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; 2607 2608 PetscFunctionBegin; 2609 if (!Y->preallocated) { 2610 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2611 } else if (!aij->nz) { 2612 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2613 } 2614 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2615 PetscFunctionReturn(0); 2616 } 2617 2618 /* -------------------------------------------------------------------*/ 2619 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2620 MatGetRow_MPIAIJ, 2621 MatRestoreRow_MPIAIJ, 2622 MatMult_MPIAIJ, 2623 /* 4*/ MatMultAdd_MPIAIJ, 2624 MatMultTranspose_MPIAIJ, 2625 MatMultTransposeAdd_MPIAIJ, 2626 #if defined(PETSC_HAVE_PBGL) 2627 MatSolve_MPIAIJ, 2628 #else 2629 0, 2630 #endif 2631 0, 2632 0, 2633 /*10*/ 0, 2634 0, 2635 0, 2636 MatSOR_MPIAIJ, 2637 MatTranspose_MPIAIJ, 2638 /*15*/ MatGetInfo_MPIAIJ, 2639 MatEqual_MPIAIJ, 2640 MatGetDiagonal_MPIAIJ, 2641 MatDiagonalScale_MPIAIJ, 2642 MatNorm_MPIAIJ, 2643 /*20*/ MatAssemblyBegin_MPIAIJ, 2644 MatAssemblyEnd_MPIAIJ, 2645 MatSetOption_MPIAIJ, 2646 MatZeroEntries_MPIAIJ, 2647 /*24*/ MatZeroRows_MPIAIJ, 2648 0, 2649 #if defined(PETSC_HAVE_PBGL) 2650 0, 2651 #else 2652 0, 2653 #endif 2654 0, 2655 0, 2656 /*29*/ MatSetUp_MPIAIJ, 2657 #if defined(PETSC_HAVE_PBGL) 2658 0, 2659 #else 2660 0, 2661 #endif 2662 0, 2663 0, 2664 0, 2665 /*34*/ MatDuplicate_MPIAIJ, 2666 0, 2667 0, 2668 0, 2669 0, 2670 /*39*/ MatAXPY_MPIAIJ, 2671 MatGetSubMatrices_MPIAIJ, 2672 MatIncreaseOverlap_MPIAIJ, 2673 MatGetValues_MPIAIJ, 2674 MatCopy_MPIAIJ, 2675 /*44*/ MatGetRowMax_MPIAIJ, 2676 MatScale_MPIAIJ, 2677 MatShift_MPIAIJ, 2678 MatDiagonalSet_MPIAIJ, 2679 MatZeroRowsColumns_MPIAIJ, 2680 /*49*/ MatSetRandom_MPIAIJ, 2681 0, 2682 0, 2683 0, 2684 0, 2685 /*54*/ MatFDColoringCreate_MPIXAIJ, 2686 0, 2687 MatSetUnfactored_MPIAIJ, 2688 MatPermute_MPIAIJ, 2689 0, 2690 /*59*/ MatGetSubMatrix_MPIAIJ, 2691 MatDestroy_MPIAIJ, 2692 MatView_MPIAIJ, 2693 0, 2694 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2695 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2696 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2697 0, 2698 0, 2699 0, 2700 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2701 MatGetRowMinAbs_MPIAIJ, 2702 0, 2703 MatSetColoring_MPIAIJ, 2704 0, 2705 MatSetValuesAdifor_MPIAIJ, 2706 /*75*/ MatFDColoringApply_AIJ, 2707 0, 2708 0, 2709 0, 2710 MatFindZeroDiagonals_MPIAIJ, 2711 /*80*/ 0, 2712 0, 2713 0, 2714 /*83*/ MatLoad_MPIAIJ, 2715 0, 2716 0, 2717 0, 2718 0, 2719 0, 2720 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2721 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2722 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2723 MatPtAP_MPIAIJ_MPIAIJ, 2724 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2725 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2726 0, 2727 0, 2728 0, 2729 0, 2730 /*99*/ 0, 2731 0, 2732 0, 2733 MatConjugate_MPIAIJ, 2734 0, 2735 /*104*/MatSetValuesRow_MPIAIJ, 2736 MatRealPart_MPIAIJ, 2737 MatImaginaryPart_MPIAIJ, 2738 0, 2739 0, 2740 /*109*/0, 2741 0, 2742 MatGetRowMin_MPIAIJ, 2743 0, 2744 0, 2745 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2746 0, 2747 MatGetGhosts_MPIAIJ, 2748 0, 2749 0, 2750 /*119*/0, 2751 0, 2752 0, 2753 0, 2754 MatGetMultiProcBlock_MPIAIJ, 2755 /*124*/MatFindNonzeroRows_MPIAIJ, 2756 MatGetColumnNorms_MPIAIJ, 2757 MatInvertBlockDiagonal_MPIAIJ, 2758 0, 2759 MatGetSubMatricesMPI_MPIAIJ, 2760 /*129*/0, 2761 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2762 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2763 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2764 0, 2765 /*134*/0, 2766 0, 2767 0, 2768 0, 2769 0, 2770 /*139*/0, 2771 0, 2772 0, 2773 MatFDColoringSetUp_MPIXAIJ, 2774 MatFindOffBlockDiagonalEntries_MPIAIJ, 2775 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2776 }; 2777 2778 /* ----------------------------------------------------------------------------------------*/ 2779 2780 #undef __FUNCT__ 2781 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2782 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2783 { 2784 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2785 PetscErrorCode ierr; 2786 2787 PetscFunctionBegin; 2788 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2789 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2790 PetscFunctionReturn(0); 2791 } 2792 2793 #undef __FUNCT__ 2794 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2795 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2796 { 2797 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2798 PetscErrorCode ierr; 2799 2800 PetscFunctionBegin; 2801 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2802 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2803 PetscFunctionReturn(0); 2804 } 2805 2806 #undef __FUNCT__ 2807 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2808 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2809 { 2810 Mat_MPIAIJ *b; 2811 PetscErrorCode ierr; 2812 2813 PetscFunctionBegin; 2814 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2815 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2816 b = (Mat_MPIAIJ*)B->data; 2817 2818 if (!B->preallocated) { 2819 /* Explicitly create 2 MATSEQAIJ matrices. */ 2820 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2821 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2822 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2823 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2824 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2825 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2826 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2827 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2828 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2829 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2830 } 2831 2832 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2833 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2834 B->preallocated = PETSC_TRUE; 2835 PetscFunctionReturn(0); 2836 } 2837 2838 #undef __FUNCT__ 2839 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2840 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2841 { 2842 Mat mat; 2843 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2844 PetscErrorCode ierr; 2845 2846 PetscFunctionBegin; 2847 *newmat = 0; 2848 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2849 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2850 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2851 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2852 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2853 a = (Mat_MPIAIJ*)mat->data; 2854 2855 mat->factortype = matin->factortype; 2856 mat->assembled = PETSC_TRUE; 2857 mat->insertmode = NOT_SET_VALUES; 2858 mat->preallocated = PETSC_TRUE; 2859 2860 a->size = oldmat->size; 2861 a->rank = oldmat->rank; 2862 a->donotstash = oldmat->donotstash; 2863 a->roworiented = oldmat->roworiented; 2864 a->rowindices = 0; 2865 a->rowvalues = 0; 2866 a->getrowactive = PETSC_FALSE; 2867 2868 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2869 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2870 2871 if (oldmat->colmap) { 2872 #if defined(PETSC_USE_CTABLE) 2873 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2874 #else 2875 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2876 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2877 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2878 #endif 2879 } else a->colmap = 0; 2880 if (oldmat->garray) { 2881 PetscInt len; 2882 len = oldmat->B->cmap->n; 2883 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2884 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2885 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2886 } else a->garray = 0; 2887 2888 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2889 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2890 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2891 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2892 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2893 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2894 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2895 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2896 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2897 *newmat = mat; 2898 PetscFunctionReturn(0); 2899 } 2900 2901 2902 2903 #undef __FUNCT__ 2904 #define __FUNCT__ "MatLoad_MPIAIJ" 2905 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2906 { 2907 PetscScalar *vals,*svals; 2908 MPI_Comm comm; 2909 PetscErrorCode ierr; 2910 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2911 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2912 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2913 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2914 PetscInt cend,cstart,n,*rowners; 2915 int fd; 2916 PetscInt bs = newMat->rmap->bs; 2917 2918 PetscFunctionBegin; 2919 /* force binary viewer to load .info file if it has not yet done so */ 2920 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2921 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2922 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2923 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2924 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2925 if (!rank) { 2926 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2927 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2928 } 2929 2930 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2931 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2932 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2933 if (bs < 0) bs = 1; 2934 2935 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2936 M = header[1]; N = header[2]; 2937 2938 /* If global sizes are set, check if they are consistent with that given in the file */ 2939 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); 2940 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); 2941 2942 /* determine ownership of all (block) rows */ 2943 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2944 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2945 else m = newMat->rmap->n; /* Set by user */ 2946 2947 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2948 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2949 2950 /* First process needs enough room for process with most rows */ 2951 if (!rank) { 2952 mmax = rowners[1]; 2953 for (i=2; i<=size; i++) { 2954 mmax = PetscMax(mmax, rowners[i]); 2955 } 2956 } else mmax = -1; /* unused, but compilers complain */ 2957 2958 rowners[0] = 0; 2959 for (i=2; i<=size; i++) { 2960 rowners[i] += rowners[i-1]; 2961 } 2962 rstart = rowners[rank]; 2963 rend = rowners[rank+1]; 2964 2965 /* distribute row lengths to all processors */ 2966 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2967 if (!rank) { 2968 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2969 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2970 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2971 for (j=0; j<m; j++) { 2972 procsnz[0] += ourlens[j]; 2973 } 2974 for (i=1; i<size; i++) { 2975 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2976 /* calculate the number of nonzeros on each processor */ 2977 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2978 procsnz[i] += rowlengths[j]; 2979 } 2980 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2981 } 2982 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2983 } else { 2984 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2985 } 2986 2987 if (!rank) { 2988 /* determine max buffer needed and allocate it */ 2989 maxnz = 0; 2990 for (i=0; i<size; i++) { 2991 maxnz = PetscMax(maxnz,procsnz[i]); 2992 } 2993 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2994 2995 /* read in my part of the matrix column indices */ 2996 nz = procsnz[0]; 2997 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2998 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2999 3000 /* read in every one elses and ship off */ 3001 for (i=1; i<size; i++) { 3002 nz = procsnz[i]; 3003 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3004 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3005 } 3006 ierr = PetscFree(cols);CHKERRQ(ierr); 3007 } else { 3008 /* determine buffer space needed for message */ 3009 nz = 0; 3010 for (i=0; i<m; i++) { 3011 nz += ourlens[i]; 3012 } 3013 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3014 3015 /* receive message of column indices*/ 3016 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3017 } 3018 3019 /* determine column ownership if matrix is not square */ 3020 if (N != M) { 3021 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3022 else n = newMat->cmap->n; 3023 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3024 cstart = cend - n; 3025 } else { 3026 cstart = rstart; 3027 cend = rend; 3028 n = cend - cstart; 3029 } 3030 3031 /* loop over local rows, determining number of off diagonal entries */ 3032 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3033 jj = 0; 3034 for (i=0; i<m; i++) { 3035 for (j=0; j<ourlens[i]; j++) { 3036 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3037 jj++; 3038 } 3039 } 3040 3041 for (i=0; i<m; i++) { 3042 ourlens[i] -= offlens[i]; 3043 } 3044 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3045 3046 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3047 3048 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3049 3050 for (i=0; i<m; i++) { 3051 ourlens[i] += offlens[i]; 3052 } 3053 3054 if (!rank) { 3055 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3056 3057 /* read in my part of the matrix numerical values */ 3058 nz = procsnz[0]; 3059 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3060 3061 /* insert into matrix */ 3062 jj = rstart; 3063 smycols = mycols; 3064 svals = vals; 3065 for (i=0; i<m; i++) { 3066 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3067 smycols += ourlens[i]; 3068 svals += ourlens[i]; 3069 jj++; 3070 } 3071 3072 /* read in other processors and ship out */ 3073 for (i=1; i<size; i++) { 3074 nz = procsnz[i]; 3075 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3076 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3077 } 3078 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3079 } else { 3080 /* receive numeric values */ 3081 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3082 3083 /* receive message of values*/ 3084 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3085 3086 /* insert into matrix */ 3087 jj = rstart; 3088 smycols = mycols; 3089 svals = vals; 3090 for (i=0; i<m; i++) { 3091 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3092 smycols += ourlens[i]; 3093 svals += ourlens[i]; 3094 jj++; 3095 } 3096 } 3097 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3098 ierr = PetscFree(vals);CHKERRQ(ierr); 3099 ierr = PetscFree(mycols);CHKERRQ(ierr); 3100 ierr = PetscFree(rowners);CHKERRQ(ierr); 3101 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3102 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3103 PetscFunctionReturn(0); 3104 } 3105 3106 #undef __FUNCT__ 3107 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3108 /* TODO: Not scalable because of ISAllGather(). */ 3109 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3110 { 3111 PetscErrorCode ierr; 3112 IS iscol_local; 3113 PetscInt csize; 3114 3115 PetscFunctionBegin; 3116 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3117 if (call == MAT_REUSE_MATRIX) { 3118 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3119 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3120 } else { 3121 PetscInt cbs; 3122 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3123 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3124 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3125 } 3126 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3127 if (call == MAT_INITIAL_MATRIX) { 3128 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3129 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3130 } 3131 PetscFunctionReturn(0); 3132 } 3133 3134 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3135 #undef __FUNCT__ 3136 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3137 /* 3138 Not great since it makes two copies of the submatrix, first an SeqAIJ 3139 in local and then by concatenating the local matrices the end result. 3140 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3141 3142 Note: This requires a sequential iscol with all indices. 3143 */ 3144 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3145 { 3146 PetscErrorCode ierr; 3147 PetscMPIInt rank,size; 3148 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3149 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3150 PetscBool allcolumns, colflag; 3151 Mat M,Mreuse; 3152 MatScalar *vwork,*aa; 3153 MPI_Comm comm; 3154 Mat_SeqAIJ *aij; 3155 3156 PetscFunctionBegin; 3157 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3158 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3159 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3160 3161 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3162 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3163 if (colflag && ncol == mat->cmap->N) { 3164 allcolumns = PETSC_TRUE; 3165 } else { 3166 allcolumns = PETSC_FALSE; 3167 } 3168 if (call == MAT_REUSE_MATRIX) { 3169 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3170 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3171 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3172 } else { 3173 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3174 } 3175 3176 /* 3177 m - number of local rows 3178 n - number of columns (same on all processors) 3179 rstart - first row in new global matrix generated 3180 */ 3181 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3182 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3183 if (call == MAT_INITIAL_MATRIX) { 3184 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3185 ii = aij->i; 3186 jj = aij->j; 3187 3188 /* 3189 Determine the number of non-zeros in the diagonal and off-diagonal 3190 portions of the matrix in order to do correct preallocation 3191 */ 3192 3193 /* first get start and end of "diagonal" columns */ 3194 if (csize == PETSC_DECIDE) { 3195 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3196 if (mglobal == n) { /* square matrix */ 3197 nlocal = m; 3198 } else { 3199 nlocal = n/size + ((n % size) > rank); 3200 } 3201 } else { 3202 nlocal = csize; 3203 } 3204 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3205 rstart = rend - nlocal; 3206 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); 3207 3208 /* next, compute all the lengths */ 3209 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3210 olens = dlens + m; 3211 for (i=0; i<m; i++) { 3212 jend = ii[i+1] - ii[i]; 3213 olen = 0; 3214 dlen = 0; 3215 for (j=0; j<jend; j++) { 3216 if (*jj < rstart || *jj >= rend) olen++; 3217 else dlen++; 3218 jj++; 3219 } 3220 olens[i] = olen; 3221 dlens[i] = dlen; 3222 } 3223 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3224 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3225 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3226 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3227 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3228 ierr = PetscFree(dlens);CHKERRQ(ierr); 3229 } else { 3230 PetscInt ml,nl; 3231 3232 M = *newmat; 3233 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3234 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3235 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3236 /* 3237 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3238 rather than the slower MatSetValues(). 3239 */ 3240 M->was_assembled = PETSC_TRUE; 3241 M->assembled = PETSC_FALSE; 3242 } 3243 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3244 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3245 ii = aij->i; 3246 jj = aij->j; 3247 aa = aij->a; 3248 for (i=0; i<m; i++) { 3249 row = rstart + i; 3250 nz = ii[i+1] - ii[i]; 3251 cwork = jj; jj += nz; 3252 vwork = aa; aa += nz; 3253 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3254 } 3255 3256 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3257 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3258 *newmat = M; 3259 3260 /* save submatrix used in processor for next request */ 3261 if (call == MAT_INITIAL_MATRIX) { 3262 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3263 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3264 } 3265 PetscFunctionReturn(0); 3266 } 3267 3268 #undef __FUNCT__ 3269 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3270 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3271 { 3272 PetscInt m,cstart, cend,j,nnz,i,d; 3273 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3274 const PetscInt *JJ; 3275 PetscScalar *values; 3276 PetscErrorCode ierr; 3277 3278 PetscFunctionBegin; 3279 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3280 3281 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3282 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3283 m = B->rmap->n; 3284 cstart = B->cmap->rstart; 3285 cend = B->cmap->rend; 3286 rstart = B->rmap->rstart; 3287 3288 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3289 3290 #if defined(PETSC_USE_DEBUGGING) 3291 for (i=0; i<m; i++) { 3292 nnz = Ii[i+1]- Ii[i]; 3293 JJ = J + Ii[i]; 3294 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3295 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3296 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); 3297 } 3298 #endif 3299 3300 for (i=0; i<m; i++) { 3301 nnz = Ii[i+1]- Ii[i]; 3302 JJ = J + Ii[i]; 3303 nnz_max = PetscMax(nnz_max,nnz); 3304 d = 0; 3305 for (j=0; j<nnz; j++) { 3306 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3307 } 3308 d_nnz[i] = d; 3309 o_nnz[i] = nnz - d; 3310 } 3311 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3312 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3313 3314 if (v) values = (PetscScalar*)v; 3315 else { 3316 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3317 } 3318 3319 for (i=0; i<m; i++) { 3320 ii = i + rstart; 3321 nnz = Ii[i+1]- Ii[i]; 3322 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3323 } 3324 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3325 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3326 3327 if (!v) { 3328 ierr = PetscFree(values);CHKERRQ(ierr); 3329 } 3330 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3331 PetscFunctionReturn(0); 3332 } 3333 3334 #undef __FUNCT__ 3335 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3336 /*@ 3337 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3338 (the default parallel PETSc format). 3339 3340 Collective on MPI_Comm 3341 3342 Input Parameters: 3343 + B - the matrix 3344 . i - the indices into j for the start of each local row (starts with zero) 3345 . j - the column indices for each local row (starts with zero) 3346 - v - optional values in the matrix 3347 3348 Level: developer 3349 3350 Notes: 3351 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3352 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3353 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3354 3355 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3356 3357 The format which is used for the sparse matrix input, is equivalent to a 3358 row-major ordering.. i.e for the following matrix, the input data expected is 3359 as shown: 3360 3361 1 0 0 3362 2 0 3 P0 3363 ------- 3364 4 5 6 P1 3365 3366 Process0 [P0]: rows_owned=[0,1] 3367 i = {0,1,3} [size = nrow+1 = 2+1] 3368 j = {0,0,2} [size = nz = 6] 3369 v = {1,2,3} [size = nz = 6] 3370 3371 Process1 [P1]: rows_owned=[2] 3372 i = {0,3} [size = nrow+1 = 1+1] 3373 j = {0,1,2} [size = nz = 6] 3374 v = {4,5,6} [size = nz = 6] 3375 3376 .keywords: matrix, aij, compressed row, sparse, parallel 3377 3378 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3379 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3380 @*/ 3381 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3382 { 3383 PetscErrorCode ierr; 3384 3385 PetscFunctionBegin; 3386 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3387 PetscFunctionReturn(0); 3388 } 3389 3390 #undef __FUNCT__ 3391 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3392 /*@C 3393 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3394 (the default parallel PETSc format). For good matrix assembly performance 3395 the user should preallocate the matrix storage by setting the parameters 3396 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3397 performance can be increased by more than a factor of 50. 3398 3399 Collective on MPI_Comm 3400 3401 Input Parameters: 3402 + B - the matrix 3403 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3404 (same value is used for all local rows) 3405 . d_nnz - array containing the number of nonzeros in the various rows of the 3406 DIAGONAL portion of the local submatrix (possibly different for each row) 3407 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3408 The size of this array is equal to the number of local rows, i.e 'm'. 3409 For matrices that will be factored, you must leave room for (and set) 3410 the diagonal entry even if it is zero. 3411 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3412 submatrix (same value is used for all local rows). 3413 - o_nnz - array containing the number of nonzeros in the various rows of the 3414 OFF-DIAGONAL portion of the local submatrix (possibly different for 3415 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3416 structure. The size of this array is equal to the number 3417 of local rows, i.e 'm'. 3418 3419 If the *_nnz parameter is given then the *_nz parameter is ignored 3420 3421 The AIJ format (also called the Yale sparse matrix format or 3422 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3423 storage. The stored row and column indices begin with zero. 3424 See Users-Manual: ch_mat for details. 3425 3426 The parallel matrix is partitioned such that the first m0 rows belong to 3427 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3428 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3429 3430 The DIAGONAL portion of the local submatrix of a processor can be defined 3431 as the submatrix which is obtained by extraction the part corresponding to 3432 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3433 first row that belongs to the processor, r2 is the last row belonging to 3434 the this processor, and c1-c2 is range of indices of the local part of a 3435 vector suitable for applying the matrix to. This is an mxn matrix. In the 3436 common case of a square matrix, the row and column ranges are the same and 3437 the DIAGONAL part is also square. The remaining portion of the local 3438 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3439 3440 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3441 3442 You can call MatGetInfo() to get information on how effective the preallocation was; 3443 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3444 You can also run with the option -info and look for messages with the string 3445 malloc in them to see if additional memory allocation was needed. 3446 3447 Example usage: 3448 3449 Consider the following 8x8 matrix with 34 non-zero values, that is 3450 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3451 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3452 as follows: 3453 3454 .vb 3455 1 2 0 | 0 3 0 | 0 4 3456 Proc0 0 5 6 | 7 0 0 | 8 0 3457 9 0 10 | 11 0 0 | 12 0 3458 ------------------------------------- 3459 13 0 14 | 15 16 17 | 0 0 3460 Proc1 0 18 0 | 19 20 21 | 0 0 3461 0 0 0 | 22 23 0 | 24 0 3462 ------------------------------------- 3463 Proc2 25 26 27 | 0 0 28 | 29 0 3464 30 0 0 | 31 32 33 | 0 34 3465 .ve 3466 3467 This can be represented as a collection of submatrices as: 3468 3469 .vb 3470 A B C 3471 D E F 3472 G H I 3473 .ve 3474 3475 Where the submatrices A,B,C are owned by proc0, D,E,F are 3476 owned by proc1, G,H,I are owned by proc2. 3477 3478 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3479 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3480 The 'M','N' parameters are 8,8, and have the same values on all procs. 3481 3482 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3483 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3484 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3485 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3486 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3487 matrix, ans [DF] as another SeqAIJ matrix. 3488 3489 When d_nz, o_nz parameters are specified, d_nz storage elements are 3490 allocated for every row of the local diagonal submatrix, and o_nz 3491 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3492 One way to choose d_nz and o_nz is to use the max nonzerors per local 3493 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3494 In this case, the values of d_nz,o_nz are: 3495 .vb 3496 proc0 : dnz = 2, o_nz = 2 3497 proc1 : dnz = 3, o_nz = 2 3498 proc2 : dnz = 1, o_nz = 4 3499 .ve 3500 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3501 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3502 for proc3. i.e we are using 12+15+10=37 storage locations to store 3503 34 values. 3504 3505 When d_nnz, o_nnz parameters are specified, the storage is specified 3506 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3507 In the above case the values for d_nnz,o_nnz are: 3508 .vb 3509 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3510 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3511 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3512 .ve 3513 Here the space allocated is sum of all the above values i.e 34, and 3514 hence pre-allocation is perfect. 3515 3516 Level: intermediate 3517 3518 .keywords: matrix, aij, compressed row, sparse, parallel 3519 3520 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3521 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3522 @*/ 3523 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3524 { 3525 PetscErrorCode ierr; 3526 3527 PetscFunctionBegin; 3528 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3529 PetscValidType(B,1); 3530 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3531 PetscFunctionReturn(0); 3532 } 3533 3534 #undef __FUNCT__ 3535 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3536 /*@ 3537 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3538 CSR format the local rows. 3539 3540 Collective on MPI_Comm 3541 3542 Input Parameters: 3543 + comm - MPI communicator 3544 . m - number of local rows (Cannot be PETSC_DECIDE) 3545 . n - This value should be the same as the local size used in creating the 3546 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3547 calculated if N is given) For square matrices n is almost always m. 3548 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3549 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3550 . i - row indices 3551 . j - column indices 3552 - a - matrix values 3553 3554 Output Parameter: 3555 . mat - the matrix 3556 3557 Level: intermediate 3558 3559 Notes: 3560 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3561 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3562 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3563 3564 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3565 3566 The format which is used for the sparse matrix input, is equivalent to a 3567 row-major ordering.. i.e for the following matrix, the input data expected is 3568 as shown: 3569 3570 1 0 0 3571 2 0 3 P0 3572 ------- 3573 4 5 6 P1 3574 3575 Process0 [P0]: rows_owned=[0,1] 3576 i = {0,1,3} [size = nrow+1 = 2+1] 3577 j = {0,0,2} [size = nz = 6] 3578 v = {1,2,3} [size = nz = 6] 3579 3580 Process1 [P1]: rows_owned=[2] 3581 i = {0,3} [size = nrow+1 = 1+1] 3582 j = {0,1,2} [size = nz = 6] 3583 v = {4,5,6} [size = nz = 6] 3584 3585 .keywords: matrix, aij, compressed row, sparse, parallel 3586 3587 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3588 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3589 @*/ 3590 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3591 { 3592 PetscErrorCode ierr; 3593 3594 PetscFunctionBegin; 3595 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3596 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3597 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3598 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3599 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3600 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3601 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3602 PetscFunctionReturn(0); 3603 } 3604 3605 #undef __FUNCT__ 3606 #define __FUNCT__ "MatCreateAIJ" 3607 /*@C 3608 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3609 (the default parallel PETSc format). For good matrix assembly performance 3610 the user should preallocate the matrix storage by setting the parameters 3611 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3612 performance can be increased by more than a factor of 50. 3613 3614 Collective on MPI_Comm 3615 3616 Input Parameters: 3617 + comm - MPI communicator 3618 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3619 This value should be the same as the local size used in creating the 3620 y vector for the matrix-vector product y = Ax. 3621 . n - This value should be the same as the local size used in creating the 3622 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3623 calculated if N is given) For square matrices n is almost always m. 3624 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3625 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3626 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3627 (same value is used for all local rows) 3628 . d_nnz - array containing the number of nonzeros in the various rows of the 3629 DIAGONAL portion of the local submatrix (possibly different for each row) 3630 or NULL, if d_nz is used to specify the nonzero structure. 3631 The size of this array is equal to the number of local rows, i.e 'm'. 3632 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3633 submatrix (same value is used for all local rows). 3634 - o_nnz - array containing the number of nonzeros in the various rows of the 3635 OFF-DIAGONAL portion of the local submatrix (possibly different for 3636 each row) or NULL, if o_nz is used to specify the nonzero 3637 structure. The size of this array is equal to the number 3638 of local rows, i.e 'm'. 3639 3640 Output Parameter: 3641 . A - the matrix 3642 3643 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3644 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3645 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3646 3647 Notes: 3648 If the *_nnz parameter is given then the *_nz parameter is ignored 3649 3650 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3651 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3652 storage requirements for this matrix. 3653 3654 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3655 processor than it must be used on all processors that share the object for 3656 that argument. 3657 3658 The user MUST specify either the local or global matrix dimensions 3659 (possibly both). 3660 3661 The parallel matrix is partitioned across processors such that the 3662 first m0 rows belong to process 0, the next m1 rows belong to 3663 process 1, the next m2 rows belong to process 2 etc.. where 3664 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3665 values corresponding to [m x N] submatrix. 3666 3667 The columns are logically partitioned with the n0 columns belonging 3668 to 0th partition, the next n1 columns belonging to the next 3669 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3670 3671 The DIAGONAL portion of the local submatrix on any given processor 3672 is the submatrix corresponding to the rows and columns m,n 3673 corresponding to the given processor. i.e diagonal matrix on 3674 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3675 etc. The remaining portion of the local submatrix [m x (N-n)] 3676 constitute the OFF-DIAGONAL portion. The example below better 3677 illustrates this concept. 3678 3679 For a square global matrix we define each processor's diagonal portion 3680 to be its local rows and the corresponding columns (a square submatrix); 3681 each processor's off-diagonal portion encompasses the remainder of the 3682 local matrix (a rectangular submatrix). 3683 3684 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3685 3686 When calling this routine with a single process communicator, a matrix of 3687 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3688 type of communicator, use the construction mechanism: 3689 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3690 3691 By default, this format uses inodes (identical nodes) when possible. 3692 We search for consecutive rows with the same nonzero structure, thereby 3693 reusing matrix information to achieve increased efficiency. 3694 3695 Options Database Keys: 3696 + -mat_no_inode - Do not use inodes 3697 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3698 - -mat_aij_oneindex - Internally use indexing starting at 1 3699 rather than 0. Note that when calling MatSetValues(), 3700 the user still MUST index entries starting at 0! 3701 3702 3703 Example usage: 3704 3705 Consider the following 8x8 matrix with 34 non-zero values, that is 3706 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3707 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3708 as follows: 3709 3710 .vb 3711 1 2 0 | 0 3 0 | 0 4 3712 Proc0 0 5 6 | 7 0 0 | 8 0 3713 9 0 10 | 11 0 0 | 12 0 3714 ------------------------------------- 3715 13 0 14 | 15 16 17 | 0 0 3716 Proc1 0 18 0 | 19 20 21 | 0 0 3717 0 0 0 | 22 23 0 | 24 0 3718 ------------------------------------- 3719 Proc2 25 26 27 | 0 0 28 | 29 0 3720 30 0 0 | 31 32 33 | 0 34 3721 .ve 3722 3723 This can be represented as a collection of submatrices as: 3724 3725 .vb 3726 A B C 3727 D E F 3728 G H I 3729 .ve 3730 3731 Where the submatrices A,B,C are owned by proc0, D,E,F are 3732 owned by proc1, G,H,I are owned by proc2. 3733 3734 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3735 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3736 The 'M','N' parameters are 8,8, and have the same values on all procs. 3737 3738 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3739 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3740 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3741 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3742 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3743 matrix, ans [DF] as another SeqAIJ matrix. 3744 3745 When d_nz, o_nz parameters are specified, d_nz storage elements are 3746 allocated for every row of the local diagonal submatrix, and o_nz 3747 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3748 One way to choose d_nz and o_nz is to use the max nonzerors per local 3749 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3750 In this case, the values of d_nz,o_nz are: 3751 .vb 3752 proc0 : dnz = 2, o_nz = 2 3753 proc1 : dnz = 3, o_nz = 2 3754 proc2 : dnz = 1, o_nz = 4 3755 .ve 3756 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3757 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3758 for proc3. i.e we are using 12+15+10=37 storage locations to store 3759 34 values. 3760 3761 When d_nnz, o_nnz parameters are specified, the storage is specified 3762 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3763 In the above case the values for d_nnz,o_nnz are: 3764 .vb 3765 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3766 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3767 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3768 .ve 3769 Here the space allocated is sum of all the above values i.e 34, and 3770 hence pre-allocation is perfect. 3771 3772 Level: intermediate 3773 3774 .keywords: matrix, aij, compressed row, sparse, parallel 3775 3776 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3777 MPIAIJ, MatCreateMPIAIJWithArrays() 3778 @*/ 3779 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) 3780 { 3781 PetscErrorCode ierr; 3782 PetscMPIInt size; 3783 3784 PetscFunctionBegin; 3785 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3786 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3787 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3788 if (size > 1) { 3789 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3790 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3791 } else { 3792 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3793 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3794 } 3795 PetscFunctionReturn(0); 3796 } 3797 3798 #undef __FUNCT__ 3799 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3800 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3801 { 3802 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3803 3804 PetscFunctionBegin; 3805 if (Ad) *Ad = a->A; 3806 if (Ao) *Ao = a->B; 3807 if (colmap) *colmap = a->garray; 3808 PetscFunctionReturn(0); 3809 } 3810 3811 #undef __FUNCT__ 3812 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3813 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3814 { 3815 PetscErrorCode ierr; 3816 PetscInt i; 3817 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3818 3819 PetscFunctionBegin; 3820 if (coloring->ctype == IS_COLORING_GLOBAL) { 3821 ISColoringValue *allcolors,*colors; 3822 ISColoring ocoloring; 3823 3824 /* set coloring for diagonal portion */ 3825 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3826 3827 /* set coloring for off-diagonal portion */ 3828 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3829 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3830 for (i=0; i<a->B->cmap->n; i++) { 3831 colors[i] = allcolors[a->garray[i]]; 3832 } 3833 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3834 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3835 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3836 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3837 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3838 ISColoringValue *colors; 3839 PetscInt *larray; 3840 ISColoring ocoloring; 3841 3842 /* set coloring for diagonal portion */ 3843 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3844 for (i=0; i<a->A->cmap->n; i++) { 3845 larray[i] = i + A->cmap->rstart; 3846 } 3847 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3848 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3849 for (i=0; i<a->A->cmap->n; i++) { 3850 colors[i] = coloring->colors[larray[i]]; 3851 } 3852 ierr = PetscFree(larray);CHKERRQ(ierr); 3853 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3854 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3855 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3856 3857 /* set coloring for off-diagonal portion */ 3858 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3859 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3860 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3861 for (i=0; i<a->B->cmap->n; i++) { 3862 colors[i] = coloring->colors[larray[i]]; 3863 } 3864 ierr = PetscFree(larray);CHKERRQ(ierr); 3865 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3866 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3867 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3868 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3869 PetscFunctionReturn(0); 3870 } 3871 3872 #undef __FUNCT__ 3873 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3874 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3875 { 3876 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3877 PetscErrorCode ierr; 3878 3879 PetscFunctionBegin; 3880 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3881 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3882 PetscFunctionReturn(0); 3883 } 3884 3885 #undef __FUNCT__ 3886 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3887 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3888 { 3889 PetscErrorCode ierr; 3890 PetscInt m,N,i,rstart,nnz,Ii; 3891 PetscInt *indx; 3892 PetscScalar *values; 3893 3894 PetscFunctionBegin; 3895 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3896 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3897 PetscInt *dnz,*onz,sum,bs,cbs; 3898 3899 if (n == PETSC_DECIDE) { 3900 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3901 } 3902 /* Check sum(n) = N */ 3903 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3904 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3905 3906 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3907 rstart -= m; 3908 3909 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3910 for (i=0; i<m; i++) { 3911 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3912 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3913 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3914 } 3915 3916 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3917 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3918 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3919 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3920 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3921 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3922 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3923 } 3924 3925 /* numeric phase */ 3926 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3927 for (i=0; i<m; i++) { 3928 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3929 Ii = i + rstart; 3930 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3931 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3932 } 3933 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3934 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3935 PetscFunctionReturn(0); 3936 } 3937 3938 #undef __FUNCT__ 3939 #define __FUNCT__ "MatFileSplit" 3940 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3941 { 3942 PetscErrorCode ierr; 3943 PetscMPIInt rank; 3944 PetscInt m,N,i,rstart,nnz; 3945 size_t len; 3946 const PetscInt *indx; 3947 PetscViewer out; 3948 char *name; 3949 Mat B; 3950 const PetscScalar *values; 3951 3952 PetscFunctionBegin; 3953 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3954 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3955 /* Should this be the type of the diagonal block of A? */ 3956 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3957 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3958 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3959 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3960 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3961 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3962 for (i=0; i<m; i++) { 3963 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3964 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3965 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3966 } 3967 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3968 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3969 3970 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3971 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3972 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3973 sprintf(name,"%s.%d",outfile,rank); 3974 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3975 ierr = PetscFree(name);CHKERRQ(ierr); 3976 ierr = MatView(B,out);CHKERRQ(ierr); 3977 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3978 ierr = MatDestroy(&B);CHKERRQ(ierr); 3979 PetscFunctionReturn(0); 3980 } 3981 3982 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3983 #undef __FUNCT__ 3984 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3985 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3986 { 3987 PetscErrorCode ierr; 3988 Mat_Merge_SeqsToMPI *merge; 3989 PetscContainer container; 3990 3991 PetscFunctionBegin; 3992 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3993 if (container) { 3994 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3995 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3996 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3997 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3998 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3999 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4000 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4001 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4002 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4003 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4004 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4005 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4006 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4007 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4008 ierr = PetscFree(merge);CHKERRQ(ierr); 4009 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4010 } 4011 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4012 PetscFunctionReturn(0); 4013 } 4014 4015 #include <../src/mat/utils/freespace.h> 4016 #include <petscbt.h> 4017 4018 #undef __FUNCT__ 4019 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4020 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4021 { 4022 PetscErrorCode ierr; 4023 MPI_Comm comm; 4024 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4025 PetscMPIInt size,rank,taga,*len_s; 4026 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4027 PetscInt proc,m; 4028 PetscInt **buf_ri,**buf_rj; 4029 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4030 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4031 MPI_Request *s_waits,*r_waits; 4032 MPI_Status *status; 4033 MatScalar *aa=a->a; 4034 MatScalar **abuf_r,*ba_i; 4035 Mat_Merge_SeqsToMPI *merge; 4036 PetscContainer container; 4037 4038 PetscFunctionBegin; 4039 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4040 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4041 4042 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4043 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4044 4045 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4046 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4047 4048 bi = merge->bi; 4049 bj = merge->bj; 4050 buf_ri = merge->buf_ri; 4051 buf_rj = merge->buf_rj; 4052 4053 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4054 owners = merge->rowmap->range; 4055 len_s = merge->len_s; 4056 4057 /* send and recv matrix values */ 4058 /*-----------------------------*/ 4059 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4060 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4061 4062 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4063 for (proc=0,k=0; proc<size; proc++) { 4064 if (!len_s[proc]) continue; 4065 i = owners[proc]; 4066 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4067 k++; 4068 } 4069 4070 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4071 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4072 ierr = PetscFree(status);CHKERRQ(ierr); 4073 4074 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4075 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4076 4077 /* insert mat values of mpimat */ 4078 /*----------------------------*/ 4079 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4080 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4081 4082 for (k=0; k<merge->nrecv; k++) { 4083 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4084 nrows = *(buf_ri_k[k]); 4085 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4086 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4087 } 4088 4089 /* set values of ba */ 4090 m = merge->rowmap->n; 4091 for (i=0; i<m; i++) { 4092 arow = owners[rank] + i; 4093 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4094 bnzi = bi[i+1] - bi[i]; 4095 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4096 4097 /* add local non-zero vals of this proc's seqmat into ba */ 4098 anzi = ai[arow+1] - ai[arow]; 4099 aj = a->j + ai[arow]; 4100 aa = a->a + ai[arow]; 4101 nextaj = 0; 4102 for (j=0; nextaj<anzi; j++) { 4103 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4104 ba_i[j] += aa[nextaj++]; 4105 } 4106 } 4107 4108 /* add received vals into ba */ 4109 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4110 /* i-th row */ 4111 if (i == *nextrow[k]) { 4112 anzi = *(nextai[k]+1) - *nextai[k]; 4113 aj = buf_rj[k] + *(nextai[k]); 4114 aa = abuf_r[k] + *(nextai[k]); 4115 nextaj = 0; 4116 for (j=0; nextaj<anzi; j++) { 4117 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4118 ba_i[j] += aa[nextaj++]; 4119 } 4120 } 4121 nextrow[k]++; nextai[k]++; 4122 } 4123 } 4124 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4125 } 4126 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4127 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4128 4129 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4130 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4131 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4132 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4133 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4134 PetscFunctionReturn(0); 4135 } 4136 4137 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4138 4139 #undef __FUNCT__ 4140 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4141 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4142 { 4143 PetscErrorCode ierr; 4144 Mat B_mpi; 4145 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4146 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4147 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4148 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4149 PetscInt len,proc,*dnz,*onz,bs,cbs; 4150 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4151 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4152 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4153 MPI_Status *status; 4154 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4155 PetscBT lnkbt; 4156 Mat_Merge_SeqsToMPI *merge; 4157 PetscContainer container; 4158 4159 PetscFunctionBegin; 4160 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4161 4162 /* make sure it is a PETSc comm */ 4163 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4164 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4165 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4166 4167 ierr = PetscNew(&merge);CHKERRQ(ierr); 4168 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4169 4170 /* determine row ownership */ 4171 /*---------------------------------------------------------*/ 4172 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4173 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4174 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4175 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4176 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4177 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4178 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4179 4180 m = merge->rowmap->n; 4181 owners = merge->rowmap->range; 4182 4183 /* determine the number of messages to send, their lengths */ 4184 /*---------------------------------------------------------*/ 4185 len_s = merge->len_s; 4186 4187 len = 0; /* length of buf_si[] */ 4188 merge->nsend = 0; 4189 for (proc=0; proc<size; proc++) { 4190 len_si[proc] = 0; 4191 if (proc == rank) { 4192 len_s[proc] = 0; 4193 } else { 4194 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4195 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4196 } 4197 if (len_s[proc]) { 4198 merge->nsend++; 4199 nrows = 0; 4200 for (i=owners[proc]; i<owners[proc+1]; i++) { 4201 if (ai[i+1] > ai[i]) nrows++; 4202 } 4203 len_si[proc] = 2*(nrows+1); 4204 len += len_si[proc]; 4205 } 4206 } 4207 4208 /* determine the number and length of messages to receive for ij-structure */ 4209 /*-------------------------------------------------------------------------*/ 4210 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4211 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4212 4213 /* post the Irecv of j-structure */ 4214 /*-------------------------------*/ 4215 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4216 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4217 4218 /* post the Isend of j-structure */ 4219 /*--------------------------------*/ 4220 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4221 4222 for (proc=0, k=0; proc<size; proc++) { 4223 if (!len_s[proc]) continue; 4224 i = owners[proc]; 4225 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4226 k++; 4227 } 4228 4229 /* receives and sends of j-structure are complete */ 4230 /*------------------------------------------------*/ 4231 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4232 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4233 4234 /* send and recv i-structure */ 4235 /*---------------------------*/ 4236 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4237 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4238 4239 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4240 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4241 for (proc=0,k=0; proc<size; proc++) { 4242 if (!len_s[proc]) continue; 4243 /* form outgoing message for i-structure: 4244 buf_si[0]: nrows to be sent 4245 [1:nrows]: row index (global) 4246 [nrows+1:2*nrows+1]: i-structure index 4247 */ 4248 /*-------------------------------------------*/ 4249 nrows = len_si[proc]/2 - 1; 4250 buf_si_i = buf_si + nrows+1; 4251 buf_si[0] = nrows; 4252 buf_si_i[0] = 0; 4253 nrows = 0; 4254 for (i=owners[proc]; i<owners[proc+1]; i++) { 4255 anzi = ai[i+1] - ai[i]; 4256 if (anzi) { 4257 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4258 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4259 nrows++; 4260 } 4261 } 4262 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4263 k++; 4264 buf_si += len_si[proc]; 4265 } 4266 4267 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4268 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4269 4270 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4271 for (i=0; i<merge->nrecv; i++) { 4272 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); 4273 } 4274 4275 ierr = PetscFree(len_si);CHKERRQ(ierr); 4276 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4277 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4278 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4279 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4280 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4281 ierr = PetscFree(status);CHKERRQ(ierr); 4282 4283 /* compute a local seq matrix in each processor */ 4284 /*----------------------------------------------*/ 4285 /* allocate bi array and free space for accumulating nonzero column info */ 4286 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4287 bi[0] = 0; 4288 4289 /* create and initialize a linked list */ 4290 nlnk = N+1; 4291 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4292 4293 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4294 len = ai[owners[rank+1]] - ai[owners[rank]]; 4295 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4296 4297 current_space = free_space; 4298 4299 /* determine symbolic info for each local row */ 4300 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4301 4302 for (k=0; k<merge->nrecv; k++) { 4303 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4304 nrows = *buf_ri_k[k]; 4305 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4306 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4307 } 4308 4309 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4310 len = 0; 4311 for (i=0; i<m; i++) { 4312 bnzi = 0; 4313 /* add local non-zero cols of this proc's seqmat into lnk */ 4314 arow = owners[rank] + i; 4315 anzi = ai[arow+1] - ai[arow]; 4316 aj = a->j + ai[arow]; 4317 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4318 bnzi += nlnk; 4319 /* add received col data into lnk */ 4320 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4321 if (i == *nextrow[k]) { /* i-th row */ 4322 anzi = *(nextai[k]+1) - *nextai[k]; 4323 aj = buf_rj[k] + *nextai[k]; 4324 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4325 bnzi += nlnk; 4326 nextrow[k]++; nextai[k]++; 4327 } 4328 } 4329 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4330 4331 /* if free space is not available, make more free space */ 4332 if (current_space->local_remaining<bnzi) { 4333 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4334 nspacedouble++; 4335 } 4336 /* copy data into free space, then initialize lnk */ 4337 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4338 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4339 4340 current_space->array += bnzi; 4341 current_space->local_used += bnzi; 4342 current_space->local_remaining -= bnzi; 4343 4344 bi[i+1] = bi[i] + bnzi; 4345 } 4346 4347 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4348 4349 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4350 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4351 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4352 4353 /* create symbolic parallel matrix B_mpi */ 4354 /*---------------------------------------*/ 4355 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4356 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4357 if (n==PETSC_DECIDE) { 4358 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4359 } else { 4360 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4361 } 4362 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4363 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4364 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4365 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4366 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4367 4368 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4369 B_mpi->assembled = PETSC_FALSE; 4370 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4371 merge->bi = bi; 4372 merge->bj = bj; 4373 merge->buf_ri = buf_ri; 4374 merge->buf_rj = buf_rj; 4375 merge->coi = NULL; 4376 merge->coj = NULL; 4377 merge->owners_co = NULL; 4378 4379 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4380 4381 /* attach the supporting struct to B_mpi for reuse */ 4382 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4383 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4384 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4385 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4386 *mpimat = B_mpi; 4387 4388 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4389 PetscFunctionReturn(0); 4390 } 4391 4392 #undef __FUNCT__ 4393 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4394 /*@C 4395 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4396 matrices from each processor 4397 4398 Collective on MPI_Comm 4399 4400 Input Parameters: 4401 + comm - the communicators the parallel matrix will live on 4402 . seqmat - the input sequential matrices 4403 . m - number of local rows (or PETSC_DECIDE) 4404 . n - number of local columns (or PETSC_DECIDE) 4405 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4406 4407 Output Parameter: 4408 . mpimat - the parallel matrix generated 4409 4410 Level: advanced 4411 4412 Notes: 4413 The dimensions of the sequential matrix in each processor MUST be the same. 4414 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4415 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4416 @*/ 4417 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4418 { 4419 PetscErrorCode ierr; 4420 PetscMPIInt size; 4421 4422 PetscFunctionBegin; 4423 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4424 if (size == 1) { 4425 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4426 if (scall == MAT_INITIAL_MATRIX) { 4427 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4428 } else { 4429 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4430 } 4431 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4432 PetscFunctionReturn(0); 4433 } 4434 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4435 if (scall == MAT_INITIAL_MATRIX) { 4436 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4437 } 4438 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4439 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4440 PetscFunctionReturn(0); 4441 } 4442 4443 #undef __FUNCT__ 4444 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4445 /*@ 4446 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4447 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4448 with MatGetSize() 4449 4450 Not Collective 4451 4452 Input Parameters: 4453 + A - the matrix 4454 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4455 4456 Output Parameter: 4457 . A_loc - the local sequential matrix generated 4458 4459 Level: developer 4460 4461 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4462 4463 @*/ 4464 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4465 { 4466 PetscErrorCode ierr; 4467 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4468 Mat_SeqAIJ *mat,*a,*b; 4469 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4470 MatScalar *aa,*ba,*cam; 4471 PetscScalar *ca; 4472 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4473 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4474 PetscBool match; 4475 MPI_Comm comm; 4476 PetscMPIInt size; 4477 4478 PetscFunctionBegin; 4479 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4480 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4481 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4482 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4483 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4484 4485 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4486 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4487 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4488 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4489 aa = a->a; ba = b->a; 4490 if (scall == MAT_INITIAL_MATRIX) { 4491 if (size == 1) { 4492 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4493 PetscFunctionReturn(0); 4494 } 4495 4496 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4497 ci[0] = 0; 4498 for (i=0; i<am; i++) { 4499 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4500 } 4501 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4502 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4503 k = 0; 4504 for (i=0; i<am; i++) { 4505 ncols_o = bi[i+1] - bi[i]; 4506 ncols_d = ai[i+1] - ai[i]; 4507 /* off-diagonal portion of A */ 4508 for (jo=0; jo<ncols_o; jo++) { 4509 col = cmap[*bj]; 4510 if (col >= cstart) break; 4511 cj[k] = col; bj++; 4512 ca[k++] = *ba++; 4513 } 4514 /* diagonal portion of A */ 4515 for (j=0; j<ncols_d; j++) { 4516 cj[k] = cstart + *aj++; 4517 ca[k++] = *aa++; 4518 } 4519 /* off-diagonal portion of A */ 4520 for (j=jo; j<ncols_o; j++) { 4521 cj[k] = cmap[*bj++]; 4522 ca[k++] = *ba++; 4523 } 4524 } 4525 /* put together the new matrix */ 4526 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4527 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4528 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4529 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4530 mat->free_a = PETSC_TRUE; 4531 mat->free_ij = PETSC_TRUE; 4532 mat->nonew = 0; 4533 } else if (scall == MAT_REUSE_MATRIX) { 4534 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4535 ci = mat->i; cj = mat->j; cam = mat->a; 4536 for (i=0; i<am; i++) { 4537 /* off-diagonal portion of A */ 4538 ncols_o = bi[i+1] - bi[i]; 4539 for (jo=0; jo<ncols_o; jo++) { 4540 col = cmap[*bj]; 4541 if (col >= cstart) break; 4542 *cam++ = *ba++; bj++; 4543 } 4544 /* diagonal portion of A */ 4545 ncols_d = ai[i+1] - ai[i]; 4546 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4547 /* off-diagonal portion of A */ 4548 for (j=jo; j<ncols_o; j++) { 4549 *cam++ = *ba++; bj++; 4550 } 4551 } 4552 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4553 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4554 PetscFunctionReturn(0); 4555 } 4556 4557 #undef __FUNCT__ 4558 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4559 /*@C 4560 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4561 4562 Not Collective 4563 4564 Input Parameters: 4565 + A - the matrix 4566 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4567 - row, col - index sets of rows and columns to extract (or NULL) 4568 4569 Output Parameter: 4570 . A_loc - the local sequential matrix generated 4571 4572 Level: developer 4573 4574 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4575 4576 @*/ 4577 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4578 { 4579 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4580 PetscErrorCode ierr; 4581 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4582 IS isrowa,iscola; 4583 Mat *aloc; 4584 PetscBool match; 4585 4586 PetscFunctionBegin; 4587 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4588 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4589 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4590 if (!row) { 4591 start = A->rmap->rstart; end = A->rmap->rend; 4592 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4593 } else { 4594 isrowa = *row; 4595 } 4596 if (!col) { 4597 start = A->cmap->rstart; 4598 cmap = a->garray; 4599 nzA = a->A->cmap->n; 4600 nzB = a->B->cmap->n; 4601 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4602 ncols = 0; 4603 for (i=0; i<nzB; i++) { 4604 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4605 else break; 4606 } 4607 imark = i; 4608 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4609 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4610 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4611 } else { 4612 iscola = *col; 4613 } 4614 if (scall != MAT_INITIAL_MATRIX) { 4615 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4616 aloc[0] = *A_loc; 4617 } 4618 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4619 *A_loc = aloc[0]; 4620 ierr = PetscFree(aloc);CHKERRQ(ierr); 4621 if (!row) { 4622 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4623 } 4624 if (!col) { 4625 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4626 } 4627 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4628 PetscFunctionReturn(0); 4629 } 4630 4631 #undef __FUNCT__ 4632 #define __FUNCT__ "MatGetBrowsOfAcols" 4633 /*@C 4634 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4635 4636 Collective on Mat 4637 4638 Input Parameters: 4639 + A,B - the matrices in mpiaij format 4640 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4641 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4642 4643 Output Parameter: 4644 + rowb, colb - index sets of rows and columns of B to extract 4645 - B_seq - the sequential matrix generated 4646 4647 Level: developer 4648 4649 @*/ 4650 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4651 { 4652 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4653 PetscErrorCode ierr; 4654 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4655 IS isrowb,iscolb; 4656 Mat *bseq=NULL; 4657 4658 PetscFunctionBegin; 4659 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4660 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); 4661 } 4662 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4663 4664 if (scall == MAT_INITIAL_MATRIX) { 4665 start = A->cmap->rstart; 4666 cmap = a->garray; 4667 nzA = a->A->cmap->n; 4668 nzB = a->B->cmap->n; 4669 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4670 ncols = 0; 4671 for (i=0; i<nzB; i++) { /* row < local row index */ 4672 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4673 else break; 4674 } 4675 imark = i; 4676 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4677 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4678 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4679 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4680 } else { 4681 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4682 isrowb = *rowb; iscolb = *colb; 4683 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4684 bseq[0] = *B_seq; 4685 } 4686 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4687 *B_seq = bseq[0]; 4688 ierr = PetscFree(bseq);CHKERRQ(ierr); 4689 if (!rowb) { 4690 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4691 } else { 4692 *rowb = isrowb; 4693 } 4694 if (!colb) { 4695 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4696 } else { 4697 *colb = iscolb; 4698 } 4699 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4700 PetscFunctionReturn(0); 4701 } 4702 4703 #undef __FUNCT__ 4704 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4705 /* 4706 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4707 of the OFF-DIAGONAL portion of local A 4708 4709 Collective on Mat 4710 4711 Input Parameters: 4712 + A,B - the matrices in mpiaij format 4713 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4714 4715 Output Parameter: 4716 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4717 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4718 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4719 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4720 4721 Level: developer 4722 4723 */ 4724 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4725 { 4726 VecScatter_MPI_General *gen_to,*gen_from; 4727 PetscErrorCode ierr; 4728 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4729 Mat_SeqAIJ *b_oth; 4730 VecScatter ctx =a->Mvctx; 4731 MPI_Comm comm; 4732 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4733 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4734 PetscScalar *rvalues,*svalues; 4735 MatScalar *b_otha,*bufa,*bufA; 4736 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4737 MPI_Request *rwaits = NULL,*swaits = NULL; 4738 MPI_Status *sstatus,rstatus; 4739 PetscMPIInt jj,size; 4740 PetscInt *cols,sbs,rbs; 4741 PetscScalar *vals; 4742 4743 PetscFunctionBegin; 4744 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4745 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4746 4747 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4748 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); 4749 } 4750 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4751 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4752 4753 gen_to = (VecScatter_MPI_General*)ctx->todata; 4754 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4755 rvalues = gen_from->values; /* holds the length of receiving row */ 4756 svalues = gen_to->values; /* holds the length of sending row */ 4757 nrecvs = gen_from->n; 4758 nsends = gen_to->n; 4759 4760 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4761 srow = gen_to->indices; /* local row index to be sent */ 4762 sstarts = gen_to->starts; 4763 sprocs = gen_to->procs; 4764 sstatus = gen_to->sstatus; 4765 sbs = gen_to->bs; 4766 rstarts = gen_from->starts; 4767 rprocs = gen_from->procs; 4768 rbs = gen_from->bs; 4769 4770 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4771 if (scall == MAT_INITIAL_MATRIX) { 4772 /* i-array */ 4773 /*---------*/ 4774 /* post receives */ 4775 for (i=0; i<nrecvs; i++) { 4776 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4777 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4778 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4779 } 4780 4781 /* pack the outgoing message */ 4782 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4783 4784 sstartsj[0] = 0; 4785 rstartsj[0] = 0; 4786 len = 0; /* total length of j or a array to be sent */ 4787 k = 0; 4788 for (i=0; i<nsends; i++) { 4789 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4790 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4791 for (j=0; j<nrows; j++) { 4792 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4793 for (l=0; l<sbs; l++) { 4794 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4795 4796 rowlen[j*sbs+l] = ncols; 4797 4798 len += ncols; 4799 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4800 } 4801 k++; 4802 } 4803 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4804 4805 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4806 } 4807 /* recvs and sends of i-array are completed */ 4808 i = nrecvs; 4809 while (i--) { 4810 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4811 } 4812 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4813 4814 /* allocate buffers for sending j and a arrays */ 4815 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4816 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4817 4818 /* create i-array of B_oth */ 4819 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4820 4821 b_othi[0] = 0; 4822 len = 0; /* total length of j or a array to be received */ 4823 k = 0; 4824 for (i=0; i<nrecvs; i++) { 4825 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4826 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4827 for (j=0; j<nrows; j++) { 4828 b_othi[k+1] = b_othi[k] + rowlen[j]; 4829 len += rowlen[j]; k++; 4830 } 4831 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4832 } 4833 4834 /* allocate space for j and a arrrays of B_oth */ 4835 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4836 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4837 4838 /* j-array */ 4839 /*---------*/ 4840 /* post receives of j-array */ 4841 for (i=0; i<nrecvs; i++) { 4842 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4843 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4844 } 4845 4846 /* pack the outgoing message j-array */ 4847 k = 0; 4848 for (i=0; i<nsends; i++) { 4849 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4850 bufJ = bufj+sstartsj[i]; 4851 for (j=0; j<nrows; j++) { 4852 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4853 for (ll=0; ll<sbs; ll++) { 4854 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4855 for (l=0; l<ncols; l++) { 4856 *bufJ++ = cols[l]; 4857 } 4858 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4859 } 4860 } 4861 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4862 } 4863 4864 /* recvs and sends of j-array are completed */ 4865 i = nrecvs; 4866 while (i--) { 4867 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4868 } 4869 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4870 } else if (scall == MAT_REUSE_MATRIX) { 4871 sstartsj = *startsj_s; 4872 rstartsj = *startsj_r; 4873 bufa = *bufa_ptr; 4874 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4875 b_otha = b_oth->a; 4876 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4877 4878 /* a-array */ 4879 /*---------*/ 4880 /* post receives of a-array */ 4881 for (i=0; i<nrecvs; i++) { 4882 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4883 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4884 } 4885 4886 /* pack the outgoing message a-array */ 4887 k = 0; 4888 for (i=0; i<nsends; i++) { 4889 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4890 bufA = bufa+sstartsj[i]; 4891 for (j=0; j<nrows; j++) { 4892 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4893 for (ll=0; ll<sbs; ll++) { 4894 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4895 for (l=0; l<ncols; l++) { 4896 *bufA++ = vals[l]; 4897 } 4898 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4899 } 4900 } 4901 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4902 } 4903 /* recvs and sends of a-array are completed */ 4904 i = nrecvs; 4905 while (i--) { 4906 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4907 } 4908 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4909 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4910 4911 if (scall == MAT_INITIAL_MATRIX) { 4912 /* put together the new matrix */ 4913 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4914 4915 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4916 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4917 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4918 b_oth->free_a = PETSC_TRUE; 4919 b_oth->free_ij = PETSC_TRUE; 4920 b_oth->nonew = 0; 4921 4922 ierr = PetscFree(bufj);CHKERRQ(ierr); 4923 if (!startsj_s || !bufa_ptr) { 4924 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4925 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4926 } else { 4927 *startsj_s = sstartsj; 4928 *startsj_r = rstartsj; 4929 *bufa_ptr = bufa; 4930 } 4931 } 4932 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4933 PetscFunctionReturn(0); 4934 } 4935 4936 #undef __FUNCT__ 4937 #define __FUNCT__ "MatGetCommunicationStructs" 4938 /*@C 4939 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4940 4941 Not Collective 4942 4943 Input Parameters: 4944 . A - The matrix in mpiaij format 4945 4946 Output Parameter: 4947 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4948 . colmap - A map from global column index to local index into lvec 4949 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4950 4951 Level: developer 4952 4953 @*/ 4954 #if defined(PETSC_USE_CTABLE) 4955 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4956 #else 4957 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4958 #endif 4959 { 4960 Mat_MPIAIJ *a; 4961 4962 PetscFunctionBegin; 4963 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4964 PetscValidPointer(lvec, 2); 4965 PetscValidPointer(colmap, 3); 4966 PetscValidPointer(multScatter, 4); 4967 a = (Mat_MPIAIJ*) A->data; 4968 if (lvec) *lvec = a->lvec; 4969 if (colmap) *colmap = a->colmap; 4970 if (multScatter) *multScatter = a->Mvctx; 4971 PetscFunctionReturn(0); 4972 } 4973 4974 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4975 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4976 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4977 #if defined(PETSC_HAVE_ELEMENTAL) 4978 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4979 #endif 4980 4981 #undef __FUNCT__ 4982 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4983 /* 4984 Computes (B'*A')' since computing B*A directly is untenable 4985 4986 n p p 4987 ( ) ( ) ( ) 4988 m ( A ) * n ( B ) = m ( C ) 4989 ( ) ( ) ( ) 4990 4991 */ 4992 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4993 { 4994 PetscErrorCode ierr; 4995 Mat At,Bt,Ct; 4996 4997 PetscFunctionBegin; 4998 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4999 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5000 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5001 ierr = MatDestroy(&At);CHKERRQ(ierr); 5002 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5003 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5004 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5005 PetscFunctionReturn(0); 5006 } 5007 5008 #undef __FUNCT__ 5009 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5010 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5011 { 5012 PetscErrorCode ierr; 5013 PetscInt m=A->rmap->n,n=B->cmap->n; 5014 Mat Cmat; 5015 5016 PetscFunctionBegin; 5017 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); 5018 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5019 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5020 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5021 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5022 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5023 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5024 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5025 5026 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5027 5028 *C = Cmat; 5029 PetscFunctionReturn(0); 5030 } 5031 5032 /* ----------------------------------------------------------------*/ 5033 #undef __FUNCT__ 5034 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5035 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5036 { 5037 PetscErrorCode ierr; 5038 5039 PetscFunctionBegin; 5040 if (scall == MAT_INITIAL_MATRIX) { 5041 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5042 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5043 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5044 } 5045 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5046 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5047 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5048 PetscFunctionReturn(0); 5049 } 5050 5051 /*MC 5052 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5053 5054 Options Database Keys: 5055 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5056 5057 Level: beginner 5058 5059 .seealso: MatCreateAIJ() 5060 M*/ 5061 5062 #undef __FUNCT__ 5063 #define __FUNCT__ "MatCreate_MPIAIJ" 5064 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5065 { 5066 Mat_MPIAIJ *b; 5067 PetscErrorCode ierr; 5068 PetscMPIInt size; 5069 5070 PetscFunctionBegin; 5071 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5072 5073 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5074 B->data = (void*)b; 5075 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5076 B->assembled = PETSC_FALSE; 5077 B->insertmode = NOT_SET_VALUES; 5078 b->size = size; 5079 5080 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5081 5082 /* build cache for off array entries formed */ 5083 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5084 5085 b->donotstash = PETSC_FALSE; 5086 b->colmap = 0; 5087 b->garray = 0; 5088 b->roworiented = PETSC_TRUE; 5089 5090 /* stuff used for matrix vector multiply */ 5091 b->lvec = NULL; 5092 b->Mvctx = NULL; 5093 5094 /* stuff for MatGetRow() */ 5095 b->rowindices = 0; 5096 b->rowvalues = 0; 5097 b->getrowactive = PETSC_FALSE; 5098 5099 /* flexible pointer used in CUSP/CUSPARSE classes */ 5100 b->spptr = NULL; 5101 5102 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5103 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5104 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5105 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5106 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5107 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5108 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5109 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5110 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5111 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5112 #if defined(PETSC_HAVE_ELEMENTAL) 5113 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5114 #endif 5115 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5116 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5117 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5118 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5119 PetscFunctionReturn(0); 5120 } 5121 5122 #undef __FUNCT__ 5123 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5124 /*@C 5125 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5126 and "off-diagonal" part of the matrix in CSR format. 5127 5128 Collective on MPI_Comm 5129 5130 Input Parameters: 5131 + comm - MPI communicator 5132 . m - number of local rows (Cannot be PETSC_DECIDE) 5133 . n - This value should be the same as the local size used in creating the 5134 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5135 calculated if N is given) For square matrices n is almost always m. 5136 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5137 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5138 . i - row indices for "diagonal" portion of matrix 5139 . j - column indices 5140 . a - matrix values 5141 . oi - row indices for "off-diagonal" portion of matrix 5142 . oj - column indices 5143 - oa - matrix values 5144 5145 Output Parameter: 5146 . mat - the matrix 5147 5148 Level: advanced 5149 5150 Notes: 5151 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5152 must free the arrays once the matrix has been destroyed and not before. 5153 5154 The i and j indices are 0 based 5155 5156 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5157 5158 This sets local rows and cannot be used to set off-processor values. 5159 5160 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5161 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5162 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5163 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5164 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5165 communication if it is known that only local entries will be set. 5166 5167 .keywords: matrix, aij, compressed row, sparse, parallel 5168 5169 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5170 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5171 @*/ 5172 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) 5173 { 5174 PetscErrorCode ierr; 5175 Mat_MPIAIJ *maij; 5176 5177 PetscFunctionBegin; 5178 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5179 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5180 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5181 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5182 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5183 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5184 maij = (Mat_MPIAIJ*) (*mat)->data; 5185 5186 (*mat)->preallocated = PETSC_TRUE; 5187 5188 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5189 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5190 5191 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5192 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5193 5194 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5195 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5196 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5197 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5198 5199 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5200 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5201 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5202 PetscFunctionReturn(0); 5203 } 5204 5205 /* 5206 Special version for direct calls from Fortran 5207 */ 5208 #include <petsc/private/fortranimpl.h> 5209 5210 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5211 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5212 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5213 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5214 #endif 5215 5216 /* Change these macros so can be used in void function */ 5217 #undef CHKERRQ 5218 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5219 #undef SETERRQ2 5220 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5221 #undef SETERRQ3 5222 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5223 #undef SETERRQ 5224 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5225 5226 #undef __FUNCT__ 5227 #define __FUNCT__ "matsetvaluesmpiaij_" 5228 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) 5229 { 5230 Mat mat = *mmat; 5231 PetscInt m = *mm, n = *mn; 5232 InsertMode addv = *maddv; 5233 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5234 PetscScalar value; 5235 PetscErrorCode ierr; 5236 5237 MatCheckPreallocated(mat,1); 5238 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5239 5240 #if defined(PETSC_USE_DEBUG) 5241 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5242 #endif 5243 { 5244 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5245 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5246 PetscBool roworiented = aij->roworiented; 5247 5248 /* Some Variables required in the macro */ 5249 Mat A = aij->A; 5250 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5251 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5252 MatScalar *aa = a->a; 5253 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5254 Mat B = aij->B; 5255 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5256 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5257 MatScalar *ba = b->a; 5258 5259 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5260 PetscInt nonew = a->nonew; 5261 MatScalar *ap1,*ap2; 5262 5263 PetscFunctionBegin; 5264 for (i=0; i<m; i++) { 5265 if (im[i] < 0) continue; 5266 #if defined(PETSC_USE_DEBUG) 5267 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); 5268 #endif 5269 if (im[i] >= rstart && im[i] < rend) { 5270 row = im[i] - rstart; 5271 lastcol1 = -1; 5272 rp1 = aj + ai[row]; 5273 ap1 = aa + ai[row]; 5274 rmax1 = aimax[row]; 5275 nrow1 = ailen[row]; 5276 low1 = 0; 5277 high1 = nrow1; 5278 lastcol2 = -1; 5279 rp2 = bj + bi[row]; 5280 ap2 = ba + bi[row]; 5281 rmax2 = bimax[row]; 5282 nrow2 = bilen[row]; 5283 low2 = 0; 5284 high2 = nrow2; 5285 5286 for (j=0; j<n; j++) { 5287 if (roworiented) value = v[i*n+j]; 5288 else value = v[i+j*m]; 5289 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5290 if (in[j] >= cstart && in[j] < cend) { 5291 col = in[j] - cstart; 5292 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5293 } else if (in[j] < 0) continue; 5294 #if defined(PETSC_USE_DEBUG) 5295 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); 5296 #endif 5297 else { 5298 if (mat->was_assembled) { 5299 if (!aij->colmap) { 5300 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5301 } 5302 #if defined(PETSC_USE_CTABLE) 5303 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5304 col--; 5305 #else 5306 col = aij->colmap[in[j]] - 1; 5307 #endif 5308 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5309 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5310 col = in[j]; 5311 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5312 B = aij->B; 5313 b = (Mat_SeqAIJ*)B->data; 5314 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5315 rp2 = bj + bi[row]; 5316 ap2 = ba + bi[row]; 5317 rmax2 = bimax[row]; 5318 nrow2 = bilen[row]; 5319 low2 = 0; 5320 high2 = nrow2; 5321 bm = aij->B->rmap->n; 5322 ba = b->a; 5323 } 5324 } else col = in[j]; 5325 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5326 } 5327 } 5328 } else if (!aij->donotstash) { 5329 if (roworiented) { 5330 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5331 } else { 5332 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5333 } 5334 } 5335 } 5336 } 5337 PetscFunctionReturnVoid(); 5338 } 5339 5340