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 @*/ 2504 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2505 { 2506 PetscErrorCode ierr; 2507 2508 PetscFunctionBegin; 2509 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2510 PetscFunctionReturn(0); 2511 } 2512 2513 #undef __FUNCT__ 2514 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2515 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2516 { 2517 PetscErrorCode ierr; 2518 PetscBool sc = PETSC_FALSE,flg; 2519 2520 PetscFunctionBegin; 2521 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2522 ierr = PetscObjectOptionsBegin((PetscObject)A); 2523 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2524 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2525 if (flg) { 2526 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2527 } 2528 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2529 PetscFunctionReturn(0); 2530 } 2531 2532 #undef __FUNCT__ 2533 #define __FUNCT__ "MatShift_MPIAIJ" 2534 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2535 { 2536 PetscErrorCode ierr; 2537 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2538 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2539 2540 PetscFunctionBegin; 2541 if (!Y->preallocated) { 2542 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2543 } else if (!aij->nz) { 2544 PetscInt nonew = aij->nonew; 2545 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2546 aij->nonew = nonew; 2547 } 2548 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2549 PetscFunctionReturn(0); 2550 } 2551 2552 #undef __FUNCT__ 2553 #define __FUNCT__ "MatMissingDiagonal_MPIAIJ" 2554 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2555 { 2556 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2557 PetscErrorCode ierr; 2558 2559 PetscFunctionBegin; 2560 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2561 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2562 if (d) { 2563 PetscInt rstart; 2564 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2565 *d += rstart; 2566 2567 } 2568 PetscFunctionReturn(0); 2569 } 2570 2571 2572 /* -------------------------------------------------------------------*/ 2573 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2574 MatGetRow_MPIAIJ, 2575 MatRestoreRow_MPIAIJ, 2576 MatMult_MPIAIJ, 2577 /* 4*/ MatMultAdd_MPIAIJ, 2578 MatMultTranspose_MPIAIJ, 2579 MatMultTransposeAdd_MPIAIJ, 2580 0, 2581 0, 2582 0, 2583 /*10*/ 0, 2584 0, 2585 0, 2586 MatSOR_MPIAIJ, 2587 MatTranspose_MPIAIJ, 2588 /*15*/ MatGetInfo_MPIAIJ, 2589 MatEqual_MPIAIJ, 2590 MatGetDiagonal_MPIAIJ, 2591 MatDiagonalScale_MPIAIJ, 2592 MatNorm_MPIAIJ, 2593 /*20*/ MatAssemblyBegin_MPIAIJ, 2594 MatAssemblyEnd_MPIAIJ, 2595 MatSetOption_MPIAIJ, 2596 MatZeroEntries_MPIAIJ, 2597 /*24*/ MatZeroRows_MPIAIJ, 2598 0, 2599 0, 2600 0, 2601 0, 2602 /*29*/ MatSetUp_MPIAIJ, 2603 0, 2604 0, 2605 0, 2606 0, 2607 /*34*/ MatDuplicate_MPIAIJ, 2608 0, 2609 0, 2610 0, 2611 0, 2612 /*39*/ MatAXPY_MPIAIJ, 2613 MatGetSubMatrices_MPIAIJ, 2614 MatIncreaseOverlap_MPIAIJ, 2615 MatGetValues_MPIAIJ, 2616 MatCopy_MPIAIJ, 2617 /*44*/ MatGetRowMax_MPIAIJ, 2618 MatScale_MPIAIJ, 2619 MatShift_MPIAIJ, 2620 MatDiagonalSet_MPIAIJ, 2621 MatZeroRowsColumns_MPIAIJ, 2622 /*49*/ MatSetRandom_MPIAIJ, 2623 0, 2624 0, 2625 0, 2626 0, 2627 /*54*/ MatFDColoringCreate_MPIXAIJ, 2628 0, 2629 MatSetUnfactored_MPIAIJ, 2630 MatPermute_MPIAIJ, 2631 0, 2632 /*59*/ MatGetSubMatrix_MPIAIJ, 2633 MatDestroy_MPIAIJ, 2634 MatView_MPIAIJ, 2635 0, 2636 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2637 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2638 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2639 0, 2640 0, 2641 0, 2642 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2643 MatGetRowMinAbs_MPIAIJ, 2644 0, 2645 MatSetColoring_MPIAIJ, 2646 0, 2647 MatSetValuesAdifor_MPIAIJ, 2648 /*75*/ MatFDColoringApply_AIJ, 2649 MatSetFromOptions_MPIAIJ, 2650 0, 2651 0, 2652 MatFindZeroDiagonals_MPIAIJ, 2653 /*80*/ 0, 2654 0, 2655 0, 2656 /*83*/ MatLoad_MPIAIJ, 2657 0, 2658 0, 2659 0, 2660 0, 2661 0, 2662 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2663 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2664 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2665 MatPtAP_MPIAIJ_MPIAIJ, 2666 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2667 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2668 0, 2669 0, 2670 0, 2671 0, 2672 /*99*/ 0, 2673 0, 2674 0, 2675 MatConjugate_MPIAIJ, 2676 0, 2677 /*104*/MatSetValuesRow_MPIAIJ, 2678 MatRealPart_MPIAIJ, 2679 MatImaginaryPart_MPIAIJ, 2680 0, 2681 0, 2682 /*109*/0, 2683 0, 2684 MatGetRowMin_MPIAIJ, 2685 0, 2686 MatMissingDiagonal_MPIAIJ, 2687 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2688 0, 2689 MatGetGhosts_MPIAIJ, 2690 0, 2691 0, 2692 /*119*/0, 2693 0, 2694 0, 2695 0, 2696 MatGetMultiProcBlock_MPIAIJ, 2697 /*124*/MatFindNonzeroRows_MPIAIJ, 2698 MatGetColumnNorms_MPIAIJ, 2699 MatInvertBlockDiagonal_MPIAIJ, 2700 0, 2701 MatGetSubMatricesMPI_MPIAIJ, 2702 /*129*/0, 2703 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2704 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2705 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2706 0, 2707 /*134*/0, 2708 0, 2709 0, 2710 0, 2711 0, 2712 /*139*/0, 2713 0, 2714 0, 2715 MatFDColoringSetUp_MPIXAIJ, 2716 MatFindOffBlockDiagonalEntries_MPIAIJ, 2717 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2718 }; 2719 2720 /* ----------------------------------------------------------------------------------------*/ 2721 2722 #undef __FUNCT__ 2723 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2724 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2725 { 2726 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2727 PetscErrorCode ierr; 2728 2729 PetscFunctionBegin; 2730 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2731 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2732 PetscFunctionReturn(0); 2733 } 2734 2735 #undef __FUNCT__ 2736 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2737 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2738 { 2739 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2740 PetscErrorCode ierr; 2741 2742 PetscFunctionBegin; 2743 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2744 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2745 PetscFunctionReturn(0); 2746 } 2747 2748 #undef __FUNCT__ 2749 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2750 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2751 { 2752 Mat_MPIAIJ *b; 2753 PetscErrorCode ierr; 2754 2755 PetscFunctionBegin; 2756 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2757 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2758 b = (Mat_MPIAIJ*)B->data; 2759 2760 if (!B->preallocated) { 2761 /* Explicitly create 2 MATSEQAIJ matrices. */ 2762 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2763 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2764 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2765 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2766 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2767 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2768 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2769 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2770 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2771 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2772 } 2773 2774 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2775 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2776 B->preallocated = PETSC_TRUE; 2777 PetscFunctionReturn(0); 2778 } 2779 2780 #undef __FUNCT__ 2781 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2782 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2783 { 2784 Mat mat; 2785 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2786 PetscErrorCode ierr; 2787 2788 PetscFunctionBegin; 2789 *newmat = 0; 2790 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2791 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2792 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2793 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2794 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2795 a = (Mat_MPIAIJ*)mat->data; 2796 2797 mat->factortype = matin->factortype; 2798 mat->assembled = PETSC_TRUE; 2799 mat->insertmode = NOT_SET_VALUES; 2800 mat->preallocated = PETSC_TRUE; 2801 2802 a->size = oldmat->size; 2803 a->rank = oldmat->rank; 2804 a->donotstash = oldmat->donotstash; 2805 a->roworiented = oldmat->roworiented; 2806 a->rowindices = 0; 2807 a->rowvalues = 0; 2808 a->getrowactive = PETSC_FALSE; 2809 2810 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2811 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2812 2813 if (oldmat->colmap) { 2814 #if defined(PETSC_USE_CTABLE) 2815 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2816 #else 2817 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2818 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2819 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2820 #endif 2821 } else a->colmap = 0; 2822 if (oldmat->garray) { 2823 PetscInt len; 2824 len = oldmat->B->cmap->n; 2825 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2826 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2827 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2828 } else a->garray = 0; 2829 2830 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2831 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2832 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2833 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2834 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2835 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2836 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2837 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2838 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2839 *newmat = mat; 2840 PetscFunctionReturn(0); 2841 } 2842 2843 2844 2845 #undef __FUNCT__ 2846 #define __FUNCT__ "MatLoad_MPIAIJ" 2847 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2848 { 2849 PetscScalar *vals,*svals; 2850 MPI_Comm comm; 2851 PetscErrorCode ierr; 2852 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2853 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2854 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2855 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2856 PetscInt cend,cstart,n,*rowners; 2857 int fd; 2858 PetscInt bs = newMat->rmap->bs; 2859 2860 PetscFunctionBegin; 2861 /* force binary viewer to load .info file if it has not yet done so */ 2862 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2863 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2864 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2865 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2866 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2867 if (!rank) { 2868 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2869 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2870 } 2871 2872 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2873 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2874 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2875 if (bs < 0) bs = 1; 2876 2877 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2878 M = header[1]; N = header[2]; 2879 2880 /* If global sizes are set, check if they are consistent with that given in the file */ 2881 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); 2882 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); 2883 2884 /* determine ownership of all (block) rows */ 2885 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2886 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2887 else m = newMat->rmap->n; /* Set by user */ 2888 2889 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2890 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2891 2892 /* First process needs enough room for process with most rows */ 2893 if (!rank) { 2894 mmax = rowners[1]; 2895 for (i=2; i<=size; i++) { 2896 mmax = PetscMax(mmax, rowners[i]); 2897 } 2898 } else mmax = -1; /* unused, but compilers complain */ 2899 2900 rowners[0] = 0; 2901 for (i=2; i<=size; i++) { 2902 rowners[i] += rowners[i-1]; 2903 } 2904 rstart = rowners[rank]; 2905 rend = rowners[rank+1]; 2906 2907 /* distribute row lengths to all processors */ 2908 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2909 if (!rank) { 2910 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2911 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2912 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2913 for (j=0; j<m; j++) { 2914 procsnz[0] += ourlens[j]; 2915 } 2916 for (i=1; i<size; i++) { 2917 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2918 /* calculate the number of nonzeros on each processor */ 2919 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2920 procsnz[i] += rowlengths[j]; 2921 } 2922 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2923 } 2924 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2925 } else { 2926 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2927 } 2928 2929 if (!rank) { 2930 /* determine max buffer needed and allocate it */ 2931 maxnz = 0; 2932 for (i=0; i<size; i++) { 2933 maxnz = PetscMax(maxnz,procsnz[i]); 2934 } 2935 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2936 2937 /* read in my part of the matrix column indices */ 2938 nz = procsnz[0]; 2939 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2940 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2941 2942 /* read in every one elses and ship off */ 2943 for (i=1; i<size; i++) { 2944 nz = procsnz[i]; 2945 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2946 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2947 } 2948 ierr = PetscFree(cols);CHKERRQ(ierr); 2949 } else { 2950 /* determine buffer space needed for message */ 2951 nz = 0; 2952 for (i=0; i<m; i++) { 2953 nz += ourlens[i]; 2954 } 2955 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2956 2957 /* receive message of column indices*/ 2958 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2959 } 2960 2961 /* determine column ownership if matrix is not square */ 2962 if (N != M) { 2963 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2964 else n = newMat->cmap->n; 2965 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2966 cstart = cend - n; 2967 } else { 2968 cstart = rstart; 2969 cend = rend; 2970 n = cend - cstart; 2971 } 2972 2973 /* loop over local rows, determining number of off diagonal entries */ 2974 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2975 jj = 0; 2976 for (i=0; i<m; i++) { 2977 for (j=0; j<ourlens[i]; j++) { 2978 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2979 jj++; 2980 } 2981 } 2982 2983 for (i=0; i<m; i++) { 2984 ourlens[i] -= offlens[i]; 2985 } 2986 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2987 2988 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2989 2990 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2991 2992 for (i=0; i<m; i++) { 2993 ourlens[i] += offlens[i]; 2994 } 2995 2996 if (!rank) { 2997 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2998 2999 /* read in my part of the matrix numerical values */ 3000 nz = procsnz[0]; 3001 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3002 3003 /* insert into matrix */ 3004 jj = rstart; 3005 smycols = mycols; 3006 svals = vals; 3007 for (i=0; i<m; i++) { 3008 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3009 smycols += ourlens[i]; 3010 svals += ourlens[i]; 3011 jj++; 3012 } 3013 3014 /* read in other processors and ship out */ 3015 for (i=1; i<size; i++) { 3016 nz = procsnz[i]; 3017 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3018 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3019 } 3020 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3021 } else { 3022 /* receive numeric values */ 3023 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3024 3025 /* receive message of values*/ 3026 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3027 3028 /* insert into matrix */ 3029 jj = rstart; 3030 smycols = mycols; 3031 svals = vals; 3032 for (i=0; i<m; i++) { 3033 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3034 smycols += ourlens[i]; 3035 svals += ourlens[i]; 3036 jj++; 3037 } 3038 } 3039 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3040 ierr = PetscFree(vals);CHKERRQ(ierr); 3041 ierr = PetscFree(mycols);CHKERRQ(ierr); 3042 ierr = PetscFree(rowners);CHKERRQ(ierr); 3043 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3044 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3045 PetscFunctionReturn(0); 3046 } 3047 3048 #undef __FUNCT__ 3049 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3050 /* TODO: Not scalable because of ISAllGather() unless getting all columns. */ 3051 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3052 { 3053 PetscErrorCode ierr; 3054 IS iscol_local; 3055 PetscInt csize; 3056 3057 PetscFunctionBegin; 3058 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3059 if (call == MAT_REUSE_MATRIX) { 3060 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3061 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3062 } else { 3063 /* check if we are grabbing all columns*/ 3064 PetscBool isstride; 3065 PetscMPIInt lisstride = 0,gisstride; 3066 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 3067 if (isstride) { 3068 PetscInt start,len,mstart,mlen; 3069 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 3070 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 3071 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 3072 if (mstart == start && mlen-mstart == len) lisstride = 1; 3073 } 3074 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 3075 if (gisstride) { 3076 PetscInt N; 3077 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 3078 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 3079 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 3080 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 3081 } else { 3082 PetscInt cbs; 3083 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3084 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3085 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3086 } 3087 } 3088 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3089 if (call == MAT_INITIAL_MATRIX) { 3090 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3091 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3092 } 3093 PetscFunctionReturn(0); 3094 } 3095 3096 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3097 #undef __FUNCT__ 3098 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3099 /* 3100 Not great since it makes two copies of the submatrix, first an SeqAIJ 3101 in local and then by concatenating the local matrices the end result. 3102 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3103 3104 Note: This requires a sequential iscol with all indices. 3105 */ 3106 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3107 { 3108 PetscErrorCode ierr; 3109 PetscMPIInt rank,size; 3110 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3111 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3112 PetscBool allcolumns, colflag; 3113 Mat M,Mreuse; 3114 MatScalar *vwork,*aa; 3115 MPI_Comm comm; 3116 Mat_SeqAIJ *aij; 3117 3118 PetscFunctionBegin; 3119 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3120 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3121 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3122 3123 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3124 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3125 if (colflag && ncol == mat->cmap->N) { 3126 allcolumns = PETSC_TRUE; 3127 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix\n");CHKERRQ(ierr); 3128 } else { 3129 allcolumns = PETSC_FALSE; 3130 } 3131 if (call == MAT_REUSE_MATRIX) { 3132 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3133 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3134 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3135 } else { 3136 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3137 } 3138 3139 /* 3140 m - number of local rows 3141 n - number of columns (same on all processors) 3142 rstart - first row in new global matrix generated 3143 */ 3144 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3145 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3146 if (call == MAT_INITIAL_MATRIX) { 3147 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3148 ii = aij->i; 3149 jj = aij->j; 3150 3151 /* 3152 Determine the number of non-zeros in the diagonal and off-diagonal 3153 portions of the matrix in order to do correct preallocation 3154 */ 3155 3156 /* first get start and end of "diagonal" columns */ 3157 if (csize == PETSC_DECIDE) { 3158 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3159 if (mglobal == n) { /* square matrix */ 3160 nlocal = m; 3161 } else { 3162 nlocal = n/size + ((n % size) > rank); 3163 } 3164 } else { 3165 nlocal = csize; 3166 } 3167 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3168 rstart = rend - nlocal; 3169 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); 3170 3171 /* next, compute all the lengths */ 3172 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3173 olens = dlens + m; 3174 for (i=0; i<m; i++) { 3175 jend = ii[i+1] - ii[i]; 3176 olen = 0; 3177 dlen = 0; 3178 for (j=0; j<jend; j++) { 3179 if (*jj < rstart || *jj >= rend) olen++; 3180 else dlen++; 3181 jj++; 3182 } 3183 olens[i] = olen; 3184 dlens[i] = dlen; 3185 } 3186 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3187 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3188 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3189 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3190 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3191 ierr = PetscFree(dlens);CHKERRQ(ierr); 3192 } else { 3193 PetscInt ml,nl; 3194 3195 M = *newmat; 3196 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3197 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3198 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3199 /* 3200 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3201 rather than the slower MatSetValues(). 3202 */ 3203 M->was_assembled = PETSC_TRUE; 3204 M->assembled = PETSC_FALSE; 3205 } 3206 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3207 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3208 ii = aij->i; 3209 jj = aij->j; 3210 aa = aij->a; 3211 for (i=0; i<m; i++) { 3212 row = rstart + i; 3213 nz = ii[i+1] - ii[i]; 3214 cwork = jj; jj += nz; 3215 vwork = aa; aa += nz; 3216 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3217 } 3218 3219 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3220 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3221 *newmat = M; 3222 3223 /* save submatrix used in processor for next request */ 3224 if (call == MAT_INITIAL_MATRIX) { 3225 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3226 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3227 } 3228 PetscFunctionReturn(0); 3229 } 3230 3231 #undef __FUNCT__ 3232 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3233 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3234 { 3235 PetscInt m,cstart, cend,j,nnz,i,d; 3236 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3237 const PetscInt *JJ; 3238 PetscScalar *values; 3239 PetscErrorCode ierr; 3240 3241 PetscFunctionBegin; 3242 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3243 3244 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3245 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3246 m = B->rmap->n; 3247 cstart = B->cmap->rstart; 3248 cend = B->cmap->rend; 3249 rstart = B->rmap->rstart; 3250 3251 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3252 3253 #if defined(PETSC_USE_DEBUGGING) 3254 for (i=0; i<m; i++) { 3255 nnz = Ii[i+1]- Ii[i]; 3256 JJ = J + Ii[i]; 3257 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3258 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3259 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); 3260 } 3261 #endif 3262 3263 for (i=0; i<m; i++) { 3264 nnz = Ii[i+1]- Ii[i]; 3265 JJ = J + Ii[i]; 3266 nnz_max = PetscMax(nnz_max,nnz); 3267 d = 0; 3268 for (j=0; j<nnz; j++) { 3269 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3270 } 3271 d_nnz[i] = d; 3272 o_nnz[i] = nnz - d; 3273 } 3274 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3275 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3276 3277 if (v) values = (PetscScalar*)v; 3278 else { 3279 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3280 } 3281 3282 for (i=0; i<m; i++) { 3283 ii = i + rstart; 3284 nnz = Ii[i+1]- Ii[i]; 3285 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3286 } 3287 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3288 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3289 3290 if (!v) { 3291 ierr = PetscFree(values);CHKERRQ(ierr); 3292 } 3293 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3294 PetscFunctionReturn(0); 3295 } 3296 3297 #undef __FUNCT__ 3298 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3299 /*@ 3300 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3301 (the default parallel PETSc format). 3302 3303 Collective on MPI_Comm 3304 3305 Input Parameters: 3306 + B - the matrix 3307 . i - the indices into j for the start of each local row (starts with zero) 3308 . j - the column indices for each local row (starts with zero) 3309 - v - optional values in the matrix 3310 3311 Level: developer 3312 3313 Notes: 3314 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3315 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3316 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3317 3318 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3319 3320 The format which is used for the sparse matrix input, is equivalent to a 3321 row-major ordering.. i.e for the following matrix, the input data expected is 3322 as shown 3323 3324 $ 1 0 0 3325 $ 2 0 3 P0 3326 $ ------- 3327 $ 4 5 6 P1 3328 $ 3329 $ Process0 [P0]: rows_owned=[0,1] 3330 $ i = {0,1,3} [size = nrow+1 = 2+1] 3331 $ j = {0,0,2} [size = 3] 3332 $ v = {1,2,3} [size = 3] 3333 $ 3334 $ Process1 [P1]: rows_owned=[2] 3335 $ i = {0,3} [size = nrow+1 = 1+1] 3336 $ j = {0,1,2} [size = 3] 3337 $ v = {4,5,6} [size = 3] 3338 3339 .keywords: matrix, aij, compressed row, sparse, parallel 3340 3341 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3342 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3343 @*/ 3344 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3345 { 3346 PetscErrorCode ierr; 3347 3348 PetscFunctionBegin; 3349 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3350 PetscFunctionReturn(0); 3351 } 3352 3353 #undef __FUNCT__ 3354 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3355 /*@C 3356 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3357 (the default parallel PETSc format). For good matrix assembly performance 3358 the user should preallocate the matrix storage by setting the parameters 3359 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3360 performance can be increased by more than a factor of 50. 3361 3362 Collective on MPI_Comm 3363 3364 Input Parameters: 3365 + B - the matrix 3366 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3367 (same value is used for all local rows) 3368 . d_nnz - array containing the number of nonzeros in the various rows of the 3369 DIAGONAL portion of the local submatrix (possibly different for each row) 3370 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3371 The size of this array is equal to the number of local rows, i.e 'm'. 3372 For matrices that will be factored, you must leave room for (and set) 3373 the diagonal entry even if it is zero. 3374 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3375 submatrix (same value is used for all local rows). 3376 - o_nnz - array containing the number of nonzeros in the various rows of the 3377 OFF-DIAGONAL portion of the local submatrix (possibly different for 3378 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3379 structure. The size of this array is equal to the number 3380 of local rows, i.e 'm'. 3381 3382 If the *_nnz parameter is given then the *_nz parameter is ignored 3383 3384 The AIJ format (also called the Yale sparse matrix format or 3385 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3386 storage. The stored row and column indices begin with zero. 3387 See Users-Manual: ch_mat for details. 3388 3389 The parallel matrix is partitioned such that the first m0 rows belong to 3390 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3391 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3392 3393 The DIAGONAL portion of the local submatrix of a processor can be defined 3394 as the submatrix which is obtained by extraction the part corresponding to 3395 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3396 first row that belongs to the processor, r2 is the last row belonging to 3397 the this processor, and c1-c2 is range of indices of the local part of a 3398 vector suitable for applying the matrix to. This is an mxn matrix. In the 3399 common case of a square matrix, the row and column ranges are the same and 3400 the DIAGONAL part is also square. The remaining portion of the local 3401 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3402 3403 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3404 3405 You can call MatGetInfo() to get information on how effective the preallocation was; 3406 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3407 You can also run with the option -info and look for messages with the string 3408 malloc in them to see if additional memory allocation was needed. 3409 3410 Example usage: 3411 3412 Consider the following 8x8 matrix with 34 non-zero values, that is 3413 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3414 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3415 as follows: 3416 3417 .vb 3418 1 2 0 | 0 3 0 | 0 4 3419 Proc0 0 5 6 | 7 0 0 | 8 0 3420 9 0 10 | 11 0 0 | 12 0 3421 ------------------------------------- 3422 13 0 14 | 15 16 17 | 0 0 3423 Proc1 0 18 0 | 19 20 21 | 0 0 3424 0 0 0 | 22 23 0 | 24 0 3425 ------------------------------------- 3426 Proc2 25 26 27 | 0 0 28 | 29 0 3427 30 0 0 | 31 32 33 | 0 34 3428 .ve 3429 3430 This can be represented as a collection of submatrices as: 3431 3432 .vb 3433 A B C 3434 D E F 3435 G H I 3436 .ve 3437 3438 Where the submatrices A,B,C are owned by proc0, D,E,F are 3439 owned by proc1, G,H,I are owned by proc2. 3440 3441 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3442 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3443 The 'M','N' parameters are 8,8, and have the same values on all procs. 3444 3445 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3446 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3447 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3448 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3449 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3450 matrix, ans [DF] as another SeqAIJ matrix. 3451 3452 When d_nz, o_nz parameters are specified, d_nz storage elements are 3453 allocated for every row of the local diagonal submatrix, and o_nz 3454 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3455 One way to choose d_nz and o_nz is to use the max nonzerors per local 3456 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3457 In this case, the values of d_nz,o_nz are: 3458 .vb 3459 proc0 : dnz = 2, o_nz = 2 3460 proc1 : dnz = 3, o_nz = 2 3461 proc2 : dnz = 1, o_nz = 4 3462 .ve 3463 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3464 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3465 for proc3. i.e we are using 12+15+10=37 storage locations to store 3466 34 values. 3467 3468 When d_nnz, o_nnz parameters are specified, the storage is specified 3469 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3470 In the above case the values for d_nnz,o_nnz are: 3471 .vb 3472 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3473 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3474 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3475 .ve 3476 Here the space allocated is sum of all the above values i.e 34, and 3477 hence pre-allocation is perfect. 3478 3479 Level: intermediate 3480 3481 .keywords: matrix, aij, compressed row, sparse, parallel 3482 3483 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3484 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3485 @*/ 3486 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3487 { 3488 PetscErrorCode ierr; 3489 3490 PetscFunctionBegin; 3491 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3492 PetscValidType(B,1); 3493 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3494 PetscFunctionReturn(0); 3495 } 3496 3497 #undef __FUNCT__ 3498 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3499 /*@ 3500 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3501 CSR format the local rows. 3502 3503 Collective on MPI_Comm 3504 3505 Input Parameters: 3506 + comm - MPI communicator 3507 . m - number of local rows (Cannot be PETSC_DECIDE) 3508 . n - This value should be the same as the local size used in creating the 3509 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3510 calculated if N is given) For square matrices n is almost always m. 3511 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3512 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3513 . i - row indices 3514 . j - column indices 3515 - a - matrix values 3516 3517 Output Parameter: 3518 . mat - the matrix 3519 3520 Level: intermediate 3521 3522 Notes: 3523 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3524 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3525 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3526 3527 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3528 3529 The format which is used for the sparse matrix input, is equivalent to a 3530 row-major ordering.. i.e for the following matrix, the input data expected is 3531 as shown 3532 3533 $ 1 0 0 3534 $ 2 0 3 P0 3535 $ ------- 3536 $ 4 5 6 P1 3537 $ 3538 $ Process0 [P0]: rows_owned=[0,1] 3539 $ i = {0,1,3} [size = nrow+1 = 2+1] 3540 $ j = {0,0,2} [size = 3] 3541 $ v = {1,2,3} [size = 3] 3542 $ 3543 $ Process1 [P1]: rows_owned=[2] 3544 $ i = {0,3} [size = nrow+1 = 1+1] 3545 $ j = {0,1,2} [size = 3] 3546 $ v = {4,5,6} [size = 3] 3547 3548 .keywords: matrix, aij, compressed row, sparse, parallel 3549 3550 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3551 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3552 @*/ 3553 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3554 { 3555 PetscErrorCode ierr; 3556 3557 PetscFunctionBegin; 3558 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3559 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3560 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3561 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3562 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3563 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3564 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3565 PetscFunctionReturn(0); 3566 } 3567 3568 #undef __FUNCT__ 3569 #define __FUNCT__ "MatCreateAIJ" 3570 /*@C 3571 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3572 (the default parallel PETSc format). For good matrix assembly performance 3573 the user should preallocate the matrix storage by setting the parameters 3574 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3575 performance can be increased by more than a factor of 50. 3576 3577 Collective on MPI_Comm 3578 3579 Input Parameters: 3580 + comm - MPI communicator 3581 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3582 This value should be the same as the local size used in creating the 3583 y vector for the matrix-vector product y = Ax. 3584 . n - This value should be the same as the local size used in creating the 3585 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3586 calculated if N is given) For square matrices n is almost always m. 3587 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3588 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3589 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3590 (same value is used for all local rows) 3591 . d_nnz - array containing the number of nonzeros in the various rows of the 3592 DIAGONAL portion of the local submatrix (possibly different for each row) 3593 or NULL, if d_nz is used to specify the nonzero structure. 3594 The size of this array is equal to the number of local rows, i.e 'm'. 3595 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3596 submatrix (same value is used for all local rows). 3597 - o_nnz - array containing the number of nonzeros in the various rows of the 3598 OFF-DIAGONAL portion of the local submatrix (possibly different for 3599 each row) or NULL, if o_nz is used to specify the nonzero 3600 structure. The size of this array is equal to the number 3601 of local rows, i.e 'm'. 3602 3603 Output Parameter: 3604 . A - the matrix 3605 3606 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3607 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3608 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3609 3610 Notes: 3611 If the *_nnz parameter is given then the *_nz parameter is ignored 3612 3613 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3614 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3615 storage requirements for this matrix. 3616 3617 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3618 processor than it must be used on all processors that share the object for 3619 that argument. 3620 3621 The user MUST specify either the local or global matrix dimensions 3622 (possibly both). 3623 3624 The parallel matrix is partitioned across processors such that the 3625 first m0 rows belong to process 0, the next m1 rows belong to 3626 process 1, the next m2 rows belong to process 2 etc.. where 3627 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3628 values corresponding to [m x N] submatrix. 3629 3630 The columns are logically partitioned with the n0 columns belonging 3631 to 0th partition, the next n1 columns belonging to the next 3632 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3633 3634 The DIAGONAL portion of the local submatrix on any given processor 3635 is the submatrix corresponding to the rows and columns m,n 3636 corresponding to the given processor. i.e diagonal matrix on 3637 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3638 etc. The remaining portion of the local submatrix [m x (N-n)] 3639 constitute the OFF-DIAGONAL portion. The example below better 3640 illustrates this concept. 3641 3642 For a square global matrix we define each processor's diagonal portion 3643 to be its local rows and the corresponding columns (a square submatrix); 3644 each processor's off-diagonal portion encompasses the remainder of the 3645 local matrix (a rectangular submatrix). 3646 3647 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3648 3649 When calling this routine with a single process communicator, a matrix of 3650 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3651 type of communicator, use the construction mechanism: 3652 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3653 3654 By default, this format uses inodes (identical nodes) when possible. 3655 We search for consecutive rows with the same nonzero structure, thereby 3656 reusing matrix information to achieve increased efficiency. 3657 3658 Options Database Keys: 3659 + -mat_no_inode - Do not use inodes 3660 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3661 - -mat_aij_oneindex - Internally use indexing starting at 1 3662 rather than 0. Note that when calling MatSetValues(), 3663 the user still MUST index entries starting at 0! 3664 3665 3666 Example usage: 3667 3668 Consider the following 8x8 matrix with 34 non-zero values, that is 3669 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3670 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3671 as follows: 3672 3673 .vb 3674 1 2 0 | 0 3 0 | 0 4 3675 Proc0 0 5 6 | 7 0 0 | 8 0 3676 9 0 10 | 11 0 0 | 12 0 3677 ------------------------------------- 3678 13 0 14 | 15 16 17 | 0 0 3679 Proc1 0 18 0 | 19 20 21 | 0 0 3680 0 0 0 | 22 23 0 | 24 0 3681 ------------------------------------- 3682 Proc2 25 26 27 | 0 0 28 | 29 0 3683 30 0 0 | 31 32 33 | 0 34 3684 .ve 3685 3686 This can be represented as a collection of submatrices as: 3687 3688 .vb 3689 A B C 3690 D E F 3691 G H I 3692 .ve 3693 3694 Where the submatrices A,B,C are owned by proc0, D,E,F are 3695 owned by proc1, G,H,I are owned by proc2. 3696 3697 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3698 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3699 The 'M','N' parameters are 8,8, and have the same values on all procs. 3700 3701 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3702 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3703 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3704 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3705 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3706 matrix, ans [DF] as another SeqAIJ matrix. 3707 3708 When d_nz, o_nz parameters are specified, d_nz storage elements are 3709 allocated for every row of the local diagonal submatrix, and o_nz 3710 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3711 One way to choose d_nz and o_nz is to use the max nonzerors per local 3712 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3713 In this case, the values of d_nz,o_nz are: 3714 .vb 3715 proc0 : dnz = 2, o_nz = 2 3716 proc1 : dnz = 3, o_nz = 2 3717 proc2 : dnz = 1, o_nz = 4 3718 .ve 3719 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3720 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3721 for proc3. i.e we are using 12+15+10=37 storage locations to store 3722 34 values. 3723 3724 When d_nnz, o_nnz parameters are specified, the storage is specified 3725 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3726 In the above case the values for d_nnz,o_nnz are: 3727 .vb 3728 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3729 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3730 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3731 .ve 3732 Here the space allocated is sum of all the above values i.e 34, and 3733 hence pre-allocation is perfect. 3734 3735 Level: intermediate 3736 3737 .keywords: matrix, aij, compressed row, sparse, parallel 3738 3739 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3740 MPIAIJ, MatCreateMPIAIJWithArrays() 3741 @*/ 3742 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) 3743 { 3744 PetscErrorCode ierr; 3745 PetscMPIInt size; 3746 3747 PetscFunctionBegin; 3748 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3749 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3750 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3751 if (size > 1) { 3752 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3753 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3754 } else { 3755 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3756 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3757 } 3758 PetscFunctionReturn(0); 3759 } 3760 3761 #undef __FUNCT__ 3762 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3763 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3764 { 3765 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3766 3767 PetscFunctionBegin; 3768 if (Ad) *Ad = a->A; 3769 if (Ao) *Ao = a->B; 3770 if (colmap) *colmap = a->garray; 3771 PetscFunctionReturn(0); 3772 } 3773 3774 #undef __FUNCT__ 3775 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3776 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3777 { 3778 PetscErrorCode ierr; 3779 PetscInt i; 3780 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3781 3782 PetscFunctionBegin; 3783 if (coloring->ctype == IS_COLORING_GLOBAL) { 3784 ISColoringValue *allcolors,*colors; 3785 ISColoring ocoloring; 3786 3787 /* set coloring for diagonal portion */ 3788 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3789 3790 /* set coloring for off-diagonal portion */ 3791 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3792 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3793 for (i=0; i<a->B->cmap->n; i++) { 3794 colors[i] = allcolors[a->garray[i]]; 3795 } 3796 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3797 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3798 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3799 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3800 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3801 ISColoringValue *colors; 3802 PetscInt *larray; 3803 ISColoring ocoloring; 3804 3805 /* set coloring for diagonal portion */ 3806 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3807 for (i=0; i<a->A->cmap->n; i++) { 3808 larray[i] = i + A->cmap->rstart; 3809 } 3810 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3811 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3812 for (i=0; i<a->A->cmap->n; i++) { 3813 colors[i] = coloring->colors[larray[i]]; 3814 } 3815 ierr = PetscFree(larray);CHKERRQ(ierr); 3816 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3817 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3818 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3819 3820 /* set coloring for off-diagonal portion */ 3821 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3822 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3823 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3824 for (i=0; i<a->B->cmap->n; i++) { 3825 colors[i] = coloring->colors[larray[i]]; 3826 } 3827 ierr = PetscFree(larray);CHKERRQ(ierr); 3828 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3829 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3830 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3831 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3832 PetscFunctionReturn(0); 3833 } 3834 3835 #undef __FUNCT__ 3836 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3837 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3838 { 3839 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3840 PetscErrorCode ierr; 3841 3842 PetscFunctionBegin; 3843 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3844 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3845 PetscFunctionReturn(0); 3846 } 3847 3848 #undef __FUNCT__ 3849 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3850 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3851 { 3852 PetscErrorCode ierr; 3853 PetscInt m,N,i,rstart,nnz,Ii; 3854 PetscInt *indx; 3855 PetscScalar *values; 3856 3857 PetscFunctionBegin; 3858 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3859 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3860 PetscInt *dnz,*onz,sum,bs,cbs; 3861 3862 if (n == PETSC_DECIDE) { 3863 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3864 } 3865 /* Check sum(n) = N */ 3866 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3867 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3868 3869 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3870 rstart -= m; 3871 3872 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3873 for (i=0; i<m; i++) { 3874 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3875 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3876 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3877 } 3878 3879 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3880 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3881 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3882 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3883 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3884 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3885 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3886 } 3887 3888 /* numeric phase */ 3889 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3890 for (i=0; i<m; i++) { 3891 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3892 Ii = i + rstart; 3893 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3894 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3895 } 3896 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3897 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3898 PetscFunctionReturn(0); 3899 } 3900 3901 #undef __FUNCT__ 3902 #define __FUNCT__ "MatFileSplit" 3903 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3904 { 3905 PetscErrorCode ierr; 3906 PetscMPIInt rank; 3907 PetscInt m,N,i,rstart,nnz; 3908 size_t len; 3909 const PetscInt *indx; 3910 PetscViewer out; 3911 char *name; 3912 Mat B; 3913 const PetscScalar *values; 3914 3915 PetscFunctionBegin; 3916 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3917 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3918 /* Should this be the type of the diagonal block of A? */ 3919 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3920 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3921 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3922 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3923 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3924 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3925 for (i=0; i<m; i++) { 3926 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3927 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3928 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3929 } 3930 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3931 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3932 3933 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3934 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3935 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3936 sprintf(name,"%s.%d",outfile,rank); 3937 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3938 ierr = PetscFree(name);CHKERRQ(ierr); 3939 ierr = MatView(B,out);CHKERRQ(ierr); 3940 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3941 ierr = MatDestroy(&B);CHKERRQ(ierr); 3942 PetscFunctionReturn(0); 3943 } 3944 3945 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3946 #undef __FUNCT__ 3947 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3948 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3949 { 3950 PetscErrorCode ierr; 3951 Mat_Merge_SeqsToMPI *merge; 3952 PetscContainer container; 3953 3954 PetscFunctionBegin; 3955 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3956 if (container) { 3957 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3958 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3959 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3960 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3961 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3962 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3963 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3964 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3965 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3966 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3967 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3968 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3969 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3970 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3971 ierr = PetscFree(merge);CHKERRQ(ierr); 3972 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3973 } 3974 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3975 PetscFunctionReturn(0); 3976 } 3977 3978 #include <../src/mat/utils/freespace.h> 3979 #include <petscbt.h> 3980 3981 #undef __FUNCT__ 3982 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 3983 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3984 { 3985 PetscErrorCode ierr; 3986 MPI_Comm comm; 3987 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 3988 PetscMPIInt size,rank,taga,*len_s; 3989 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 3990 PetscInt proc,m; 3991 PetscInt **buf_ri,**buf_rj; 3992 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3993 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3994 MPI_Request *s_waits,*r_waits; 3995 MPI_Status *status; 3996 MatScalar *aa=a->a; 3997 MatScalar **abuf_r,*ba_i; 3998 Mat_Merge_SeqsToMPI *merge; 3999 PetscContainer container; 4000 4001 PetscFunctionBegin; 4002 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4003 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4004 4005 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4006 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4007 4008 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4009 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4010 4011 bi = merge->bi; 4012 bj = merge->bj; 4013 buf_ri = merge->buf_ri; 4014 buf_rj = merge->buf_rj; 4015 4016 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4017 owners = merge->rowmap->range; 4018 len_s = merge->len_s; 4019 4020 /* send and recv matrix values */ 4021 /*-----------------------------*/ 4022 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4023 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4024 4025 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4026 for (proc=0,k=0; proc<size; proc++) { 4027 if (!len_s[proc]) continue; 4028 i = owners[proc]; 4029 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4030 k++; 4031 } 4032 4033 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4034 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4035 ierr = PetscFree(status);CHKERRQ(ierr); 4036 4037 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4038 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4039 4040 /* insert mat values of mpimat */ 4041 /*----------------------------*/ 4042 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4043 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4044 4045 for (k=0; k<merge->nrecv; k++) { 4046 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4047 nrows = *(buf_ri_k[k]); 4048 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4049 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4050 } 4051 4052 /* set values of ba */ 4053 m = merge->rowmap->n; 4054 for (i=0; i<m; i++) { 4055 arow = owners[rank] + i; 4056 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4057 bnzi = bi[i+1] - bi[i]; 4058 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4059 4060 /* add local non-zero vals of this proc's seqmat into ba */ 4061 anzi = ai[arow+1] - ai[arow]; 4062 aj = a->j + ai[arow]; 4063 aa = a->a + ai[arow]; 4064 nextaj = 0; 4065 for (j=0; nextaj<anzi; j++) { 4066 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4067 ba_i[j] += aa[nextaj++]; 4068 } 4069 } 4070 4071 /* add received vals into ba */ 4072 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4073 /* i-th row */ 4074 if (i == *nextrow[k]) { 4075 anzi = *(nextai[k]+1) - *nextai[k]; 4076 aj = buf_rj[k] + *(nextai[k]); 4077 aa = abuf_r[k] + *(nextai[k]); 4078 nextaj = 0; 4079 for (j=0; nextaj<anzi; j++) { 4080 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4081 ba_i[j] += aa[nextaj++]; 4082 } 4083 } 4084 nextrow[k]++; nextai[k]++; 4085 } 4086 } 4087 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4088 } 4089 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4090 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4091 4092 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4093 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4094 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4095 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4096 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4097 PetscFunctionReturn(0); 4098 } 4099 4100 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4101 4102 #undef __FUNCT__ 4103 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4104 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4105 { 4106 PetscErrorCode ierr; 4107 Mat B_mpi; 4108 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4109 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4110 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4111 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4112 PetscInt len,proc,*dnz,*onz,bs,cbs; 4113 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4114 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4115 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4116 MPI_Status *status; 4117 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4118 PetscBT lnkbt; 4119 Mat_Merge_SeqsToMPI *merge; 4120 PetscContainer container; 4121 4122 PetscFunctionBegin; 4123 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4124 4125 /* make sure it is a PETSc comm */ 4126 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4127 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4128 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4129 4130 ierr = PetscNew(&merge);CHKERRQ(ierr); 4131 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4132 4133 /* determine row ownership */ 4134 /*---------------------------------------------------------*/ 4135 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4136 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4137 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4138 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4139 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4140 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4141 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4142 4143 m = merge->rowmap->n; 4144 owners = merge->rowmap->range; 4145 4146 /* determine the number of messages to send, their lengths */ 4147 /*---------------------------------------------------------*/ 4148 len_s = merge->len_s; 4149 4150 len = 0; /* length of buf_si[] */ 4151 merge->nsend = 0; 4152 for (proc=0; proc<size; proc++) { 4153 len_si[proc] = 0; 4154 if (proc == rank) { 4155 len_s[proc] = 0; 4156 } else { 4157 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4158 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4159 } 4160 if (len_s[proc]) { 4161 merge->nsend++; 4162 nrows = 0; 4163 for (i=owners[proc]; i<owners[proc+1]; i++) { 4164 if (ai[i+1] > ai[i]) nrows++; 4165 } 4166 len_si[proc] = 2*(nrows+1); 4167 len += len_si[proc]; 4168 } 4169 } 4170 4171 /* determine the number and length of messages to receive for ij-structure */ 4172 /*-------------------------------------------------------------------------*/ 4173 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4174 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4175 4176 /* post the Irecv of j-structure */ 4177 /*-------------------------------*/ 4178 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4179 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4180 4181 /* post the Isend of j-structure */ 4182 /*--------------------------------*/ 4183 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4184 4185 for (proc=0, k=0; proc<size; proc++) { 4186 if (!len_s[proc]) continue; 4187 i = owners[proc]; 4188 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4189 k++; 4190 } 4191 4192 /* receives and sends of j-structure are complete */ 4193 /*------------------------------------------------*/ 4194 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4195 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4196 4197 /* send and recv i-structure */ 4198 /*---------------------------*/ 4199 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4200 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4201 4202 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4203 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4204 for (proc=0,k=0; proc<size; proc++) { 4205 if (!len_s[proc]) continue; 4206 /* form outgoing message for i-structure: 4207 buf_si[0]: nrows to be sent 4208 [1:nrows]: row index (global) 4209 [nrows+1:2*nrows+1]: i-structure index 4210 */ 4211 /*-------------------------------------------*/ 4212 nrows = len_si[proc]/2 - 1; 4213 buf_si_i = buf_si + nrows+1; 4214 buf_si[0] = nrows; 4215 buf_si_i[0] = 0; 4216 nrows = 0; 4217 for (i=owners[proc]; i<owners[proc+1]; i++) { 4218 anzi = ai[i+1] - ai[i]; 4219 if (anzi) { 4220 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4221 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4222 nrows++; 4223 } 4224 } 4225 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4226 k++; 4227 buf_si += len_si[proc]; 4228 } 4229 4230 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4231 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4232 4233 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4234 for (i=0; i<merge->nrecv; i++) { 4235 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); 4236 } 4237 4238 ierr = PetscFree(len_si);CHKERRQ(ierr); 4239 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4240 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4241 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4242 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4243 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4244 ierr = PetscFree(status);CHKERRQ(ierr); 4245 4246 /* compute a local seq matrix in each processor */ 4247 /*----------------------------------------------*/ 4248 /* allocate bi array and free space for accumulating nonzero column info */ 4249 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4250 bi[0] = 0; 4251 4252 /* create and initialize a linked list */ 4253 nlnk = N+1; 4254 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4255 4256 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4257 len = ai[owners[rank+1]] - ai[owners[rank]]; 4258 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4259 4260 current_space = free_space; 4261 4262 /* determine symbolic info for each local row */ 4263 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4264 4265 for (k=0; k<merge->nrecv; k++) { 4266 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4267 nrows = *buf_ri_k[k]; 4268 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4269 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4270 } 4271 4272 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4273 len = 0; 4274 for (i=0; i<m; i++) { 4275 bnzi = 0; 4276 /* add local non-zero cols of this proc's seqmat into lnk */ 4277 arow = owners[rank] + i; 4278 anzi = ai[arow+1] - ai[arow]; 4279 aj = a->j + ai[arow]; 4280 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4281 bnzi += nlnk; 4282 /* add received col data into lnk */ 4283 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4284 if (i == *nextrow[k]) { /* i-th row */ 4285 anzi = *(nextai[k]+1) - *nextai[k]; 4286 aj = buf_rj[k] + *nextai[k]; 4287 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4288 bnzi += nlnk; 4289 nextrow[k]++; nextai[k]++; 4290 } 4291 } 4292 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4293 4294 /* if free space is not available, make more free space */ 4295 if (current_space->local_remaining<bnzi) { 4296 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4297 nspacedouble++; 4298 } 4299 /* copy data into free space, then initialize lnk */ 4300 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4301 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4302 4303 current_space->array += bnzi; 4304 current_space->local_used += bnzi; 4305 current_space->local_remaining -= bnzi; 4306 4307 bi[i+1] = bi[i] + bnzi; 4308 } 4309 4310 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4311 4312 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4313 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4314 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4315 4316 /* create symbolic parallel matrix B_mpi */ 4317 /*---------------------------------------*/ 4318 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4319 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4320 if (n==PETSC_DECIDE) { 4321 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4322 } else { 4323 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4324 } 4325 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4326 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4327 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4328 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4329 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4330 4331 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4332 B_mpi->assembled = PETSC_FALSE; 4333 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4334 merge->bi = bi; 4335 merge->bj = bj; 4336 merge->buf_ri = buf_ri; 4337 merge->buf_rj = buf_rj; 4338 merge->coi = NULL; 4339 merge->coj = NULL; 4340 merge->owners_co = NULL; 4341 4342 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4343 4344 /* attach the supporting struct to B_mpi for reuse */ 4345 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4346 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4347 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4348 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4349 *mpimat = B_mpi; 4350 4351 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4352 PetscFunctionReturn(0); 4353 } 4354 4355 #undef __FUNCT__ 4356 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4357 /*@C 4358 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4359 matrices from each processor 4360 4361 Collective on MPI_Comm 4362 4363 Input Parameters: 4364 + comm - the communicators the parallel matrix will live on 4365 . seqmat - the input sequential matrices 4366 . m - number of local rows (or PETSC_DECIDE) 4367 . n - number of local columns (or PETSC_DECIDE) 4368 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4369 4370 Output Parameter: 4371 . mpimat - the parallel matrix generated 4372 4373 Level: advanced 4374 4375 Notes: 4376 The dimensions of the sequential matrix in each processor MUST be the same. 4377 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4378 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4379 @*/ 4380 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4381 { 4382 PetscErrorCode ierr; 4383 PetscMPIInt size; 4384 4385 PetscFunctionBegin; 4386 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4387 if (size == 1) { 4388 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4389 if (scall == MAT_INITIAL_MATRIX) { 4390 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4391 } else { 4392 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4393 } 4394 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4395 PetscFunctionReturn(0); 4396 } 4397 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4398 if (scall == MAT_INITIAL_MATRIX) { 4399 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4400 } 4401 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4402 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4403 PetscFunctionReturn(0); 4404 } 4405 4406 #undef __FUNCT__ 4407 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4408 /*@ 4409 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4410 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4411 with MatGetSize() 4412 4413 Not Collective 4414 4415 Input Parameters: 4416 + A - the matrix 4417 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4418 4419 Output Parameter: 4420 . A_loc - the local sequential matrix generated 4421 4422 Level: developer 4423 4424 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4425 4426 @*/ 4427 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4428 { 4429 PetscErrorCode ierr; 4430 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4431 Mat_SeqAIJ *mat,*a,*b; 4432 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4433 MatScalar *aa,*ba,*cam; 4434 PetscScalar *ca; 4435 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4436 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4437 PetscBool match; 4438 MPI_Comm comm; 4439 PetscMPIInt size; 4440 4441 PetscFunctionBegin; 4442 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4443 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4444 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4445 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4446 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4447 4448 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4449 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4450 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4451 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4452 aa = a->a; ba = b->a; 4453 if (scall == MAT_INITIAL_MATRIX) { 4454 if (size == 1) { 4455 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4456 PetscFunctionReturn(0); 4457 } 4458 4459 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4460 ci[0] = 0; 4461 for (i=0; i<am; i++) { 4462 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4463 } 4464 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4465 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4466 k = 0; 4467 for (i=0; i<am; i++) { 4468 ncols_o = bi[i+1] - bi[i]; 4469 ncols_d = ai[i+1] - ai[i]; 4470 /* off-diagonal portion of A */ 4471 for (jo=0; jo<ncols_o; jo++) { 4472 col = cmap[*bj]; 4473 if (col >= cstart) break; 4474 cj[k] = col; bj++; 4475 ca[k++] = *ba++; 4476 } 4477 /* diagonal portion of A */ 4478 for (j=0; j<ncols_d; j++) { 4479 cj[k] = cstart + *aj++; 4480 ca[k++] = *aa++; 4481 } 4482 /* off-diagonal portion of A */ 4483 for (j=jo; j<ncols_o; j++) { 4484 cj[k] = cmap[*bj++]; 4485 ca[k++] = *ba++; 4486 } 4487 } 4488 /* put together the new matrix */ 4489 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4490 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4491 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4492 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4493 mat->free_a = PETSC_TRUE; 4494 mat->free_ij = PETSC_TRUE; 4495 mat->nonew = 0; 4496 } else if (scall == MAT_REUSE_MATRIX) { 4497 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4498 ci = mat->i; cj = mat->j; cam = mat->a; 4499 for (i=0; i<am; i++) { 4500 /* off-diagonal portion of A */ 4501 ncols_o = bi[i+1] - bi[i]; 4502 for (jo=0; jo<ncols_o; jo++) { 4503 col = cmap[*bj]; 4504 if (col >= cstart) break; 4505 *cam++ = *ba++; bj++; 4506 } 4507 /* diagonal portion of A */ 4508 ncols_d = ai[i+1] - ai[i]; 4509 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4510 /* off-diagonal portion of A */ 4511 for (j=jo; j<ncols_o; j++) { 4512 *cam++ = *ba++; bj++; 4513 } 4514 } 4515 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4516 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4517 PetscFunctionReturn(0); 4518 } 4519 4520 #undef __FUNCT__ 4521 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4522 /*@C 4523 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4524 4525 Not Collective 4526 4527 Input Parameters: 4528 + A - the matrix 4529 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4530 - row, col - index sets of rows and columns to extract (or NULL) 4531 4532 Output Parameter: 4533 . A_loc - the local sequential matrix generated 4534 4535 Level: developer 4536 4537 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4538 4539 @*/ 4540 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4541 { 4542 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4543 PetscErrorCode ierr; 4544 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4545 IS isrowa,iscola; 4546 Mat *aloc; 4547 PetscBool match; 4548 4549 PetscFunctionBegin; 4550 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4551 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4552 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4553 if (!row) { 4554 start = A->rmap->rstart; end = A->rmap->rend; 4555 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4556 } else { 4557 isrowa = *row; 4558 } 4559 if (!col) { 4560 start = A->cmap->rstart; 4561 cmap = a->garray; 4562 nzA = a->A->cmap->n; 4563 nzB = a->B->cmap->n; 4564 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4565 ncols = 0; 4566 for (i=0; i<nzB; i++) { 4567 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4568 else break; 4569 } 4570 imark = i; 4571 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4572 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4573 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4574 } else { 4575 iscola = *col; 4576 } 4577 if (scall != MAT_INITIAL_MATRIX) { 4578 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4579 aloc[0] = *A_loc; 4580 } 4581 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4582 *A_loc = aloc[0]; 4583 ierr = PetscFree(aloc);CHKERRQ(ierr); 4584 if (!row) { 4585 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4586 } 4587 if (!col) { 4588 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4589 } 4590 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4591 PetscFunctionReturn(0); 4592 } 4593 4594 #undef __FUNCT__ 4595 #define __FUNCT__ "MatGetBrowsOfAcols" 4596 /*@C 4597 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4598 4599 Collective on Mat 4600 4601 Input Parameters: 4602 + A,B - the matrices in mpiaij format 4603 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4604 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4605 4606 Output Parameter: 4607 + rowb, colb - index sets of rows and columns of B to extract 4608 - B_seq - the sequential matrix generated 4609 4610 Level: developer 4611 4612 @*/ 4613 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4614 { 4615 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4616 PetscErrorCode ierr; 4617 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4618 IS isrowb,iscolb; 4619 Mat *bseq=NULL; 4620 4621 PetscFunctionBegin; 4622 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4623 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); 4624 } 4625 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4626 4627 if (scall == MAT_INITIAL_MATRIX) { 4628 start = A->cmap->rstart; 4629 cmap = a->garray; 4630 nzA = a->A->cmap->n; 4631 nzB = a->B->cmap->n; 4632 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4633 ncols = 0; 4634 for (i=0; i<nzB; i++) { /* row < local row index */ 4635 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4636 else break; 4637 } 4638 imark = i; 4639 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4640 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4641 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4642 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4643 } else { 4644 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4645 isrowb = *rowb; iscolb = *colb; 4646 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4647 bseq[0] = *B_seq; 4648 } 4649 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4650 *B_seq = bseq[0]; 4651 ierr = PetscFree(bseq);CHKERRQ(ierr); 4652 if (!rowb) { 4653 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4654 } else { 4655 *rowb = isrowb; 4656 } 4657 if (!colb) { 4658 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4659 } else { 4660 *colb = iscolb; 4661 } 4662 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4663 PetscFunctionReturn(0); 4664 } 4665 4666 #undef __FUNCT__ 4667 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4668 /* 4669 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4670 of the OFF-DIAGONAL portion of local A 4671 4672 Collective on Mat 4673 4674 Input Parameters: 4675 + A,B - the matrices in mpiaij format 4676 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4677 4678 Output Parameter: 4679 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4680 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4681 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4682 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4683 4684 Level: developer 4685 4686 */ 4687 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4688 { 4689 VecScatter_MPI_General *gen_to,*gen_from; 4690 PetscErrorCode ierr; 4691 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4692 Mat_SeqAIJ *b_oth; 4693 VecScatter ctx =a->Mvctx; 4694 MPI_Comm comm; 4695 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4696 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4697 PetscScalar *rvalues,*svalues; 4698 MatScalar *b_otha,*bufa,*bufA; 4699 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4700 MPI_Request *rwaits = NULL,*swaits = NULL; 4701 MPI_Status *sstatus,rstatus; 4702 PetscMPIInt jj,size; 4703 PetscInt *cols,sbs,rbs; 4704 PetscScalar *vals; 4705 4706 PetscFunctionBegin; 4707 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4708 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4709 4710 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4711 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); 4712 } 4713 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4714 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4715 4716 gen_to = (VecScatter_MPI_General*)ctx->todata; 4717 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4718 rvalues = gen_from->values; /* holds the length of receiving row */ 4719 svalues = gen_to->values; /* holds the length of sending row */ 4720 nrecvs = gen_from->n; 4721 nsends = gen_to->n; 4722 4723 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4724 srow = gen_to->indices; /* local row index to be sent */ 4725 sstarts = gen_to->starts; 4726 sprocs = gen_to->procs; 4727 sstatus = gen_to->sstatus; 4728 sbs = gen_to->bs; 4729 rstarts = gen_from->starts; 4730 rprocs = gen_from->procs; 4731 rbs = gen_from->bs; 4732 4733 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4734 if (scall == MAT_INITIAL_MATRIX) { 4735 /* i-array */ 4736 /*---------*/ 4737 /* post receives */ 4738 for (i=0; i<nrecvs; i++) { 4739 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4740 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4741 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4742 } 4743 4744 /* pack the outgoing message */ 4745 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4746 4747 sstartsj[0] = 0; 4748 rstartsj[0] = 0; 4749 len = 0; /* total length of j or a array to be sent */ 4750 k = 0; 4751 for (i=0; i<nsends; i++) { 4752 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4753 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4754 for (j=0; j<nrows; j++) { 4755 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4756 for (l=0; l<sbs; l++) { 4757 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4758 4759 rowlen[j*sbs+l] = ncols; 4760 4761 len += ncols; 4762 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4763 } 4764 k++; 4765 } 4766 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4767 4768 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4769 } 4770 /* recvs and sends of i-array are completed */ 4771 i = nrecvs; 4772 while (i--) { 4773 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4774 } 4775 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4776 4777 /* allocate buffers for sending j and a arrays */ 4778 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4779 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4780 4781 /* create i-array of B_oth */ 4782 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4783 4784 b_othi[0] = 0; 4785 len = 0; /* total length of j or a array to be received */ 4786 k = 0; 4787 for (i=0; i<nrecvs; i++) { 4788 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4789 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4790 for (j=0; j<nrows; j++) { 4791 b_othi[k+1] = b_othi[k] + rowlen[j]; 4792 ierr = PetscIntSumError(rowlen[j],len,&len); 4793 k++; 4794 } 4795 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4796 } 4797 4798 /* allocate space for j and a arrrays of B_oth */ 4799 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4800 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4801 4802 /* j-array */ 4803 /*---------*/ 4804 /* post receives of j-array */ 4805 for (i=0; i<nrecvs; i++) { 4806 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4807 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4808 } 4809 4810 /* pack the outgoing message j-array */ 4811 k = 0; 4812 for (i=0; i<nsends; i++) { 4813 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4814 bufJ = bufj+sstartsj[i]; 4815 for (j=0; j<nrows; j++) { 4816 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4817 for (ll=0; ll<sbs; ll++) { 4818 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4819 for (l=0; l<ncols; l++) { 4820 *bufJ++ = cols[l]; 4821 } 4822 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4823 } 4824 } 4825 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4826 } 4827 4828 /* recvs and sends of j-array are completed */ 4829 i = nrecvs; 4830 while (i--) { 4831 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4832 } 4833 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4834 } else if (scall == MAT_REUSE_MATRIX) { 4835 sstartsj = *startsj_s; 4836 rstartsj = *startsj_r; 4837 bufa = *bufa_ptr; 4838 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4839 b_otha = b_oth->a; 4840 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4841 4842 /* a-array */ 4843 /*---------*/ 4844 /* post receives of a-array */ 4845 for (i=0; i<nrecvs; i++) { 4846 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4847 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4848 } 4849 4850 /* pack the outgoing message a-array */ 4851 k = 0; 4852 for (i=0; i<nsends; i++) { 4853 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4854 bufA = bufa+sstartsj[i]; 4855 for (j=0; j<nrows; j++) { 4856 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4857 for (ll=0; ll<sbs; ll++) { 4858 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4859 for (l=0; l<ncols; l++) { 4860 *bufA++ = vals[l]; 4861 } 4862 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4863 } 4864 } 4865 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4866 } 4867 /* recvs and sends of a-array are completed */ 4868 i = nrecvs; 4869 while (i--) { 4870 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4871 } 4872 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4873 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4874 4875 if (scall == MAT_INITIAL_MATRIX) { 4876 /* put together the new matrix */ 4877 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4878 4879 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4880 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4881 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4882 b_oth->free_a = PETSC_TRUE; 4883 b_oth->free_ij = PETSC_TRUE; 4884 b_oth->nonew = 0; 4885 4886 ierr = PetscFree(bufj);CHKERRQ(ierr); 4887 if (!startsj_s || !bufa_ptr) { 4888 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4889 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4890 } else { 4891 *startsj_s = sstartsj; 4892 *startsj_r = rstartsj; 4893 *bufa_ptr = bufa; 4894 } 4895 } 4896 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4897 PetscFunctionReturn(0); 4898 } 4899 4900 #undef __FUNCT__ 4901 #define __FUNCT__ "MatGetCommunicationStructs" 4902 /*@C 4903 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4904 4905 Not Collective 4906 4907 Input Parameters: 4908 . A - The matrix in mpiaij format 4909 4910 Output Parameter: 4911 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4912 . colmap - A map from global column index to local index into lvec 4913 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4914 4915 Level: developer 4916 4917 @*/ 4918 #if defined(PETSC_USE_CTABLE) 4919 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4920 #else 4921 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4922 #endif 4923 { 4924 Mat_MPIAIJ *a; 4925 4926 PetscFunctionBegin; 4927 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4928 PetscValidPointer(lvec, 2); 4929 PetscValidPointer(colmap, 3); 4930 PetscValidPointer(multScatter, 4); 4931 a = (Mat_MPIAIJ*) A->data; 4932 if (lvec) *lvec = a->lvec; 4933 if (colmap) *colmap = a->colmap; 4934 if (multScatter) *multScatter = a->Mvctx; 4935 PetscFunctionReturn(0); 4936 } 4937 4938 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4939 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4940 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4941 #if defined(PETSC_HAVE_ELEMENTAL) 4942 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4943 #endif 4944 4945 #undef __FUNCT__ 4946 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4947 /* 4948 Computes (B'*A')' since computing B*A directly is untenable 4949 4950 n p p 4951 ( ) ( ) ( ) 4952 m ( A ) * n ( B ) = m ( C ) 4953 ( ) ( ) ( ) 4954 4955 */ 4956 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4957 { 4958 PetscErrorCode ierr; 4959 Mat At,Bt,Ct; 4960 4961 PetscFunctionBegin; 4962 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4963 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4964 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4965 ierr = MatDestroy(&At);CHKERRQ(ierr); 4966 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4967 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4968 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4969 PetscFunctionReturn(0); 4970 } 4971 4972 #undef __FUNCT__ 4973 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4974 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4975 { 4976 PetscErrorCode ierr; 4977 PetscInt m=A->rmap->n,n=B->cmap->n; 4978 Mat Cmat; 4979 4980 PetscFunctionBegin; 4981 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); 4982 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4983 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4984 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4985 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4986 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4987 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4988 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4989 4990 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 4991 4992 *C = Cmat; 4993 PetscFunctionReturn(0); 4994 } 4995 4996 /* ----------------------------------------------------------------*/ 4997 #undef __FUNCT__ 4998 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4999 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5000 { 5001 PetscErrorCode ierr; 5002 5003 PetscFunctionBegin; 5004 if (scall == MAT_INITIAL_MATRIX) { 5005 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5006 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5007 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5008 } 5009 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5010 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5011 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5012 PetscFunctionReturn(0); 5013 } 5014 5015 /*MC 5016 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5017 5018 Options Database Keys: 5019 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5020 5021 Level: beginner 5022 5023 .seealso: MatCreateAIJ() 5024 M*/ 5025 5026 #undef __FUNCT__ 5027 #define __FUNCT__ "MatCreate_MPIAIJ" 5028 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5029 { 5030 Mat_MPIAIJ *b; 5031 PetscErrorCode ierr; 5032 PetscMPIInt size; 5033 5034 PetscFunctionBegin; 5035 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5036 5037 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5038 B->data = (void*)b; 5039 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5040 B->assembled = PETSC_FALSE; 5041 B->insertmode = NOT_SET_VALUES; 5042 b->size = size; 5043 5044 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5045 5046 /* build cache for off array entries formed */ 5047 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5048 5049 b->donotstash = PETSC_FALSE; 5050 b->colmap = 0; 5051 b->garray = 0; 5052 b->roworiented = PETSC_TRUE; 5053 5054 /* stuff used for matrix vector multiply */ 5055 b->lvec = NULL; 5056 b->Mvctx = NULL; 5057 5058 /* stuff for MatGetRow() */ 5059 b->rowindices = 0; 5060 b->rowvalues = 0; 5061 b->getrowactive = PETSC_FALSE; 5062 5063 /* flexible pointer used in CUSP/CUSPARSE classes */ 5064 b->spptr = NULL; 5065 5066 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5067 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5072 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5074 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5076 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5077 #if defined(PETSC_HAVE_ELEMENTAL) 5078 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5079 #endif 5080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5083 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5084 PetscFunctionReturn(0); 5085 } 5086 5087 #undef __FUNCT__ 5088 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5089 /*@C 5090 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5091 and "off-diagonal" part of the matrix in CSR format. 5092 5093 Collective on MPI_Comm 5094 5095 Input Parameters: 5096 + comm - MPI communicator 5097 . m - number of local rows (Cannot be PETSC_DECIDE) 5098 . n - This value should be the same as the local size used in creating the 5099 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5100 calculated if N is given) For square matrices n is almost always m. 5101 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5102 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5103 . i - row indices for "diagonal" portion of matrix 5104 . j - column indices 5105 . a - matrix values 5106 . oi - row indices for "off-diagonal" portion of matrix 5107 . oj - column indices 5108 - oa - matrix values 5109 5110 Output Parameter: 5111 . mat - the matrix 5112 5113 Level: advanced 5114 5115 Notes: 5116 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5117 must free the arrays once the matrix has been destroyed and not before. 5118 5119 The i and j indices are 0 based 5120 5121 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5122 5123 This sets local rows and cannot be used to set off-processor values. 5124 5125 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5126 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5127 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5128 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5129 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5130 communication if it is known that only local entries will be set. 5131 5132 .keywords: matrix, aij, compressed row, sparse, parallel 5133 5134 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5135 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5136 @*/ 5137 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) 5138 { 5139 PetscErrorCode ierr; 5140 Mat_MPIAIJ *maij; 5141 5142 PetscFunctionBegin; 5143 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5144 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5145 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5146 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5147 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5148 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5149 maij = (Mat_MPIAIJ*) (*mat)->data; 5150 5151 (*mat)->preallocated = PETSC_TRUE; 5152 5153 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5154 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5155 5156 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5157 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5158 5159 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5160 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5161 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5162 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5163 5164 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5165 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5166 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5167 PetscFunctionReturn(0); 5168 } 5169 5170 /* 5171 Special version for direct calls from Fortran 5172 */ 5173 #include <petsc/private/fortranimpl.h> 5174 5175 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5176 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5177 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5178 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5179 #endif 5180 5181 /* Change these macros so can be used in void function */ 5182 #undef CHKERRQ 5183 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5184 #undef SETERRQ2 5185 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5186 #undef SETERRQ3 5187 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5188 #undef SETERRQ 5189 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5190 5191 #undef __FUNCT__ 5192 #define __FUNCT__ "matsetvaluesmpiaij_" 5193 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) 5194 { 5195 Mat mat = *mmat; 5196 PetscInt m = *mm, n = *mn; 5197 InsertMode addv = *maddv; 5198 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5199 PetscScalar value; 5200 PetscErrorCode ierr; 5201 5202 MatCheckPreallocated(mat,1); 5203 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5204 5205 #if defined(PETSC_USE_DEBUG) 5206 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5207 #endif 5208 { 5209 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5210 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5211 PetscBool roworiented = aij->roworiented; 5212 5213 /* Some Variables required in the macro */ 5214 Mat A = aij->A; 5215 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5216 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5217 MatScalar *aa = a->a; 5218 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5219 Mat B = aij->B; 5220 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5221 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5222 MatScalar *ba = b->a; 5223 5224 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5225 PetscInt nonew = a->nonew; 5226 MatScalar *ap1,*ap2; 5227 5228 PetscFunctionBegin; 5229 for (i=0; i<m; i++) { 5230 if (im[i] < 0) continue; 5231 #if defined(PETSC_USE_DEBUG) 5232 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); 5233 #endif 5234 if (im[i] >= rstart && im[i] < rend) { 5235 row = im[i] - rstart; 5236 lastcol1 = -1; 5237 rp1 = aj + ai[row]; 5238 ap1 = aa + ai[row]; 5239 rmax1 = aimax[row]; 5240 nrow1 = ailen[row]; 5241 low1 = 0; 5242 high1 = nrow1; 5243 lastcol2 = -1; 5244 rp2 = bj + bi[row]; 5245 ap2 = ba + bi[row]; 5246 rmax2 = bimax[row]; 5247 nrow2 = bilen[row]; 5248 low2 = 0; 5249 high2 = nrow2; 5250 5251 for (j=0; j<n; j++) { 5252 if (roworiented) value = v[i*n+j]; 5253 else value = v[i+j*m]; 5254 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5255 if (in[j] >= cstart && in[j] < cend) { 5256 col = in[j] - cstart; 5257 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5258 } else if (in[j] < 0) continue; 5259 #if defined(PETSC_USE_DEBUG) 5260 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); 5261 #endif 5262 else { 5263 if (mat->was_assembled) { 5264 if (!aij->colmap) { 5265 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5266 } 5267 #if defined(PETSC_USE_CTABLE) 5268 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5269 col--; 5270 #else 5271 col = aij->colmap[in[j]] - 1; 5272 #endif 5273 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5274 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5275 col = in[j]; 5276 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5277 B = aij->B; 5278 b = (Mat_SeqAIJ*)B->data; 5279 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5280 rp2 = bj + bi[row]; 5281 ap2 = ba + bi[row]; 5282 rmax2 = bimax[row]; 5283 nrow2 = bilen[row]; 5284 low2 = 0; 5285 high2 = nrow2; 5286 bm = aij->B->rmap->n; 5287 ba = b->a; 5288 } 5289 } else col = in[j]; 5290 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5291 } 5292 } 5293 } else if (!aij->donotstash) { 5294 if (roworiented) { 5295 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5296 } else { 5297 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5298 } 5299 } 5300 } 5301 } 5302 PetscFunctionReturnVoid(); 5303 } 5304 5305