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__ "MatGetInfo_MPIAIJ" 1683 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1684 { 1685 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1686 Mat A = mat->A,B = mat->B; 1687 PetscErrorCode ierr; 1688 PetscReal isend[5],irecv[5]; 1689 1690 PetscFunctionBegin; 1691 info->block_size = 1.0; 1692 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1693 1694 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1695 isend[3] = info->memory; isend[4] = info->mallocs; 1696 1697 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1698 1699 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1700 isend[3] += info->memory; isend[4] += info->mallocs; 1701 if (flag == MAT_LOCAL) { 1702 info->nz_used = isend[0]; 1703 info->nz_allocated = isend[1]; 1704 info->nz_unneeded = isend[2]; 1705 info->memory = isend[3]; 1706 info->mallocs = isend[4]; 1707 } else if (flag == MAT_GLOBAL_MAX) { 1708 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1709 1710 info->nz_used = irecv[0]; 1711 info->nz_allocated = irecv[1]; 1712 info->nz_unneeded = irecv[2]; 1713 info->memory = irecv[3]; 1714 info->mallocs = irecv[4]; 1715 } else if (flag == MAT_GLOBAL_SUM) { 1716 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1717 1718 info->nz_used = irecv[0]; 1719 info->nz_allocated = irecv[1]; 1720 info->nz_unneeded = irecv[2]; 1721 info->memory = irecv[3]; 1722 info->mallocs = irecv[4]; 1723 } 1724 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1725 info->fill_ratio_needed = 0; 1726 info->factor_mallocs = 0; 1727 PetscFunctionReturn(0); 1728 } 1729 1730 #undef __FUNCT__ 1731 #define __FUNCT__ "MatSetOption_MPIAIJ" 1732 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1733 { 1734 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1735 PetscErrorCode ierr; 1736 1737 PetscFunctionBegin; 1738 switch (op) { 1739 case MAT_NEW_NONZERO_LOCATIONS: 1740 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1741 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1742 case MAT_KEEP_NONZERO_PATTERN: 1743 case MAT_NEW_NONZERO_LOCATION_ERR: 1744 case MAT_USE_INODES: 1745 case MAT_IGNORE_ZERO_ENTRIES: 1746 MatCheckPreallocated(A,1); 1747 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1748 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1749 break; 1750 case MAT_ROW_ORIENTED: 1751 a->roworiented = flg; 1752 1753 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1754 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1755 break; 1756 case MAT_NEW_DIAGONALS: 1757 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1758 break; 1759 case MAT_IGNORE_OFF_PROC_ENTRIES: 1760 a->donotstash = flg; 1761 break; 1762 case MAT_SPD: 1763 A->spd_set = PETSC_TRUE; 1764 A->spd = flg; 1765 if (flg) { 1766 A->symmetric = PETSC_TRUE; 1767 A->structurally_symmetric = PETSC_TRUE; 1768 A->symmetric_set = PETSC_TRUE; 1769 A->structurally_symmetric_set = PETSC_TRUE; 1770 } 1771 break; 1772 case MAT_SYMMETRIC: 1773 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1774 break; 1775 case MAT_STRUCTURALLY_SYMMETRIC: 1776 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1777 break; 1778 case MAT_HERMITIAN: 1779 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1780 break; 1781 case MAT_SYMMETRY_ETERNAL: 1782 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1783 break; 1784 default: 1785 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1786 } 1787 PetscFunctionReturn(0); 1788 } 1789 1790 #undef __FUNCT__ 1791 #define __FUNCT__ "MatGetRow_MPIAIJ" 1792 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1793 { 1794 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1795 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1796 PetscErrorCode ierr; 1797 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1798 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1799 PetscInt *cmap,*idx_p; 1800 1801 PetscFunctionBegin; 1802 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1803 mat->getrowactive = PETSC_TRUE; 1804 1805 if (!mat->rowvalues && (idx || v)) { 1806 /* 1807 allocate enough space to hold information from the longest row. 1808 */ 1809 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1810 PetscInt max = 1,tmp; 1811 for (i=0; i<matin->rmap->n; i++) { 1812 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1813 if (max < tmp) max = tmp; 1814 } 1815 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1816 } 1817 1818 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1819 lrow = row - rstart; 1820 1821 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1822 if (!v) {pvA = 0; pvB = 0;} 1823 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1824 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1825 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1826 nztot = nzA + nzB; 1827 1828 cmap = mat->garray; 1829 if (v || idx) { 1830 if (nztot) { 1831 /* Sort by increasing column numbers, assuming A and B already sorted */ 1832 PetscInt imark = -1; 1833 if (v) { 1834 *v = v_p = mat->rowvalues; 1835 for (i=0; i<nzB; i++) { 1836 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1837 else break; 1838 } 1839 imark = i; 1840 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1841 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1842 } 1843 if (idx) { 1844 *idx = idx_p = mat->rowindices; 1845 if (imark > -1) { 1846 for (i=0; i<imark; i++) { 1847 idx_p[i] = cmap[cworkB[i]]; 1848 } 1849 } else { 1850 for (i=0; i<nzB; i++) { 1851 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1852 else break; 1853 } 1854 imark = i; 1855 } 1856 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1857 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1858 } 1859 } else { 1860 if (idx) *idx = 0; 1861 if (v) *v = 0; 1862 } 1863 } 1864 *nz = nztot; 1865 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1866 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1867 PetscFunctionReturn(0); 1868 } 1869 1870 #undef __FUNCT__ 1871 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1872 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1873 { 1874 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1875 1876 PetscFunctionBegin; 1877 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1878 aij->getrowactive = PETSC_FALSE; 1879 PetscFunctionReturn(0); 1880 } 1881 1882 #undef __FUNCT__ 1883 #define __FUNCT__ "MatNorm_MPIAIJ" 1884 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1885 { 1886 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1887 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1888 PetscErrorCode ierr; 1889 PetscInt i,j,cstart = mat->cmap->rstart; 1890 PetscReal sum = 0.0; 1891 MatScalar *v; 1892 1893 PetscFunctionBegin; 1894 if (aij->size == 1) { 1895 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1896 } else { 1897 if (type == NORM_FROBENIUS) { 1898 v = amat->a; 1899 for (i=0; i<amat->nz; i++) { 1900 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1901 } 1902 v = bmat->a; 1903 for (i=0; i<bmat->nz; i++) { 1904 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1905 } 1906 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1907 *norm = PetscSqrtReal(*norm); 1908 } else if (type == NORM_1) { /* max column norm */ 1909 PetscReal *tmp,*tmp2; 1910 PetscInt *jj,*garray = aij->garray; 1911 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1912 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1913 *norm = 0.0; 1914 v = amat->a; jj = amat->j; 1915 for (j=0; j<amat->nz; j++) { 1916 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1917 } 1918 v = bmat->a; jj = bmat->j; 1919 for (j=0; j<bmat->nz; j++) { 1920 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1921 } 1922 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1923 for (j=0; j<mat->cmap->N; j++) { 1924 if (tmp2[j] > *norm) *norm = tmp2[j]; 1925 } 1926 ierr = PetscFree(tmp);CHKERRQ(ierr); 1927 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1928 } else if (type == NORM_INFINITY) { /* max row norm */ 1929 PetscReal ntemp = 0.0; 1930 for (j=0; j<aij->A->rmap->n; j++) { 1931 v = amat->a + amat->i[j]; 1932 sum = 0.0; 1933 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1934 sum += PetscAbsScalar(*v); v++; 1935 } 1936 v = bmat->a + bmat->i[j]; 1937 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1938 sum += PetscAbsScalar(*v); v++; 1939 } 1940 if (sum > ntemp) ntemp = sum; 1941 } 1942 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1943 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1944 } 1945 PetscFunctionReturn(0); 1946 } 1947 1948 #undef __FUNCT__ 1949 #define __FUNCT__ "MatTranspose_MPIAIJ" 1950 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1951 { 1952 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1953 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1954 PetscErrorCode ierr; 1955 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1956 PetscInt cstart = A->cmap->rstart,ncol; 1957 Mat B; 1958 MatScalar *array; 1959 1960 PetscFunctionBegin; 1961 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1962 1963 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1964 ai = Aloc->i; aj = Aloc->j; 1965 bi = Bloc->i; bj = Bloc->j; 1966 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1967 PetscInt *d_nnz,*g_nnz,*o_nnz; 1968 PetscSFNode *oloc; 1969 PETSC_UNUSED PetscSF sf; 1970 1971 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1972 /* compute d_nnz for preallocation */ 1973 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1974 for (i=0; i<ai[ma]; i++) { 1975 d_nnz[aj[i]]++; 1976 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1977 } 1978 /* compute local off-diagonal contributions */ 1979 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1980 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1981 /* map those to global */ 1982 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1983 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1984 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1985 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1986 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1987 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1988 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1989 1990 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1991 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1992 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1993 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1994 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1995 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1996 } else { 1997 B = *matout; 1998 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1999 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2000 } 2001 2002 /* copy over the A part */ 2003 array = Aloc->a; 2004 row = A->rmap->rstart; 2005 for (i=0; i<ma; i++) { 2006 ncol = ai[i+1]-ai[i]; 2007 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2008 row++; 2009 array += ncol; aj += ncol; 2010 } 2011 aj = Aloc->j; 2012 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2013 2014 /* copy over the B part */ 2015 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2016 array = Bloc->a; 2017 row = A->rmap->rstart; 2018 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2019 cols_tmp = cols; 2020 for (i=0; i<mb; i++) { 2021 ncol = bi[i+1]-bi[i]; 2022 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2023 row++; 2024 array += ncol; cols_tmp += ncol; 2025 } 2026 ierr = PetscFree(cols);CHKERRQ(ierr); 2027 2028 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2029 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2030 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2031 *matout = B; 2032 } else { 2033 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2034 } 2035 PetscFunctionReturn(0); 2036 } 2037 2038 #undef __FUNCT__ 2039 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2040 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2041 { 2042 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2043 Mat a = aij->A,b = aij->B; 2044 PetscErrorCode ierr; 2045 PetscInt s1,s2,s3; 2046 2047 PetscFunctionBegin; 2048 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2049 if (rr) { 2050 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2051 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2052 /* Overlap communication with computation. */ 2053 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2054 } 2055 if (ll) { 2056 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2057 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2058 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2059 } 2060 /* scale the diagonal block */ 2061 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2062 2063 if (rr) { 2064 /* Do a scatter end and then right scale the off-diagonal block */ 2065 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2066 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2067 } 2068 PetscFunctionReturn(0); 2069 } 2070 2071 #undef __FUNCT__ 2072 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2073 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2074 { 2075 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2076 PetscErrorCode ierr; 2077 2078 PetscFunctionBegin; 2079 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2080 PetscFunctionReturn(0); 2081 } 2082 2083 #undef __FUNCT__ 2084 #define __FUNCT__ "MatEqual_MPIAIJ" 2085 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2086 { 2087 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2088 Mat a,b,c,d; 2089 PetscBool flg; 2090 PetscErrorCode ierr; 2091 2092 PetscFunctionBegin; 2093 a = matA->A; b = matA->B; 2094 c = matB->A; d = matB->B; 2095 2096 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2097 if (flg) { 2098 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2099 } 2100 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2101 PetscFunctionReturn(0); 2102 } 2103 2104 #undef __FUNCT__ 2105 #define __FUNCT__ "MatCopy_MPIAIJ" 2106 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2107 { 2108 PetscErrorCode ierr; 2109 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2110 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2111 2112 PetscFunctionBegin; 2113 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2114 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2115 /* because of the column compression in the off-processor part of the matrix a->B, 2116 the number of columns in a->B and b->B may be different, hence we cannot call 2117 the MatCopy() directly on the two parts. If need be, we can provide a more 2118 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2119 then copying the submatrices */ 2120 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2121 } else { 2122 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2123 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2124 } 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatSetUp_MPIAIJ" 2130 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2131 { 2132 PetscErrorCode ierr; 2133 2134 PetscFunctionBegin; 2135 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2136 PetscFunctionReturn(0); 2137 } 2138 2139 /* 2140 Computes the number of nonzeros per row needed for preallocation when X and Y 2141 have different nonzero structure. 2142 */ 2143 #undef __FUNCT__ 2144 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2145 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) 2146 { 2147 PetscInt i,j,k,nzx,nzy; 2148 2149 PetscFunctionBegin; 2150 /* Set the number of nonzeros in the new matrix */ 2151 for (i=0; i<m; i++) { 2152 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2153 nzx = xi[i+1] - xi[i]; 2154 nzy = yi[i+1] - yi[i]; 2155 nnz[i] = 0; 2156 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2157 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2158 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2159 nnz[i]++; 2160 } 2161 for (; k<nzy; k++) nnz[i]++; 2162 } 2163 PetscFunctionReturn(0); 2164 } 2165 2166 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2169 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2170 { 2171 PetscErrorCode ierr; 2172 PetscInt m = Y->rmap->N; 2173 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2174 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2175 2176 PetscFunctionBegin; 2177 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2178 PetscFunctionReturn(0); 2179 } 2180 2181 #undef __FUNCT__ 2182 #define __FUNCT__ "MatAXPY_MPIAIJ" 2183 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2184 { 2185 PetscErrorCode ierr; 2186 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2187 PetscBLASInt bnz,one=1; 2188 Mat_SeqAIJ *x,*y; 2189 2190 PetscFunctionBegin; 2191 if (str == SAME_NONZERO_PATTERN) { 2192 PetscScalar alpha = a; 2193 x = (Mat_SeqAIJ*)xx->A->data; 2194 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2195 y = (Mat_SeqAIJ*)yy->A->data; 2196 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2197 x = (Mat_SeqAIJ*)xx->B->data; 2198 y = (Mat_SeqAIJ*)yy->B->data; 2199 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2200 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2201 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2202 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2203 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2204 } else { 2205 Mat B; 2206 PetscInt *nnz_d,*nnz_o; 2207 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2208 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2209 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2210 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2211 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2212 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2213 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2214 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2215 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2216 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2217 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2218 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2219 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2220 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2221 } 2222 PetscFunctionReturn(0); 2223 } 2224 2225 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2226 2227 #undef __FUNCT__ 2228 #define __FUNCT__ "MatConjugate_MPIAIJ" 2229 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2230 { 2231 #if defined(PETSC_USE_COMPLEX) 2232 PetscErrorCode ierr; 2233 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2234 2235 PetscFunctionBegin; 2236 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2237 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2238 #else 2239 PetscFunctionBegin; 2240 #endif 2241 PetscFunctionReturn(0); 2242 } 2243 2244 #undef __FUNCT__ 2245 #define __FUNCT__ "MatRealPart_MPIAIJ" 2246 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2247 { 2248 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2249 PetscErrorCode ierr; 2250 2251 PetscFunctionBegin; 2252 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2253 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2259 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2260 { 2261 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2262 PetscErrorCode ierr; 2263 2264 PetscFunctionBegin; 2265 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2266 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2267 PetscFunctionReturn(0); 2268 } 2269 2270 #if defined(PETSC_HAVE_PBGL) 2271 2272 #include <boost/parallel/mpi/bsp_process_group.hpp> 2273 #include <boost/graph/distributed/ilu_default_graph.hpp> 2274 #include <boost/graph/distributed/ilu_0_block.hpp> 2275 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2276 #include <boost/graph/distributed/petsc/interface.hpp> 2277 #include <boost/multi_array.hpp> 2278 #include <boost/parallel/distributed_property_map->hpp> 2279 2280 #undef __FUNCT__ 2281 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2282 /* 2283 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2284 */ 2285 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2286 { 2287 namespace petsc = boost::distributed::petsc; 2288 2289 namespace graph_dist = boost::graph::distributed; 2290 using boost::graph::distributed::ilu_default::process_group_type; 2291 using boost::graph::ilu_permuted; 2292 2293 PetscBool row_identity, col_identity; 2294 PetscContainer c; 2295 PetscInt m, n, M, N; 2296 PetscErrorCode ierr; 2297 2298 PetscFunctionBegin; 2299 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2300 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2301 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2302 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2303 2304 process_group_type pg; 2305 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2306 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2307 lgraph_type& level_graph = *lgraph_p; 2308 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2309 2310 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2311 ilu_permuted(level_graph); 2312 2313 /* put together the new matrix */ 2314 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2315 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2316 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2317 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2318 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2319 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2320 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2321 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2322 2323 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2324 ierr = PetscContainerSetPointer(c, lgraph_p); 2325 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2326 ierr = PetscContainerDestroy(&c); 2327 PetscFunctionReturn(0); 2328 } 2329 2330 #undef __FUNCT__ 2331 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2332 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2333 { 2334 PetscFunctionBegin; 2335 PetscFunctionReturn(0); 2336 } 2337 2338 #undef __FUNCT__ 2339 #define __FUNCT__ "MatSolve_MPIAIJ" 2340 /* 2341 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2342 */ 2343 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2344 { 2345 namespace graph_dist = boost::graph::distributed; 2346 2347 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2348 lgraph_type *lgraph_p; 2349 PetscContainer c; 2350 PetscErrorCode ierr; 2351 2352 PetscFunctionBegin; 2353 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2354 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2355 ierr = VecCopy(b, x);CHKERRQ(ierr); 2356 2357 PetscScalar *array_x; 2358 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2359 PetscInt sx; 2360 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2361 2362 PetscScalar *array_b; 2363 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2364 PetscInt sb; 2365 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2366 2367 lgraph_type& level_graph = *lgraph_p; 2368 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2369 2370 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2371 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2372 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2373 2374 typedef boost::iterator_property_map<array_ref_type::iterator, 2375 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2376 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2377 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2378 2379 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2380 PetscFunctionReturn(0); 2381 } 2382 #endif 2383 2384 #undef __FUNCT__ 2385 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2386 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2387 { 2388 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2389 PetscErrorCode ierr; 2390 PetscInt i,*idxb = 0; 2391 PetscScalar *va,*vb; 2392 Vec vtmp; 2393 2394 PetscFunctionBegin; 2395 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2396 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2397 if (idx) { 2398 for (i=0; i<A->rmap->n; i++) { 2399 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2400 } 2401 } 2402 2403 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2404 if (idx) { 2405 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2406 } 2407 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2408 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2409 2410 for (i=0; i<A->rmap->n; i++) { 2411 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2412 va[i] = vb[i]; 2413 if (idx) idx[i] = a->garray[idxb[i]]; 2414 } 2415 } 2416 2417 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2418 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2419 ierr = PetscFree(idxb);CHKERRQ(ierr); 2420 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 #undef __FUNCT__ 2425 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2426 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2427 { 2428 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2429 PetscErrorCode ierr; 2430 PetscInt i,*idxb = 0; 2431 PetscScalar *va,*vb; 2432 Vec vtmp; 2433 2434 PetscFunctionBegin; 2435 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2436 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2437 if (idx) { 2438 for (i=0; i<A->cmap->n; i++) { 2439 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2440 } 2441 } 2442 2443 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2444 if (idx) { 2445 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2446 } 2447 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2448 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2449 2450 for (i=0; i<A->rmap->n; i++) { 2451 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2452 va[i] = vb[i]; 2453 if (idx) idx[i] = a->garray[idxb[i]]; 2454 } 2455 } 2456 2457 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2458 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2459 ierr = PetscFree(idxb);CHKERRQ(ierr); 2460 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2466 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2467 { 2468 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2469 PetscInt n = A->rmap->n; 2470 PetscInt cstart = A->cmap->rstart; 2471 PetscInt *cmap = mat->garray; 2472 PetscInt *diagIdx, *offdiagIdx; 2473 Vec diagV, offdiagV; 2474 PetscScalar *a, *diagA, *offdiagA; 2475 PetscInt r; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2480 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2481 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2482 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2483 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2484 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2485 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2486 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2487 for (r = 0; r < n; ++r) { 2488 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2489 a[r] = diagA[r]; 2490 idx[r] = cstart + diagIdx[r]; 2491 } else { 2492 a[r] = offdiagA[r]; 2493 idx[r] = cmap[offdiagIdx[r]]; 2494 } 2495 } 2496 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2497 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2498 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2499 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2500 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2501 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2502 PetscFunctionReturn(0); 2503 } 2504 2505 #undef __FUNCT__ 2506 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2507 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2508 { 2509 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2510 PetscInt n = A->rmap->n; 2511 PetscInt cstart = A->cmap->rstart; 2512 PetscInt *cmap = mat->garray; 2513 PetscInt *diagIdx, *offdiagIdx; 2514 Vec diagV, offdiagV; 2515 PetscScalar *a, *diagA, *offdiagA; 2516 PetscInt r; 2517 PetscErrorCode ierr; 2518 2519 PetscFunctionBegin; 2520 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2521 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2522 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2523 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2524 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2525 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2526 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2527 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2528 for (r = 0; r < n; ++r) { 2529 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2530 a[r] = diagA[r]; 2531 idx[r] = cstart + diagIdx[r]; 2532 } else { 2533 a[r] = offdiagA[r]; 2534 idx[r] = cmap[offdiagIdx[r]]; 2535 } 2536 } 2537 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2538 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2539 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2540 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2541 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2542 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2543 PetscFunctionReturn(0); 2544 } 2545 2546 #undef __FUNCT__ 2547 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2548 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2549 { 2550 PetscErrorCode ierr; 2551 Mat *dummy; 2552 2553 PetscFunctionBegin; 2554 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2555 *newmat = *dummy; 2556 ierr = PetscFree(dummy);CHKERRQ(ierr); 2557 PetscFunctionReturn(0); 2558 } 2559 2560 #undef __FUNCT__ 2561 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2562 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2563 { 2564 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2565 PetscErrorCode ierr; 2566 2567 PetscFunctionBegin; 2568 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 #undef __FUNCT__ 2573 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2574 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2575 { 2576 PetscErrorCode ierr; 2577 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2578 2579 PetscFunctionBegin; 2580 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2581 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2582 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2583 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2584 PetscFunctionReturn(0); 2585 } 2586 2587 #undef __FUNCT__ 2588 #define __FUNCT__ "MatShift_MPIAIJ" 2589 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2590 { 2591 PetscErrorCode ierr; 2592 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2593 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data,*bij = (Mat_SeqAIJ*)maij->B->data; 2594 2595 PetscFunctionBegin; 2596 if (!aij->nz && !bij->nz) { 2597 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2598 } 2599 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2600 PetscFunctionReturn(0); 2601 } 2602 2603 /* -------------------------------------------------------------------*/ 2604 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2605 MatGetRow_MPIAIJ, 2606 MatRestoreRow_MPIAIJ, 2607 MatMult_MPIAIJ, 2608 /* 4*/ MatMultAdd_MPIAIJ, 2609 MatMultTranspose_MPIAIJ, 2610 MatMultTransposeAdd_MPIAIJ, 2611 #if defined(PETSC_HAVE_PBGL) 2612 MatSolve_MPIAIJ, 2613 #else 2614 0, 2615 #endif 2616 0, 2617 0, 2618 /*10*/ 0, 2619 0, 2620 0, 2621 MatSOR_MPIAIJ, 2622 MatTranspose_MPIAIJ, 2623 /*15*/ MatGetInfo_MPIAIJ, 2624 MatEqual_MPIAIJ, 2625 MatGetDiagonal_MPIAIJ, 2626 MatDiagonalScale_MPIAIJ, 2627 MatNorm_MPIAIJ, 2628 /*20*/ MatAssemblyBegin_MPIAIJ, 2629 MatAssemblyEnd_MPIAIJ, 2630 MatSetOption_MPIAIJ, 2631 MatZeroEntries_MPIAIJ, 2632 /*24*/ MatZeroRows_MPIAIJ, 2633 0, 2634 #if defined(PETSC_HAVE_PBGL) 2635 0, 2636 #else 2637 0, 2638 #endif 2639 0, 2640 0, 2641 /*29*/ MatSetUp_MPIAIJ, 2642 #if defined(PETSC_HAVE_PBGL) 2643 0, 2644 #else 2645 0, 2646 #endif 2647 0, 2648 0, 2649 0, 2650 /*34*/ MatDuplicate_MPIAIJ, 2651 0, 2652 0, 2653 0, 2654 0, 2655 /*39*/ MatAXPY_MPIAIJ, 2656 MatGetSubMatrices_MPIAIJ, 2657 MatIncreaseOverlap_MPIAIJ, 2658 MatGetValues_MPIAIJ, 2659 MatCopy_MPIAIJ, 2660 /*44*/ MatGetRowMax_MPIAIJ, 2661 MatScale_MPIAIJ, 2662 MatShift_MPIAIJ, 2663 MatDiagonalSet_MPIAIJ, 2664 MatZeroRowsColumns_MPIAIJ, 2665 /*49*/ MatSetRandom_MPIAIJ, 2666 0, 2667 0, 2668 0, 2669 0, 2670 /*54*/ MatFDColoringCreate_MPIXAIJ, 2671 0, 2672 MatSetUnfactored_MPIAIJ, 2673 MatPermute_MPIAIJ, 2674 0, 2675 /*59*/ MatGetSubMatrix_MPIAIJ, 2676 MatDestroy_MPIAIJ, 2677 MatView_MPIAIJ, 2678 0, 2679 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2680 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2681 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2682 0, 2683 0, 2684 0, 2685 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2686 MatGetRowMinAbs_MPIAIJ, 2687 0, 2688 MatSetColoring_MPIAIJ, 2689 0, 2690 MatSetValuesAdifor_MPIAIJ, 2691 /*75*/ MatFDColoringApply_AIJ, 2692 0, 2693 0, 2694 0, 2695 MatFindZeroDiagonals_MPIAIJ, 2696 /*80*/ 0, 2697 0, 2698 0, 2699 /*83*/ MatLoad_MPIAIJ, 2700 0, 2701 0, 2702 0, 2703 0, 2704 0, 2705 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2706 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2707 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2708 MatPtAP_MPIAIJ_MPIAIJ, 2709 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2710 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2711 0, 2712 0, 2713 0, 2714 0, 2715 /*99*/ 0, 2716 0, 2717 0, 2718 MatConjugate_MPIAIJ, 2719 0, 2720 /*104*/MatSetValuesRow_MPIAIJ, 2721 MatRealPart_MPIAIJ, 2722 MatImaginaryPart_MPIAIJ, 2723 0, 2724 0, 2725 /*109*/0, 2726 0, 2727 MatGetRowMin_MPIAIJ, 2728 0, 2729 0, 2730 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2731 0, 2732 0, 2733 0, 2734 0, 2735 /*119*/0, 2736 0, 2737 0, 2738 0, 2739 MatGetMultiProcBlock_MPIAIJ, 2740 /*124*/MatFindNonzeroRows_MPIAIJ, 2741 MatGetColumnNorms_MPIAIJ, 2742 MatInvertBlockDiagonal_MPIAIJ, 2743 0, 2744 MatGetSubMatricesMPI_MPIAIJ, 2745 /*129*/0, 2746 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2747 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2748 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2749 0, 2750 /*134*/0, 2751 0, 2752 0, 2753 0, 2754 0, 2755 /*139*/0, 2756 0, 2757 0, 2758 MatFDColoringSetUp_MPIXAIJ, 2759 MatFindOffBlockDiagonalEntries_MPIAIJ, 2760 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2761 }; 2762 2763 /* ----------------------------------------------------------------------------------------*/ 2764 2765 #undef __FUNCT__ 2766 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2767 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2768 { 2769 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2770 PetscErrorCode ierr; 2771 2772 PetscFunctionBegin; 2773 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2774 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2775 PetscFunctionReturn(0); 2776 } 2777 2778 #undef __FUNCT__ 2779 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2780 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2781 { 2782 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2783 PetscErrorCode ierr; 2784 2785 PetscFunctionBegin; 2786 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2787 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2788 PetscFunctionReturn(0); 2789 } 2790 2791 #undef __FUNCT__ 2792 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2793 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2794 { 2795 Mat_MPIAIJ *b; 2796 PetscErrorCode ierr; 2797 2798 PetscFunctionBegin; 2799 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2800 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2801 b = (Mat_MPIAIJ*)B->data; 2802 2803 if (!B->preallocated) { 2804 /* Explicitly create 2 MATSEQAIJ matrices. */ 2805 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2806 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2807 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2808 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2809 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2810 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2811 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2812 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2813 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2814 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2815 } 2816 2817 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2818 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2819 B->preallocated = PETSC_TRUE; 2820 PetscFunctionReturn(0); 2821 } 2822 2823 #undef __FUNCT__ 2824 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2825 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2826 { 2827 Mat mat; 2828 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2829 PetscErrorCode ierr; 2830 2831 PetscFunctionBegin; 2832 *newmat = 0; 2833 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2834 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2835 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2836 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2837 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2838 a = (Mat_MPIAIJ*)mat->data; 2839 2840 mat->factortype = matin->factortype; 2841 mat->assembled = PETSC_TRUE; 2842 mat->insertmode = NOT_SET_VALUES; 2843 mat->preallocated = PETSC_TRUE; 2844 2845 a->size = oldmat->size; 2846 a->rank = oldmat->rank; 2847 a->donotstash = oldmat->donotstash; 2848 a->roworiented = oldmat->roworiented; 2849 a->rowindices = 0; 2850 a->rowvalues = 0; 2851 a->getrowactive = PETSC_FALSE; 2852 2853 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2854 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2855 2856 if (oldmat->colmap) { 2857 #if defined(PETSC_USE_CTABLE) 2858 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2859 #else 2860 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2861 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2862 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2863 #endif 2864 } else a->colmap = 0; 2865 if (oldmat->garray) { 2866 PetscInt len; 2867 len = oldmat->B->cmap->n; 2868 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2869 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2870 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2871 } else a->garray = 0; 2872 2873 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2874 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2875 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2876 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2877 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2878 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2879 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2880 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2881 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2882 *newmat = mat; 2883 PetscFunctionReturn(0); 2884 } 2885 2886 2887 2888 #undef __FUNCT__ 2889 #define __FUNCT__ "MatLoad_MPIAIJ" 2890 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2891 { 2892 PetscScalar *vals,*svals; 2893 MPI_Comm comm; 2894 PetscErrorCode ierr; 2895 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2896 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2897 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2898 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2899 PetscInt cend,cstart,n,*rowners; 2900 int fd; 2901 PetscInt bs = newMat->rmap->bs; 2902 2903 PetscFunctionBegin; 2904 /* force binary viewer to load .info file if it has not yet done so */ 2905 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2906 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2907 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2908 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2909 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2910 if (!rank) { 2911 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2912 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2913 } 2914 2915 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2916 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2917 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2918 if (bs < 0) bs = 1; 2919 2920 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2921 M = header[1]; N = header[2]; 2922 2923 /* If global sizes are set, check if they are consistent with that given in the file */ 2924 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); 2925 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); 2926 2927 /* determine ownership of all (block) rows */ 2928 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2929 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2930 else m = newMat->rmap->n; /* Set by user */ 2931 2932 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2933 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2934 2935 /* First process needs enough room for process with most rows */ 2936 if (!rank) { 2937 mmax = rowners[1]; 2938 for (i=2; i<=size; i++) { 2939 mmax = PetscMax(mmax, rowners[i]); 2940 } 2941 } else mmax = -1; /* unused, but compilers complain */ 2942 2943 rowners[0] = 0; 2944 for (i=2; i<=size; i++) { 2945 rowners[i] += rowners[i-1]; 2946 } 2947 rstart = rowners[rank]; 2948 rend = rowners[rank+1]; 2949 2950 /* distribute row lengths to all processors */ 2951 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2952 if (!rank) { 2953 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2954 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2955 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2956 for (j=0; j<m; j++) { 2957 procsnz[0] += ourlens[j]; 2958 } 2959 for (i=1; i<size; i++) { 2960 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2961 /* calculate the number of nonzeros on each processor */ 2962 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2963 procsnz[i] += rowlengths[j]; 2964 } 2965 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2966 } 2967 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2968 } else { 2969 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2970 } 2971 2972 if (!rank) { 2973 /* determine max buffer needed and allocate it */ 2974 maxnz = 0; 2975 for (i=0; i<size; i++) { 2976 maxnz = PetscMax(maxnz,procsnz[i]); 2977 } 2978 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2979 2980 /* read in my part of the matrix column indices */ 2981 nz = procsnz[0]; 2982 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2983 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2984 2985 /* read in every one elses and ship off */ 2986 for (i=1; i<size; i++) { 2987 nz = procsnz[i]; 2988 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2989 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2990 } 2991 ierr = PetscFree(cols);CHKERRQ(ierr); 2992 } else { 2993 /* determine buffer space needed for message */ 2994 nz = 0; 2995 for (i=0; i<m; i++) { 2996 nz += ourlens[i]; 2997 } 2998 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2999 3000 /* receive message of column indices*/ 3001 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3002 } 3003 3004 /* determine column ownership if matrix is not square */ 3005 if (N != M) { 3006 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3007 else n = newMat->cmap->n; 3008 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3009 cstart = cend - n; 3010 } else { 3011 cstart = rstart; 3012 cend = rend; 3013 n = cend - cstart; 3014 } 3015 3016 /* loop over local rows, determining number of off diagonal entries */ 3017 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3018 jj = 0; 3019 for (i=0; i<m; i++) { 3020 for (j=0; j<ourlens[i]; j++) { 3021 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3022 jj++; 3023 } 3024 } 3025 3026 for (i=0; i<m; i++) { 3027 ourlens[i] -= offlens[i]; 3028 } 3029 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3030 3031 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3032 3033 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3034 3035 for (i=0; i<m; i++) { 3036 ourlens[i] += offlens[i]; 3037 } 3038 3039 if (!rank) { 3040 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3041 3042 /* read in my part of the matrix numerical values */ 3043 nz = procsnz[0]; 3044 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3045 3046 /* insert into matrix */ 3047 jj = rstart; 3048 smycols = mycols; 3049 svals = vals; 3050 for (i=0; i<m; i++) { 3051 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3052 smycols += ourlens[i]; 3053 svals += ourlens[i]; 3054 jj++; 3055 } 3056 3057 /* read in other processors and ship out */ 3058 for (i=1; i<size; i++) { 3059 nz = procsnz[i]; 3060 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3061 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3062 } 3063 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3064 } else { 3065 /* receive numeric values */ 3066 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3067 3068 /* receive message of values*/ 3069 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3070 3071 /* insert into matrix */ 3072 jj = rstart; 3073 smycols = mycols; 3074 svals = vals; 3075 for (i=0; i<m; i++) { 3076 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3077 smycols += ourlens[i]; 3078 svals += ourlens[i]; 3079 jj++; 3080 } 3081 } 3082 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3083 ierr = PetscFree(vals);CHKERRQ(ierr); 3084 ierr = PetscFree(mycols);CHKERRQ(ierr); 3085 ierr = PetscFree(rowners);CHKERRQ(ierr); 3086 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3087 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3088 PetscFunctionReturn(0); 3089 } 3090 3091 #undef __FUNCT__ 3092 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3093 /* TODO: Not scalable because of ISAllGather(). */ 3094 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3095 { 3096 PetscErrorCode ierr; 3097 IS iscol_local; 3098 PetscInt csize; 3099 3100 PetscFunctionBegin; 3101 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3102 if (call == MAT_REUSE_MATRIX) { 3103 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3104 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3105 } else { 3106 PetscInt cbs; 3107 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3108 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3109 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3110 } 3111 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3112 if (call == MAT_INITIAL_MATRIX) { 3113 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3114 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3115 } 3116 PetscFunctionReturn(0); 3117 } 3118 3119 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3120 #undef __FUNCT__ 3121 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3122 /* 3123 Not great since it makes two copies of the submatrix, first an SeqAIJ 3124 in local and then by concatenating the local matrices the end result. 3125 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3126 3127 Note: This requires a sequential iscol with all indices. 3128 */ 3129 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3130 { 3131 PetscErrorCode ierr; 3132 PetscMPIInt rank,size; 3133 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3134 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3135 PetscBool allcolumns, colflag; 3136 Mat M,Mreuse; 3137 MatScalar *vwork,*aa; 3138 MPI_Comm comm; 3139 Mat_SeqAIJ *aij; 3140 3141 PetscFunctionBegin; 3142 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3143 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3144 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3145 3146 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3147 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3148 if (colflag && ncol == mat->cmap->N) { 3149 allcolumns = PETSC_TRUE; 3150 } else { 3151 allcolumns = PETSC_FALSE; 3152 } 3153 if (call == MAT_REUSE_MATRIX) { 3154 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3155 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3156 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3157 } else { 3158 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3159 } 3160 3161 /* 3162 m - number of local rows 3163 n - number of columns (same on all processors) 3164 rstart - first row in new global matrix generated 3165 */ 3166 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3167 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3168 if (call == MAT_INITIAL_MATRIX) { 3169 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3170 ii = aij->i; 3171 jj = aij->j; 3172 3173 /* 3174 Determine the number of non-zeros in the diagonal and off-diagonal 3175 portions of the matrix in order to do correct preallocation 3176 */ 3177 3178 /* first get start and end of "diagonal" columns */ 3179 if (csize == PETSC_DECIDE) { 3180 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3181 if (mglobal == n) { /* square matrix */ 3182 nlocal = m; 3183 } else { 3184 nlocal = n/size + ((n % size) > rank); 3185 } 3186 } else { 3187 nlocal = csize; 3188 } 3189 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3190 rstart = rend - nlocal; 3191 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); 3192 3193 /* next, compute all the lengths */ 3194 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3195 olens = dlens + m; 3196 for (i=0; i<m; i++) { 3197 jend = ii[i+1] - ii[i]; 3198 olen = 0; 3199 dlen = 0; 3200 for (j=0; j<jend; j++) { 3201 if (*jj < rstart || *jj >= rend) olen++; 3202 else dlen++; 3203 jj++; 3204 } 3205 olens[i] = olen; 3206 dlens[i] = dlen; 3207 } 3208 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3209 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3210 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3211 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3212 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3213 ierr = PetscFree(dlens);CHKERRQ(ierr); 3214 } else { 3215 PetscInt ml,nl; 3216 3217 M = *newmat; 3218 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3219 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3220 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3221 /* 3222 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3223 rather than the slower MatSetValues(). 3224 */ 3225 M->was_assembled = PETSC_TRUE; 3226 M->assembled = PETSC_FALSE; 3227 } 3228 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3229 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3230 ii = aij->i; 3231 jj = aij->j; 3232 aa = aij->a; 3233 for (i=0; i<m; i++) { 3234 row = rstart + i; 3235 nz = ii[i+1] - ii[i]; 3236 cwork = jj; jj += nz; 3237 vwork = aa; aa += nz; 3238 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3239 } 3240 3241 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3242 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3243 *newmat = M; 3244 3245 /* save submatrix used in processor for next request */ 3246 if (call == MAT_INITIAL_MATRIX) { 3247 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3248 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3249 } 3250 PetscFunctionReturn(0); 3251 } 3252 3253 #undef __FUNCT__ 3254 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3255 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3256 { 3257 PetscInt m,cstart, cend,j,nnz,i,d; 3258 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3259 const PetscInt *JJ; 3260 PetscScalar *values; 3261 PetscErrorCode ierr; 3262 3263 PetscFunctionBegin; 3264 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3265 3266 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3267 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3268 m = B->rmap->n; 3269 cstart = B->cmap->rstart; 3270 cend = B->cmap->rend; 3271 rstart = B->rmap->rstart; 3272 3273 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3274 3275 #if defined(PETSC_USE_DEBUGGING) 3276 for (i=0; i<m; i++) { 3277 nnz = Ii[i+1]- Ii[i]; 3278 JJ = J + Ii[i]; 3279 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3280 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3281 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); 3282 } 3283 #endif 3284 3285 for (i=0; i<m; i++) { 3286 nnz = Ii[i+1]- Ii[i]; 3287 JJ = J + Ii[i]; 3288 nnz_max = PetscMax(nnz_max,nnz); 3289 d = 0; 3290 for (j=0; j<nnz; j++) { 3291 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3292 } 3293 d_nnz[i] = d; 3294 o_nnz[i] = nnz - d; 3295 } 3296 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3297 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3298 3299 if (v) values = (PetscScalar*)v; 3300 else { 3301 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3302 } 3303 3304 for (i=0; i<m; i++) { 3305 ii = i + rstart; 3306 nnz = Ii[i+1]- Ii[i]; 3307 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3308 } 3309 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3310 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3311 3312 if (!v) { 3313 ierr = PetscFree(values);CHKERRQ(ierr); 3314 } 3315 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3316 PetscFunctionReturn(0); 3317 } 3318 3319 #undef __FUNCT__ 3320 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3321 /*@ 3322 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3323 (the default parallel PETSc format). 3324 3325 Collective on MPI_Comm 3326 3327 Input Parameters: 3328 + B - the matrix 3329 . i - the indices into j for the start of each local row (starts with zero) 3330 . j - the column indices for each local row (starts with zero) 3331 - v - optional values in the matrix 3332 3333 Level: developer 3334 3335 Notes: 3336 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3337 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3338 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3339 3340 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3341 3342 The format which is used for the sparse matrix input, is equivalent to a 3343 row-major ordering.. i.e for the following matrix, the input data expected is 3344 as shown: 3345 3346 1 0 0 3347 2 0 3 P0 3348 ------- 3349 4 5 6 P1 3350 3351 Process0 [P0]: rows_owned=[0,1] 3352 i = {0,1,3} [size = nrow+1 = 2+1] 3353 j = {0,0,2} [size = nz = 6] 3354 v = {1,2,3} [size = nz = 6] 3355 3356 Process1 [P1]: rows_owned=[2] 3357 i = {0,3} [size = nrow+1 = 1+1] 3358 j = {0,1,2} [size = nz = 6] 3359 v = {4,5,6} [size = nz = 6] 3360 3361 .keywords: matrix, aij, compressed row, sparse, parallel 3362 3363 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3364 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3365 @*/ 3366 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3367 { 3368 PetscErrorCode ierr; 3369 3370 PetscFunctionBegin; 3371 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3372 PetscFunctionReturn(0); 3373 } 3374 3375 #undef __FUNCT__ 3376 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3377 /*@C 3378 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3379 (the default parallel PETSc format). For good matrix assembly performance 3380 the user should preallocate the matrix storage by setting the parameters 3381 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3382 performance can be increased by more than a factor of 50. 3383 3384 Collective on MPI_Comm 3385 3386 Input Parameters: 3387 + B - the matrix 3388 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3389 (same value is used for all local rows) 3390 . d_nnz - array containing the number of nonzeros in the various rows of the 3391 DIAGONAL portion of the local submatrix (possibly different for each row) 3392 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3393 The size of this array is equal to the number of local rows, i.e 'm'. 3394 For matrices that will be factored, you must leave room for (and set) 3395 the diagonal entry even if it is zero. 3396 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3397 submatrix (same value is used for all local rows). 3398 - o_nnz - array containing the number of nonzeros in the various rows of the 3399 OFF-DIAGONAL portion of the local submatrix (possibly different for 3400 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3401 structure. The size of this array is equal to the number 3402 of local rows, i.e 'm'. 3403 3404 If the *_nnz parameter is given then the *_nz parameter is ignored 3405 3406 The AIJ format (also called the Yale sparse matrix format or 3407 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3408 storage. The stored row and column indices begin with zero. 3409 See Users-Manual: ch_mat for details. 3410 3411 The parallel matrix is partitioned such that the first m0 rows belong to 3412 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3413 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3414 3415 The DIAGONAL portion of the local submatrix of a processor can be defined 3416 as the submatrix which is obtained by extraction the part corresponding to 3417 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3418 first row that belongs to the processor, r2 is the last row belonging to 3419 the this processor, and c1-c2 is range of indices of the local part of a 3420 vector suitable for applying the matrix to. This is an mxn matrix. In the 3421 common case of a square matrix, the row and column ranges are the same and 3422 the DIAGONAL part is also square. The remaining portion of the local 3423 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3424 3425 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3426 3427 You can call MatGetInfo() to get information on how effective the preallocation was; 3428 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3429 You can also run with the option -info and look for messages with the string 3430 malloc in them to see if additional memory allocation was needed. 3431 3432 Example usage: 3433 3434 Consider the following 8x8 matrix with 34 non-zero values, that is 3435 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3436 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3437 as follows: 3438 3439 .vb 3440 1 2 0 | 0 3 0 | 0 4 3441 Proc0 0 5 6 | 7 0 0 | 8 0 3442 9 0 10 | 11 0 0 | 12 0 3443 ------------------------------------- 3444 13 0 14 | 15 16 17 | 0 0 3445 Proc1 0 18 0 | 19 20 21 | 0 0 3446 0 0 0 | 22 23 0 | 24 0 3447 ------------------------------------- 3448 Proc2 25 26 27 | 0 0 28 | 29 0 3449 30 0 0 | 31 32 33 | 0 34 3450 .ve 3451 3452 This can be represented as a collection of submatrices as: 3453 3454 .vb 3455 A B C 3456 D E F 3457 G H I 3458 .ve 3459 3460 Where the submatrices A,B,C are owned by proc0, D,E,F are 3461 owned by proc1, G,H,I are owned by proc2. 3462 3463 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3464 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3465 The 'M','N' parameters are 8,8, and have the same values on all procs. 3466 3467 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3468 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3469 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3470 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3471 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3472 matrix, ans [DF] as another SeqAIJ matrix. 3473 3474 When d_nz, o_nz parameters are specified, d_nz storage elements are 3475 allocated for every row of the local diagonal submatrix, and o_nz 3476 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3477 One way to choose d_nz and o_nz is to use the max nonzerors per local 3478 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3479 In this case, the values of d_nz,o_nz are: 3480 .vb 3481 proc0 : dnz = 2, o_nz = 2 3482 proc1 : dnz = 3, o_nz = 2 3483 proc2 : dnz = 1, o_nz = 4 3484 .ve 3485 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3486 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3487 for proc3. i.e we are using 12+15+10=37 storage locations to store 3488 34 values. 3489 3490 When d_nnz, o_nnz parameters are specified, the storage is specified 3491 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3492 In the above case the values for d_nnz,o_nnz are: 3493 .vb 3494 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3495 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3496 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3497 .ve 3498 Here the space allocated is sum of all the above values i.e 34, and 3499 hence pre-allocation is perfect. 3500 3501 Level: intermediate 3502 3503 .keywords: matrix, aij, compressed row, sparse, parallel 3504 3505 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3506 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3507 @*/ 3508 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3509 { 3510 PetscErrorCode ierr; 3511 3512 PetscFunctionBegin; 3513 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3514 PetscValidType(B,1); 3515 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3516 PetscFunctionReturn(0); 3517 } 3518 3519 #undef __FUNCT__ 3520 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3521 /*@ 3522 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3523 CSR format the local rows. 3524 3525 Collective on MPI_Comm 3526 3527 Input Parameters: 3528 + comm - MPI communicator 3529 . m - number of local rows (Cannot be PETSC_DECIDE) 3530 . n - This value should be the same as the local size used in creating the 3531 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3532 calculated if N is given) For square matrices n is almost always m. 3533 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3534 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3535 . i - row indices 3536 . j - column indices 3537 - a - matrix values 3538 3539 Output Parameter: 3540 . mat - the matrix 3541 3542 Level: intermediate 3543 3544 Notes: 3545 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3546 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3547 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3548 3549 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3550 3551 The format which is used for the sparse matrix input, is equivalent to a 3552 row-major ordering.. i.e for the following matrix, the input data expected is 3553 as shown: 3554 3555 1 0 0 3556 2 0 3 P0 3557 ------- 3558 4 5 6 P1 3559 3560 Process0 [P0]: rows_owned=[0,1] 3561 i = {0,1,3} [size = nrow+1 = 2+1] 3562 j = {0,0,2} [size = nz = 6] 3563 v = {1,2,3} [size = nz = 6] 3564 3565 Process1 [P1]: rows_owned=[2] 3566 i = {0,3} [size = nrow+1 = 1+1] 3567 j = {0,1,2} [size = nz = 6] 3568 v = {4,5,6} [size = nz = 6] 3569 3570 .keywords: matrix, aij, compressed row, sparse, parallel 3571 3572 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3573 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3574 @*/ 3575 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3576 { 3577 PetscErrorCode ierr; 3578 3579 PetscFunctionBegin; 3580 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3581 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3582 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3583 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3584 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3585 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3586 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3587 PetscFunctionReturn(0); 3588 } 3589 3590 #undef __FUNCT__ 3591 #define __FUNCT__ "MatCreateAIJ" 3592 /*@C 3593 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3594 (the default parallel PETSc format). For good matrix assembly performance 3595 the user should preallocate the matrix storage by setting the parameters 3596 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3597 performance can be increased by more than a factor of 50. 3598 3599 Collective on MPI_Comm 3600 3601 Input Parameters: 3602 + comm - MPI communicator 3603 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3604 This value should be the same as the local size used in creating the 3605 y vector for the matrix-vector product y = Ax. 3606 . n - This value should be the same as the local size used in creating the 3607 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3608 calculated if N is given) For square matrices n is almost always m. 3609 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3610 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3611 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3612 (same value is used for all local rows) 3613 . d_nnz - array containing the number of nonzeros in the various rows of the 3614 DIAGONAL portion of the local submatrix (possibly different for each row) 3615 or NULL, if d_nz is used to specify the nonzero structure. 3616 The size of this array is equal to the number of local rows, i.e 'm'. 3617 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3618 submatrix (same value is used for all local rows). 3619 - o_nnz - array containing the number of nonzeros in the various rows of the 3620 OFF-DIAGONAL portion of the local submatrix (possibly different for 3621 each row) or NULL, if o_nz is used to specify the nonzero 3622 structure. The size of this array is equal to the number 3623 of local rows, i.e 'm'. 3624 3625 Output Parameter: 3626 . A - the matrix 3627 3628 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3629 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3630 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3631 3632 Notes: 3633 If the *_nnz parameter is given then the *_nz parameter is ignored 3634 3635 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3636 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3637 storage requirements for this matrix. 3638 3639 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3640 processor than it must be used on all processors that share the object for 3641 that argument. 3642 3643 The user MUST specify either the local or global matrix dimensions 3644 (possibly both). 3645 3646 The parallel matrix is partitioned across processors such that the 3647 first m0 rows belong to process 0, the next m1 rows belong to 3648 process 1, the next m2 rows belong to process 2 etc.. where 3649 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3650 values corresponding to [m x N] submatrix. 3651 3652 The columns are logically partitioned with the n0 columns belonging 3653 to 0th partition, the next n1 columns belonging to the next 3654 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3655 3656 The DIAGONAL portion of the local submatrix on any given processor 3657 is the submatrix corresponding to the rows and columns m,n 3658 corresponding to the given processor. i.e diagonal matrix on 3659 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3660 etc. The remaining portion of the local submatrix [m x (N-n)] 3661 constitute the OFF-DIAGONAL portion. The example below better 3662 illustrates this concept. 3663 3664 For a square global matrix we define each processor's diagonal portion 3665 to be its local rows and the corresponding columns (a square submatrix); 3666 each processor's off-diagonal portion encompasses the remainder of the 3667 local matrix (a rectangular submatrix). 3668 3669 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3670 3671 When calling this routine with a single process communicator, a matrix of 3672 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3673 type of communicator, use the construction mechanism: 3674 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3675 3676 By default, this format uses inodes (identical nodes) when possible. 3677 We search for consecutive rows with the same nonzero structure, thereby 3678 reusing matrix information to achieve increased efficiency. 3679 3680 Options Database Keys: 3681 + -mat_no_inode - Do not use inodes 3682 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3683 - -mat_aij_oneindex - Internally use indexing starting at 1 3684 rather than 0. Note that when calling MatSetValues(), 3685 the user still MUST index entries starting at 0! 3686 3687 3688 Example usage: 3689 3690 Consider the following 8x8 matrix with 34 non-zero values, that is 3691 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3692 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3693 as follows: 3694 3695 .vb 3696 1 2 0 | 0 3 0 | 0 4 3697 Proc0 0 5 6 | 7 0 0 | 8 0 3698 9 0 10 | 11 0 0 | 12 0 3699 ------------------------------------- 3700 13 0 14 | 15 16 17 | 0 0 3701 Proc1 0 18 0 | 19 20 21 | 0 0 3702 0 0 0 | 22 23 0 | 24 0 3703 ------------------------------------- 3704 Proc2 25 26 27 | 0 0 28 | 29 0 3705 30 0 0 | 31 32 33 | 0 34 3706 .ve 3707 3708 This can be represented as a collection of submatrices as: 3709 3710 .vb 3711 A B C 3712 D E F 3713 G H I 3714 .ve 3715 3716 Where the submatrices A,B,C are owned by proc0, D,E,F are 3717 owned by proc1, G,H,I are owned by proc2. 3718 3719 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3720 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3721 The 'M','N' parameters are 8,8, and have the same values on all procs. 3722 3723 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3724 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3725 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3726 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3727 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3728 matrix, ans [DF] as another SeqAIJ matrix. 3729 3730 When d_nz, o_nz parameters are specified, d_nz storage elements are 3731 allocated for every row of the local diagonal submatrix, and o_nz 3732 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3733 One way to choose d_nz and o_nz is to use the max nonzerors per local 3734 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3735 In this case, the values of d_nz,o_nz are: 3736 .vb 3737 proc0 : dnz = 2, o_nz = 2 3738 proc1 : dnz = 3, o_nz = 2 3739 proc2 : dnz = 1, o_nz = 4 3740 .ve 3741 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3742 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3743 for proc3. i.e we are using 12+15+10=37 storage locations to store 3744 34 values. 3745 3746 When d_nnz, o_nnz parameters are specified, the storage is specified 3747 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3748 In the above case the values for d_nnz,o_nnz are: 3749 .vb 3750 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3751 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3752 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3753 .ve 3754 Here the space allocated is sum of all the above values i.e 34, and 3755 hence pre-allocation is perfect. 3756 3757 Level: intermediate 3758 3759 .keywords: matrix, aij, compressed row, sparse, parallel 3760 3761 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3762 MPIAIJ, MatCreateMPIAIJWithArrays() 3763 @*/ 3764 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) 3765 { 3766 PetscErrorCode ierr; 3767 PetscMPIInt size; 3768 3769 PetscFunctionBegin; 3770 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3771 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3772 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3773 if (size > 1) { 3774 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3775 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3776 } else { 3777 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3778 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3779 } 3780 PetscFunctionReturn(0); 3781 } 3782 3783 #undef __FUNCT__ 3784 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3785 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3786 { 3787 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3788 3789 PetscFunctionBegin; 3790 if (Ad) *Ad = a->A; 3791 if (Ao) *Ao = a->B; 3792 if (colmap) *colmap = a->garray; 3793 PetscFunctionReturn(0); 3794 } 3795 3796 #undef __FUNCT__ 3797 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3798 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3799 { 3800 PetscErrorCode ierr; 3801 PetscInt i; 3802 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3803 3804 PetscFunctionBegin; 3805 if (coloring->ctype == IS_COLORING_GLOBAL) { 3806 ISColoringValue *allcolors,*colors; 3807 ISColoring ocoloring; 3808 3809 /* set coloring for diagonal portion */ 3810 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3811 3812 /* set coloring for off-diagonal portion */ 3813 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3814 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3815 for (i=0; i<a->B->cmap->n; i++) { 3816 colors[i] = allcolors[a->garray[i]]; 3817 } 3818 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3819 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3820 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3821 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3822 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3823 ISColoringValue *colors; 3824 PetscInt *larray; 3825 ISColoring ocoloring; 3826 3827 /* set coloring for diagonal portion */ 3828 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3829 for (i=0; i<a->A->cmap->n; i++) { 3830 larray[i] = i + A->cmap->rstart; 3831 } 3832 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3833 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3834 for (i=0; i<a->A->cmap->n; i++) { 3835 colors[i] = coloring->colors[larray[i]]; 3836 } 3837 ierr = PetscFree(larray);CHKERRQ(ierr); 3838 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3839 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3840 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3841 3842 /* set coloring for off-diagonal portion */ 3843 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3844 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3845 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3846 for (i=0; i<a->B->cmap->n; i++) { 3847 colors[i] = coloring->colors[larray[i]]; 3848 } 3849 ierr = PetscFree(larray);CHKERRQ(ierr); 3850 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3851 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3852 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3853 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3854 PetscFunctionReturn(0); 3855 } 3856 3857 #undef __FUNCT__ 3858 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3859 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3860 { 3861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3862 PetscErrorCode ierr; 3863 3864 PetscFunctionBegin; 3865 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3866 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3867 PetscFunctionReturn(0); 3868 } 3869 3870 #undef __FUNCT__ 3871 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3872 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3873 { 3874 PetscErrorCode ierr; 3875 PetscInt m,N,i,rstart,nnz,Ii; 3876 PetscInt *indx; 3877 PetscScalar *values; 3878 3879 PetscFunctionBegin; 3880 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3881 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3882 PetscInt *dnz,*onz,sum,bs,cbs; 3883 3884 if (n == PETSC_DECIDE) { 3885 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3886 } 3887 /* Check sum(n) = N */ 3888 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3889 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3890 3891 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3892 rstart -= m; 3893 3894 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3895 for (i=0; i<m; i++) { 3896 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3897 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3898 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3899 } 3900 3901 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3902 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3903 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3904 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3905 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3906 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3907 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3908 } 3909 3910 /* numeric phase */ 3911 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3912 for (i=0; i<m; i++) { 3913 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3914 Ii = i + rstart; 3915 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3916 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3917 } 3918 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3919 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3920 PetscFunctionReturn(0); 3921 } 3922 3923 #undef __FUNCT__ 3924 #define __FUNCT__ "MatFileSplit" 3925 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3926 { 3927 PetscErrorCode ierr; 3928 PetscMPIInt rank; 3929 PetscInt m,N,i,rstart,nnz; 3930 size_t len; 3931 const PetscInt *indx; 3932 PetscViewer out; 3933 char *name; 3934 Mat B; 3935 const PetscScalar *values; 3936 3937 PetscFunctionBegin; 3938 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3939 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3940 /* Should this be the type of the diagonal block of A? */ 3941 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3942 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3943 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3944 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3945 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3946 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3947 for (i=0; i<m; i++) { 3948 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3949 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3950 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3951 } 3952 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3953 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3954 3955 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3956 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3957 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3958 sprintf(name,"%s.%d",outfile,rank); 3959 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3960 ierr = PetscFree(name);CHKERRQ(ierr); 3961 ierr = MatView(B,out);CHKERRQ(ierr); 3962 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3963 ierr = MatDestroy(&B);CHKERRQ(ierr); 3964 PetscFunctionReturn(0); 3965 } 3966 3967 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3968 #undef __FUNCT__ 3969 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3970 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3971 { 3972 PetscErrorCode ierr; 3973 Mat_Merge_SeqsToMPI *merge; 3974 PetscContainer container; 3975 3976 PetscFunctionBegin; 3977 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3978 if (container) { 3979 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3980 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3981 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3982 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3983 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3984 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3985 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3986 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3987 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3988 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3989 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3990 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3991 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3992 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3993 ierr = PetscFree(merge);CHKERRQ(ierr); 3994 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3995 } 3996 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3997 PetscFunctionReturn(0); 3998 } 3999 4000 #include <../src/mat/utils/freespace.h> 4001 #include <petscbt.h> 4002 4003 #undef __FUNCT__ 4004 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4005 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4006 { 4007 PetscErrorCode ierr; 4008 MPI_Comm comm; 4009 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4010 PetscMPIInt size,rank,taga,*len_s; 4011 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4012 PetscInt proc,m; 4013 PetscInt **buf_ri,**buf_rj; 4014 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4015 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4016 MPI_Request *s_waits,*r_waits; 4017 MPI_Status *status; 4018 MatScalar *aa=a->a; 4019 MatScalar **abuf_r,*ba_i; 4020 Mat_Merge_SeqsToMPI *merge; 4021 PetscContainer container; 4022 4023 PetscFunctionBegin; 4024 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4025 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4026 4027 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4028 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4029 4030 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4031 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4032 4033 bi = merge->bi; 4034 bj = merge->bj; 4035 buf_ri = merge->buf_ri; 4036 buf_rj = merge->buf_rj; 4037 4038 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4039 owners = merge->rowmap->range; 4040 len_s = merge->len_s; 4041 4042 /* send and recv matrix values */ 4043 /*-----------------------------*/ 4044 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4045 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4046 4047 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4048 for (proc=0,k=0; proc<size; proc++) { 4049 if (!len_s[proc]) continue; 4050 i = owners[proc]; 4051 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4052 k++; 4053 } 4054 4055 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4056 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4057 ierr = PetscFree(status);CHKERRQ(ierr); 4058 4059 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4060 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4061 4062 /* insert mat values of mpimat */ 4063 /*----------------------------*/ 4064 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4065 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4066 4067 for (k=0; k<merge->nrecv; k++) { 4068 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4069 nrows = *(buf_ri_k[k]); 4070 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4071 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4072 } 4073 4074 /* set values of ba */ 4075 m = merge->rowmap->n; 4076 for (i=0; i<m; i++) { 4077 arow = owners[rank] + i; 4078 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4079 bnzi = bi[i+1] - bi[i]; 4080 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4081 4082 /* add local non-zero vals of this proc's seqmat into ba */ 4083 anzi = ai[arow+1] - ai[arow]; 4084 aj = a->j + ai[arow]; 4085 aa = a->a + ai[arow]; 4086 nextaj = 0; 4087 for (j=0; nextaj<anzi; j++) { 4088 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4089 ba_i[j] += aa[nextaj++]; 4090 } 4091 } 4092 4093 /* add received vals into ba */ 4094 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4095 /* i-th row */ 4096 if (i == *nextrow[k]) { 4097 anzi = *(nextai[k]+1) - *nextai[k]; 4098 aj = buf_rj[k] + *(nextai[k]); 4099 aa = abuf_r[k] + *(nextai[k]); 4100 nextaj = 0; 4101 for (j=0; nextaj<anzi; j++) { 4102 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4103 ba_i[j] += aa[nextaj++]; 4104 } 4105 } 4106 nextrow[k]++; nextai[k]++; 4107 } 4108 } 4109 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4110 } 4111 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4112 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4113 4114 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4115 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4116 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4117 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4118 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4119 PetscFunctionReturn(0); 4120 } 4121 4122 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4123 4124 #undef __FUNCT__ 4125 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4126 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4127 { 4128 PetscErrorCode ierr; 4129 Mat B_mpi; 4130 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4131 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4132 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4133 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4134 PetscInt len,proc,*dnz,*onz,bs,cbs; 4135 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4136 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4137 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4138 MPI_Status *status; 4139 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4140 PetscBT lnkbt; 4141 Mat_Merge_SeqsToMPI *merge; 4142 PetscContainer container; 4143 4144 PetscFunctionBegin; 4145 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4146 4147 /* make sure it is a PETSc comm */ 4148 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4149 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4150 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4151 4152 ierr = PetscNew(&merge);CHKERRQ(ierr); 4153 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4154 4155 /* determine row ownership */ 4156 /*---------------------------------------------------------*/ 4157 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4158 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4159 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4160 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4161 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4162 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4163 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4164 4165 m = merge->rowmap->n; 4166 owners = merge->rowmap->range; 4167 4168 /* determine the number of messages to send, their lengths */ 4169 /*---------------------------------------------------------*/ 4170 len_s = merge->len_s; 4171 4172 len = 0; /* length of buf_si[] */ 4173 merge->nsend = 0; 4174 for (proc=0; proc<size; proc++) { 4175 len_si[proc] = 0; 4176 if (proc == rank) { 4177 len_s[proc] = 0; 4178 } else { 4179 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4180 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4181 } 4182 if (len_s[proc]) { 4183 merge->nsend++; 4184 nrows = 0; 4185 for (i=owners[proc]; i<owners[proc+1]; i++) { 4186 if (ai[i+1] > ai[i]) nrows++; 4187 } 4188 len_si[proc] = 2*(nrows+1); 4189 len += len_si[proc]; 4190 } 4191 } 4192 4193 /* determine the number and length of messages to receive for ij-structure */ 4194 /*-------------------------------------------------------------------------*/ 4195 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4196 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4197 4198 /* post the Irecv of j-structure */ 4199 /*-------------------------------*/ 4200 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4201 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4202 4203 /* post the Isend of j-structure */ 4204 /*--------------------------------*/ 4205 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4206 4207 for (proc=0, k=0; proc<size; proc++) { 4208 if (!len_s[proc]) continue; 4209 i = owners[proc]; 4210 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4211 k++; 4212 } 4213 4214 /* receives and sends of j-structure are complete */ 4215 /*------------------------------------------------*/ 4216 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4217 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4218 4219 /* send and recv i-structure */ 4220 /*---------------------------*/ 4221 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4222 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4223 4224 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4225 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4226 for (proc=0,k=0; proc<size; proc++) { 4227 if (!len_s[proc]) continue; 4228 /* form outgoing message for i-structure: 4229 buf_si[0]: nrows to be sent 4230 [1:nrows]: row index (global) 4231 [nrows+1:2*nrows+1]: i-structure index 4232 */ 4233 /*-------------------------------------------*/ 4234 nrows = len_si[proc]/2 - 1; 4235 buf_si_i = buf_si + nrows+1; 4236 buf_si[0] = nrows; 4237 buf_si_i[0] = 0; 4238 nrows = 0; 4239 for (i=owners[proc]; i<owners[proc+1]; i++) { 4240 anzi = ai[i+1] - ai[i]; 4241 if (anzi) { 4242 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4243 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4244 nrows++; 4245 } 4246 } 4247 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4248 k++; 4249 buf_si += len_si[proc]; 4250 } 4251 4252 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4253 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4254 4255 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4256 for (i=0; i<merge->nrecv; i++) { 4257 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); 4258 } 4259 4260 ierr = PetscFree(len_si);CHKERRQ(ierr); 4261 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4262 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4263 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4264 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4265 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4266 ierr = PetscFree(status);CHKERRQ(ierr); 4267 4268 /* compute a local seq matrix in each processor */ 4269 /*----------------------------------------------*/ 4270 /* allocate bi array and free space for accumulating nonzero column info */ 4271 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4272 bi[0] = 0; 4273 4274 /* create and initialize a linked list */ 4275 nlnk = N+1; 4276 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4277 4278 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4279 len = ai[owners[rank+1]] - ai[owners[rank]]; 4280 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4281 4282 current_space = free_space; 4283 4284 /* determine symbolic info for each local row */ 4285 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4286 4287 for (k=0; k<merge->nrecv; k++) { 4288 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4289 nrows = *buf_ri_k[k]; 4290 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4291 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4292 } 4293 4294 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4295 len = 0; 4296 for (i=0; i<m; i++) { 4297 bnzi = 0; 4298 /* add local non-zero cols of this proc's seqmat into lnk */ 4299 arow = owners[rank] + i; 4300 anzi = ai[arow+1] - ai[arow]; 4301 aj = a->j + ai[arow]; 4302 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4303 bnzi += nlnk; 4304 /* add received col data into lnk */ 4305 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4306 if (i == *nextrow[k]) { /* i-th row */ 4307 anzi = *(nextai[k]+1) - *nextai[k]; 4308 aj = buf_rj[k] + *nextai[k]; 4309 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4310 bnzi += nlnk; 4311 nextrow[k]++; nextai[k]++; 4312 } 4313 } 4314 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4315 4316 /* if free space is not available, make more free space */ 4317 if (current_space->local_remaining<bnzi) { 4318 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4319 nspacedouble++; 4320 } 4321 /* copy data into free space, then initialize lnk */ 4322 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4323 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4324 4325 current_space->array += bnzi; 4326 current_space->local_used += bnzi; 4327 current_space->local_remaining -= bnzi; 4328 4329 bi[i+1] = bi[i] + bnzi; 4330 } 4331 4332 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4333 4334 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4335 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4336 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4337 4338 /* create symbolic parallel matrix B_mpi */ 4339 /*---------------------------------------*/ 4340 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4341 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4342 if (n==PETSC_DECIDE) { 4343 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4344 } else { 4345 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4346 } 4347 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4348 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4349 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4350 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4351 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4352 4353 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4354 B_mpi->assembled = PETSC_FALSE; 4355 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4356 merge->bi = bi; 4357 merge->bj = bj; 4358 merge->buf_ri = buf_ri; 4359 merge->buf_rj = buf_rj; 4360 merge->coi = NULL; 4361 merge->coj = NULL; 4362 merge->owners_co = NULL; 4363 4364 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4365 4366 /* attach the supporting struct to B_mpi for reuse */ 4367 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4368 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4369 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4370 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4371 *mpimat = B_mpi; 4372 4373 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4374 PetscFunctionReturn(0); 4375 } 4376 4377 #undef __FUNCT__ 4378 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4379 /*@C 4380 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4381 matrices from each processor 4382 4383 Collective on MPI_Comm 4384 4385 Input Parameters: 4386 + comm - the communicators the parallel matrix will live on 4387 . seqmat - the input sequential matrices 4388 . m - number of local rows (or PETSC_DECIDE) 4389 . n - number of local columns (or PETSC_DECIDE) 4390 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4391 4392 Output Parameter: 4393 . mpimat - the parallel matrix generated 4394 4395 Level: advanced 4396 4397 Notes: 4398 The dimensions of the sequential matrix in each processor MUST be the same. 4399 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4400 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4401 @*/ 4402 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4403 { 4404 PetscErrorCode ierr; 4405 PetscMPIInt size; 4406 4407 PetscFunctionBegin; 4408 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4409 if (size == 1) { 4410 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4411 if (scall == MAT_INITIAL_MATRIX) { 4412 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4413 } else { 4414 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4415 } 4416 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4417 PetscFunctionReturn(0); 4418 } 4419 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4420 if (scall == MAT_INITIAL_MATRIX) { 4421 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4422 } 4423 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4424 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4425 PetscFunctionReturn(0); 4426 } 4427 4428 #undef __FUNCT__ 4429 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4430 /*@ 4431 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4432 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4433 with MatGetSize() 4434 4435 Not Collective 4436 4437 Input Parameters: 4438 + A - the matrix 4439 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4440 4441 Output Parameter: 4442 . A_loc - the local sequential matrix generated 4443 4444 Level: developer 4445 4446 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4447 4448 @*/ 4449 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4450 { 4451 PetscErrorCode ierr; 4452 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4453 Mat_SeqAIJ *mat,*a,*b; 4454 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4455 MatScalar *aa,*ba,*cam; 4456 PetscScalar *ca; 4457 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4458 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4459 PetscBool match; 4460 MPI_Comm comm; 4461 PetscMPIInt size; 4462 4463 PetscFunctionBegin; 4464 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4465 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4466 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4467 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4468 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4469 4470 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4471 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4472 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4473 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4474 aa = a->a; ba = b->a; 4475 if (scall == MAT_INITIAL_MATRIX) { 4476 if (size == 1) { 4477 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4478 PetscFunctionReturn(0); 4479 } 4480 4481 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4482 ci[0] = 0; 4483 for (i=0; i<am; i++) { 4484 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4485 } 4486 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4487 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4488 k = 0; 4489 for (i=0; i<am; i++) { 4490 ncols_o = bi[i+1] - bi[i]; 4491 ncols_d = ai[i+1] - ai[i]; 4492 /* off-diagonal portion of A */ 4493 for (jo=0; jo<ncols_o; jo++) { 4494 col = cmap[*bj]; 4495 if (col >= cstart) break; 4496 cj[k] = col; bj++; 4497 ca[k++] = *ba++; 4498 } 4499 /* diagonal portion of A */ 4500 for (j=0; j<ncols_d; j++) { 4501 cj[k] = cstart + *aj++; 4502 ca[k++] = *aa++; 4503 } 4504 /* off-diagonal portion of A */ 4505 for (j=jo; j<ncols_o; j++) { 4506 cj[k] = cmap[*bj++]; 4507 ca[k++] = *ba++; 4508 } 4509 } 4510 /* put together the new matrix */ 4511 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4512 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4513 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4514 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4515 mat->free_a = PETSC_TRUE; 4516 mat->free_ij = PETSC_TRUE; 4517 mat->nonew = 0; 4518 } else if (scall == MAT_REUSE_MATRIX) { 4519 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4520 ci = mat->i; cj = mat->j; cam = mat->a; 4521 for (i=0; i<am; i++) { 4522 /* off-diagonal portion of A */ 4523 ncols_o = bi[i+1] - bi[i]; 4524 for (jo=0; jo<ncols_o; jo++) { 4525 col = cmap[*bj]; 4526 if (col >= cstart) break; 4527 *cam++ = *ba++; bj++; 4528 } 4529 /* diagonal portion of A */ 4530 ncols_d = ai[i+1] - ai[i]; 4531 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4532 /* off-diagonal portion of A */ 4533 for (j=jo; j<ncols_o; j++) { 4534 *cam++ = *ba++; bj++; 4535 } 4536 } 4537 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4538 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4539 PetscFunctionReturn(0); 4540 } 4541 4542 #undef __FUNCT__ 4543 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4544 /*@C 4545 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4546 4547 Not Collective 4548 4549 Input Parameters: 4550 + A - the matrix 4551 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4552 - row, col - index sets of rows and columns to extract (or NULL) 4553 4554 Output Parameter: 4555 . A_loc - the local sequential matrix generated 4556 4557 Level: developer 4558 4559 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4560 4561 @*/ 4562 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4563 { 4564 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4565 PetscErrorCode ierr; 4566 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4567 IS isrowa,iscola; 4568 Mat *aloc; 4569 PetscBool match; 4570 4571 PetscFunctionBegin; 4572 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4573 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4574 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4575 if (!row) { 4576 start = A->rmap->rstart; end = A->rmap->rend; 4577 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4578 } else { 4579 isrowa = *row; 4580 } 4581 if (!col) { 4582 start = A->cmap->rstart; 4583 cmap = a->garray; 4584 nzA = a->A->cmap->n; 4585 nzB = a->B->cmap->n; 4586 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4587 ncols = 0; 4588 for (i=0; i<nzB; i++) { 4589 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4590 else break; 4591 } 4592 imark = i; 4593 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4594 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4595 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4596 } else { 4597 iscola = *col; 4598 } 4599 if (scall != MAT_INITIAL_MATRIX) { 4600 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4601 aloc[0] = *A_loc; 4602 } 4603 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4604 *A_loc = aloc[0]; 4605 ierr = PetscFree(aloc);CHKERRQ(ierr); 4606 if (!row) { 4607 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4608 } 4609 if (!col) { 4610 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4611 } 4612 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4613 PetscFunctionReturn(0); 4614 } 4615 4616 #undef __FUNCT__ 4617 #define __FUNCT__ "MatGetBrowsOfAcols" 4618 /*@C 4619 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4620 4621 Collective on Mat 4622 4623 Input Parameters: 4624 + A,B - the matrices in mpiaij format 4625 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4626 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4627 4628 Output Parameter: 4629 + rowb, colb - index sets of rows and columns of B to extract 4630 - B_seq - the sequential matrix generated 4631 4632 Level: developer 4633 4634 @*/ 4635 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4636 { 4637 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4638 PetscErrorCode ierr; 4639 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4640 IS isrowb,iscolb; 4641 Mat *bseq=NULL; 4642 4643 PetscFunctionBegin; 4644 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4645 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); 4646 } 4647 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4648 4649 if (scall == MAT_INITIAL_MATRIX) { 4650 start = A->cmap->rstart; 4651 cmap = a->garray; 4652 nzA = a->A->cmap->n; 4653 nzB = a->B->cmap->n; 4654 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4655 ncols = 0; 4656 for (i=0; i<nzB; i++) { /* row < local row index */ 4657 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4658 else break; 4659 } 4660 imark = i; 4661 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4662 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4663 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4664 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4665 } else { 4666 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4667 isrowb = *rowb; iscolb = *colb; 4668 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4669 bseq[0] = *B_seq; 4670 } 4671 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4672 *B_seq = bseq[0]; 4673 ierr = PetscFree(bseq);CHKERRQ(ierr); 4674 if (!rowb) { 4675 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4676 } else { 4677 *rowb = isrowb; 4678 } 4679 if (!colb) { 4680 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4681 } else { 4682 *colb = iscolb; 4683 } 4684 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4685 PetscFunctionReturn(0); 4686 } 4687 4688 #undef __FUNCT__ 4689 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4690 /* 4691 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4692 of the OFF-DIAGONAL portion of local A 4693 4694 Collective on Mat 4695 4696 Input Parameters: 4697 + A,B - the matrices in mpiaij format 4698 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4699 4700 Output Parameter: 4701 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4702 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4703 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4704 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4705 4706 Level: developer 4707 4708 */ 4709 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4710 { 4711 VecScatter_MPI_General *gen_to,*gen_from; 4712 PetscErrorCode ierr; 4713 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4714 Mat_SeqAIJ *b_oth; 4715 VecScatter ctx =a->Mvctx; 4716 MPI_Comm comm; 4717 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4718 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4719 PetscScalar *rvalues,*svalues; 4720 MatScalar *b_otha,*bufa,*bufA; 4721 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4722 MPI_Request *rwaits = NULL,*swaits = NULL; 4723 MPI_Status *sstatus,rstatus; 4724 PetscMPIInt jj,size; 4725 PetscInt *cols,sbs,rbs; 4726 PetscScalar *vals; 4727 4728 PetscFunctionBegin; 4729 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4730 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4731 4732 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4733 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); 4734 } 4735 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4736 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4737 4738 gen_to = (VecScatter_MPI_General*)ctx->todata; 4739 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4740 rvalues = gen_from->values; /* holds the length of receiving row */ 4741 svalues = gen_to->values; /* holds the length of sending row */ 4742 nrecvs = gen_from->n; 4743 nsends = gen_to->n; 4744 4745 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4746 srow = gen_to->indices; /* local row index to be sent */ 4747 sstarts = gen_to->starts; 4748 sprocs = gen_to->procs; 4749 sstatus = gen_to->sstatus; 4750 sbs = gen_to->bs; 4751 rstarts = gen_from->starts; 4752 rprocs = gen_from->procs; 4753 rbs = gen_from->bs; 4754 4755 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4756 if (scall == MAT_INITIAL_MATRIX) { 4757 /* i-array */ 4758 /*---------*/ 4759 /* post receives */ 4760 for (i=0; i<nrecvs; i++) { 4761 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4762 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4763 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4764 } 4765 4766 /* pack the outgoing message */ 4767 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4768 4769 sstartsj[0] = 0; 4770 rstartsj[0] = 0; 4771 len = 0; /* total length of j or a array to be sent */ 4772 k = 0; 4773 for (i=0; i<nsends; i++) { 4774 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4775 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4776 for (j=0; j<nrows; j++) { 4777 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4778 for (l=0; l<sbs; l++) { 4779 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4780 4781 rowlen[j*sbs+l] = ncols; 4782 4783 len += ncols; 4784 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4785 } 4786 k++; 4787 } 4788 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4789 4790 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4791 } 4792 /* recvs and sends of i-array are completed */ 4793 i = nrecvs; 4794 while (i--) { 4795 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4796 } 4797 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4798 4799 /* allocate buffers for sending j and a arrays */ 4800 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4801 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4802 4803 /* create i-array of B_oth */ 4804 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4805 4806 b_othi[0] = 0; 4807 len = 0; /* total length of j or a array to be received */ 4808 k = 0; 4809 for (i=0; i<nrecvs; i++) { 4810 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4811 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4812 for (j=0; j<nrows; j++) { 4813 b_othi[k+1] = b_othi[k] + rowlen[j]; 4814 len += rowlen[j]; k++; 4815 } 4816 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4817 } 4818 4819 /* allocate space for j and a arrrays of B_oth */ 4820 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4821 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4822 4823 /* j-array */ 4824 /*---------*/ 4825 /* post receives of j-array */ 4826 for (i=0; i<nrecvs; i++) { 4827 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4828 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4829 } 4830 4831 /* pack the outgoing message j-array */ 4832 k = 0; 4833 for (i=0; i<nsends; i++) { 4834 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4835 bufJ = bufj+sstartsj[i]; 4836 for (j=0; j<nrows; j++) { 4837 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4838 for (ll=0; ll<sbs; ll++) { 4839 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4840 for (l=0; l<ncols; l++) { 4841 *bufJ++ = cols[l]; 4842 } 4843 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4844 } 4845 } 4846 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4847 } 4848 4849 /* recvs and sends of j-array are completed */ 4850 i = nrecvs; 4851 while (i--) { 4852 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4853 } 4854 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4855 } else if (scall == MAT_REUSE_MATRIX) { 4856 sstartsj = *startsj_s; 4857 rstartsj = *startsj_r; 4858 bufa = *bufa_ptr; 4859 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4860 b_otha = b_oth->a; 4861 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4862 4863 /* a-array */ 4864 /*---------*/ 4865 /* post receives of a-array */ 4866 for (i=0; i<nrecvs; i++) { 4867 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4868 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4869 } 4870 4871 /* pack the outgoing message a-array */ 4872 k = 0; 4873 for (i=0; i<nsends; i++) { 4874 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4875 bufA = bufa+sstartsj[i]; 4876 for (j=0; j<nrows; j++) { 4877 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4878 for (ll=0; ll<sbs; ll++) { 4879 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4880 for (l=0; l<ncols; l++) { 4881 *bufA++ = vals[l]; 4882 } 4883 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4884 } 4885 } 4886 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4887 } 4888 /* recvs and sends of a-array are completed */ 4889 i = nrecvs; 4890 while (i--) { 4891 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4892 } 4893 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4894 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4895 4896 if (scall == MAT_INITIAL_MATRIX) { 4897 /* put together the new matrix */ 4898 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4899 4900 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4901 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4902 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4903 b_oth->free_a = PETSC_TRUE; 4904 b_oth->free_ij = PETSC_TRUE; 4905 b_oth->nonew = 0; 4906 4907 ierr = PetscFree(bufj);CHKERRQ(ierr); 4908 if (!startsj_s || !bufa_ptr) { 4909 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4910 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4911 } else { 4912 *startsj_s = sstartsj; 4913 *startsj_r = rstartsj; 4914 *bufa_ptr = bufa; 4915 } 4916 } 4917 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4918 PetscFunctionReturn(0); 4919 } 4920 4921 #undef __FUNCT__ 4922 #define __FUNCT__ "MatGetCommunicationStructs" 4923 /*@C 4924 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4925 4926 Not Collective 4927 4928 Input Parameters: 4929 . A - The matrix in mpiaij format 4930 4931 Output Parameter: 4932 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4933 . colmap - A map from global column index to local index into lvec 4934 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4935 4936 Level: developer 4937 4938 @*/ 4939 #if defined(PETSC_USE_CTABLE) 4940 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4941 #else 4942 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4943 #endif 4944 { 4945 Mat_MPIAIJ *a; 4946 4947 PetscFunctionBegin; 4948 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4949 PetscValidPointer(lvec, 2); 4950 PetscValidPointer(colmap, 3); 4951 PetscValidPointer(multScatter, 4); 4952 a = (Mat_MPIAIJ*) A->data; 4953 if (lvec) *lvec = a->lvec; 4954 if (colmap) *colmap = a->colmap; 4955 if (multScatter) *multScatter = a->Mvctx; 4956 PetscFunctionReturn(0); 4957 } 4958 4959 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4960 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4961 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4962 #if defined(PETSC_HAVE_ELEMENTAL) 4963 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4964 #endif 4965 4966 #undef __FUNCT__ 4967 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4968 /* 4969 Computes (B'*A')' since computing B*A directly is untenable 4970 4971 n p p 4972 ( ) ( ) ( ) 4973 m ( A ) * n ( B ) = m ( C ) 4974 ( ) ( ) ( ) 4975 4976 */ 4977 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4978 { 4979 PetscErrorCode ierr; 4980 Mat At,Bt,Ct; 4981 4982 PetscFunctionBegin; 4983 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4984 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4985 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4986 ierr = MatDestroy(&At);CHKERRQ(ierr); 4987 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4988 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4989 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4990 PetscFunctionReturn(0); 4991 } 4992 4993 #undef __FUNCT__ 4994 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4995 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4996 { 4997 PetscErrorCode ierr; 4998 PetscInt m=A->rmap->n,n=B->cmap->n; 4999 Mat Cmat; 5000 5001 PetscFunctionBegin; 5002 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); 5003 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5004 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5005 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5006 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5007 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5008 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5009 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5010 5011 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5012 5013 *C = Cmat; 5014 PetscFunctionReturn(0); 5015 } 5016 5017 /* ----------------------------------------------------------------*/ 5018 #undef __FUNCT__ 5019 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5020 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5021 { 5022 PetscErrorCode ierr; 5023 5024 PetscFunctionBegin; 5025 if (scall == MAT_INITIAL_MATRIX) { 5026 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5027 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5028 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5029 } 5030 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5031 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5032 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5033 PetscFunctionReturn(0); 5034 } 5035 5036 /*MC 5037 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5038 5039 Options Database Keys: 5040 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5041 5042 Level: beginner 5043 5044 .seealso: MatCreateAIJ() 5045 M*/ 5046 5047 #undef __FUNCT__ 5048 #define __FUNCT__ "MatCreate_MPIAIJ" 5049 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5050 { 5051 Mat_MPIAIJ *b; 5052 PetscErrorCode ierr; 5053 PetscMPIInt size; 5054 5055 PetscFunctionBegin; 5056 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5057 5058 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5059 B->data = (void*)b; 5060 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5061 B->assembled = PETSC_FALSE; 5062 B->insertmode = NOT_SET_VALUES; 5063 b->size = size; 5064 5065 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5066 5067 /* build cache for off array entries formed */ 5068 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5069 5070 b->donotstash = PETSC_FALSE; 5071 b->colmap = 0; 5072 b->garray = 0; 5073 b->roworiented = PETSC_TRUE; 5074 5075 /* stuff used for matrix vector multiply */ 5076 b->lvec = NULL; 5077 b->Mvctx = NULL; 5078 5079 /* stuff for MatGetRow() */ 5080 b->rowindices = 0; 5081 b->rowvalues = 0; 5082 b->getrowactive = PETSC_FALSE; 5083 5084 /* flexible pointer used in CUSP/CUSPARSE classes */ 5085 b->spptr = NULL; 5086 5087 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5091 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5092 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5093 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5094 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5095 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5096 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5097 #if defined(PETSC_HAVE_ELEMENTAL) 5098 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5099 #endif 5100 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5101 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5102 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5103 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5104 PetscFunctionReturn(0); 5105 } 5106 5107 #undef __FUNCT__ 5108 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5109 /*@C 5110 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5111 and "off-diagonal" part of the matrix in CSR format. 5112 5113 Collective on MPI_Comm 5114 5115 Input Parameters: 5116 + comm - MPI communicator 5117 . m - number of local rows (Cannot be PETSC_DECIDE) 5118 . n - This value should be the same as the local size used in creating the 5119 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5120 calculated if N is given) For square matrices n is almost always m. 5121 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5122 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5123 . i - row indices for "diagonal" portion of matrix 5124 . j - column indices 5125 . a - matrix values 5126 . oi - row indices for "off-diagonal" portion of matrix 5127 . oj - column indices 5128 - oa - matrix values 5129 5130 Output Parameter: 5131 . mat - the matrix 5132 5133 Level: advanced 5134 5135 Notes: 5136 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5137 must free the arrays once the matrix has been destroyed and not before. 5138 5139 The i and j indices are 0 based 5140 5141 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5142 5143 This sets local rows and cannot be used to set off-processor values. 5144 5145 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5146 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5147 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5148 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5149 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5150 communication if it is known that only local entries will be set. 5151 5152 .keywords: matrix, aij, compressed row, sparse, parallel 5153 5154 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5155 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5156 @*/ 5157 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) 5158 { 5159 PetscErrorCode ierr; 5160 Mat_MPIAIJ *maij; 5161 5162 PetscFunctionBegin; 5163 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5164 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5165 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5166 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5167 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5168 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5169 maij = (Mat_MPIAIJ*) (*mat)->data; 5170 5171 (*mat)->preallocated = PETSC_TRUE; 5172 5173 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5174 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5175 5176 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5177 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5178 5179 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5180 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5181 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5182 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5183 5184 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5185 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5186 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5187 PetscFunctionReturn(0); 5188 } 5189 5190 /* 5191 Special version for direct calls from Fortran 5192 */ 5193 #include <petsc/private/fortranimpl.h> 5194 5195 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5196 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5197 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5198 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5199 #endif 5200 5201 /* Change these macros so can be used in void function */ 5202 #undef CHKERRQ 5203 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5204 #undef SETERRQ2 5205 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5206 #undef SETERRQ3 5207 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5208 #undef SETERRQ 5209 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5210 5211 #undef __FUNCT__ 5212 #define __FUNCT__ "matsetvaluesmpiaij_" 5213 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) 5214 { 5215 Mat mat = *mmat; 5216 PetscInt m = *mm, n = *mn; 5217 InsertMode addv = *maddv; 5218 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5219 PetscScalar value; 5220 PetscErrorCode ierr; 5221 5222 MatCheckPreallocated(mat,1); 5223 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5224 5225 #if defined(PETSC_USE_DEBUG) 5226 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5227 #endif 5228 { 5229 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5230 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5231 PetscBool roworiented = aij->roworiented; 5232 5233 /* Some Variables required in the macro */ 5234 Mat A = aij->A; 5235 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5236 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5237 MatScalar *aa = a->a; 5238 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5239 Mat B = aij->B; 5240 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5241 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5242 MatScalar *ba = b->a; 5243 5244 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5245 PetscInt nonew = a->nonew; 5246 MatScalar *ap1,*ap2; 5247 5248 PetscFunctionBegin; 5249 for (i=0; i<m; i++) { 5250 if (im[i] < 0) continue; 5251 #if defined(PETSC_USE_DEBUG) 5252 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); 5253 #endif 5254 if (im[i] >= rstart && im[i] < rend) { 5255 row = im[i] - rstart; 5256 lastcol1 = -1; 5257 rp1 = aj + ai[row]; 5258 ap1 = aa + ai[row]; 5259 rmax1 = aimax[row]; 5260 nrow1 = ailen[row]; 5261 low1 = 0; 5262 high1 = nrow1; 5263 lastcol2 = -1; 5264 rp2 = bj + bi[row]; 5265 ap2 = ba + bi[row]; 5266 rmax2 = bimax[row]; 5267 nrow2 = bilen[row]; 5268 low2 = 0; 5269 high2 = nrow2; 5270 5271 for (j=0; j<n; j++) { 5272 if (roworiented) value = v[i*n+j]; 5273 else value = v[i+j*m]; 5274 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5275 if (in[j] >= cstart && in[j] < cend) { 5276 col = in[j] - cstart; 5277 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5278 } else if (in[j] < 0) continue; 5279 #if defined(PETSC_USE_DEBUG) 5280 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); 5281 #endif 5282 else { 5283 if (mat->was_assembled) { 5284 if (!aij->colmap) { 5285 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5286 } 5287 #if defined(PETSC_USE_CTABLE) 5288 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5289 col--; 5290 #else 5291 col = aij->colmap[in[j]] - 1; 5292 #endif 5293 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5294 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5295 col = in[j]; 5296 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5297 B = aij->B; 5298 b = (Mat_SeqAIJ*)B->data; 5299 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5300 rp2 = bj + bi[row]; 5301 ap2 = ba + bi[row]; 5302 rmax2 = bimax[row]; 5303 nrow2 = bilen[row]; 5304 low2 = 0; 5305 high2 = nrow2; 5306 bm = aij->B->rmap->n; 5307 ba = b->a; 5308 } 5309 } else col = in[j]; 5310 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5311 } 5312 } 5313 } else if (!aij->donotstash) { 5314 if (roworiented) { 5315 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5316 } else { 5317 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5318 } 5319 } 5320 } 5321 } 5322 PetscFunctionReturnVoid(); 5323 } 5324 5325