558 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3559 PetscFunctionReturn(0); 3560 } 3561 3562 #undef __FUNCT__ 3563 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3564 /*@ 3565 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3566 CSR format the local rows. 3567 3568 Collective on MPI_Comm 3569 3570 Input Parameters: 3571 + comm - MPI communicator 3572 . m - number of local rows (Cannot be PETSC_DECIDE) 3573 . n - This value should be the same as the local size used in creating the 3574 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3575 calculated if N is given) For square matrices n is almost always m. 3576 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3577 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3578 . i - row indices 3579 . j - column indices 3580 - a - matrix values 3581 3582 Output Parameter: 3583 . mat - the matrix 3584 3585 Level: intermediate 3586 3587 Notes: 3588 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3589 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3590 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3591 3592 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3593 3594 The format which is used for the sparse matrix input, is equivalent to a 3595 row-major ordering.. i.e for the following matrix, the input data expected is 3596 as shown: 3597 3598 1 0 0 3599 2 0 3 P0 3600 ------- 3601 4 5 6 P1 3602 3603 Process0 [P0]: rows_owned=[0,1] 3604 i = {0,1,3} [size = nrow+1 = 2+1] 3605 j = {0,0,2} [size = nz = 6] 3606 v = {1,2,3} [size = nz = 6] 3607 3608 Process1 [P1]: rows_owned=[2] 3609 i = {0,3} [size = nrow+1 = 1+1] 3610 j = {0,1,2} [size = nz = 6] 3611 v = {4,5,6} [size = nz = 6] 3612 3613 .keywords: matrix, aij, compressed row, sparse, parallel 3614 3615 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3616 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3617 @*/ 3618 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3619 { 3620 PetscErrorCode ierr; 3621 3622 PetscFunctionBegin; 3623 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3624 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3625 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3626 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3627 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3628 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3629 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3630 PetscFunctionReturn(0); 3631 } 3632 3633 #undef __FUNCT__ 3634 #define __FUNCT__ "MatCreateAIJ" 3635 /*@C 3636 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3637 (the default parallel PETSc format). For good matrix assembly performance 3638 the user should preallocate the matrix storage by setting the parameters 3639 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3640 performance can be increased by more than a factor of 50. 3641 3642 Collective on MPI_Comm 3643 3644 Input Parameters: 3645 + comm - MPI communicator 3646 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3647 This value should be the same as the local size used in creating the 3648 y vector for the matrix-vector product y = Ax. 3649 . n - This value should be the same as the local size used in creating the 3650 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3651 calculated if N is given) For square matrices n is almost always m. 3652 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3653 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3654 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3655 (same value is used for all local rows) 3656 . d_nnz - array containing the number of nonzeros in the various rows of the 3657 DIAGONAL portion of the local submatrix (possibly different for each row) 3658 or NULL, if d_nz is used to specify the nonzero structure. 3659 The size of this array is equal to the number of local rows, i.e 'm'. 3660 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3661 submatrix (same value is used for all local rows). 3662 - o_nnz - array containing the number of nonzeros in the various rows of the 3663 OFF-DIAGONAL portion of the local submatrix (possibly different for 3664 each row) or NULL, if o_nz is used to specify the nonzero 3665 structure. The size of this array is equal to the number 3666 of local rows, i.e 'm'. 3667 3668 Output Parameter: 3669 . A - the matrix 3670 3671 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3672 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3673 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3674 3675 Notes: 3676 If the *_nnz parameter is given then the *_nz parameter is ignored 3677 3678 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3679 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3680 storage requirements for this matrix. 3681 3682 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3683 processor than it must be used on all processors that share the object for 3684 that argument. 3685 3686 The user MUST specify either the local or global matrix dimensions 3687 (possibly both). 3688 3689 The parallel matrix is partitioned across processors such that the 3690 first m0 rows belong to process 0, the next m1 rows belong to 3691 process 1, the next m2 rows belong to process 2 etc.. where 3692 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3693 values corresponding to [m x N] submatrix. 3694 3695 The columns are logically partitioned with the n0 columns belonging 3696 to 0th partition, the next n1 columns belonging to the next 3697 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3698 3699 The DIAGONAL portion of the local submatrix on any given processor 3700 is the submatrix corresponding to the rows and columns m,n 3701 corresponding to the given processor. i.e diagonal matrix on 3702 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3703 etc. The remaining portion of the local submatrix [m x (N-n)] 3704 constitute the OFF-DIAGONAL portion. The example below better 3705 illustrates this concept. 3706 3707 For a square global matrix we define each processor's diagonal portion 3708 to be its local rows and the corresponding columns (a square submatrix); 3709 each processor's off-diagonal portion encompasses the remainder of the 3710 local matrix (a rectangular submatrix). 3711 3712 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3713 3714 When calling this routine with a single process communicator, a matrix of 3715 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3716 type of communicator, use the construction mechanism: 3717 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3718 3719 By default, this format uses inodes (identical nodes) when possible. 3720 We search for consecutive rows with the same nonzero structure, thereby 3721 reusing matrix information to achieve increased efficiency. 3722 3723 Options Database Keys: 3724 + -mat_no_inode - Do not use inodes 3725 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3726 - -mat_aij_oneindex - Internally use indexing starting at 1 3727 rather than 0. Note that when calling MatSetValues(), 3728 the user still MUST index entries starting at 0! 3729 3730 3731 Example usage: 3732 3733 Consider the following 8x8 matrix with 34 non-zero values, that is 3734 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3735 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3736 as follows: 3737 3738 .vb 3739 1 2 0 | 0 3 0 | 0 4 3740 Proc0 0 5 6 | 7 0 0 | 8 0 3741 9 0 10 | 11 0 0 | 12 0 3742 ------------------------------------- 3743 13 0 14 | 15 16 17 | 0 0 3744 Proc1 0 18 0 | 19 20 21 | 0 0 3745 0 0 0 | 22 23 0 | 24 0 3746 ------------------------------------- 3747 Proc2 25 26 27 | 0 0 28 | 29 0 3748 30 0 0 | 31 32 33 | 0 34 3749 .ve 3750 3751 This can be represented as a collection of submatrices as: 3752 3753 .vb 3754 A B C 3755 D E F 3756 G H I 3757 .ve 3758 3759 Where the submatrices A,B,C are owned by proc0, D,E,F are 3760 owned by proc1, G,H,I are owned by proc2. 3761 3762 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3763 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3764 The 'M','N' parameters are 8,8, and have the same values on all procs. 3765 3766 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3767 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3768 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3769 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3770 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3771 matrix, ans [DF] as another SeqAIJ matrix. 3772 3773 When d_nz, o_nz parameters are specified, d_nz storage elements are 3774 allocated for every row of the local diagonal submatrix, and o_nz 3775 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3776 One way to choose d_nz and o_nz is to use the max nonzerors per local 3777 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3778 In this case, the values of d_nz,o_nz are: 3779 .vb 3780 proc0 : dnz = 2, o_nz = 2 3781 proc1 : dnz = 3, o_nz = 2 3782 proc2 : dnz = 1, o_nz = 4 3783 .ve 3784 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3785 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3786 for proc3. i.e we are using 12+15+10=37 storage locations to store 3787 34 values. 3788 3789 When d_nnz, o_nnz parameters are specified, the storage is specified 3790 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3791 In the above case the values for d_nnz,o_nnz are: 3792 .vb 3793 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3794 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3795 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3796 .ve 3797 Here the space allocated is sum of all the above values i.e 34, and 3798 hence pre-allocation is perfect. 3799 3800 Level: intermediate 3801 3802 .keywords: matrix, aij, compressed row, sparse, parallel 3803 3804 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3805 MPIAIJ, MatCreateMPIAIJWithArrays() 3806 @*/ 3807 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) 3808 { 3809 PetscErrorCode ierr; 3810 PetscMPIInt size; 3811 3812 PetscFunctionBegin; 3813 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3814 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3815 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3816 if (size > 1) { 3817 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3818 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3819 } else { 3820 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3821 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3822 } 3823 PetscFunctionReturn(0); 3824 } 3825 3826 #undef __FUNCT__ 3827 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3828 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3829 { 3830 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3831 3832 PetscFunctionBegin; 3833 if (Ad) *Ad = a->A; 3834 if (Ao) *Ao = a->B; 3835 if (colmap) *colmap = a->garray; 3836 PetscFunctionReturn(0); 3837 } 3838 3839 #undef __FUNCT__ 3840 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3841 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3842 { 3843 PetscErrorCode ierr; 3844 PetscInt i; 3845 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3846 3847 PetscFunctionBegin; 3848 if (coloring->ctype == IS_COLORING_GLOBAL) { 3849 ISColoringValue *allcolors,*colors; 3850 ISColoring ocoloring; 3851 3852 /* set coloring for diagonal portion */ 3853 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3854 3855 /* set coloring for off-diagonal portion */ 3856 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3857 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3858 for (i=0; i<a->B->cmap->n; i++) { 3859 colors[i] = allcolors[a->garray[i]]; 3860 } 3861 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3862 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3863 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3864 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3865 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3866 ISColoringValue *colors; 3867 PetscInt *larray; 3868 ISColoring ocoloring; 3869 3870 /* set coloring for diagonal portion */ 3871 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3872 for (i=0; i<a->A->cmap->n; i++) { 3873 larray[i] = i + A->cmap->rstart; 3874 } 3875 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3876 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3877 for (i=0; i<a->A->cmap->n; i++) { 3878 colors[i] = coloring->colors[larray[i]]; 3879 } 3880 ierr = PetscFree(larray);CHKERRQ(ierr); 3881 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3882 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3883 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3884 3885 /* set coloring for off-diagonal portion */ 3886 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3887 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3888 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3889 for (i=0; i<a->B->cmap->n; i++) { 3890 colors[i] = coloring->colors[larray[i]]; 3891 } 3892 ierr = PetscFree(larray);CHKERRQ(ierr); 3893 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3894 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3895 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3896 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3897 PetscFunctionReturn(0); 3898 } 3899 3900 #undef __FUNCT__ 3901 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3902 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3903 { 3904 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3905 PetscErrorCode ierr; 3906 3907 PetscFunctionBegin; 3908 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3909 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3910 PetscFunctionReturn(0); 3911 } 3912 3913 #undef __FUNCT__ 3914 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3915 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3916 { 3917 PetscErrorCode ierr; 3918 PetscInt m,N,i,rstart,nnz,Ii; 3919 PetscInt *indx; 3920 PetscScalar *values; 3921 3922 PetscFunctionBegin; 3923 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3924 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3925 PetscInt *dnz,*onz,sum,bs,cbs; 3926 3927 if (n == PETSC_DECIDE) { 3928 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3929 } 3930 /* Check sum(n) = N */ 3931 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3932 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3933 3934 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3935 rstart -= m; 3936 3937 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3938 for (i=0; i<m; i++) { 3939 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3940 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3941 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3942 } 3943 3944 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3945 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3946 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3947 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3948 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3949 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3950 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3951 } 3952 3953 /* numeric phase */ 3954 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3955 for (i=0; i<m; i++) { 3956 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3957 Ii = i + rstart; 3958 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3959 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3960 } 3961 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3962 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3963 PetscFunctionReturn(0); 3964 } 3965 3966 #undef __FUNCT__ 3967 #define __FUNCT__ "MatFileSplit" 3968 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3969 { 3970 PetscErrorCode ierr; 3971 PetscMPIInt rank; 3972 PetscInt m,N,i,rstart,nnz; 3973 size_t len; 3974 const PetscInt *indx; 3975 PetscViewer out; 3976 char *name; 3977 Mat B; 3978 const PetscScalar *values; 3979 3980 PetscFunctionBegin; 3981 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3982 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3983 /* Should this be the type of the diagonal block of A? */ 3984 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3985 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3986 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3987 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3988 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3989 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3990 for (i=0; i<m; i++) { 3991 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3992 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3993 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3994 } 3995 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3996 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3997 3998 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3999 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4000 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4001 sprintf(name,"%s.%d",outfile,rank); 4002 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4003 ierr = PetscFree(name);CHKERRQ(ierr); 4004 ierr = MatView(B,out);CHKERRQ(ierr); 4005 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4006 ierr = MatDestroy(&B);CHKERRQ(ierr); 4007 PetscFunctionReturn(0); 4008 } 4009 4010 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4011 #undef __FUNCT__ 4012 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4013 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4014 { 4015 PetscErrorCode ierr; 4016 Mat_Merge_SeqsToMPI *merge; 4017 PetscContainer container; 4018 4019 PetscFunctionBegin; 4020 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4021 if (container) { 4022 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4023 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4024 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4025 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4026 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4027 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4028 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4029 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4030 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4031 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4032 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4033 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4034 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4035 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4036 ierr = PetscFree(merge);CHKERRQ(ierr); 4037 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4038 } 4039 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4040 PetscFunctionReturn(0); 4041 } 4042 4043 #include <../src/mat/utils/freespace.h> 4044 #include <petscbt.h> 4045 4046 #undef __FUNCT__ 4047 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4048 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4049 { 4050 PetscErrorCode ierr; 4051 MPI_Comm comm; 4052 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4053 PetscMPIInt size,rank,taga,*len_s; 4054 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4055 PetscInt proc,m; 4056 PetscInt **buf_ri,**buf_rj; 4057 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4058 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4059 MPI_Request *s_waits,*r_waits; 4060 MPI_Status *status; 4061 MatScalar *aa=a->a; 4062 MatScalar **abuf_r,*ba_i; 4063 Mat_Merge_SeqsToMPI *merge; 4064 PetscContainer container; 4065 4066 PetscFunctionBegin; 4067 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4068 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4069 4070 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4071 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4072 4073 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4074 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4075 4076 bi = merge->bi; 4077 bj = merge->bj; 4078 buf_ri = merge->buf_ri; 4079 buf_rj = merge->buf_rj; 4080 4081 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4082 owners = merge->rowmap->range; 4083 len_s = merge->len_s; 4084 4085 /* send and recv matrix values */ 4086 /*-----------------------------*/ 4087 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4088 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4089 4090 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4091 for (proc=0,k=0; proc<size; proc++) { 4092 if (!len_s[proc]) continue; 4093 i = owners[proc]; 4094 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4095 k++; 4096 } 4097 4098 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4099 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4100 ierr = PetscFree(status);CHKERRQ(ierr); 4101 4102 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4103 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4104 4105 /* insert mat values of mpimat */ 4106 /*----------------------------*/ 4107 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4108 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4109 4110 for (k=0; k<merge->nrecv; k++) { 4111 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4112 nrows = *(buf_ri_k[k]); 4113 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4114 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4115 } 4116 4117 /* set values of ba */ 4118 m = merge->rowmap->n; 4119 for (i=0; i<m; i++) { 4120 arow = owners[rank] + i; 4121 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4122 bnzi = bi[i+1] - bi[i]; 4123 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4124 4125 /* add local non-zero vals of this proc's seqmat into ba */ 4126 anzi = ai[arow+1] - ai[arow]; 4127 aj = a->j + ai[arow]; 4128 aa = a->a + ai[arow]; 4129 nextaj = 0; 4130 for (j=0; nextaj<anzi; j++) { 4131 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4132 ba_i[j] += aa[nextaj++]; 4133 } 4134 } 4135 4136 /* add received vals into ba */ 4137 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4138 /* i-th row */ 4139 if (i == *nextrow[k]) { 4140 anzi = *(nextai[k]+1) - *nextai[k]; 4141 aj = buf_rj[k] + *(nextai[k]); 4142 aa = abuf_r[k] + *(nextai[k]); 4143 nextaj = 0; 4144 for (j=0; nextaj<anzi; j++) { 4145 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4146 ba_i[j] += aa[nextaj++]; 4147 } 4148 } 4149 nextrow[k]++; nextai[k]++; 4150 } 4151 } 4152 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4153 } 4154 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4155 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4156 4157 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4158 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4159 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4160 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4161 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4162 PetscFunctionReturn(0); 4163 } 4164 4165 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4166 4167 #undef __FUNCT__ 4168 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4169 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4170 { 4171 PetscErrorCode ierr; 4172 Mat B_mpi; 4173 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4174 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4175 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4176 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4177 PetscInt len,proc,*dnz,*onz,bs,cbs; 4178 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4179 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4180 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4181 MPI_Status *status; 4182 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4183 PetscBT lnkbt; 4184 Mat_Merge_SeqsToMPI *merge; 4185 PetscContainer container; 4186 4187 PetscFunctionBegin; 4188 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4189 4190 /* make sure it is a PETSc comm */ 4191 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4192 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4193 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4194 4195 ierr = PetscNew(&merge);CHKERRQ(ierr); 4196 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4197 4198 /* determine row ownership */ 4199 /*---------------------------------------------------------*/ 4200 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4201 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4202 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4203 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4204 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4205 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4206 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4207 4208 m = merge->rowmap->n; 4209 owners = merge->rowmap->range; 4210 4211 /* determine the number of messages to send, their lengths */ 4212 /*---------------------------------------------------------*/ 4213 len_s = merge->len_s; 4214 4215 len = 0; /* length of buf_si[] */ 4216 merge->nsend = 0; 4217 for (proc=0; proc<size; proc++) { 4218 len_si[proc] = 0; 4219 if (proc == rank) { 4220 len_s[proc] = 0; 4221 } else { 4222 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4223 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4224 } 4225 if (len_s[proc]) { 4226 merge->nsend++; 4227 nrows = 0; 4228 for (i=owners[proc]; i<owners[proc+1]; i++) { 4229 if (ai[i+1] > ai[i]) nrows++; 4230 } 4231 len_si[proc] = 2*(nrows+1); 4232 len += len_si[proc]; 4233 } 4234 } 4235 4236 /* determine the number and length of messages to receive for ij-structure */ 4237 /*-------------------------------------------------------------------------*/ 4238 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4239 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4240 4241 /* post the Irecv of j-structure */ 4242 /*-------------------------------*/ 4243 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4244 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4245 4246 /* post the Isend of j-structure */ 4247 /*--------------------------------*/ 4248 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4249 4250 for (proc=0, k=0; proc<size; proc++) { 4251 if (!len_s[proc]) continue; 4252 i = owners[proc]; 4253 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4254 k++; 4255 } 4256 4257 /* receives and sends of j-structure are complete */ 4258 /*------------------------------------------------*/ 4259 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4260 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4261 4262 /* send and recv i-structure */ 4263 /*---------------------------*/ 4264 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4265 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4266 4267 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4268 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4269 for (proc=0,k=0; proc<size; proc++) { 4270 if (!len_s[proc]) continue; 4271 /* form outgoing message for i-structure: 4272 buf_si[0]: nrows to be sent 4273 [1:nrows]: row index (global) 4274 [nrows+1:2*nrows+1]: i-structure index 4275 */ 4276 /*-------------------------------------------*/ 4277 nrows = len_si[proc]/2 - 1; 4278 buf_si_i = buf_si + nrows+1; 4279 buf_si[0] = nrows; 4280 buf_si_i[0] = 0; 4281 nrows = 0; 4282 for (i=owners[proc]; i<owners[proc+1]; i++) { 4283 anzi = ai[i+1] - ai[i]; 4284 if (anzi) { 4285 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4286 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4287 nrows++; 4288 } 4289 } 4290 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4291 k++; 4292 buf_si += len_si[proc]; 4293 } 4294 4295 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4296 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4297 4298 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4299 for (i=0; i<merge->nrecv; i++) { 4300 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); 4301 } 4302 4303 ierr = PetscFree(len_si);CHKERRQ(ierr); 4304 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4305 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4306 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4307 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4308 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4309 ierr = PetscFree(status);CHKERRQ(ierr); 4310 4311 /* compute a local seq matrix in each processor */ 4312 /*----------------------------------------------*/ 4313 /* allocate bi array and free space for accumulating nonzero column info */ 4314 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4315 bi[0] = 0; 4316 4317 /* create and initialize a linked list */ 4318 nlnk = N+1; 4319 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4320 4321 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4322 len = ai[owners[rank+1]] - ai[owners[rank]]; 4323 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4324 4325 current_space = free_space; 4326 4327 /* determine symbolic info for each local row */ 4328 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4329 4330 for (k=0; k<merge->nrecv; k++) { 4331 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4332 nrows = *buf_ri_k[k]; 4333 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4334 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4335 } 4336 4337 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4338 len = 0; 4339 for (i=0; i<m; i++) { 4340 bnzi = 0; 4341 /* add local non-zero cols of this proc's seqmat into lnk */ 4342 arow = owners[rank] + i; 4343 anzi = ai[arow+1] - ai[arow]; 4344 aj = a->j + ai[arow]; 4345 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4346 bnzi += nlnk; 4347 /* add received col data into lnk */ 4348 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4349 if (i == *nextrow[k]) { /* i-th row */ 4350 anzi = *(nextai[k]+1) - *nextai[k]; 4351 aj = buf_rj[k] + *nextai[k]; 4352 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4353 bnzi += nlnk; 4354 nextrow[k]++; nextai[k]++; 4355 } 4356 } 4357 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4358 4359 /* if free space is not available, make more free space */ 4360 if (current_space->local_remaining<bnzi) { 4361 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4362 nspacedouble++; 4363 } 4364 /* copy data into free space, then initialize lnk */ 4365 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4366 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4367 4368 current_space->array += bnzi; 4369 current_space->local_used += bnzi; 4370 current_space->local_remaining -= bnzi; 4371 4372 bi[i+1] = bi[i] + bnzi; 4373 } 4374 4375 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4376 4377 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4378 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4379 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4380 4381 /* create symbolic parallel matrix B_mpi */ 4382 /*---------------------------------------*/ 4383 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4384 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4385 if (n==PETSC_DECIDE) { 4386 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4387 } else { 4388 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4389 } 4390 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4391 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4392 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4393 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4394 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4395 4396 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4397 B_mpi->assembled = PETSC_FALSE; 4398 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4399 merge->bi = bi; 4400 merge->bj = bj; 4401 merge->buf_ri = buf_ri; 4402 merge->buf_rj = buf_rj; 4403 merge->coi = NULL; 4404 merge->coj = NULL; 4405 merge->owners_co = NULL; 4406 4407 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4408 4409 /* attach the supporting struct to B_mpi for reuse */ 4410 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4411 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4412 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4413 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4414 *mpimat = B_mpi; 4415 4416 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4417 PetscFunctionReturn(0); 4418 } 4419 4420 #undef __FUNCT__ 4421 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4422 /*@C 4423 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4424 matrices from each processor 4425 4426 Collective on MPI_Comm 4427 4428 Input Parameters: 4429 + comm - the communicators the parallel matrix will live on 4430 . seqmat - the input sequential matrices 4431 . m - number of local rows (or PETSC_DECIDE) 4432 . n - number of local columns (or PETSC_DECIDE) 4433 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4434 4435 Output Parameter: 4436 . mpimat - the parallel matrix generated 4437 4438 Level: advanced 4439 4440 Notes: 4441 The dimensions of the sequential matrix in each processor MUST be the same. 4442 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4443 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4444 @*/ 4445 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4446 { 4447 PetscErrorCode ierr; 4448 PetscMPIInt size; 4449 4450 PetscFunctionBegin; 4451 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4452 if (size == 1) { 4453 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4454 if (scall == MAT_INITIAL_MATRIX) { 4455 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4456 } else { 4457 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4458 } 4459 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4460 PetscFunctionReturn(0); 4461 } 4462 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4463 if (scall == MAT_INITIAL_MATRIX) { 4464 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4465 } 4466 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4467 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4468 PetscFunctionReturn(0); 4469 } 4470 4471 #undef __FUNCT__ 4472 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4473 /*@ 4474 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4475 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4476 with MatGetSize() 4477 4478 Not Collective 4479 4480 Input Parameters: 4481 + A - the matrix 4482 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4483 4484 Output Parameter: 4485 . A_loc - the local sequential matrix generated 4486 4487 Level: developer 4488 4489 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4490 4491 @*/ 4492 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4493 { 4494 PetscErrorCode ierr; 4495 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4496 Mat_SeqAIJ *mat,*a,*b; 4497 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4498 MatScalar *aa,*ba,*cam; 4499 PetscScalar *ca; 4500 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4501 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4502 PetscBool match; 4503 MPI_Comm comm; 4504 PetscMPIInt size; 4505 4506 PetscFunctionBegin; 4507 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4508 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4509 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4510 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4511 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4512 4513 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4514 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4515 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4516 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4517 aa = a->a; ba = b->a; 4518 if (scall == MAT_INITIAL_MATRIX) { 4519 if (size == 1) { 4520 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4521 PetscFunctionReturn(0); 4522 } 4523 4524 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4525 ci[0] = 0; 4526 for (i=0; i<am; i++) { 4527 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4528 } 4529 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4530 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4531 k = 0; 4532 for (i=0; i<am; i++) { 4533 ncols_o = bi[i+1] - bi[i]; 4534 ncols_d = ai[i+1] - ai[i]; 4535 /* off-diagonal portion of A */ 4536 for (jo=0; jo<ncols_o; jo++) { 4537 col = cmap[*bj]; 4538 if (col >= cstart) break; 4539 cj[k] = col; bj++; 4540 ca[k++] = *ba++; 4541 } 4542 /* diagonal portion of A */ 4543 for (j=0; j<ncols_d; j++) { 4544 cj[k] = cstart + *aj++; 4545 ca[k++] = *aa++; 4546 } 4547 /* off-diagonal portion of A */ 4548 for (j=jo; j<ncols_o; j++) { 4549 cj[k] = cmap[*bj++]; 4550 ca[k++] = *ba++; 4551 } 4552 } 4553 /* put together the new matrix */ 4554 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4555 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4556 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4557 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4558 mat->free_a = PETSC_TRUE; 4559 mat->free_ij = PETSC_TRUE; 4560 mat->nonew = 0; 4561 } else if (scall == MAT_REUSE_MATRIX) { 4562 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4563 ci = mat->i; cj = mat->j; cam = mat->a; 4564 for (i=0; i<am; i++) { 4565 /* off-diagonal portion of A */ 4566 ncols_o = bi[i+1] - bi[i]; 4567 for (jo=0; jo<ncols_o; jo++) { 4568 col = cmap[*bj]; 4569 if (col >= cstart) break; 4570 *cam++ = *ba++; bj++; 4571 } 4572 /* diagonal portion of A */ 4573 ncols_d = ai[i+1] - ai[i]; 4574 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4575 /* off-diagonal portion of A */ 4576 for (j=jo; j<ncols_o; j++) { 4577 *cam++ = *ba++; bj++; 4578 } 4579 } 4580 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4581 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4582 PetscFunctionReturn(0); 4583 } 4584 4585 #undef __FUNCT__ 4586 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4587 /*@C 4588 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4589 4590 Not Collective 4591 4592 Input Parameters: 4593 + A - the matrix 4594 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4595 - row, col - index sets of rows and columns to extract (or NULL) 4596 4597 Output Parameter: 4598 . A_loc - the local sequential matrix generated 4599 4600 Level: developer 4601 4602 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4603 4604 @*/ 4605 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4606 { 4607 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4608 PetscErrorCode ierr; 4609 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4610 IS isrowa,iscola; 4611 Mat *aloc; 4612 PetscBool match; 4613 4614 PetscFunctionBegin; 4615 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4616 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4617 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4618 if (!row) { 4619 start = A->rmap->rstart; end = A->rmap->rend; 4620 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4621 } else { 4622 isrowa = *row; 4623 } 4624 if (!col) { 4625 start = A->cmap->rstart; 4626 cmap = a->garray; 4627 nzA = a->A->cmap->n; 4628 nzB = a->B->cmap->n; 4629 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4630 ncols = 0; 4631 for (i=0; i<nzB; i++) { 4632 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4633 else break; 4634 } 4635 imark = i; 4636 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4637 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4638 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4639 } else { 4640 iscola = *col; 4641 } 4642 if (scall != MAT_INITIAL_MATRIX) { 4643 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4644 aloc[0] = *A_loc; 4645 } 4646 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4647 *A_loc = aloc[0]; 4648 ierr = PetscFree(aloc);CHKERRQ(ierr); 4649 if (!row) { 4650 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4651 } 4652 if (!col) { 4653 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4654 } 4655 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4656 PetscFunctionReturn(0); 4657 } 4658 4659 #undef __FUNCT__ 4660 #define __FUNCT__ "MatGetBrowsOfAcols" 4661 /*@C 4662 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4663 4664 Collective on Mat 4665 4666 Input Parameters: 4667 + A,B - the matrices in mpiaij format 4668 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4669 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4670 4671 Output Parameter: 4672 + rowb, colb - index sets of rows and columns of B to extract 4673 - B_seq - the sequential matrix generated 4674 4675 Level: developer 4676 4677 @*/ 4678 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4679 { 4680 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4681 PetscErrorCode ierr; 4682 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4683 IS isrowb,iscolb; 4684 Mat *bseq=NULL; 4685 4686 PetscFunctionBegin; 4687 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4688 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); 4689 } 4690 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4691 4692 if (scall == MAT_INITIAL_MATRIX) { 4693 start = A->cmap->rstart; 4694 cmap = a->garray; 4695 nzA = a->A->cmap->n; 4696 nzB = a->B->cmap->n; 4697 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4698 ncols = 0; 4699 for (i=0; i<nzB; i++) { /* row < local row index */ 4700 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4701 else break; 4702 } 4703 imark = i; 4704 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4705 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4706 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4707 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4708 } else { 4709 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4710 isrowb = *rowb; iscolb = *colb; 4711 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4712 bseq[0] = *B_seq; 4713 } 4714 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4715 *B_seq = bseq[0]; 4716 ierr = PetscFree(bseq);CHKERRQ(ierr); 4717 if (!rowb) { 4718 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4719 } else { 4720 *rowb = isrowb; 4721 } 4722 if (!colb) { 4723 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4724 } else { 4725 *colb = iscolb; 4726 } 4727 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4728 PetscFunctionReturn(0); 4729 } 4730 4731 #undef __FUNCT__ 4732 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4733 /* 4734 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4735 of the OFF-DIAGONAL portion of local A 4736 4737 Collective on Mat 4738 4739 Input Parameters: 4740 + A,B - the matrices in mpiaij format 4741 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4742 4743 Output Parameter: 4744 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4745 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4746 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4747 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4748 4749 Level: developer 4750 4751 */ 4752 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4753 { 4754 VecScatter_MPI_General *gen_to,*gen_from; 4755 PetscErrorCode ierr; 4756 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4757 Mat_SeqAIJ *b_oth; 4758 VecScatter ctx =a->Mvctx; 4759 MPI_Comm comm; 4760 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4761 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4762 PetscScalar *rvalues,*svalues; 4763 MatScalar *b_otha,*bufa,*bufA; 4764 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4765 MPI_Request *rwaits = NULL,*swaits = NULL; 4766 MPI_Status *sstatus,rstatus; 4767 PetscMPIInt jj,size; 4768 PetscInt *cols,sbs,rbs; 4769 PetscScalar *vals; 4770 4771 PetscFunctionBegin; 4772 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4773 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4774 4775 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4776 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); 4777 } 4778 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4779 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4780 4781 gen_to = (VecScatter_MPI_General*)ctx->todata; 4782 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4783 rvalues = gen_from->values; /* holds the length of receiving row */ 4784 svalues = gen_to->values; /* holds the length of sending row */ 4785 nrecvs = gen_from->n; 4786 nsends = gen_to->n; 4787 4788 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4789 srow = gen_to->indices; /* local row index to be sent */ 4790 sstarts = gen_to->starts; 4791 sprocs = gen_to->procs; 4792 sstatus = gen_to->sstatus; 4793 sbs = gen_to->bs; 4794 rstarts = gen_from->starts; 4795 rprocs = gen_from->procs; 4796 rbs = gen_from->bs; 4797 4798 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4799 if (scall == MAT_INITIAL_MATRIX) { 4800 /* i-array */ 4801 /*---------*/ 4802 /* post receives */ 4803 for (i=0; i<nrecvs; i++) { 4804 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4805 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4806 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4807 } 4808 4809 /* pack the outgoing message */ 4810 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4811 4812 sstartsj[0] = 0; 4813 rstartsj[0] = 0; 4814 len = 0; /* total length of j or a array to be sent */ 4815 k = 0; 4816 for (i=0; i<nsends; i++) { 4817 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4818 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4819 for (j=0; j<nrows; j++) { 4820 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4821 for (l=0; l<sbs; l++) { 4822 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4823 4824 rowlen[j*sbs+l] = ncols; 4825 4826 len += ncols; 4827 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4828 } 4829 k++; 4830 } 4831 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4832 4833 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4834 } 4835 /* recvs and sends of i-array are completed */ 4836 i = nrecvs; 4837 while (i--) { 4838 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4839 } 4840 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4841 4842 /* allocate buffers for sending j and a arrays */ 4843 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4844 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4845 4846 /* create i-array of B_oth */ 4847 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4848 4849 b_othi[0] = 0; 4850 len = 0; /* total length of j or a array to be received */ 4851 k = 0; 4852 for (i=0; i<nrecvs; i++) { 4853 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4854 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4855 for (j=0; j<nrows; j++) { 4856 b_othi[k+1] = b_othi[k] + rowlen[j]; 4857 len += rowlen[j]; k++; 4858 } 4859 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4860 } 4861 4862 /* allocate space for j and a arrrays of B_oth */ 4863 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4864 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4865 4866 /* j-array */ 4867 /*---------*/ 4868 /* post receives of j-array */ 4869 for (i=0; i<nrecvs; i++) { 4870 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4871 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4872 } 4873 4874 /* pack the outgoing message j-array */ 4875 k = 0; 4876 for (i=0; i<nsends; i++) { 4877 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4878 bufJ = bufj+sstartsj[i]; 4879 for (j=0; j<nrows; j++) { 4880 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4881 for (ll=0; ll<sbs; ll++) { 4882 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4883 for (l=0; l<ncols; l++) { 4884 *bufJ++ = cols[l]; 4885 } 4886 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4887 } 4888 } 4889 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4890 } 4891 4892 /* recvs and sends of j-array are completed */ 4893 i = nrecvs; 4894 while (i--) { 4895 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4896 } 4897 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4898 } else if (scall == MAT_REUSE_MATRIX) { 4899 sstartsj = *startsj_s; 4900 rstartsj = *startsj_r; 4901 bufa = *bufa_ptr; 4902 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4903 b_otha = b_oth->a; 4904 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4905 4906 /* a-array */ 4907 /*---------*/ 4908 /* post receives of a-array */ 4909 for (i=0; i<nrecvs; i++) { 4910 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4911 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4912 } 4913 4914 /* pack the outgoing message a-array */ 4915 k = 0; 4916 for (i=0; i<nsends; i++) { 4917 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4918 bufA = bufa+sstartsj[i]; 4919 for (j=0; j<nrows; j++) { 4920 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4921 for (ll=0; ll<sbs; ll++) { 4922 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4923 for (l=0; l<ncols; l++) { 4924 *bufA++ = vals[l]; 4925 } 4926 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4927 } 4928 } 4929 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4930 } 4931 /* recvs and sends of a-array are completed */ 4932 i = nrecvs; 4933 while (i--) { 4934 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4935 } 4936 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4937 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4938 4939 if (scall == MAT_INITIAL_MATRIX) { 4940 /* put together the new matrix */ 4941 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4942 4943 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4944 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4945 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4946 b_oth->free_a = PETSC_TRUE; 4947 b_oth->free_ij = PETSC_TRUE; 4948 b_oth->nonew = 0; 4949 4950 ierr = PetscFree(bufj);CHKERRQ(ierr); 4951 if (!startsj_s || !bufa_ptr) { 4952 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4953 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4954 } else { 4955 *startsj_s = sstartsj; 4956 *startsj_r = rstartsj; 4957 *bufa_ptr = bufa; 4958 } 4959 } 4960 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4961 PetscFunctionReturn(0); 4962 } 4963 4964 #undef __FUNCT__ 4965 #define __FUNCT__ "MatGetCommunicationStructs" 4966 /*@C 4967 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4968 4969 Not Collective 4970 4971 Input Parameters: 4972 . A - The matrix in mpiaij format 4973 4974 Output Parameter: 4975 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4976 . colmap - A map from global column index to local index into lvec 4977 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4978 4979 Level: developer 4980 4981 @*/ 4982 #if defined(PETSC_USE_CTABLE) 4983 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4984 #else 4985 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4986 #endif 4987 { 4988 Mat_MPIAIJ *a; 4989 4990 PetscFunctionBegin; 4991 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4992 PetscValidPointer(lvec, 2); 4993 PetscValidPointer(colmap, 3); 4994 PetscValidPointer(multScatter, 4); 4995 a = (Mat_MPIAIJ*) A->data; 4996 if (lvec) *lvec = a->lvec; 4997 if (colmap) *colmap = a->colmap; 4998 if (multScatter) *multScatter = a->Mvctx; 4999 PetscFunctionReturn(0); 5000 } 5001 5002 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5003 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5004 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5005 #if defined(PETSC_HAVE_ELEMENTAL) 5006 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5007 #endif 5008 5009 #undef __FUNCT__ 5010 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5011 /* 5012 Computes (B'*A')' since computing B*A directly is untenable 5013 5014 n p p 5015 ( ) ( ) ( ) 5016 m ( A ) * n ( B ) = m ( C ) 5017 ( ) ( ) ( ) 5018 5019 */ 5020 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5021 { 5022 PetscErrorCode ierr; 5023 Mat At,Bt,Ct; 5024 5025 PetscFunctionBegin; 5026 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5027 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5028 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5029 ierr = MatDestroy(&At);CHKERRQ(ierr); 5030 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5031 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5032 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5033 PetscFunctionReturn(0); 5034 } 5035 5036 #undef __FUNCT__ 5037 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5038 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5039 { 5040 PetscErrorCode ierr; 5041 PetscInt m=A->rmap->n,n=B->cmap->n; 5042 Mat Cmat; 5043 5044 PetscFunctionBegin; 5045 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); 5046 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5047 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5048 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5049 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5050 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5051 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5052 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5053 5054 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5055 5056 *C = Cmat; 5057 PetscFunctionReturn(0); 5058 } 5059 5060 /* ----------------------------------------------------------------*/ 5061 #undef __FUNCT__ 5062 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5063 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5064 { 5065 PetscErrorCode ierr; 5066 5067 PetscFunctionBegin; 5068 if (scall == MAT_INITIAL_MATRIX) { 5069 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5070 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5071 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5072 } 5073 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5074 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5075 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5076 PetscFunctionReturn(0); 5077 } 5078 5079 /*MC 5080 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5081 5082 Options Database Keys: 5083 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5084 5085 Level: beginner 5086 5087 .seealso: MatCreateAIJ() 5088 M*/ 5089 5090 #undef __FUNCT__ 5091 #define __FUNCT__ "MatCreate_MPIAIJ" 5092 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5093 { 5094 Mat_MPIAIJ *b; 5095 PetscErrorCode ierr; 5096 PetscMPIInt size; 5097 5098 PetscFunctionBegin; 5099 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5100 5101 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5102 B->data = (void*)b; 5103 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5104 B->assembled = PETSC_FALSE; 5105 B->insertmode = NOT_SET_VALUES; 5106 b->size = size; 5107 5108 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5109 5110 /* build cache for off array entries formed */ 5111 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5112 5113 b->donotstash = PETSC_FALSE; 5114 b->colmap = 0; 5115 b->garray = 0; 5116 b->roworiented = PETSC_TRUE; 5117 5118 /* stuff used for matrix vector multiply */ 5119 b->lvec = NULL; 5120 b->Mvctx = NULL; 5121 5122 /* stuff for MatGetRow() */ 5123 b->rowindices = 0; 5124 b->rowvalues = 0; 5125 b->getrowactive = PETSC_FALSE; 5126 5127 /* flexible pointer used in CUSP/CUSPARSE classes */ 5128 b->spptr = NULL; 5129 5130 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5132 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5133 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5134 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5135 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5136 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5138 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5139 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5141 #if defined(PETSC_HAVE_ELEMENTAL) 5142 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5143 #endif 5144 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5145 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5146 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5147 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5148 PetscFunctionReturn(0); 5149 } 5150 5151 #undef __FUNCT__ 5152 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5153 /*@C 5154 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5155 and "off-diagonal" part of the matrix in CSR format. 5156 5157 Collective on MPI_Comm 5158 5159 Input Parameters: 5160 + comm - MPI communicator 5161 . m - number of local rows (Cannot be PETSC_DECIDE) 5162 . n - This value should be the same as the local size used in creating the 5163 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5164 calculated if N is given) For square matrices n is almost always m. 5165 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5166 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5167 . i - row indices for "diagonal" portion of matrix 5168 . j - column indices 5169 . a - matrix values 5170 . oi - row indices for "off-diagonal" portion of matrix 5171 . oj - column indices 5172 - oa - matrix values 5173 5174 Output Parameter: 5175 . mat - the matrix 5176 5177 Level: advanced 5178 5179 Notes: 5180 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5181 must free the arrays once the matrix has been destroyed and not before. 5182 5183 The i and j indices are 0 based 5184 5185 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5186 5187 This sets local rows and cannot be used to set off-processor values. 5188 5189 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5190 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5191 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5192 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5193 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5194 communication if it is known that only local entries will be set. 5195 5196 .keywords: matrix, aij, compressed row, sparse, parallel 5197 5198 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5199 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5200 @*/ 5201 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) 5202 { 5203 PetscErrorCode ierr; 5204 Mat_MPIAIJ *maij; 5205 5206 PetscFunctionBegin; 5207 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5208 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5209 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5210 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5211 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5212 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5213 maij = (Mat_MPIAIJ*) (*mat)->data; 5214 5215 (*mat)->preallocated = PETSC_TRUE; 5216 5217 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5218 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5219 5220 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5221 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5222 5223 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5224 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5225 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5226 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5227 5228 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5229 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5230 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5231 PetscFunctionReturn(0); 5232 } 5233 5234 /* 5235 Special version for direct calls from Fortran 5236 */ 5237 #include <petsc-private/fortranimpl.h> 5238 5239 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5240 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5241 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5242 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5243 #endif 5244 5245 /* Change these macros so can be used in void function */ 5246 #undef CHKERRQ 5247 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5248 #undef SETERRQ2 5249 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5250 #undef SETERRQ3 5251 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5252 #undef SETERRQ 5253 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5254 5255 #undef __FUNCT__ 5256 #define __FUNCT__ "matsetvaluesmpiaij_" 5257 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) 5258 { 5259 Mat mat = *mmat; 5260 PetscInt m = *mm, n = *mn; 5261 InsertMode addv = *maddv; 5262 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5263 PetscScalar value; 5264 PetscErrorCode ierr; 5265 5266 MatCheckPreallocated(mat,1); 5267 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5268 5269 #if defined(PETSC_USE_DEBUG) 5270 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5271 #endif 5272 { 5273 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5274 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5275 PetscBool roworiented = aij->roworiented; 5276 5277 /* Some Variables required in the macro */ 5278 Mat A = aij->A; 5279 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5280 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5281 MatScalar *aa = a->a; 5282 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5283 Mat B = aij->B; 5284 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5285 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5286 MatScalar *ba = b->a; 5287 5288 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5289 PetscInt nonew = a->nonew; 5290 MatScalar *ap1,*ap2; 5291 5292 PetscFunctionBegin; 5293 for (i=0; i<m; i++) { 5294 if (im[i] < 0) continue; 5295 #if defined(PETSC_USE_DEBUG) 5296 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); 5297 #endif 5298 if (im[i] >= rstart && im[i] < rend) { 5299 row = im[i] - rstart; 5300 lastcol1 = -1; 5301 rp1 = aj + ai[row]; 5302 ap1 = aa + ai[row]; 5303 rmax1 = aimax[row]; 5304 nrow1 = ailen[row]; 5305 low1 = 0; 5306 high1 = nrow1; 5307 lastcol2 = -1; 5308 rp2 = bj + bi[row]; 5309 ap2 = ba + bi[row]; 5310 rmax2 = bimax[row]; 5311 nrow2 = bilen[row]; 5312 low2 = 0; 5313 high2 = nrow2; 5314 5315 for (j=0; j<n; j++) { 5316 if (roworiented) value = v[i*n+j]; 5317 else value = v[i+j*m]; 5318 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5319 if (in[j] >= cstart && in[j] < cend) { 5320 col = in[j] - cstart; 5321 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5322 } else if (in[j] < 0) continue; 5323 #if defined(PETSC_USE_DEBUG) 5324 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); 5325 #endif 5326 else { 5327 if (mat->was_assembled) { 5328 if (!aij->colmap) { 5329 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5330 } 5331 #if defined(PETSC_USE_CTABLE) 5332 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5333 col--; 5334 #else 5335 col = aij->colmap[in[j]] - 1; 5336 #endif 5337 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5338 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5339 col = in[j]; 5340 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5341 B = aij->B; 5342 b = (Mat_SeqAIJ*)B->data; 5343 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5344 rp2 = bj + bi[row]; 5345 ap2 = ba + bi[row]; 5346 rmax2 = bimax[row]; 5347 nrow2 = bilen[row]; 5348 low2 = 0; 5349 high2 = nrow2; 5350 bm = aij->B->rmap->n; 5351 ba = b->a; 5352 } 5353 } else col = in[j]; 5354 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5355 } 5356 } 5357 } else if (!aij->donotstash) { 5358 if (roworiented) { 5359 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5360 } else { 5361 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5362 } 5363 } 5364 } 5365 } 5366 PetscFunctionReturnVoid(); 5367 } 5368 5369