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