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