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