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