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