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 1567 matin->errortype = mat->A->errortype; 1568 PetscFunctionReturn(0); 1569 } 1570 1571 #undef __FUNCT__ 1572 #define __FUNCT__ "MatPermute_MPIAIJ" 1573 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1574 { 1575 Mat aA,aB,Aperm; 1576 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1577 PetscScalar *aa,*ba; 1578 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1579 PetscSF rowsf,sf; 1580 IS parcolp = NULL; 1581 PetscBool done; 1582 PetscErrorCode ierr; 1583 1584 PetscFunctionBegin; 1585 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1586 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1587 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1588 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1589 1590 /* Invert row permutation to find out where my rows should go */ 1591 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1592 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1593 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1594 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1595 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1596 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1597 1598 /* Invert column permutation to find out where my columns should go */ 1599 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1600 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1601 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1602 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1603 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1604 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1605 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1606 1607 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1608 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1609 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1610 1611 /* Find out where my gcols should go */ 1612 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1613 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1614 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1615 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1616 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1617 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1618 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1619 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1620 1621 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1622 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1623 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1624 for (i=0; i<m; i++) { 1625 PetscInt row = rdest[i],rowner; 1626 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1627 for (j=ai[i]; j<ai[i+1]; j++) { 1628 PetscInt cowner,col = cdest[aj[j]]; 1629 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1630 if (rowner == cowner) dnnz[i]++; 1631 else onnz[i]++; 1632 } 1633 for (j=bi[i]; j<bi[i+1]; j++) { 1634 PetscInt cowner,col = gcdest[bj[j]]; 1635 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1636 if (rowner == cowner) dnnz[i]++; 1637 else onnz[i]++; 1638 } 1639 } 1640 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1641 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1642 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1643 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1644 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1645 1646 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1647 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1648 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1649 for (i=0; i<m; i++) { 1650 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1651 PetscInt j0,rowlen; 1652 rowlen = ai[i+1] - ai[i]; 1653 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1654 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1655 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1656 } 1657 rowlen = bi[i+1] - bi[i]; 1658 for (j0=j=0; j<rowlen; j0=j) { 1659 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1660 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1661 } 1662 } 1663 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1664 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1665 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1666 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1667 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1668 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1669 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1670 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1671 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1672 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1673 *B = Aperm; 1674 PetscFunctionReturn(0); 1675 } 1676 1677 #undef __FUNCT__ 1678 #define __FUNCT__ "MatGetGhosts_MPIAIJ" 1679 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1680 { 1681 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1682 PetscErrorCode ierr; 1683 1684 PetscFunctionBegin; 1685 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1686 if (ghosts) *ghosts = aij->garray; 1687 PetscFunctionReturn(0); 1688 } 1689 1690 #undef __FUNCT__ 1691 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1692 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1693 { 1694 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1695 Mat A = mat->A,B = mat->B; 1696 PetscErrorCode ierr; 1697 PetscReal isend[5],irecv[5]; 1698 1699 PetscFunctionBegin; 1700 info->block_size = 1.0; 1701 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1702 1703 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1704 isend[3] = info->memory; isend[4] = info->mallocs; 1705 1706 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1707 1708 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1709 isend[3] += info->memory; isend[4] += info->mallocs; 1710 if (flag == MAT_LOCAL) { 1711 info->nz_used = isend[0]; 1712 info->nz_allocated = isend[1]; 1713 info->nz_unneeded = isend[2]; 1714 info->memory = isend[3]; 1715 info->mallocs = isend[4]; 1716 } else if (flag == MAT_GLOBAL_MAX) { 1717 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1718 1719 info->nz_used = irecv[0]; 1720 info->nz_allocated = irecv[1]; 1721 info->nz_unneeded = irecv[2]; 1722 info->memory = irecv[3]; 1723 info->mallocs = irecv[4]; 1724 } else if (flag == MAT_GLOBAL_SUM) { 1725 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1726 1727 info->nz_used = irecv[0]; 1728 info->nz_allocated = irecv[1]; 1729 info->nz_unneeded = irecv[2]; 1730 info->memory = irecv[3]; 1731 info->mallocs = irecv[4]; 1732 } 1733 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1734 info->fill_ratio_needed = 0; 1735 info->factor_mallocs = 0; 1736 PetscFunctionReturn(0); 1737 } 1738 1739 #undef __FUNCT__ 1740 #define __FUNCT__ "MatSetOption_MPIAIJ" 1741 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1742 { 1743 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1744 PetscErrorCode ierr; 1745 1746 PetscFunctionBegin; 1747 switch (op) { 1748 case MAT_NEW_NONZERO_LOCATIONS: 1749 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1750 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1751 case MAT_KEEP_NONZERO_PATTERN: 1752 case MAT_NEW_NONZERO_LOCATION_ERR: 1753 case MAT_USE_INODES: 1754 case MAT_IGNORE_ZERO_ENTRIES: 1755 MatCheckPreallocated(A,1); 1756 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1757 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1758 break; 1759 case MAT_ROW_ORIENTED: 1760 a->roworiented = flg; 1761 1762 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1763 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1764 break; 1765 case MAT_NEW_DIAGONALS: 1766 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1767 break; 1768 case MAT_IGNORE_OFF_PROC_ENTRIES: 1769 a->donotstash = flg; 1770 break; 1771 case MAT_SPD: 1772 A->spd_set = PETSC_TRUE; 1773 A->spd = flg; 1774 if (flg) { 1775 A->symmetric = PETSC_TRUE; 1776 A->structurally_symmetric = PETSC_TRUE; 1777 A->symmetric_set = PETSC_TRUE; 1778 A->structurally_symmetric_set = PETSC_TRUE; 1779 } 1780 break; 1781 case MAT_SYMMETRIC: 1782 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1783 break; 1784 case MAT_STRUCTURALLY_SYMMETRIC: 1785 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1786 break; 1787 case MAT_HERMITIAN: 1788 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1789 break; 1790 case MAT_SYMMETRY_ETERNAL: 1791 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1792 break; 1793 default: 1794 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1795 } 1796 PetscFunctionReturn(0); 1797 } 1798 1799 #undef __FUNCT__ 1800 #define __FUNCT__ "MatGetRow_MPIAIJ" 1801 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1802 { 1803 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1804 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1805 PetscErrorCode ierr; 1806 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1807 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1808 PetscInt *cmap,*idx_p; 1809 1810 PetscFunctionBegin; 1811 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1812 mat->getrowactive = PETSC_TRUE; 1813 1814 if (!mat->rowvalues && (idx || v)) { 1815 /* 1816 allocate enough space to hold information from the longest row. 1817 */ 1818 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1819 PetscInt max = 1,tmp; 1820 for (i=0; i<matin->rmap->n; i++) { 1821 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1822 if (max < tmp) max = tmp; 1823 } 1824 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1825 } 1826 1827 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1828 lrow = row - rstart; 1829 1830 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1831 if (!v) {pvA = 0; pvB = 0;} 1832 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1833 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1834 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1835 nztot = nzA + nzB; 1836 1837 cmap = mat->garray; 1838 if (v || idx) { 1839 if (nztot) { 1840 /* Sort by increasing column numbers, assuming A and B already sorted */ 1841 PetscInt imark = -1; 1842 if (v) { 1843 *v = v_p = mat->rowvalues; 1844 for (i=0; i<nzB; i++) { 1845 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1846 else break; 1847 } 1848 imark = i; 1849 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1850 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1851 } 1852 if (idx) { 1853 *idx = idx_p = mat->rowindices; 1854 if (imark > -1) { 1855 for (i=0; i<imark; i++) { 1856 idx_p[i] = cmap[cworkB[i]]; 1857 } 1858 } else { 1859 for (i=0; i<nzB; i++) { 1860 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1861 else break; 1862 } 1863 imark = i; 1864 } 1865 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1866 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1867 } 1868 } else { 1869 if (idx) *idx = 0; 1870 if (v) *v = 0; 1871 } 1872 } 1873 *nz = nztot; 1874 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1875 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1876 PetscFunctionReturn(0); 1877 } 1878 1879 #undef __FUNCT__ 1880 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1881 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1882 { 1883 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1884 1885 PetscFunctionBegin; 1886 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1887 aij->getrowactive = PETSC_FALSE; 1888 PetscFunctionReturn(0); 1889 } 1890 1891 #undef __FUNCT__ 1892 #define __FUNCT__ "MatNorm_MPIAIJ" 1893 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1894 { 1895 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1896 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1897 PetscErrorCode ierr; 1898 PetscInt i,j,cstart = mat->cmap->rstart; 1899 PetscReal sum = 0.0; 1900 MatScalar *v; 1901 1902 PetscFunctionBegin; 1903 if (aij->size == 1) { 1904 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1905 } else { 1906 if (type == NORM_FROBENIUS) { 1907 v = amat->a; 1908 for (i=0; i<amat->nz; i++) { 1909 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1910 } 1911 v = bmat->a; 1912 for (i=0; i<bmat->nz; i++) { 1913 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1914 } 1915 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1916 *norm = PetscSqrtReal(*norm); 1917 } else if (type == NORM_1) { /* max column norm */ 1918 PetscReal *tmp,*tmp2; 1919 PetscInt *jj,*garray = aij->garray; 1920 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1921 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1922 *norm = 0.0; 1923 v = amat->a; jj = amat->j; 1924 for (j=0; j<amat->nz; j++) { 1925 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1926 } 1927 v = bmat->a; jj = bmat->j; 1928 for (j=0; j<bmat->nz; j++) { 1929 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1930 } 1931 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1932 for (j=0; j<mat->cmap->N; j++) { 1933 if (tmp2[j] > *norm) *norm = tmp2[j]; 1934 } 1935 ierr = PetscFree(tmp);CHKERRQ(ierr); 1936 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1937 } else if (type == NORM_INFINITY) { /* max row norm */ 1938 PetscReal ntemp = 0.0; 1939 for (j=0; j<aij->A->rmap->n; j++) { 1940 v = amat->a + amat->i[j]; 1941 sum = 0.0; 1942 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1943 sum += PetscAbsScalar(*v); v++; 1944 } 1945 v = bmat->a + bmat->i[j]; 1946 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1947 sum += PetscAbsScalar(*v); v++; 1948 } 1949 if (sum > ntemp) ntemp = sum; 1950 } 1951 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1952 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1953 } 1954 PetscFunctionReturn(0); 1955 } 1956 1957 #undef __FUNCT__ 1958 #define __FUNCT__ "MatTranspose_MPIAIJ" 1959 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1960 { 1961 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1962 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1963 PetscErrorCode ierr; 1964 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1965 PetscInt cstart = A->cmap->rstart,ncol; 1966 Mat B; 1967 MatScalar *array; 1968 1969 PetscFunctionBegin; 1970 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1971 1972 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1973 ai = Aloc->i; aj = Aloc->j; 1974 bi = Bloc->i; bj = Bloc->j; 1975 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1976 PetscInt *d_nnz,*g_nnz,*o_nnz; 1977 PetscSFNode *oloc; 1978 PETSC_UNUSED PetscSF sf; 1979 1980 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1981 /* compute d_nnz for preallocation */ 1982 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1983 for (i=0; i<ai[ma]; i++) { 1984 d_nnz[aj[i]]++; 1985 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1986 } 1987 /* compute local off-diagonal contributions */ 1988 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1989 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1990 /* map those to global */ 1991 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1992 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1993 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1994 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1995 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1996 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1997 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1998 1999 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2000 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2001 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2002 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2003 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2004 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2005 } else { 2006 B = *matout; 2007 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2008 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2009 } 2010 2011 /* copy over the A part */ 2012 array = Aloc->a; 2013 row = A->rmap->rstart; 2014 for (i=0; i<ma; i++) { 2015 ncol = ai[i+1]-ai[i]; 2016 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2017 row++; 2018 array += ncol; aj += ncol; 2019 } 2020 aj = Aloc->j; 2021 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2022 2023 /* copy over the B part */ 2024 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2025 array = Bloc->a; 2026 row = A->rmap->rstart; 2027 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2028 cols_tmp = cols; 2029 for (i=0; i<mb; i++) { 2030 ncol = bi[i+1]-bi[i]; 2031 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2032 row++; 2033 array += ncol; cols_tmp += ncol; 2034 } 2035 ierr = PetscFree(cols);CHKERRQ(ierr); 2036 2037 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2038 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2039 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2040 *matout = B; 2041 } else { 2042 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 2043 } 2044 PetscFunctionReturn(0); 2045 } 2046 2047 #undef __FUNCT__ 2048 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2049 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2050 { 2051 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2052 Mat a = aij->A,b = aij->B; 2053 PetscErrorCode ierr; 2054 PetscInt s1,s2,s3; 2055 2056 PetscFunctionBegin; 2057 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2058 if (rr) { 2059 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2060 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2061 /* Overlap communication with computation. */ 2062 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2063 } 2064 if (ll) { 2065 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2066 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2067 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2068 } 2069 /* scale the diagonal block */ 2070 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2071 2072 if (rr) { 2073 /* Do a scatter end and then right scale the off-diagonal block */ 2074 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2075 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2076 } 2077 PetscFunctionReturn(0); 2078 } 2079 2080 #undef __FUNCT__ 2081 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2082 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2083 { 2084 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2085 PetscErrorCode ierr; 2086 2087 PetscFunctionBegin; 2088 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2089 PetscFunctionReturn(0); 2090 } 2091 2092 #undef __FUNCT__ 2093 #define __FUNCT__ "MatEqual_MPIAIJ" 2094 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2095 { 2096 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2097 Mat a,b,c,d; 2098 PetscBool flg; 2099 PetscErrorCode ierr; 2100 2101 PetscFunctionBegin; 2102 a = matA->A; b = matA->B; 2103 c = matB->A; d = matB->B; 2104 2105 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2106 if (flg) { 2107 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2108 } 2109 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2110 PetscFunctionReturn(0); 2111 } 2112 2113 #undef __FUNCT__ 2114 #define __FUNCT__ "MatCopy_MPIAIJ" 2115 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2116 { 2117 PetscErrorCode ierr; 2118 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2119 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2120 2121 PetscFunctionBegin; 2122 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2123 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2124 /* because of the column compression in the off-processor part of the matrix a->B, 2125 the number of columns in a->B and b->B may be different, hence we cannot call 2126 the MatCopy() directly on the two parts. If need be, we can provide a more 2127 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2128 then copying the submatrices */ 2129 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2130 } else { 2131 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2132 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2133 } 2134 PetscFunctionReturn(0); 2135 } 2136 2137 #undef __FUNCT__ 2138 #define __FUNCT__ "MatSetUp_MPIAIJ" 2139 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2140 { 2141 PetscErrorCode ierr; 2142 2143 PetscFunctionBegin; 2144 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2145 PetscFunctionReturn(0); 2146 } 2147 2148 /* 2149 Computes the number of nonzeros per row needed for preallocation when X and Y 2150 have different nonzero structure. 2151 */ 2152 #undef __FUNCT__ 2153 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2154 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) 2155 { 2156 PetscInt i,j,k,nzx,nzy; 2157 2158 PetscFunctionBegin; 2159 /* Set the number of nonzeros in the new matrix */ 2160 for (i=0; i<m; i++) { 2161 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2162 nzx = xi[i+1] - xi[i]; 2163 nzy = yi[i+1] - yi[i]; 2164 nnz[i] = 0; 2165 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2166 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2167 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2168 nnz[i]++; 2169 } 2170 for (; k<nzy; k++) nnz[i]++; 2171 } 2172 PetscFunctionReturn(0); 2173 } 2174 2175 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2176 #undef __FUNCT__ 2177 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2178 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2179 { 2180 PetscErrorCode ierr; 2181 PetscInt m = Y->rmap->N; 2182 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2183 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2184 2185 PetscFunctionBegin; 2186 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2187 PetscFunctionReturn(0); 2188 } 2189 2190 #undef __FUNCT__ 2191 #define __FUNCT__ "MatAXPY_MPIAIJ" 2192 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2193 { 2194 PetscErrorCode ierr; 2195 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2196 PetscBLASInt bnz,one=1; 2197 Mat_SeqAIJ *x,*y; 2198 2199 PetscFunctionBegin; 2200 if (str == SAME_NONZERO_PATTERN) { 2201 PetscScalar alpha = a; 2202 x = (Mat_SeqAIJ*)xx->A->data; 2203 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2204 y = (Mat_SeqAIJ*)yy->A->data; 2205 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2206 x = (Mat_SeqAIJ*)xx->B->data; 2207 y = (Mat_SeqAIJ*)yy->B->data; 2208 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2209 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2210 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2211 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2212 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2213 } else { 2214 Mat B; 2215 PetscInt *nnz_d,*nnz_o; 2216 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2217 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2218 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2219 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2220 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2221 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2222 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2223 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2224 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2225 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2226 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2227 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2228 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2229 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2230 } 2231 PetscFunctionReturn(0); 2232 } 2233 2234 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2235 2236 #undef __FUNCT__ 2237 #define __FUNCT__ "MatConjugate_MPIAIJ" 2238 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2239 { 2240 #if defined(PETSC_USE_COMPLEX) 2241 PetscErrorCode ierr; 2242 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2243 2244 PetscFunctionBegin; 2245 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2246 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2247 #else 2248 PetscFunctionBegin; 2249 #endif 2250 PetscFunctionReturn(0); 2251 } 2252 2253 #undef __FUNCT__ 2254 #define __FUNCT__ "MatRealPart_MPIAIJ" 2255 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2256 { 2257 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2258 PetscErrorCode ierr; 2259 2260 PetscFunctionBegin; 2261 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2262 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2263 PetscFunctionReturn(0); 2264 } 2265 2266 #undef __FUNCT__ 2267 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2268 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2269 { 2270 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2271 PetscErrorCode ierr; 2272 2273 PetscFunctionBegin; 2274 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2275 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2276 PetscFunctionReturn(0); 2277 } 2278 2279 #undef __FUNCT__ 2280 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2281 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2282 { 2283 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2284 PetscErrorCode ierr; 2285 PetscInt i,*idxb = 0; 2286 PetscScalar *va,*vb; 2287 Vec vtmp; 2288 2289 PetscFunctionBegin; 2290 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2291 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2292 if (idx) { 2293 for (i=0; i<A->rmap->n; i++) { 2294 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2295 } 2296 } 2297 2298 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2299 if (idx) { 2300 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2301 } 2302 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2303 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2304 2305 for (i=0; i<A->rmap->n; i++) { 2306 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2307 va[i] = vb[i]; 2308 if (idx) idx[i] = a->garray[idxb[i]]; 2309 } 2310 } 2311 2312 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2313 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2314 ierr = PetscFree(idxb);CHKERRQ(ierr); 2315 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2316 PetscFunctionReturn(0); 2317 } 2318 2319 #undef __FUNCT__ 2320 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2321 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2322 { 2323 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2324 PetscErrorCode ierr; 2325 PetscInt i,*idxb = 0; 2326 PetscScalar *va,*vb; 2327 Vec vtmp; 2328 2329 PetscFunctionBegin; 2330 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2331 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2332 if (idx) { 2333 for (i=0; i<A->cmap->n; i++) { 2334 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2335 } 2336 } 2337 2338 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2339 if (idx) { 2340 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2341 } 2342 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2343 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2344 2345 for (i=0; i<A->rmap->n; i++) { 2346 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2347 va[i] = vb[i]; 2348 if (idx) idx[i] = a->garray[idxb[i]]; 2349 } 2350 } 2351 2352 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2353 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2354 ierr = PetscFree(idxb);CHKERRQ(ierr); 2355 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2356 PetscFunctionReturn(0); 2357 } 2358 2359 #undef __FUNCT__ 2360 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2361 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2362 { 2363 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2364 PetscInt n = A->rmap->n; 2365 PetscInt cstart = A->cmap->rstart; 2366 PetscInt *cmap = mat->garray; 2367 PetscInt *diagIdx, *offdiagIdx; 2368 Vec diagV, offdiagV; 2369 PetscScalar *a, *diagA, *offdiagA; 2370 PetscInt r; 2371 PetscErrorCode ierr; 2372 2373 PetscFunctionBegin; 2374 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2375 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2376 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2377 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2378 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2379 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2380 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2381 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2382 for (r = 0; r < n; ++r) { 2383 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2384 a[r] = diagA[r]; 2385 idx[r] = cstart + diagIdx[r]; 2386 } else { 2387 a[r] = offdiagA[r]; 2388 idx[r] = cmap[offdiagIdx[r]]; 2389 } 2390 } 2391 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2392 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2393 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2394 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2395 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2396 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2397 PetscFunctionReturn(0); 2398 } 2399 2400 #undef __FUNCT__ 2401 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2402 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2403 { 2404 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2405 PetscInt n = A->rmap->n; 2406 PetscInt cstart = A->cmap->rstart; 2407 PetscInt *cmap = mat->garray; 2408 PetscInt *diagIdx, *offdiagIdx; 2409 Vec diagV, offdiagV; 2410 PetscScalar *a, *diagA, *offdiagA; 2411 PetscInt r; 2412 PetscErrorCode ierr; 2413 2414 PetscFunctionBegin; 2415 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2416 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2417 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2418 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2419 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2420 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2421 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2422 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2423 for (r = 0; r < n; ++r) { 2424 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2425 a[r] = diagA[r]; 2426 idx[r] = cstart + diagIdx[r]; 2427 } else { 2428 a[r] = offdiagA[r]; 2429 idx[r] = cmap[offdiagIdx[r]]; 2430 } 2431 } 2432 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2433 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2434 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2435 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2436 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2437 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2438 PetscFunctionReturn(0); 2439 } 2440 2441 #undef __FUNCT__ 2442 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2443 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2444 { 2445 PetscErrorCode ierr; 2446 Mat *dummy; 2447 2448 PetscFunctionBegin; 2449 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2450 *newmat = *dummy; 2451 ierr = PetscFree(dummy);CHKERRQ(ierr); 2452 PetscFunctionReturn(0); 2453 } 2454 2455 #undef __FUNCT__ 2456 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2457 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2458 { 2459 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2460 PetscErrorCode ierr; 2461 2462 PetscFunctionBegin; 2463 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2464 PetscFunctionReturn(0); 2465 } 2466 2467 #undef __FUNCT__ 2468 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2469 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2470 { 2471 PetscErrorCode ierr; 2472 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2473 2474 PetscFunctionBegin; 2475 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2476 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2477 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2478 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2479 PetscFunctionReturn(0); 2480 } 2481 2482 #undef __FUNCT__ 2483 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ" 2484 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2485 { 2486 PetscFunctionBegin; 2487 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2488 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2489 PetscFunctionReturn(0); 2490 } 2491 2492 #undef __FUNCT__ 2493 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap" 2494 /*@ 2495 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2496 2497 Collective on Mat 2498 2499 Input Parameters: 2500 + A - the matrix 2501 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2502 2503 Level: advanced 2504 2505 @*/ 2506 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2507 { 2508 PetscErrorCode ierr; 2509 2510 PetscFunctionBegin; 2511 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2512 PetscFunctionReturn(0); 2513 } 2514 2515 #undef __FUNCT__ 2516 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2517 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2518 { 2519 PetscErrorCode ierr; 2520 PetscBool sc = PETSC_FALSE,flg; 2521 2522 PetscFunctionBegin; 2523 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2524 ierr = PetscObjectOptionsBegin((PetscObject)A); 2525 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2526 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2527 if (flg) { 2528 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2529 } 2530 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2531 PetscFunctionReturn(0); 2532 } 2533 2534 #undef __FUNCT__ 2535 #define __FUNCT__ "MatShift_MPIAIJ" 2536 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2537 { 2538 PetscErrorCode ierr; 2539 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2540 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2541 2542 PetscFunctionBegin; 2543 if (!Y->preallocated) { 2544 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2545 } else if (!aij->nz) { 2546 PetscInt nonew = aij->nonew; 2547 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2548 aij->nonew = nonew; 2549 } 2550 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2551 PetscFunctionReturn(0); 2552 } 2553 2554 #undef __FUNCT__ 2555 #define __FUNCT__ "MatMissingDiagonal_MPIAIJ" 2556 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2557 { 2558 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2559 PetscErrorCode ierr; 2560 2561 PetscFunctionBegin; 2562 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2563 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2564 if (d) { 2565 PetscInt rstart; 2566 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2567 *d += rstart; 2568 2569 } 2570 PetscFunctionReturn(0); 2571 } 2572 2573 2574 /* -------------------------------------------------------------------*/ 2575 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2576 MatGetRow_MPIAIJ, 2577 MatRestoreRow_MPIAIJ, 2578 MatMult_MPIAIJ, 2579 /* 4*/ MatMultAdd_MPIAIJ, 2580 MatMultTranspose_MPIAIJ, 2581 MatMultTransposeAdd_MPIAIJ, 2582 0, 2583 0, 2584 0, 2585 /*10*/ 0, 2586 0, 2587 0, 2588 MatSOR_MPIAIJ, 2589 MatTranspose_MPIAIJ, 2590 /*15*/ MatGetInfo_MPIAIJ, 2591 MatEqual_MPIAIJ, 2592 MatGetDiagonal_MPIAIJ, 2593 MatDiagonalScale_MPIAIJ, 2594 MatNorm_MPIAIJ, 2595 /*20*/ MatAssemblyBegin_MPIAIJ, 2596 MatAssemblyEnd_MPIAIJ, 2597 MatSetOption_MPIAIJ, 2598 MatZeroEntries_MPIAIJ, 2599 /*24*/ MatZeroRows_MPIAIJ, 2600 0, 2601 0, 2602 0, 2603 0, 2604 /*29*/ MatSetUp_MPIAIJ, 2605 0, 2606 0, 2607 0, 2608 0, 2609 /*34*/ MatDuplicate_MPIAIJ, 2610 0, 2611 0, 2612 0, 2613 0, 2614 /*39*/ MatAXPY_MPIAIJ, 2615 MatGetSubMatrices_MPIAIJ, 2616 MatIncreaseOverlap_MPIAIJ, 2617 MatGetValues_MPIAIJ, 2618 MatCopy_MPIAIJ, 2619 /*44*/ MatGetRowMax_MPIAIJ, 2620 MatScale_MPIAIJ, 2621 MatShift_MPIAIJ, 2622 MatDiagonalSet_MPIAIJ, 2623 MatZeroRowsColumns_MPIAIJ, 2624 /*49*/ MatSetRandom_MPIAIJ, 2625 0, 2626 0, 2627 0, 2628 0, 2629 /*54*/ MatFDColoringCreate_MPIXAIJ, 2630 0, 2631 MatSetUnfactored_MPIAIJ, 2632 MatPermute_MPIAIJ, 2633 0, 2634 /*59*/ MatGetSubMatrix_MPIAIJ, 2635 MatDestroy_MPIAIJ, 2636 MatView_MPIAIJ, 2637 0, 2638 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2639 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2640 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2641 0, 2642 0, 2643 0, 2644 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2645 MatGetRowMinAbs_MPIAIJ, 2646 0, 2647 MatSetColoring_MPIAIJ, 2648 0, 2649 MatSetValuesAdifor_MPIAIJ, 2650 /*75*/ MatFDColoringApply_AIJ, 2651 MatSetFromOptions_MPIAIJ, 2652 0, 2653 0, 2654 MatFindZeroDiagonals_MPIAIJ, 2655 /*80*/ 0, 2656 0, 2657 0, 2658 /*83*/ MatLoad_MPIAIJ, 2659 0, 2660 0, 2661 0, 2662 0, 2663 0, 2664 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2665 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2666 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2667 MatPtAP_MPIAIJ_MPIAIJ, 2668 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2669 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2670 0, 2671 0, 2672 0, 2673 0, 2674 /*99*/ 0, 2675 0, 2676 0, 2677 MatConjugate_MPIAIJ, 2678 0, 2679 /*104*/MatSetValuesRow_MPIAIJ, 2680 MatRealPart_MPIAIJ, 2681 MatImaginaryPart_MPIAIJ, 2682 0, 2683 0, 2684 /*109*/0, 2685 0, 2686 MatGetRowMin_MPIAIJ, 2687 0, 2688 MatMissingDiagonal_MPIAIJ, 2689 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2690 0, 2691 MatGetGhosts_MPIAIJ, 2692 0, 2693 0, 2694 /*119*/0, 2695 0, 2696 0, 2697 0, 2698 MatGetMultiProcBlock_MPIAIJ, 2699 /*124*/MatFindNonzeroRows_MPIAIJ, 2700 MatGetColumnNorms_MPIAIJ, 2701 MatInvertBlockDiagonal_MPIAIJ, 2702 0, 2703 MatGetSubMatricesMPI_MPIAIJ, 2704 /*129*/0, 2705 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2706 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2707 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2708 0, 2709 /*134*/0, 2710 0, 2711 0, 2712 0, 2713 0, 2714 /*139*/0, 2715 0, 2716 0, 2717 MatFDColoringSetUp_MPIXAIJ, 2718 MatFindOffBlockDiagonalEntries_MPIAIJ, 2719 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2720 }; 2721 2722 /* ----------------------------------------------------------------------------------------*/ 2723 2724 #undef __FUNCT__ 2725 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2726 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2727 { 2728 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2729 PetscErrorCode ierr; 2730 2731 PetscFunctionBegin; 2732 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2733 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2734 PetscFunctionReturn(0); 2735 } 2736 2737 #undef __FUNCT__ 2738 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2739 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2740 { 2741 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2742 PetscErrorCode ierr; 2743 2744 PetscFunctionBegin; 2745 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2746 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2747 PetscFunctionReturn(0); 2748 } 2749 2750 #undef __FUNCT__ 2751 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2752 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2753 { 2754 Mat_MPIAIJ *b; 2755 PetscErrorCode ierr; 2756 2757 PetscFunctionBegin; 2758 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2759 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2760 b = (Mat_MPIAIJ*)B->data; 2761 2762 if (!B->preallocated) { 2763 /* Explicitly create 2 MATSEQAIJ matrices. */ 2764 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2765 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2766 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2767 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2768 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2769 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2770 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2771 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2772 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2773 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2774 } 2775 2776 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2777 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2778 B->preallocated = PETSC_TRUE; 2779 PetscFunctionReturn(0); 2780 } 2781 2782 #undef __FUNCT__ 2783 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2784 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2785 { 2786 Mat mat; 2787 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2788 PetscErrorCode ierr; 2789 2790 PetscFunctionBegin; 2791 *newmat = 0; 2792 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2793 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2794 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2795 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2796 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2797 a = (Mat_MPIAIJ*)mat->data; 2798 2799 mat->factortype = matin->factortype; 2800 mat->assembled = PETSC_TRUE; 2801 mat->insertmode = NOT_SET_VALUES; 2802 mat->preallocated = PETSC_TRUE; 2803 2804 a->size = oldmat->size; 2805 a->rank = oldmat->rank; 2806 a->donotstash = oldmat->donotstash; 2807 a->roworiented = oldmat->roworiented; 2808 a->rowindices = 0; 2809 a->rowvalues = 0; 2810 a->getrowactive = PETSC_FALSE; 2811 2812 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2813 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2814 2815 if (oldmat->colmap) { 2816 #if defined(PETSC_USE_CTABLE) 2817 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2818 #else 2819 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2820 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2821 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2822 #endif 2823 } else a->colmap = 0; 2824 if (oldmat->garray) { 2825 PetscInt len; 2826 len = oldmat->B->cmap->n; 2827 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2828 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2829 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2830 } else a->garray = 0; 2831 2832 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2833 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2834 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2835 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2836 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2837 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2838 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2839 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2840 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2841 *newmat = mat; 2842 PetscFunctionReturn(0); 2843 } 2844 2845 2846 2847 #undef __FUNCT__ 2848 #define __FUNCT__ "MatLoad_MPIAIJ" 2849 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2850 { 2851 PetscScalar *vals,*svals; 2852 MPI_Comm comm; 2853 PetscErrorCode ierr; 2854 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2855 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2856 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2857 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2858 PetscInt cend,cstart,n,*rowners; 2859 int fd; 2860 PetscInt bs = newMat->rmap->bs; 2861 2862 PetscFunctionBegin; 2863 /* force binary viewer to load .info file if it has not yet done so */ 2864 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2865 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2866 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2867 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2868 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2869 if (!rank) { 2870 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2871 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2872 } 2873 2874 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2875 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2876 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2877 if (bs < 0) bs = 1; 2878 2879 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2880 M = header[1]; N = header[2]; 2881 2882 /* If global sizes are set, check if they are consistent with that given in the file */ 2883 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); 2884 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); 2885 2886 /* determine ownership of all (block) rows */ 2887 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2888 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2889 else m = newMat->rmap->n; /* Set by user */ 2890 2891 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2892 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2893 2894 /* First process needs enough room for process with most rows */ 2895 if (!rank) { 2896 mmax = rowners[1]; 2897 for (i=2; i<=size; i++) { 2898 mmax = PetscMax(mmax, rowners[i]); 2899 } 2900 } else mmax = -1; /* unused, but compilers complain */ 2901 2902 rowners[0] = 0; 2903 for (i=2; i<=size; i++) { 2904 rowners[i] += rowners[i-1]; 2905 } 2906 rstart = rowners[rank]; 2907 rend = rowners[rank+1]; 2908 2909 /* distribute row lengths to all processors */ 2910 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2911 if (!rank) { 2912 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2913 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2914 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2915 for (j=0; j<m; j++) { 2916 procsnz[0] += ourlens[j]; 2917 } 2918 for (i=1; i<size; i++) { 2919 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2920 /* calculate the number of nonzeros on each processor */ 2921 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2922 procsnz[i] += rowlengths[j]; 2923 } 2924 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2925 } 2926 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2927 } else { 2928 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2929 } 2930 2931 if (!rank) { 2932 /* determine max buffer needed and allocate it */ 2933 maxnz = 0; 2934 for (i=0; i<size; i++) { 2935 maxnz = PetscMax(maxnz,procsnz[i]); 2936 } 2937 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2938 2939 /* read in my part of the matrix column indices */ 2940 nz = procsnz[0]; 2941 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2942 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2943 2944 /* read in every one elses and ship off */ 2945 for (i=1; i<size; i++) { 2946 nz = procsnz[i]; 2947 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2948 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2949 } 2950 ierr = PetscFree(cols);CHKERRQ(ierr); 2951 } else { 2952 /* determine buffer space needed for message */ 2953 nz = 0; 2954 for (i=0; i<m; i++) { 2955 nz += ourlens[i]; 2956 } 2957 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2958 2959 /* receive message of column indices*/ 2960 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2961 } 2962 2963 /* determine column ownership if matrix is not square */ 2964 if (N != M) { 2965 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2966 else n = newMat->cmap->n; 2967 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2968 cstart = cend - n; 2969 } else { 2970 cstart = rstart; 2971 cend = rend; 2972 n = cend - cstart; 2973 } 2974 2975 /* loop over local rows, determining number of off diagonal entries */ 2976 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2977 jj = 0; 2978 for (i=0; i<m; i++) { 2979 for (j=0; j<ourlens[i]; j++) { 2980 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2981 jj++; 2982 } 2983 } 2984 2985 for (i=0; i<m; i++) { 2986 ourlens[i] -= offlens[i]; 2987 } 2988 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2989 2990 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2991 2992 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2993 2994 for (i=0; i<m; i++) { 2995 ourlens[i] += offlens[i]; 2996 } 2997 2998 if (!rank) { 2999 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3000 3001 /* read in my part of the matrix numerical values */ 3002 nz = procsnz[0]; 3003 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3004 3005 /* insert into matrix */ 3006 jj = rstart; 3007 smycols = mycols; 3008 svals = vals; 3009 for (i=0; i<m; i++) { 3010 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3011 smycols += ourlens[i]; 3012 svals += ourlens[i]; 3013 jj++; 3014 } 3015 3016 /* read in other processors and ship out */ 3017 for (i=1; i<size; i++) { 3018 nz = procsnz[i]; 3019 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3020 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3021 } 3022 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3023 } else { 3024 /* receive numeric values */ 3025 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3026 3027 /* receive message of values*/ 3028 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3029 3030 /* insert into matrix */ 3031 jj = rstart; 3032 smycols = mycols; 3033 svals = vals; 3034 for (i=0; i<m; i++) { 3035 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3036 smycols += ourlens[i]; 3037 svals += ourlens[i]; 3038 jj++; 3039 } 3040 } 3041 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3042 ierr = PetscFree(vals);CHKERRQ(ierr); 3043 ierr = PetscFree(mycols);CHKERRQ(ierr); 3044 ierr = PetscFree(rowners);CHKERRQ(ierr); 3045 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3046 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3047 PetscFunctionReturn(0); 3048 } 3049 3050 #undef __FUNCT__ 3051 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3052 /* TODO: Not scalable because of ISAllGather() unless getting all columns. */ 3053 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3054 { 3055 PetscErrorCode ierr; 3056 IS iscol_local; 3057 PetscInt csize; 3058 3059 PetscFunctionBegin; 3060 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3061 if (call == MAT_REUSE_MATRIX) { 3062 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3063 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3064 } else { 3065 /* check if we are grabbing all columns*/ 3066 PetscBool isstride; 3067 PetscMPIInt lisstride = 0,gisstride; 3068 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 3069 if (isstride) { 3070 PetscInt start,len,mstart,mlen; 3071 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 3072 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 3073 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 3074 if (mstart == start && mlen-mstart == len) lisstride = 1; 3075 } 3076 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 3077 if (gisstride) { 3078 PetscInt N; 3079 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 3080 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 3081 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 3082 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 3083 } else { 3084 PetscInt cbs; 3085 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3086 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3087 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3088 } 3089 } 3090 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3091 if (call == MAT_INITIAL_MATRIX) { 3092 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3093 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3094 } 3095 PetscFunctionReturn(0); 3096 } 3097 3098 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3099 #undef __FUNCT__ 3100 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3101 /* 3102 Not great since it makes two copies of the submatrix, first an SeqAIJ 3103 in local and then by concatenating the local matrices the end result. 3104 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3105 3106 Note: This requires a sequential iscol with all indices. 3107 */ 3108 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3109 { 3110 PetscErrorCode ierr; 3111 PetscMPIInt rank,size; 3112 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3113 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3114 PetscBool allcolumns, colflag; 3115 Mat M,Mreuse; 3116 MatScalar *vwork,*aa; 3117 MPI_Comm comm; 3118 Mat_SeqAIJ *aij; 3119 3120 PetscFunctionBegin; 3121 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3122 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3123 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3124 3125 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3126 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3127 if (colflag && ncol == mat->cmap->N) { 3128 allcolumns = PETSC_TRUE; 3129 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix\n");CHKERRQ(ierr); 3130 } else { 3131 allcolumns = PETSC_FALSE; 3132 } 3133 if (call == MAT_REUSE_MATRIX) { 3134 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3135 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3136 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3137 } else { 3138 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3139 } 3140 3141 /* 3142 m - number of local rows 3143 n - number of columns (same on all processors) 3144 rstart - first row in new global matrix generated 3145 */ 3146 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3147 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3148 if (call == MAT_INITIAL_MATRIX) { 3149 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3150 ii = aij->i; 3151 jj = aij->j; 3152 3153 /* 3154 Determine the number of non-zeros in the diagonal and off-diagonal 3155 portions of the matrix in order to do correct preallocation 3156 */ 3157 3158 /* first get start and end of "diagonal" columns */ 3159 if (csize == PETSC_DECIDE) { 3160 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3161 if (mglobal == n) { /* square matrix */ 3162 nlocal = m; 3163 } else { 3164 nlocal = n/size + ((n % size) > rank); 3165 } 3166 } else { 3167 nlocal = csize; 3168 } 3169 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3170 rstart = rend - nlocal; 3171 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); 3172 3173 /* next, compute all the lengths */ 3174 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3175 olens = dlens + m; 3176 for (i=0; i<m; i++) { 3177 jend = ii[i+1] - ii[i]; 3178 olen = 0; 3179 dlen = 0; 3180 for (j=0; j<jend; j++) { 3181 if (*jj < rstart || *jj >= rend) olen++; 3182 else dlen++; 3183 jj++; 3184 } 3185 olens[i] = olen; 3186 dlens[i] = dlen; 3187 } 3188 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3189 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3190 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3191 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3192 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3193 ierr = PetscFree(dlens);CHKERRQ(ierr); 3194 } else { 3195 PetscInt ml,nl; 3196 3197 M = *newmat; 3198 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3199 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3200 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3201 /* 3202 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3203 rather than the slower MatSetValues(). 3204 */ 3205 M->was_assembled = PETSC_TRUE; 3206 M->assembled = PETSC_FALSE; 3207 } 3208 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3209 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3210 ii = aij->i; 3211 jj = aij->j; 3212 aa = aij->a; 3213 for (i=0; i<m; i++) { 3214 row = rstart + i; 3215 nz = ii[i+1] - ii[i]; 3216 cwork = jj; jj += nz; 3217 vwork = aa; aa += nz; 3218 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3219 } 3220 3221 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3222 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3223 *newmat = M; 3224 3225 /* save submatrix used in processor for next request */ 3226 if (call == MAT_INITIAL_MATRIX) { 3227 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3228 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3229 } 3230 PetscFunctionReturn(0); 3231 } 3232 3233 #undef __FUNCT__ 3234 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3235 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3236 { 3237 PetscInt m,cstart, cend,j,nnz,i,d; 3238 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3239 const PetscInt *JJ; 3240 PetscScalar *values; 3241 PetscErrorCode ierr; 3242 3243 PetscFunctionBegin; 3244 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3245 3246 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3247 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3248 m = B->rmap->n; 3249 cstart = B->cmap->rstart; 3250 cend = B->cmap->rend; 3251 rstart = B->rmap->rstart; 3252 3253 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3254 3255 #if defined(PETSC_USE_DEBUGGING) 3256 for (i=0; i<m; i++) { 3257 nnz = Ii[i+1]- Ii[i]; 3258 JJ = J + Ii[i]; 3259 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3260 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3261 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); 3262 } 3263 #endif 3264 3265 for (i=0; i<m; i++) { 3266 nnz = Ii[i+1]- Ii[i]; 3267 JJ = J + Ii[i]; 3268 nnz_max = PetscMax(nnz_max,nnz); 3269 d = 0; 3270 for (j=0; j<nnz; j++) { 3271 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3272 } 3273 d_nnz[i] = d; 3274 o_nnz[i] = nnz - d; 3275 } 3276 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3277 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3278 3279 if (v) values = (PetscScalar*)v; 3280 else { 3281 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3282 } 3283 3284 for (i=0; i<m; i++) { 3285 ii = i + rstart; 3286 nnz = Ii[i+1]- Ii[i]; 3287 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3288 } 3289 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3290 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3291 3292 if (!v) { 3293 ierr = PetscFree(values);CHKERRQ(ierr); 3294 } 3295 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3296 PetscFunctionReturn(0); 3297 } 3298 3299 #undef __FUNCT__ 3300 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3301 /*@ 3302 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3303 (the default parallel PETSc format). 3304 3305 Collective on MPI_Comm 3306 3307 Input Parameters: 3308 + B - the matrix 3309 . i - the indices into j for the start of each local row (starts with zero) 3310 . j - the column indices for each local row (starts with zero) 3311 - v - optional values in the matrix 3312 3313 Level: developer 3314 3315 Notes: 3316 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3317 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3318 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3319 3320 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3321 3322 The format which is used for the sparse matrix input, is equivalent to a 3323 row-major ordering.. i.e for the following matrix, the input data expected is 3324 as shown 3325 3326 $ 1 0 0 3327 $ 2 0 3 P0 3328 $ ------- 3329 $ 4 5 6 P1 3330 $ 3331 $ Process0 [P0]: rows_owned=[0,1] 3332 $ i = {0,1,3} [size = nrow+1 = 2+1] 3333 $ j = {0,0,2} [size = 3] 3334 $ v = {1,2,3} [size = 3] 3335 $ 3336 $ Process1 [P1]: rows_owned=[2] 3337 $ i = {0,3} [size = nrow+1 = 1+1] 3338 $ j = {0,1,2} [size = 3] 3339 $ v = {4,5,6} [size = 3] 3340 3341 .keywords: matrix, aij, compressed row, sparse, parallel 3342 3343 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3344 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3345 @*/ 3346 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3347 { 3348 PetscErrorCode ierr; 3349 3350 PetscFunctionBegin; 3351 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3352 PetscFunctionReturn(0); 3353 } 3354 3355 #undef __FUNCT__ 3356 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3357 /*@C 3358 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3359 (the default parallel PETSc format). For good matrix assembly performance 3360 the user should preallocate the matrix storage by setting the parameters 3361 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3362 performance can be increased by more than a factor of 50. 3363 3364 Collective on MPI_Comm 3365 3366 Input Parameters: 3367 + B - the matrix 3368 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3369 (same value is used for all local rows) 3370 . d_nnz - array containing the number of nonzeros in the various rows of the 3371 DIAGONAL portion of the local submatrix (possibly different for each row) 3372 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3373 The size of this array is equal to the number of local rows, i.e 'm'. 3374 For matrices that will be factored, you must leave room for (and set) 3375 the diagonal entry even if it is zero. 3376 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3377 submatrix (same value is used for all local rows). 3378 - o_nnz - array containing the number of nonzeros in the various rows of the 3379 OFF-DIAGONAL portion of the local submatrix (possibly different for 3380 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3381 structure. The size of this array is equal to the number 3382 of local rows, i.e 'm'. 3383 3384 If the *_nnz parameter is given then the *_nz parameter is ignored 3385 3386 The AIJ format (also called the Yale sparse matrix format or 3387 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3388 storage. The stored row and column indices begin with zero. 3389 See Users-Manual: ch_mat for details. 3390 3391 The parallel matrix is partitioned such that the first m0 rows belong to 3392 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3393 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3394 3395 The DIAGONAL portion of the local submatrix of a processor can be defined 3396 as the submatrix which is obtained by extraction the part corresponding to 3397 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3398 first row that belongs to the processor, r2 is the last row belonging to 3399 the this processor, and c1-c2 is range of indices of the local part of a 3400 vector suitable for applying the matrix to. This is an mxn matrix. In the 3401 common case of a square matrix, the row and column ranges are the same and 3402 the DIAGONAL part is also square. The remaining portion of the local 3403 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3404 3405 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3406 3407 You can call MatGetInfo() to get information on how effective the preallocation was; 3408 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3409 You can also run with the option -info and look for messages with the string 3410 malloc in them to see if additional memory allocation was needed. 3411 3412 Example usage: 3413 3414 Consider the following 8x8 matrix with 34 non-zero values, that is 3415 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3416 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3417 as follows: 3418 3419 .vb 3420 1 2 0 | 0 3 0 | 0 4 3421 Proc0 0 5 6 | 7 0 0 | 8 0 3422 9 0 10 | 11 0 0 | 12 0 3423 ------------------------------------- 3424 13 0 14 | 15 16 17 | 0 0 3425 Proc1 0 18 0 | 19 20 21 | 0 0 3426 0 0 0 | 22 23 0 | 24 0 3427 ------------------------------------- 3428 Proc2 25 26 27 | 0 0 28 | 29 0 3429 30 0 0 | 31 32 33 | 0 34 3430 .ve 3431 3432 This can be represented as a collection of submatrices as: 3433 3434 .vb 3435 A B C 3436 D E F 3437 G H I 3438 .ve 3439 3440 Where the submatrices A,B,C are owned by proc0, D,E,F are 3441 owned by proc1, G,H,I are owned by proc2. 3442 3443 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3444 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3445 The 'M','N' parameters are 8,8, and have the same values on all procs. 3446 3447 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3448 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3449 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3450 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3451 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3452 matrix, ans [DF] as another SeqAIJ matrix. 3453 3454 When d_nz, o_nz parameters are specified, d_nz storage elements are 3455 allocated for every row of the local diagonal submatrix, and o_nz 3456 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3457 One way to choose d_nz and o_nz is to use the max nonzerors per local 3458 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3459 In this case, the values of d_nz,o_nz are: 3460 .vb 3461 proc0 : dnz = 2, o_nz = 2 3462 proc1 : dnz = 3, o_nz = 2 3463 proc2 : dnz = 1, o_nz = 4 3464 .ve 3465 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3466 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3467 for proc3. i.e we are using 12+15+10=37 storage locations to store 3468 34 values. 3469 3470 When d_nnz, o_nnz parameters are specified, the storage is specified 3471 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3472 In the above case the values for d_nnz,o_nnz are: 3473 .vb 3474 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3475 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3476 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3477 .ve 3478 Here the space allocated is sum of all the above values i.e 34, and 3479 hence pre-allocation is perfect. 3480 3481 Level: intermediate 3482 3483 .keywords: matrix, aij, compressed row, sparse, parallel 3484 3485 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3486 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3487 @*/ 3488 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3489 { 3490 PetscErrorCode ierr; 3491 3492 PetscFunctionBegin; 3493 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3494 PetscValidType(B,1); 3495 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3496 PetscFunctionReturn(0); 3497 } 3498 3499 #undef __FUNCT__ 3500 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3501 /*@ 3502 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3503 CSR format the local rows. 3504 3505 Collective on MPI_Comm 3506 3507 Input Parameters: 3508 + comm - MPI communicator 3509 . m - number of local rows (Cannot be PETSC_DECIDE) 3510 . n - This value should be the same as the local size used in creating the 3511 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3512 calculated if N is given) For square matrices n is almost always m. 3513 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3514 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3515 . i - row indices 3516 . j - column indices 3517 - a - matrix values 3518 3519 Output Parameter: 3520 . mat - the matrix 3521 3522 Level: intermediate 3523 3524 Notes: 3525 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3526 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3527 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3528 3529 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3530 3531 The format which is used for the sparse matrix input, is equivalent to a 3532 row-major ordering.. i.e for the following matrix, the input data expected is 3533 as shown 3534 3535 $ 1 0 0 3536 $ 2 0 3 P0 3537 $ ------- 3538 $ 4 5 6 P1 3539 $ 3540 $ Process0 [P0]: rows_owned=[0,1] 3541 $ i = {0,1,3} [size = nrow+1 = 2+1] 3542 $ j = {0,0,2} [size = 3] 3543 $ v = {1,2,3} [size = 3] 3544 $ 3545 $ Process1 [P1]: rows_owned=[2] 3546 $ i = {0,3} [size = nrow+1 = 1+1] 3547 $ j = {0,1,2} [size = 3] 3548 $ v = {4,5,6} [size = 3] 3549 3550 .keywords: matrix, aij, compressed row, sparse, parallel 3551 3552 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3553 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3554 @*/ 3555 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3556 { 3557 PetscErrorCode ierr; 3558 3559 PetscFunctionBegin; 3560 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3561 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3562 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3563 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3564 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3565 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3566 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3567 PetscFunctionReturn(0); 3568 } 3569 3570 #undef __FUNCT__ 3571 #define __FUNCT__ "MatCreateAIJ" 3572 /*@C 3573 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3574 (the default parallel PETSc format). For good matrix assembly performance 3575 the user should preallocate the matrix storage by setting the parameters 3576 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3577 performance can be increased by more than a factor of 50. 3578 3579 Collective on MPI_Comm 3580 3581 Input Parameters: 3582 + comm - MPI communicator 3583 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3584 This value should be the same as the local size used in creating the 3585 y vector for the matrix-vector product y = Ax. 3586 . n - This value should be the same as the local size used in creating the 3587 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3588 calculated if N is given) For square matrices n is almost always m. 3589 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3590 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3591 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3592 (same value is used for all local rows) 3593 . d_nnz - array containing the number of nonzeros in the various rows of the 3594 DIAGONAL portion of the local submatrix (possibly different for each row) 3595 or NULL, if d_nz is used to specify the nonzero structure. 3596 The size of this array is equal to the number of local rows, i.e 'm'. 3597 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3598 submatrix (same value is used for all local rows). 3599 - o_nnz - array containing the number of nonzeros in the various rows of the 3600 OFF-DIAGONAL portion of the local submatrix (possibly different for 3601 each row) or NULL, if o_nz is used to specify the nonzero 3602 structure. The size of this array is equal to the number 3603 of local rows, i.e 'm'. 3604 3605 Output Parameter: 3606 . A - the matrix 3607 3608 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3609 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3610 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3611 3612 Notes: 3613 If the *_nnz parameter is given then the *_nz parameter is ignored 3614 3615 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3616 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3617 storage requirements for this matrix. 3618 3619 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3620 processor than it must be used on all processors that share the object for 3621 that argument. 3622 3623 The user MUST specify either the local or global matrix dimensions 3624 (possibly both). 3625 3626 The parallel matrix is partitioned across processors such that the 3627 first m0 rows belong to process 0, the next m1 rows belong to 3628 process 1, the next m2 rows belong to process 2 etc.. where 3629 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3630 values corresponding to [m x N] submatrix. 3631 3632 The columns are logically partitioned with the n0 columns belonging 3633 to 0th partition, the next n1 columns belonging to the next 3634 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3635 3636 The DIAGONAL portion of the local submatrix on any given processor 3637 is the submatrix corresponding to the rows and columns m,n 3638 corresponding to the given processor. i.e diagonal matrix on 3639 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3640 etc. The remaining portion of the local submatrix [m x (N-n)] 3641 constitute the OFF-DIAGONAL portion. The example below better 3642 illustrates this concept. 3643 3644 For a square global matrix we define each processor's diagonal portion 3645 to be its local rows and the corresponding columns (a square submatrix); 3646 each processor's off-diagonal portion encompasses the remainder of the 3647 local matrix (a rectangular submatrix). 3648 3649 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3650 3651 When calling this routine with a single process communicator, a matrix of 3652 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3653 type of communicator, use the construction mechanism: 3654 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3655 3656 By default, this format uses inodes (identical nodes) when possible. 3657 We search for consecutive rows with the same nonzero structure, thereby 3658 reusing matrix information to achieve increased efficiency. 3659 3660 Options Database Keys: 3661 + -mat_no_inode - Do not use inodes 3662 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3663 - -mat_aij_oneindex - Internally use indexing starting at 1 3664 rather than 0. Note that when calling MatSetValues(), 3665 the user still MUST index entries starting at 0! 3666 3667 3668 Example usage: 3669 3670 Consider the following 8x8 matrix with 34 non-zero values, that is 3671 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3672 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3673 as follows: 3674 3675 .vb 3676 1 2 0 | 0 3 0 | 0 4 3677 Proc0 0 5 6 | 7 0 0 | 8 0 3678 9 0 10 | 11 0 0 | 12 0 3679 ------------------------------------- 3680 13 0 14 | 15 16 17 | 0 0 3681 Proc1 0 18 0 | 19 20 21 | 0 0 3682 0 0 0 | 22 23 0 | 24 0 3683 ------------------------------------- 3684 Proc2 25 26 27 | 0 0 28 | 29 0 3685 30 0 0 | 31 32 33 | 0 34 3686 .ve 3687 3688 This can be represented as a collection of submatrices as: 3689 3690 .vb 3691 A B C 3692 D E F 3693 G H I 3694 .ve 3695 3696 Where the submatrices A,B,C are owned by proc0, D,E,F are 3697 owned by proc1, G,H,I are owned by proc2. 3698 3699 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3700 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3701 The 'M','N' parameters are 8,8, and have the same values on all procs. 3702 3703 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3704 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3705 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3706 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3707 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3708 matrix, ans [DF] as another SeqAIJ matrix. 3709 3710 When d_nz, o_nz parameters are specified, d_nz storage elements are 3711 allocated for every row of the local diagonal submatrix, and o_nz 3712 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3713 One way to choose d_nz and o_nz is to use the max nonzerors per local 3714 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3715 In this case, the values of d_nz,o_nz are: 3716 .vb 3717 proc0 : dnz = 2, o_nz = 2 3718 proc1 : dnz = 3, o_nz = 2 3719 proc2 : dnz = 1, o_nz = 4 3720 .ve 3721 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3722 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3723 for proc3. i.e we are using 12+15+10=37 storage locations to store 3724 34 values. 3725 3726 When d_nnz, o_nnz parameters are specified, the storage is specified 3727 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3728 In the above case the values for d_nnz,o_nnz are: 3729 .vb 3730 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3731 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3732 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3733 .ve 3734 Here the space allocated is sum of all the above values i.e 34, and 3735 hence pre-allocation is perfect. 3736 3737 Level: intermediate 3738 3739 .keywords: matrix, aij, compressed row, sparse, parallel 3740 3741 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3742 MPIAIJ, MatCreateMPIAIJWithArrays() 3743 @*/ 3744 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) 3745 { 3746 PetscErrorCode ierr; 3747 PetscMPIInt size; 3748 3749 PetscFunctionBegin; 3750 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3751 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3752 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3753 if (size > 1) { 3754 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3755 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3756 } else { 3757 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3758 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3759 } 3760 PetscFunctionReturn(0); 3761 } 3762 3763 #undef __FUNCT__ 3764 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3765 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3766 { 3767 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3768 3769 PetscFunctionBegin; 3770 if (Ad) *Ad = a->A; 3771 if (Ao) *Ao = a->B; 3772 if (colmap) *colmap = a->garray; 3773 PetscFunctionReturn(0); 3774 } 3775 3776 #undef __FUNCT__ 3777 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3778 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3779 { 3780 PetscErrorCode ierr; 3781 PetscInt i; 3782 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3783 3784 PetscFunctionBegin; 3785 if (coloring->ctype == IS_COLORING_GLOBAL) { 3786 ISColoringValue *allcolors,*colors; 3787 ISColoring ocoloring; 3788 3789 /* set coloring for diagonal portion */ 3790 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3791 3792 /* set coloring for off-diagonal portion */ 3793 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3794 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3795 for (i=0; i<a->B->cmap->n; i++) { 3796 colors[i] = allcolors[a->garray[i]]; 3797 } 3798 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3799 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3800 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3801 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3802 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3803 ISColoringValue *colors; 3804 PetscInt *larray; 3805 ISColoring ocoloring; 3806 3807 /* set coloring for diagonal portion */ 3808 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3809 for (i=0; i<a->A->cmap->n; i++) { 3810 larray[i] = i + A->cmap->rstart; 3811 } 3812 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3813 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3814 for (i=0; i<a->A->cmap->n; i++) { 3815 colors[i] = coloring->colors[larray[i]]; 3816 } 3817 ierr = PetscFree(larray);CHKERRQ(ierr); 3818 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3819 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3820 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3821 3822 /* set coloring for off-diagonal portion */ 3823 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3824 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3825 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3826 for (i=0; i<a->B->cmap->n; i++) { 3827 colors[i] = coloring->colors[larray[i]]; 3828 } 3829 ierr = PetscFree(larray);CHKERRQ(ierr); 3830 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3831 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3832 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3833 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3834 PetscFunctionReturn(0); 3835 } 3836 3837 #undef __FUNCT__ 3838 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3839 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3840 { 3841 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3842 PetscErrorCode ierr; 3843 3844 PetscFunctionBegin; 3845 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3846 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3847 PetscFunctionReturn(0); 3848 } 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3852 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3853 { 3854 PetscErrorCode ierr; 3855 PetscInt m,N,i,rstart,nnz,Ii; 3856 PetscInt *indx; 3857 PetscScalar *values; 3858 3859 PetscFunctionBegin; 3860 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3861 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3862 PetscInt *dnz,*onz,sum,bs,cbs; 3863 3864 if (n == PETSC_DECIDE) { 3865 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3866 } 3867 /* Check sum(n) = N */ 3868 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3869 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3870 3871 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3872 rstart -= m; 3873 3874 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3875 for (i=0; i<m; i++) { 3876 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3877 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3878 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3879 } 3880 3881 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3882 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3883 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3884 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3885 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3886 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3887 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3888 } 3889 3890 /* numeric phase */ 3891 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3892 for (i=0; i<m; i++) { 3893 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3894 Ii = i + rstart; 3895 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3896 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3897 } 3898 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3899 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3900 PetscFunctionReturn(0); 3901 } 3902 3903 #undef __FUNCT__ 3904 #define __FUNCT__ "MatFileSplit" 3905 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3906 { 3907 PetscErrorCode ierr; 3908 PetscMPIInt rank; 3909 PetscInt m,N,i,rstart,nnz; 3910 size_t len; 3911 const PetscInt *indx; 3912 PetscViewer out; 3913 char *name; 3914 Mat B; 3915 const PetscScalar *values; 3916 3917 PetscFunctionBegin; 3918 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3919 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3920 /* Should this be the type of the diagonal block of A? */ 3921 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3922 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3923 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3924 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3925 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3926 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3927 for (i=0; i<m; i++) { 3928 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3929 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3930 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3931 } 3932 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3933 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3934 3935 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3936 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3937 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3938 sprintf(name,"%s.%d",outfile,rank); 3939 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3940 ierr = PetscFree(name);CHKERRQ(ierr); 3941 ierr = MatView(B,out);CHKERRQ(ierr); 3942 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3943 ierr = MatDestroy(&B);CHKERRQ(ierr); 3944 PetscFunctionReturn(0); 3945 } 3946 3947 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3948 #undef __FUNCT__ 3949 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3950 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3951 { 3952 PetscErrorCode ierr; 3953 Mat_Merge_SeqsToMPI *merge; 3954 PetscContainer container; 3955 3956 PetscFunctionBegin; 3957 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3958 if (container) { 3959 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3960 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3961 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3962 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3963 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3964 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3965 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3966 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3967 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3968 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3969 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3970 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3971 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3972 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3973 ierr = PetscFree(merge);CHKERRQ(ierr); 3974 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3975 } 3976 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3977 PetscFunctionReturn(0); 3978 } 3979 3980 #include <../src/mat/utils/freespace.h> 3981 #include <petscbt.h> 3982 3983 #undef __FUNCT__ 3984 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 3985 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3986 { 3987 PetscErrorCode ierr; 3988 MPI_Comm comm; 3989 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 3990 PetscMPIInt size,rank,taga,*len_s; 3991 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 3992 PetscInt proc,m; 3993 PetscInt **buf_ri,**buf_rj; 3994 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3995 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3996 MPI_Request *s_waits,*r_waits; 3997 MPI_Status *status; 3998 MatScalar *aa=a->a; 3999 MatScalar **abuf_r,*ba_i; 4000 Mat_Merge_SeqsToMPI *merge; 4001 PetscContainer container; 4002 4003 PetscFunctionBegin; 4004 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4005 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4006 4007 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4008 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4009 4010 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4011 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4012 4013 bi = merge->bi; 4014 bj = merge->bj; 4015 buf_ri = merge->buf_ri; 4016 buf_rj = merge->buf_rj; 4017 4018 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4019 owners = merge->rowmap->range; 4020 len_s = merge->len_s; 4021 4022 /* send and recv matrix values */ 4023 /*-----------------------------*/ 4024 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4025 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4026 4027 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4028 for (proc=0,k=0; proc<size; proc++) { 4029 if (!len_s[proc]) continue; 4030 i = owners[proc]; 4031 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4032 k++; 4033 } 4034 4035 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4036 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4037 ierr = PetscFree(status);CHKERRQ(ierr); 4038 4039 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4040 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4041 4042 /* insert mat values of mpimat */ 4043 /*----------------------------*/ 4044 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4045 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4046 4047 for (k=0; k<merge->nrecv; k++) { 4048 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4049 nrows = *(buf_ri_k[k]); 4050 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4051 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4052 } 4053 4054 /* set values of ba */ 4055 m = merge->rowmap->n; 4056 for (i=0; i<m; i++) { 4057 arow = owners[rank] + i; 4058 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4059 bnzi = bi[i+1] - bi[i]; 4060 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4061 4062 /* add local non-zero vals of this proc's seqmat into ba */ 4063 anzi = ai[arow+1] - ai[arow]; 4064 aj = a->j + ai[arow]; 4065 aa = a->a + ai[arow]; 4066 nextaj = 0; 4067 for (j=0; nextaj<anzi; j++) { 4068 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4069 ba_i[j] += aa[nextaj++]; 4070 } 4071 } 4072 4073 /* add received vals into ba */ 4074 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4075 /* i-th row */ 4076 if (i == *nextrow[k]) { 4077 anzi = *(nextai[k]+1) - *nextai[k]; 4078 aj = buf_rj[k] + *(nextai[k]); 4079 aa = abuf_r[k] + *(nextai[k]); 4080 nextaj = 0; 4081 for (j=0; nextaj<anzi; j++) { 4082 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4083 ba_i[j] += aa[nextaj++]; 4084 } 4085 } 4086 nextrow[k]++; nextai[k]++; 4087 } 4088 } 4089 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4090 } 4091 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4092 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4093 4094 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4095 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4096 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4097 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4098 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4099 PetscFunctionReturn(0); 4100 } 4101 4102 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4103 4104 #undef __FUNCT__ 4105 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4106 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4107 { 4108 PetscErrorCode ierr; 4109 Mat B_mpi; 4110 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4111 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4112 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4113 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4114 PetscInt len,proc,*dnz,*onz,bs,cbs; 4115 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4116 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4117 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4118 MPI_Status *status; 4119 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4120 PetscBT lnkbt; 4121 Mat_Merge_SeqsToMPI *merge; 4122 PetscContainer container; 4123 4124 PetscFunctionBegin; 4125 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4126 4127 /* make sure it is a PETSc comm */ 4128 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4129 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4130 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4131 4132 ierr = PetscNew(&merge);CHKERRQ(ierr); 4133 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4134 4135 /* determine row ownership */ 4136 /*---------------------------------------------------------*/ 4137 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4138 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4139 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4140 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4141 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4142 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4143 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4144 4145 m = merge->rowmap->n; 4146 owners = merge->rowmap->range; 4147 4148 /* determine the number of messages to send, their lengths */ 4149 /*---------------------------------------------------------*/ 4150 len_s = merge->len_s; 4151 4152 len = 0; /* length of buf_si[] */ 4153 merge->nsend = 0; 4154 for (proc=0; proc<size; proc++) { 4155 len_si[proc] = 0; 4156 if (proc == rank) { 4157 len_s[proc] = 0; 4158 } else { 4159 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4160 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4161 } 4162 if (len_s[proc]) { 4163 merge->nsend++; 4164 nrows = 0; 4165 for (i=owners[proc]; i<owners[proc+1]; i++) { 4166 if (ai[i+1] > ai[i]) nrows++; 4167 } 4168 len_si[proc] = 2*(nrows+1); 4169 len += len_si[proc]; 4170 } 4171 } 4172 4173 /* determine the number and length of messages to receive for ij-structure */ 4174 /*-------------------------------------------------------------------------*/ 4175 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4176 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4177 4178 /* post the Irecv of j-structure */ 4179 /*-------------------------------*/ 4180 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4181 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4182 4183 /* post the Isend of j-structure */ 4184 /*--------------------------------*/ 4185 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4186 4187 for (proc=0, k=0; proc<size; proc++) { 4188 if (!len_s[proc]) continue; 4189 i = owners[proc]; 4190 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4191 k++; 4192 } 4193 4194 /* receives and sends of j-structure are complete */ 4195 /*------------------------------------------------*/ 4196 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4197 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4198 4199 /* send and recv i-structure */ 4200 /*---------------------------*/ 4201 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4202 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4203 4204 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4205 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4206 for (proc=0,k=0; proc<size; proc++) { 4207 if (!len_s[proc]) continue; 4208 /* form outgoing message for i-structure: 4209 buf_si[0]: nrows to be sent 4210 [1:nrows]: row index (global) 4211 [nrows+1:2*nrows+1]: i-structure index 4212 */ 4213 /*-------------------------------------------*/ 4214 nrows = len_si[proc]/2 - 1; 4215 buf_si_i = buf_si + nrows+1; 4216 buf_si[0] = nrows; 4217 buf_si_i[0] = 0; 4218 nrows = 0; 4219 for (i=owners[proc]; i<owners[proc+1]; i++) { 4220 anzi = ai[i+1] - ai[i]; 4221 if (anzi) { 4222 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4223 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4224 nrows++; 4225 } 4226 } 4227 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4228 k++; 4229 buf_si += len_si[proc]; 4230 } 4231 4232 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4233 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4234 4235 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4236 for (i=0; i<merge->nrecv; i++) { 4237 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); 4238 } 4239 4240 ierr = PetscFree(len_si);CHKERRQ(ierr); 4241 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4242 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4243 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4244 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4245 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4246 ierr = PetscFree(status);CHKERRQ(ierr); 4247 4248 /* compute a local seq matrix in each processor */ 4249 /*----------------------------------------------*/ 4250 /* allocate bi array and free space for accumulating nonzero column info */ 4251 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4252 bi[0] = 0; 4253 4254 /* create and initialize a linked list */ 4255 nlnk = N+1; 4256 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4257 4258 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4259 len = ai[owners[rank+1]] - ai[owners[rank]]; 4260 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4261 4262 current_space = free_space; 4263 4264 /* determine symbolic info for each local row */ 4265 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4266 4267 for (k=0; k<merge->nrecv; k++) { 4268 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4269 nrows = *buf_ri_k[k]; 4270 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4271 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4272 } 4273 4274 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4275 len = 0; 4276 for (i=0; i<m; i++) { 4277 bnzi = 0; 4278 /* add local non-zero cols of this proc's seqmat into lnk */ 4279 arow = owners[rank] + i; 4280 anzi = ai[arow+1] - ai[arow]; 4281 aj = a->j + ai[arow]; 4282 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4283 bnzi += nlnk; 4284 /* add received col data into lnk */ 4285 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4286 if (i == *nextrow[k]) { /* i-th row */ 4287 anzi = *(nextai[k]+1) - *nextai[k]; 4288 aj = buf_rj[k] + *nextai[k]; 4289 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4290 bnzi += nlnk; 4291 nextrow[k]++; nextai[k]++; 4292 } 4293 } 4294 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4295 4296 /* if free space is not available, make more free space */ 4297 if (current_space->local_remaining<bnzi) { 4298 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4299 nspacedouble++; 4300 } 4301 /* copy data into free space, then initialize lnk */ 4302 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4303 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4304 4305 current_space->array += bnzi; 4306 current_space->local_used += bnzi; 4307 current_space->local_remaining -= bnzi; 4308 4309 bi[i+1] = bi[i] + bnzi; 4310 } 4311 4312 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4313 4314 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4315 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4316 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4317 4318 /* create symbolic parallel matrix B_mpi */ 4319 /*---------------------------------------*/ 4320 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4321 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4322 if (n==PETSC_DECIDE) { 4323 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4324 } else { 4325 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4326 } 4327 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4328 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4329 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4330 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4331 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4332 4333 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4334 B_mpi->assembled = PETSC_FALSE; 4335 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4336 merge->bi = bi; 4337 merge->bj = bj; 4338 merge->buf_ri = buf_ri; 4339 merge->buf_rj = buf_rj; 4340 merge->coi = NULL; 4341 merge->coj = NULL; 4342 merge->owners_co = NULL; 4343 4344 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4345 4346 /* attach the supporting struct to B_mpi for reuse */ 4347 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4348 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4349 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4350 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4351 *mpimat = B_mpi; 4352 4353 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4354 PetscFunctionReturn(0); 4355 } 4356 4357 #undef __FUNCT__ 4358 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4359 /*@C 4360 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4361 matrices from each processor 4362 4363 Collective on MPI_Comm 4364 4365 Input Parameters: 4366 + comm - the communicators the parallel matrix will live on 4367 . seqmat - the input sequential matrices 4368 . m - number of local rows (or PETSC_DECIDE) 4369 . n - number of local columns (or PETSC_DECIDE) 4370 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4371 4372 Output Parameter: 4373 . mpimat - the parallel matrix generated 4374 4375 Level: advanced 4376 4377 Notes: 4378 The dimensions of the sequential matrix in each processor MUST be the same. 4379 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4380 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4381 @*/ 4382 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4383 { 4384 PetscErrorCode ierr; 4385 PetscMPIInt size; 4386 4387 PetscFunctionBegin; 4388 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4389 if (size == 1) { 4390 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4391 if (scall == MAT_INITIAL_MATRIX) { 4392 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4393 } else { 4394 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4395 } 4396 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4397 PetscFunctionReturn(0); 4398 } 4399 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4400 if (scall == MAT_INITIAL_MATRIX) { 4401 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4402 } 4403 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4404 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4405 PetscFunctionReturn(0); 4406 } 4407 4408 #undef __FUNCT__ 4409 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4410 /*@ 4411 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4412 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4413 with MatGetSize() 4414 4415 Not Collective 4416 4417 Input Parameters: 4418 + A - the matrix 4419 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4420 4421 Output Parameter: 4422 . A_loc - the local sequential matrix generated 4423 4424 Level: developer 4425 4426 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4427 4428 @*/ 4429 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4430 { 4431 PetscErrorCode ierr; 4432 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4433 Mat_SeqAIJ *mat,*a,*b; 4434 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4435 MatScalar *aa,*ba,*cam; 4436 PetscScalar *ca; 4437 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4438 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4439 PetscBool match; 4440 MPI_Comm comm; 4441 PetscMPIInt size; 4442 4443 PetscFunctionBegin; 4444 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4445 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4446 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4447 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4448 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4449 4450 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4451 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4452 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4453 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4454 aa = a->a; ba = b->a; 4455 if (scall == MAT_INITIAL_MATRIX) { 4456 if (size == 1) { 4457 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4458 PetscFunctionReturn(0); 4459 } 4460 4461 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4462 ci[0] = 0; 4463 for (i=0; i<am; i++) { 4464 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4465 } 4466 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4467 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4468 k = 0; 4469 for (i=0; i<am; i++) { 4470 ncols_o = bi[i+1] - bi[i]; 4471 ncols_d = ai[i+1] - ai[i]; 4472 /* off-diagonal portion of A */ 4473 for (jo=0; jo<ncols_o; jo++) { 4474 col = cmap[*bj]; 4475 if (col >= cstart) break; 4476 cj[k] = col; bj++; 4477 ca[k++] = *ba++; 4478 } 4479 /* diagonal portion of A */ 4480 for (j=0; j<ncols_d; j++) { 4481 cj[k] = cstart + *aj++; 4482 ca[k++] = *aa++; 4483 } 4484 /* off-diagonal portion of A */ 4485 for (j=jo; j<ncols_o; j++) { 4486 cj[k] = cmap[*bj++]; 4487 ca[k++] = *ba++; 4488 } 4489 } 4490 /* put together the new matrix */ 4491 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4492 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4493 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4494 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4495 mat->free_a = PETSC_TRUE; 4496 mat->free_ij = PETSC_TRUE; 4497 mat->nonew = 0; 4498 } else if (scall == MAT_REUSE_MATRIX) { 4499 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4500 ci = mat->i; cj = mat->j; cam = mat->a; 4501 for (i=0; i<am; i++) { 4502 /* off-diagonal portion of A */ 4503 ncols_o = bi[i+1] - bi[i]; 4504 for (jo=0; jo<ncols_o; jo++) { 4505 col = cmap[*bj]; 4506 if (col >= cstart) break; 4507 *cam++ = *ba++; bj++; 4508 } 4509 /* diagonal portion of A */ 4510 ncols_d = ai[i+1] - ai[i]; 4511 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4512 /* off-diagonal portion of A */ 4513 for (j=jo; j<ncols_o; j++) { 4514 *cam++ = *ba++; bj++; 4515 } 4516 } 4517 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4518 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4519 PetscFunctionReturn(0); 4520 } 4521 4522 #undef __FUNCT__ 4523 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4524 /*@C 4525 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4526 4527 Not Collective 4528 4529 Input Parameters: 4530 + A - the matrix 4531 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4532 - row, col - index sets of rows and columns to extract (or NULL) 4533 4534 Output Parameter: 4535 . A_loc - the local sequential matrix generated 4536 4537 Level: developer 4538 4539 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4540 4541 @*/ 4542 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4543 { 4544 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4545 PetscErrorCode ierr; 4546 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4547 IS isrowa,iscola; 4548 Mat *aloc; 4549 PetscBool match; 4550 4551 PetscFunctionBegin; 4552 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4553 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4554 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4555 if (!row) { 4556 start = A->rmap->rstart; end = A->rmap->rend; 4557 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4558 } else { 4559 isrowa = *row; 4560 } 4561 if (!col) { 4562 start = A->cmap->rstart; 4563 cmap = a->garray; 4564 nzA = a->A->cmap->n; 4565 nzB = a->B->cmap->n; 4566 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4567 ncols = 0; 4568 for (i=0; i<nzB; i++) { 4569 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4570 else break; 4571 } 4572 imark = i; 4573 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4574 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4575 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4576 } else { 4577 iscola = *col; 4578 } 4579 if (scall != MAT_INITIAL_MATRIX) { 4580 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4581 aloc[0] = *A_loc; 4582 } 4583 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4584 *A_loc = aloc[0]; 4585 ierr = PetscFree(aloc);CHKERRQ(ierr); 4586 if (!row) { 4587 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4588 } 4589 if (!col) { 4590 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4591 } 4592 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4593 PetscFunctionReturn(0); 4594 } 4595 4596 #undef __FUNCT__ 4597 #define __FUNCT__ "MatGetBrowsOfAcols" 4598 /*@C 4599 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4600 4601 Collective on Mat 4602 4603 Input Parameters: 4604 + A,B - the matrices in mpiaij format 4605 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4606 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4607 4608 Output Parameter: 4609 + rowb, colb - index sets of rows and columns of B to extract 4610 - B_seq - the sequential matrix generated 4611 4612 Level: developer 4613 4614 @*/ 4615 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4616 { 4617 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4618 PetscErrorCode ierr; 4619 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4620 IS isrowb,iscolb; 4621 Mat *bseq=NULL; 4622 4623 PetscFunctionBegin; 4624 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4625 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); 4626 } 4627 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4628 4629 if (scall == MAT_INITIAL_MATRIX) { 4630 start = A->cmap->rstart; 4631 cmap = a->garray; 4632 nzA = a->A->cmap->n; 4633 nzB = a->B->cmap->n; 4634 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4635 ncols = 0; 4636 for (i=0; i<nzB; i++) { /* row < local row index */ 4637 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4638 else break; 4639 } 4640 imark = i; 4641 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4642 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4643 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4644 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4645 } else { 4646 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4647 isrowb = *rowb; iscolb = *colb; 4648 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4649 bseq[0] = *B_seq; 4650 } 4651 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4652 *B_seq = bseq[0]; 4653 ierr = PetscFree(bseq);CHKERRQ(ierr); 4654 if (!rowb) { 4655 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4656 } else { 4657 *rowb = isrowb; 4658 } 4659 if (!colb) { 4660 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4661 } else { 4662 *colb = iscolb; 4663 } 4664 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4665 PetscFunctionReturn(0); 4666 } 4667 4668 #undef __FUNCT__ 4669 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4670 /* 4671 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4672 of the OFF-DIAGONAL portion of local A 4673 4674 Collective on Mat 4675 4676 Input Parameters: 4677 + A,B - the matrices in mpiaij format 4678 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4679 4680 Output Parameter: 4681 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4682 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4683 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4684 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4685 4686 Level: developer 4687 4688 */ 4689 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4690 { 4691 VecScatter_MPI_General *gen_to,*gen_from; 4692 PetscErrorCode ierr; 4693 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4694 Mat_SeqAIJ *b_oth; 4695 VecScatter ctx =a->Mvctx; 4696 MPI_Comm comm; 4697 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4698 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4699 PetscScalar *rvalues,*svalues; 4700 MatScalar *b_otha,*bufa,*bufA; 4701 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4702 MPI_Request *rwaits = NULL,*swaits = NULL; 4703 MPI_Status *sstatus,rstatus; 4704 PetscMPIInt jj,size; 4705 PetscInt *cols,sbs,rbs; 4706 PetscScalar *vals; 4707 4708 PetscFunctionBegin; 4709 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4710 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4711 4712 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4713 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); 4714 } 4715 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4716 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4717 4718 gen_to = (VecScatter_MPI_General*)ctx->todata; 4719 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4720 rvalues = gen_from->values; /* holds the length of receiving row */ 4721 svalues = gen_to->values; /* holds the length of sending row */ 4722 nrecvs = gen_from->n; 4723 nsends = gen_to->n; 4724 4725 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4726 srow = gen_to->indices; /* local row index to be sent */ 4727 sstarts = gen_to->starts; 4728 sprocs = gen_to->procs; 4729 sstatus = gen_to->sstatus; 4730 sbs = gen_to->bs; 4731 rstarts = gen_from->starts; 4732 rprocs = gen_from->procs; 4733 rbs = gen_from->bs; 4734 4735 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4736 if (scall == MAT_INITIAL_MATRIX) { 4737 /* i-array */ 4738 /*---------*/ 4739 /* post receives */ 4740 for (i=0; i<nrecvs; i++) { 4741 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4742 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4743 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4744 } 4745 4746 /* pack the outgoing message */ 4747 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4748 4749 sstartsj[0] = 0; 4750 rstartsj[0] = 0; 4751 len = 0; /* total length of j or a array to be sent */ 4752 k = 0; 4753 for (i=0; i<nsends; i++) { 4754 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4755 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4756 for (j=0; j<nrows; j++) { 4757 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4758 for (l=0; l<sbs; l++) { 4759 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4760 4761 rowlen[j*sbs+l] = ncols; 4762 4763 len += ncols; 4764 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4765 } 4766 k++; 4767 } 4768 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4769 4770 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4771 } 4772 /* recvs and sends of i-array are completed */ 4773 i = nrecvs; 4774 while (i--) { 4775 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4776 } 4777 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4778 4779 /* allocate buffers for sending j and a arrays */ 4780 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4781 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4782 4783 /* create i-array of B_oth */ 4784 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4785 4786 b_othi[0] = 0; 4787 len = 0; /* total length of j or a array to be received */ 4788 k = 0; 4789 for (i=0; i<nrecvs; i++) { 4790 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4791 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4792 for (j=0; j<nrows; j++) { 4793 b_othi[k+1] = b_othi[k] + rowlen[j]; 4794 ierr = PetscIntSumError(rowlen[j],len,&len); 4795 k++; 4796 } 4797 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4798 } 4799 4800 /* allocate space for j and a arrrays of B_oth */ 4801 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4802 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4803 4804 /* j-array */ 4805 /*---------*/ 4806 /* post receives of j-array */ 4807 for (i=0; i<nrecvs; i++) { 4808 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4809 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4810 } 4811 4812 /* pack the outgoing message j-array */ 4813 k = 0; 4814 for (i=0; i<nsends; i++) { 4815 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4816 bufJ = bufj+sstartsj[i]; 4817 for (j=0; j<nrows; j++) { 4818 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4819 for (ll=0; ll<sbs; ll++) { 4820 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4821 for (l=0; l<ncols; l++) { 4822 *bufJ++ = cols[l]; 4823 } 4824 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4825 } 4826 } 4827 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4828 } 4829 4830 /* recvs and sends of j-array are completed */ 4831 i = nrecvs; 4832 while (i--) { 4833 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4834 } 4835 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4836 } else if (scall == MAT_REUSE_MATRIX) { 4837 sstartsj = *startsj_s; 4838 rstartsj = *startsj_r; 4839 bufa = *bufa_ptr; 4840 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4841 b_otha = b_oth->a; 4842 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4843 4844 /* a-array */ 4845 /*---------*/ 4846 /* post receives of a-array */ 4847 for (i=0; i<nrecvs; i++) { 4848 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4849 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4850 } 4851 4852 /* pack the outgoing message a-array */ 4853 k = 0; 4854 for (i=0; i<nsends; i++) { 4855 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4856 bufA = bufa+sstartsj[i]; 4857 for (j=0; j<nrows; j++) { 4858 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4859 for (ll=0; ll<sbs; ll++) { 4860 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4861 for (l=0; l<ncols; l++) { 4862 *bufA++ = vals[l]; 4863 } 4864 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4865 } 4866 } 4867 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4868 } 4869 /* recvs and sends of a-array are completed */ 4870 i = nrecvs; 4871 while (i--) { 4872 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4873 } 4874 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4875 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4876 4877 if (scall == MAT_INITIAL_MATRIX) { 4878 /* put together the new matrix */ 4879 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4880 4881 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4882 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4883 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4884 b_oth->free_a = PETSC_TRUE; 4885 b_oth->free_ij = PETSC_TRUE; 4886 b_oth->nonew = 0; 4887 4888 ierr = PetscFree(bufj);CHKERRQ(ierr); 4889 if (!startsj_s || !bufa_ptr) { 4890 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4891 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4892 } else { 4893 *startsj_s = sstartsj; 4894 *startsj_r = rstartsj; 4895 *bufa_ptr = bufa; 4896 } 4897 } 4898 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4899 PetscFunctionReturn(0); 4900 } 4901 4902 #undef __FUNCT__ 4903 #define __FUNCT__ "MatGetCommunicationStructs" 4904 /*@C 4905 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4906 4907 Not Collective 4908 4909 Input Parameters: 4910 . A - The matrix in mpiaij format 4911 4912 Output Parameter: 4913 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4914 . colmap - A map from global column index to local index into lvec 4915 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4916 4917 Level: developer 4918 4919 @*/ 4920 #if defined(PETSC_USE_CTABLE) 4921 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4922 #else 4923 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4924 #endif 4925 { 4926 Mat_MPIAIJ *a; 4927 4928 PetscFunctionBegin; 4929 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4930 PetscValidPointer(lvec, 2); 4931 PetscValidPointer(colmap, 3); 4932 PetscValidPointer(multScatter, 4); 4933 a = (Mat_MPIAIJ*) A->data; 4934 if (lvec) *lvec = a->lvec; 4935 if (colmap) *colmap = a->colmap; 4936 if (multScatter) *multScatter = a->Mvctx; 4937 PetscFunctionReturn(0); 4938 } 4939 4940 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4941 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4942 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4943 #if defined(PETSC_HAVE_ELEMENTAL) 4944 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4945 #endif 4946 4947 #undef __FUNCT__ 4948 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4949 /* 4950 Computes (B'*A')' since computing B*A directly is untenable 4951 4952 n p p 4953 ( ) ( ) ( ) 4954 m ( A ) * n ( B ) = m ( C ) 4955 ( ) ( ) ( ) 4956 4957 */ 4958 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4959 { 4960 PetscErrorCode ierr; 4961 Mat At,Bt,Ct; 4962 4963 PetscFunctionBegin; 4964 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4965 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4966 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4967 ierr = MatDestroy(&At);CHKERRQ(ierr); 4968 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4969 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4970 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4971 PetscFunctionReturn(0); 4972 } 4973 4974 #undef __FUNCT__ 4975 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4976 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4977 { 4978 PetscErrorCode ierr; 4979 PetscInt m=A->rmap->n,n=B->cmap->n; 4980 Mat Cmat; 4981 4982 PetscFunctionBegin; 4983 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); 4984 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4985 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4986 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4987 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4988 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4989 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4990 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4991 4992 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 4993 4994 *C = Cmat; 4995 PetscFunctionReturn(0); 4996 } 4997 4998 /* ----------------------------------------------------------------*/ 4999 #undef __FUNCT__ 5000 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5001 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5002 { 5003 PetscErrorCode ierr; 5004 5005 PetscFunctionBegin; 5006 if (scall == MAT_INITIAL_MATRIX) { 5007 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5008 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5009 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5010 } 5011 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5012 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5013 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5014 PetscFunctionReturn(0); 5015 } 5016 5017 /*MC 5018 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5019 5020 Options Database Keys: 5021 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5022 5023 Level: beginner 5024 5025 .seealso: MatCreateAIJ() 5026 M*/ 5027 5028 #undef __FUNCT__ 5029 #define __FUNCT__ "MatCreate_MPIAIJ" 5030 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5031 { 5032 Mat_MPIAIJ *b; 5033 PetscErrorCode ierr; 5034 PetscMPIInt size; 5035 5036 PetscFunctionBegin; 5037 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5038 5039 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5040 B->data = (void*)b; 5041 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5042 B->assembled = PETSC_FALSE; 5043 B->insertmode = NOT_SET_VALUES; 5044 b->size = size; 5045 5046 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5047 5048 /* build cache for off array entries formed */ 5049 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5050 5051 b->donotstash = PETSC_FALSE; 5052 b->colmap = 0; 5053 b->garray = 0; 5054 b->roworiented = PETSC_TRUE; 5055 5056 /* stuff used for matrix vector multiply */ 5057 b->lvec = NULL; 5058 b->Mvctx = NULL; 5059 5060 /* stuff for MatGetRow() */ 5061 b->rowindices = 0; 5062 b->rowvalues = 0; 5063 b->getrowactive = PETSC_FALSE; 5064 5065 /* flexible pointer used in CUSP/CUSPARSE classes */ 5066 b->spptr = NULL; 5067 5068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5072 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5074 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5076 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5077 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5078 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5079 #if defined(PETSC_HAVE_ELEMENTAL) 5080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5081 #endif 5082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5083 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5084 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5085 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5086 PetscFunctionReturn(0); 5087 } 5088 5089 #undef __FUNCT__ 5090 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5091 /*@C 5092 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5093 and "off-diagonal" part of the matrix in CSR format. 5094 5095 Collective on MPI_Comm 5096 5097 Input Parameters: 5098 + comm - MPI communicator 5099 . m - number of local rows (Cannot be PETSC_DECIDE) 5100 . n - This value should be the same as the local size used in creating the 5101 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5102 calculated if N is given) For square matrices n is almost always m. 5103 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5104 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5105 . i - row indices for "diagonal" portion of matrix 5106 . j - column indices 5107 . a - matrix values 5108 . oi - row indices for "off-diagonal" portion of matrix 5109 . oj - column indices 5110 - oa - matrix values 5111 5112 Output Parameter: 5113 . mat - the matrix 5114 5115 Level: advanced 5116 5117 Notes: 5118 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5119 must free the arrays once the matrix has been destroyed and not before. 5120 5121 The i and j indices are 0 based 5122 5123 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5124 5125 This sets local rows and cannot be used to set off-processor values. 5126 5127 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5128 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5129 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5130 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5131 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5132 communication if it is known that only local entries will be set. 5133 5134 .keywords: matrix, aij, compressed row, sparse, parallel 5135 5136 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5137 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5138 @*/ 5139 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) 5140 { 5141 PetscErrorCode ierr; 5142 Mat_MPIAIJ *maij; 5143 5144 PetscFunctionBegin; 5145 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5146 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5147 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5148 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5149 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5150 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5151 maij = (Mat_MPIAIJ*) (*mat)->data; 5152 5153 (*mat)->preallocated = PETSC_TRUE; 5154 5155 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5156 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5157 5158 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5159 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5160 5161 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5162 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5163 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5164 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5165 5166 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5167 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5168 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5169 PetscFunctionReturn(0); 5170 } 5171 5172 /* 5173 Special version for direct calls from Fortran 5174 */ 5175 #include <petsc/private/fortranimpl.h> 5176 5177 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5178 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5179 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5180 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5181 #endif 5182 5183 /* Change these macros so can be used in void function */ 5184 #undef CHKERRQ 5185 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5186 #undef SETERRQ2 5187 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5188 #undef SETERRQ3 5189 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5190 #undef SETERRQ 5191 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5192 5193 #undef __FUNCT__ 5194 #define __FUNCT__ "matsetvaluesmpiaij_" 5195 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) 5196 { 5197 Mat mat = *mmat; 5198 PetscInt m = *mm, n = *mn; 5199 InsertMode addv = *maddv; 5200 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5201 PetscScalar value; 5202 PetscErrorCode ierr; 5203 5204 MatCheckPreallocated(mat,1); 5205 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5206 5207 #if defined(PETSC_USE_DEBUG) 5208 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5209 #endif 5210 { 5211 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5212 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5213 PetscBool roworiented = aij->roworiented; 5214 5215 /* Some Variables required in the macro */ 5216 Mat A = aij->A; 5217 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5218 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5219 MatScalar *aa = a->a; 5220 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5221 Mat B = aij->B; 5222 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5223 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5224 MatScalar *ba = b->a; 5225 5226 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5227 PetscInt nonew = a->nonew; 5228 MatScalar *ap1,*ap2; 5229 5230 PetscFunctionBegin; 5231 for (i=0; i<m; i++) { 5232 if (im[i] < 0) continue; 5233 #if defined(PETSC_USE_DEBUG) 5234 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); 5235 #endif 5236 if (im[i] >= rstart && im[i] < rend) { 5237 row = im[i] - rstart; 5238 lastcol1 = -1; 5239 rp1 = aj + ai[row]; 5240 ap1 = aa + ai[row]; 5241 rmax1 = aimax[row]; 5242 nrow1 = ailen[row]; 5243 low1 = 0; 5244 high1 = nrow1; 5245 lastcol2 = -1; 5246 rp2 = bj + bi[row]; 5247 ap2 = ba + bi[row]; 5248 rmax2 = bimax[row]; 5249 nrow2 = bilen[row]; 5250 low2 = 0; 5251 high2 = nrow2; 5252 5253 for (j=0; j<n; j++) { 5254 if (roworiented) value = v[i*n+j]; 5255 else value = v[i+j*m]; 5256 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5257 if (in[j] >= cstart && in[j] < cend) { 5258 col = in[j] - cstart; 5259 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5260 } else if (in[j] < 0) continue; 5261 #if defined(PETSC_USE_DEBUG) 5262 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); 5263 #endif 5264 else { 5265 if (mat->was_assembled) { 5266 if (!aij->colmap) { 5267 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5268 } 5269 #if defined(PETSC_USE_CTABLE) 5270 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5271 col--; 5272 #else 5273 col = aij->colmap[in[j]] - 1; 5274 #endif 5275 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5276 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5277 col = in[j]; 5278 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5279 B = aij->B; 5280 b = (Mat_SeqAIJ*)B->data; 5281 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5282 rp2 = bj + bi[row]; 5283 ap2 = ba + bi[row]; 5284 rmax2 = bimax[row]; 5285 nrow2 = bilen[row]; 5286 low2 = 0; 5287 high2 = nrow2; 5288 bm = aij->B->rmap->n; 5289 ba = b->a; 5290 } 5291 } else col = in[j]; 5292 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5293 } 5294 } 5295 } else if (!aij->donotstash) { 5296 if (roworiented) { 5297 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5298 } else { 5299 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5300 } 5301 } 5302 } 5303 } 5304 PetscFunctionReturnVoid(); 5305 } 5306 5307