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