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