1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 #undef __FUNCT__ 499 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 500 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 501 { 502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 504 PetscErrorCode ierr; 505 PetscInt l,*garray = mat->garray,diag; 506 507 PetscFunctionBegin; 508 /* code only works for square matrices A */ 509 510 /* find size of row to the left of the diagonal part */ 511 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 512 row = row - diag; 513 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 514 if (garray[b->j[b->i[row]+l]] > diag) break; 515 } 516 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 517 518 /* diagonal part */ 519 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 520 521 /* right of diagonal part */ 522 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 523 PetscFunctionReturn(0); 524 } 525 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatSetValues_MPIAIJ" 528 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 529 { 530 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 531 PetscScalar value; 532 PetscErrorCode ierr; 533 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 534 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 535 PetscBool roworiented = aij->roworiented; 536 537 /* Some Variables required in the macro */ 538 Mat A = aij->A; 539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 540 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 541 MatScalar *aa = a->a; 542 PetscBool ignorezeroentries = a->ignorezeroentries; 543 Mat B = aij->B; 544 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 545 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 546 MatScalar *ba = b->a; 547 548 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 549 PetscInt nonew; 550 MatScalar *ap1,*ap2; 551 552 PetscFunctionBegin; 553 for (i=0; i<m; i++) { 554 if (im[i] < 0) continue; 555 #if defined(PETSC_USE_DEBUG) 556 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 557 #endif 558 if (im[i] >= rstart && im[i] < rend) { 559 row = im[i] - rstart; 560 lastcol1 = -1; 561 rp1 = aj + ai[row]; 562 ap1 = aa + ai[row]; 563 rmax1 = aimax[row]; 564 nrow1 = ailen[row]; 565 low1 = 0; 566 high1 = nrow1; 567 lastcol2 = -1; 568 rp2 = bj + bi[row]; 569 ap2 = ba + bi[row]; 570 rmax2 = bimax[row]; 571 nrow2 = bilen[row]; 572 low2 = 0; 573 high2 = nrow2; 574 575 for (j=0; j<n; j++) { 576 if (roworiented) value = v[i*n+j]; 577 else value = v[i+j*m]; 578 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 579 if (in[j] >= cstart && in[j] < cend) { 580 col = in[j] - cstart; 581 nonew = a->nonew; 582 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 583 } else if (in[j] < 0) continue; 584 #if defined(PETSC_USE_DEBUG) 585 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 586 #endif 587 else { 588 if (mat->was_assembled) { 589 if (!aij->colmap) { 590 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 591 } 592 #if defined(PETSC_USE_CTABLE) 593 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 594 col--; 595 #else 596 col = aij->colmap[in[j]] - 1; 597 #endif 598 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 599 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 600 col = in[j]; 601 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 602 B = aij->B; 603 b = (Mat_SeqAIJ*)B->data; 604 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 605 rp2 = bj + bi[row]; 606 ap2 = ba + bi[row]; 607 rmax2 = bimax[row]; 608 nrow2 = bilen[row]; 609 low2 = 0; 610 high2 = nrow2; 611 bm = aij->B->rmap->n; 612 ba = b->a; 613 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 614 } else col = in[j]; 615 nonew = b->nonew; 616 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 617 } 618 } 619 } else { 620 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 621 if (!aij->donotstash) { 622 mat->assembled = PETSC_FALSE; 623 if (roworiented) { 624 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 625 } else { 626 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 627 } 628 } 629 } 630 } 631 PetscFunctionReturn(0); 632 } 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatGetValues_MPIAIJ" 636 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 641 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 642 643 PetscFunctionBegin; 644 for (i=0; i<m; i++) { 645 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 646 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 647 if (idxm[i] >= rstart && idxm[i] < rend) { 648 row = idxm[i] - rstart; 649 for (j=0; j<n; j++) { 650 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 651 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 652 if (idxn[j] >= cstart && idxn[j] < cend) { 653 col = idxn[j] - cstart; 654 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 655 } else { 656 if (!aij->colmap) { 657 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 658 } 659 #if defined(PETSC_USE_CTABLE) 660 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 661 col--; 662 #else 663 col = aij->colmap[idxn[j]] - 1; 664 #endif 665 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 666 else { 667 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 668 } 669 } 670 } 671 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 672 } 673 PetscFunctionReturn(0); 674 } 675 676 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 680 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 681 { 682 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 683 PetscErrorCode ierr; 684 PetscInt nstash,reallocs; 685 686 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 = MPI_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 = MPI_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 = MPI_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 = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 971 } 972 PetscFunctionReturn(0); 973 } 974 975 #undef __FUNCT__ 976 #define __FUNCT__ "MatMult_MPIAIJ" 977 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 978 { 979 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 980 PetscErrorCode ierr; 981 PetscInt nt; 982 983 PetscFunctionBegin; 984 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 985 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 986 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 987 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 988 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 989 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 990 PetscFunctionReturn(0); 991 } 992 993 #undef __FUNCT__ 994 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 995 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 996 { 997 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 998 PetscErrorCode ierr; 999 1000 PetscFunctionBegin; 1001 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1002 PetscFunctionReturn(0); 1003 } 1004 1005 #undef __FUNCT__ 1006 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1007 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1008 { 1009 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1010 PetscErrorCode ierr; 1011 1012 PetscFunctionBegin; 1013 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1014 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1015 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1016 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1017 PetscFunctionReturn(0); 1018 } 1019 1020 #undef __FUNCT__ 1021 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1022 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1023 { 1024 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1025 PetscErrorCode ierr; 1026 PetscBool merged; 1027 1028 PetscFunctionBegin; 1029 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1030 /* do nondiagonal part */ 1031 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1032 if (!merged) { 1033 /* send it on its way */ 1034 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1035 /* do local part */ 1036 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1037 /* receive remote parts: note this assumes the values are not actually */ 1038 /* added in yy until the next line, */ 1039 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1040 } else { 1041 /* do local part */ 1042 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1043 /* send it on its way */ 1044 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1045 /* values actually were received in the Begin() but we need to call this nop */ 1046 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1047 } 1048 PetscFunctionReturn(0); 1049 } 1050 1051 #undef __FUNCT__ 1052 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1053 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1054 { 1055 MPI_Comm comm; 1056 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1057 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1058 IS Me,Notme; 1059 PetscErrorCode ierr; 1060 PetscInt M,N,first,last,*notme,i; 1061 PetscMPIInt size; 1062 1063 PetscFunctionBegin; 1064 /* Easy test: symmetric diagonal block */ 1065 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1066 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1067 if (!*f) PetscFunctionReturn(0); 1068 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1069 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1070 if (size == 1) PetscFunctionReturn(0); 1071 1072 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1073 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1074 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1075 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1076 for (i=0; i<first; i++) notme[i] = i; 1077 for (i=last; i<M; i++) notme[i-last+first] = i; 1078 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1079 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1080 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1081 Aoff = Aoffs[0]; 1082 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1083 Boff = Boffs[0]; 1084 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1085 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1086 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1087 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1088 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1089 ierr = PetscFree(notme);CHKERRQ(ierr); 1090 PetscFunctionReturn(0); 1091 } 1092 1093 #undef __FUNCT__ 1094 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1095 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1096 { 1097 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1098 PetscErrorCode ierr; 1099 1100 PetscFunctionBegin; 1101 /* do nondiagonal part */ 1102 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1103 /* send it on its way */ 1104 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1105 /* do local part */ 1106 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1107 /* receive remote parts */ 1108 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1109 PetscFunctionReturn(0); 1110 } 1111 1112 /* 1113 This only works correctly for square matrices where the subblock A->A is the 1114 diagonal block 1115 */ 1116 #undef __FUNCT__ 1117 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1118 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1119 { 1120 PetscErrorCode ierr; 1121 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1122 1123 PetscFunctionBegin; 1124 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1125 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1126 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatScale_MPIAIJ" 1132 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1139 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatDestroy_MPIAIJ" 1145 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1146 { 1147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1148 PetscErrorCode ierr; 1149 1150 PetscFunctionBegin; 1151 #if defined(PETSC_USE_LOG) 1152 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1153 #endif 1154 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1155 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1156 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1157 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1158 #if defined(PETSC_USE_CTABLE) 1159 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1160 #else 1161 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1162 #endif 1163 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1164 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1165 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1166 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1167 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1168 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1169 1170 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1171 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1172 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1173 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1174 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1175 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1176 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1177 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1178 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1179 #if defined(PETSC_HAVE_ELEMENTAL) 1180 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1181 #endif 1182 PetscFunctionReturn(0); 1183 } 1184 1185 #undef __FUNCT__ 1186 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1187 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1188 { 1189 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1190 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1191 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1192 PetscErrorCode ierr; 1193 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1194 int fd; 1195 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1196 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1197 PetscScalar *column_values; 1198 PetscInt message_count,flowcontrolcount; 1199 FILE *file; 1200 1201 PetscFunctionBegin; 1202 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1203 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1204 nz = A->nz + B->nz; 1205 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1206 if (!rank) { 1207 header[0] = MAT_FILE_CLASSID; 1208 header[1] = mat->rmap->N; 1209 header[2] = mat->cmap->N; 1210 1211 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1212 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1213 /* get largest number of rows any processor has */ 1214 rlen = mat->rmap->n; 1215 range = mat->rmap->range; 1216 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1217 } else { 1218 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 rlen = mat->rmap->n; 1220 } 1221 1222 /* load up the local row counts */ 1223 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1224 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1225 1226 /* store the row lengths to the file */ 1227 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1228 if (!rank) { 1229 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1230 for (i=1; i<size; i++) { 1231 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1232 rlen = range[i+1] - range[i]; 1233 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1234 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1235 } 1236 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1237 } else { 1238 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1239 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1240 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1241 } 1242 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1243 1244 /* load up the local column indices */ 1245 nzmax = nz; /* th processor needs space a largest processor needs */ 1246 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1247 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1248 cnt = 0; 1249 for (i=0; i<mat->rmap->n; i++) { 1250 for (j=B->i[i]; j<B->i[i+1]; j++) { 1251 if ((col = garray[B->j[j]]) > cstart) break; 1252 column_indices[cnt++] = col; 1253 } 1254 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1255 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1256 } 1257 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1258 1259 /* store the column indices to the file */ 1260 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1261 if (!rank) { 1262 MPI_Status status; 1263 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1264 for (i=1; i<size; i++) { 1265 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1266 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1267 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1268 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1269 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1270 } 1271 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1272 } else { 1273 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1274 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1275 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1276 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1277 } 1278 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1279 1280 /* load up the local column values */ 1281 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1282 cnt = 0; 1283 for (i=0; i<mat->rmap->n; i++) { 1284 for (j=B->i[i]; j<B->i[i+1]; j++) { 1285 if (garray[B->j[j]] > cstart) break; 1286 column_values[cnt++] = B->a[j]; 1287 } 1288 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1289 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1290 } 1291 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1292 1293 /* store the column values to the file */ 1294 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1295 if (!rank) { 1296 MPI_Status status; 1297 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1298 for (i=1; i<size; i++) { 1299 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1300 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1301 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1302 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1303 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1304 } 1305 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1306 } else { 1307 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1308 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1309 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1310 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1311 } 1312 ierr = PetscFree(column_values);CHKERRQ(ierr); 1313 1314 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1315 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1316 PetscFunctionReturn(0); 1317 } 1318 1319 #include <petscdraw.h> 1320 #undef __FUNCT__ 1321 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1322 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1323 { 1324 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1325 PetscErrorCode ierr; 1326 PetscMPIInt rank = aij->rank,size = aij->size; 1327 PetscBool isdraw,iascii,isbinary; 1328 PetscViewer sviewer; 1329 PetscViewerFormat format; 1330 1331 PetscFunctionBegin; 1332 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1333 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1334 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1335 if (iascii) { 1336 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1337 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1338 MatInfo info; 1339 PetscBool inodes; 1340 1341 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1342 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1343 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1344 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1345 if (!inodes) { 1346 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1347 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1348 } else { 1349 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1350 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1351 } 1352 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1353 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1354 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1355 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1356 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1357 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1358 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1359 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1360 PetscFunctionReturn(0); 1361 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1362 PetscInt inodecount,inodelimit,*inodes; 1363 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1364 if (inodes) { 1365 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1366 } else { 1367 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1368 } 1369 PetscFunctionReturn(0); 1370 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1371 PetscFunctionReturn(0); 1372 } 1373 } else if (isbinary) { 1374 if (size == 1) { 1375 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1376 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1377 } else { 1378 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1379 } 1380 PetscFunctionReturn(0); 1381 } else if (isdraw) { 1382 PetscDraw draw; 1383 PetscBool isnull; 1384 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1385 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1386 } 1387 1388 { 1389 /* assemble the entire matrix onto first processor. */ 1390 Mat A; 1391 Mat_SeqAIJ *Aloc; 1392 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1393 MatScalar *a; 1394 1395 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1396 if (!rank) { 1397 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1398 } else { 1399 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1400 } 1401 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1402 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1403 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1404 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1405 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1406 1407 /* copy over the A part */ 1408 Aloc = (Mat_SeqAIJ*)aij->A->data; 1409 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1410 row = mat->rmap->rstart; 1411 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1412 for (i=0; i<m; i++) { 1413 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1414 row++; 1415 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1416 } 1417 aj = Aloc->j; 1418 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1419 1420 /* copy over the B part */ 1421 Aloc = (Mat_SeqAIJ*)aij->B->data; 1422 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1423 row = mat->rmap->rstart; 1424 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1425 ct = cols; 1426 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1427 for (i=0; i<m; i++) { 1428 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1429 row++; 1430 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1431 } 1432 ierr = PetscFree(ct);CHKERRQ(ierr); 1433 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1434 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1435 /* 1436 Everyone has to call to draw the matrix since the graphics waits are 1437 synchronized across all processors that share the PetscDraw object 1438 */ 1439 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1440 if (!rank) { 1441 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1442 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1443 } 1444 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1445 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1446 ierr = MatDestroy(&A);CHKERRQ(ierr); 1447 } 1448 PetscFunctionReturn(0); 1449 } 1450 1451 #undef __FUNCT__ 1452 #define __FUNCT__ "MatView_MPIAIJ" 1453 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1454 { 1455 PetscErrorCode ierr; 1456 PetscBool iascii,isdraw,issocket,isbinary; 1457 1458 PetscFunctionBegin; 1459 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1460 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1461 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1462 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1463 if (iascii || isdraw || isbinary || issocket) { 1464 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1465 } 1466 PetscFunctionReturn(0); 1467 } 1468 1469 #undef __FUNCT__ 1470 #define __FUNCT__ "MatSOR_MPIAIJ" 1471 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1472 { 1473 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1474 PetscErrorCode ierr; 1475 Vec bb1 = 0; 1476 PetscBool hasop; 1477 1478 PetscFunctionBegin; 1479 if (flag == SOR_APPLY_UPPER) { 1480 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1481 PetscFunctionReturn(0); 1482 } 1483 1484 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1485 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1486 } 1487 1488 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1489 if (flag & SOR_ZERO_INITIAL_GUESS) { 1490 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1491 its--; 1492 } 1493 1494 while (its--) { 1495 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1496 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1497 1498 /* update rhs: bb1 = bb - B*x */ 1499 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1500 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1501 1502 /* local sweep */ 1503 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1504 } 1505 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1506 if (flag & SOR_ZERO_INITIAL_GUESS) { 1507 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1508 its--; 1509 } 1510 while (its--) { 1511 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1512 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1513 1514 /* update rhs: bb1 = bb - B*x */ 1515 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1516 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1517 1518 /* local sweep */ 1519 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1520 } 1521 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1522 if (flag & SOR_ZERO_INITIAL_GUESS) { 1523 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1524 its--; 1525 } 1526 while (its--) { 1527 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1528 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1529 1530 /* update rhs: bb1 = bb - B*x */ 1531 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1532 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1533 1534 /* local sweep */ 1535 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1536 } 1537 } else if (flag & SOR_EISENSTAT) { 1538 Vec xx1; 1539 1540 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1541 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1542 1543 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1544 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1545 if (!mat->diag) { 1546 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1547 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1548 } 1549 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1550 if (hasop) { 1551 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1552 } else { 1553 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1554 } 1555 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1556 1557 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1558 1559 /* local sweep */ 1560 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1561 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1562 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1563 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1564 1565 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1566 PetscFunctionReturn(0); 1567 } 1568 1569 #undef __FUNCT__ 1570 #define __FUNCT__ "MatPermute_MPIAIJ" 1571 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1572 { 1573 Mat aA,aB,Aperm; 1574 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1575 PetscScalar *aa,*ba; 1576 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1577 PetscSF rowsf,sf; 1578 IS parcolp = NULL; 1579 PetscBool done; 1580 PetscErrorCode ierr; 1581 1582 PetscFunctionBegin; 1583 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1584 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1585 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1586 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1587 1588 /* Invert row permutation to find out where my rows should go */ 1589 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1590 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1591 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1592 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1593 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1594 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1595 1596 /* Invert column permutation to find out where my columns should go */ 1597 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1598 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1599 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1600 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1601 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1602 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1603 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1604 1605 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1606 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1607 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1608 1609 /* Find out where my gcols should go */ 1610 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1611 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1612 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1613 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1614 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1615 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1616 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1617 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1618 1619 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1620 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1621 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1622 for (i=0; i<m; i++) { 1623 PetscInt row = rdest[i],rowner; 1624 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1625 for (j=ai[i]; j<ai[i+1]; j++) { 1626 PetscInt cowner,col = cdest[aj[j]]; 1627 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1628 if (rowner == cowner) dnnz[i]++; 1629 else onnz[i]++; 1630 } 1631 for (j=bi[i]; j<bi[i+1]; j++) { 1632 PetscInt cowner,col = gcdest[bj[j]]; 1633 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1634 if (rowner == cowner) dnnz[i]++; 1635 else onnz[i]++; 1636 } 1637 } 1638 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1639 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1640 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1641 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1642 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1643 1644 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1645 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1646 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1647 for (i=0; i<m; i++) { 1648 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1649 PetscInt j0,rowlen; 1650 rowlen = ai[i+1] - ai[i]; 1651 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1652 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1653 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1654 } 1655 rowlen = bi[i+1] - bi[i]; 1656 for (j0=j=0; j<rowlen; j0=j) { 1657 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1658 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1659 } 1660 } 1661 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1662 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1663 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1664 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1665 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1666 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1667 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1668 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1669 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1670 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1671 *B = Aperm; 1672 PetscFunctionReturn(0); 1673 } 1674 1675 #undef __FUNCT__ 1676 #define __FUNCT__ "MatGetGhosts_MPIAIJ" 1677 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1678 { 1679 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1680 PetscErrorCode ierr; 1681 1682 PetscFunctionBegin; 1683 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1684 if (ghosts) *ghosts = aij->garray; 1685 PetscFunctionReturn(0); 1686 } 1687 1688 #undef __FUNCT__ 1689 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1690 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1691 { 1692 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1693 Mat A = mat->A,B = mat->B; 1694 PetscErrorCode ierr; 1695 PetscReal isend[5],irecv[5]; 1696 1697 PetscFunctionBegin; 1698 info->block_size = 1.0; 1699 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1700 1701 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1702 isend[3] = info->memory; isend[4] = info->mallocs; 1703 1704 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1705 1706 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1707 isend[3] += info->memory; isend[4] += info->mallocs; 1708 if (flag == MAT_LOCAL) { 1709 info->nz_used = isend[0]; 1710 info->nz_allocated = isend[1]; 1711 info->nz_unneeded = isend[2]; 1712 info->memory = isend[3]; 1713 info->mallocs = isend[4]; 1714 } else if (flag == MAT_GLOBAL_MAX) { 1715 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1716 1717 info->nz_used = irecv[0]; 1718 info->nz_allocated = irecv[1]; 1719 info->nz_unneeded = irecv[2]; 1720 info->memory = irecv[3]; 1721 info->mallocs = irecv[4]; 1722 } else if (flag == MAT_GLOBAL_SUM) { 1723 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1724 1725 info->nz_used = irecv[0]; 1726 info->nz_allocated = irecv[1]; 1727 info->nz_unneeded = irecv[2]; 1728 info->memory = irecv[3]; 1729 info->mallocs = irecv[4]; 1730 } 1731 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1732 info->fill_ratio_needed = 0; 1733 info->factor_mallocs = 0; 1734 PetscFunctionReturn(0); 1735 } 1736 1737 #undef __FUNCT__ 1738 #define __FUNCT__ "MatSetOption_MPIAIJ" 1739 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1740 { 1741 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1742 PetscErrorCode ierr; 1743 1744 PetscFunctionBegin; 1745 switch (op) { 1746 case MAT_NEW_NONZERO_LOCATIONS: 1747 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1748 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1749 case MAT_KEEP_NONZERO_PATTERN: 1750 case MAT_NEW_NONZERO_LOCATION_ERR: 1751 case MAT_USE_INODES: 1752 case MAT_IGNORE_ZERO_ENTRIES: 1753 MatCheckPreallocated(A,1); 1754 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1755 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1756 break; 1757 case MAT_ROW_ORIENTED: 1758 a->roworiented = flg; 1759 1760 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1761 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1762 break; 1763 case MAT_NEW_DIAGONALS: 1764 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1765 break; 1766 case MAT_IGNORE_OFF_PROC_ENTRIES: 1767 a->donotstash = flg; 1768 break; 1769 case MAT_SPD: 1770 A->spd_set = PETSC_TRUE; 1771 A->spd = flg; 1772 if (flg) { 1773 A->symmetric = PETSC_TRUE; 1774 A->structurally_symmetric = PETSC_TRUE; 1775 A->symmetric_set = PETSC_TRUE; 1776 A->structurally_symmetric_set = PETSC_TRUE; 1777 } 1778 break; 1779 case MAT_SYMMETRIC: 1780 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1781 break; 1782 case MAT_STRUCTURALLY_SYMMETRIC: 1783 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1784 break; 1785 case MAT_HERMITIAN: 1786 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1787 break; 1788 case MAT_SYMMETRY_ETERNAL: 1789 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1790 break; 1791 default: 1792 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1793 } 1794 PetscFunctionReturn(0); 1795 } 1796 1797 #undef __FUNCT__ 1798 #define __FUNCT__ "MatGetRow_MPIAIJ" 1799 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1800 { 1801 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1802 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1803 PetscErrorCode ierr; 1804 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1805 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1806 PetscInt *cmap,*idx_p; 1807 1808 PetscFunctionBegin; 1809 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1810 mat->getrowactive = PETSC_TRUE; 1811 1812 if (!mat->rowvalues && (idx || v)) { 1813 /* 1814 allocate enough space to hold information from the longest row. 1815 */ 1816 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1817 PetscInt max = 1,tmp; 1818 for (i=0; i<matin->rmap->n; i++) { 1819 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1820 if (max < tmp) max = tmp; 1821 } 1822 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1823 } 1824 1825 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1826 lrow = row - rstart; 1827 1828 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1829 if (!v) {pvA = 0; pvB = 0;} 1830 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1831 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1832 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1833 nztot = nzA + nzB; 1834 1835 cmap = mat->garray; 1836 if (v || idx) { 1837 if (nztot) { 1838 /* Sort by increasing column numbers, assuming A and B already sorted */ 1839 PetscInt imark = -1; 1840 if (v) { 1841 *v = v_p = mat->rowvalues; 1842 for (i=0; i<nzB; i++) { 1843 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1844 else break; 1845 } 1846 imark = i; 1847 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1848 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1849 } 1850 if (idx) { 1851 *idx = idx_p = mat->rowindices; 1852 if (imark > -1) { 1853 for (i=0; i<imark; i++) { 1854 idx_p[i] = cmap[cworkB[i]]; 1855 } 1856 } else { 1857 for (i=0; i<nzB; i++) { 1858 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1859 else break; 1860 } 1861 imark = i; 1862 } 1863 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1864 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1865 } 1866 } else { 1867 if (idx) *idx = 0; 1868 if (v) *v = 0; 1869 } 1870 } 1871 *nz = nztot; 1872 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1873 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1874 PetscFunctionReturn(0); 1875 } 1876 1877 #undef __FUNCT__ 1878 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1879 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1880 { 1881 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1882 1883 PetscFunctionBegin; 1884 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1885 aij->getrowactive = PETSC_FALSE; 1886 PetscFunctionReturn(0); 1887 } 1888 1889 #undef __FUNCT__ 1890 #define __FUNCT__ "MatNorm_MPIAIJ" 1891 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1892 { 1893 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1894 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1895 PetscErrorCode ierr; 1896 PetscInt i,j,cstart = mat->cmap->rstart; 1897 PetscReal sum = 0.0; 1898 MatScalar *v; 1899 1900 PetscFunctionBegin; 1901 if (aij->size == 1) { 1902 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1903 } else { 1904 if (type == NORM_FROBENIUS) { 1905 v = amat->a; 1906 for (i=0; i<amat->nz; i++) { 1907 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1908 } 1909 v = bmat->a; 1910 for (i=0; i<bmat->nz; i++) { 1911 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1912 } 1913 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1914 *norm = PetscSqrtReal(*norm); 1915 } else if (type == NORM_1) { /* max column norm */ 1916 PetscReal *tmp,*tmp2; 1917 PetscInt *jj,*garray = aij->garray; 1918 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1919 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1920 *norm = 0.0; 1921 v = amat->a; jj = amat->j; 1922 for (j=0; j<amat->nz; j++) { 1923 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1924 } 1925 v = bmat->a; jj = bmat->j; 1926 for (j=0; j<bmat->nz; j++) { 1927 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1928 } 1929 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1930 for (j=0; j<mat->cmap->N; j++) { 1931 if (tmp2[j] > *norm) *norm = tmp2[j]; 1932 } 1933 ierr = PetscFree(tmp);CHKERRQ(ierr); 1934 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1935 } else if (type == NORM_INFINITY) { /* max row norm */ 1936 PetscReal ntemp = 0.0; 1937 for (j=0; j<aij->A->rmap->n; j++) { 1938 v = amat->a + amat->i[j]; 1939 sum = 0.0; 1940 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1941 sum += PetscAbsScalar(*v); v++; 1942 } 1943 v = bmat->a + bmat->i[j]; 1944 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1945 sum += PetscAbsScalar(*v); v++; 1946 } 1947 if (sum > ntemp) ntemp = sum; 1948 } 1949 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1950 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1951 } 1952 PetscFunctionReturn(0); 1953 } 1954 1955 #undef __FUNCT__ 1956 #define __FUNCT__ "MatTranspose_MPIAIJ" 1957 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1958 { 1959 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1960 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1961 PetscErrorCode ierr; 1962 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1963 PetscInt cstart = A->cmap->rstart,ncol; 1964 Mat B; 1965 MatScalar *array; 1966 1967 PetscFunctionBegin; 1968 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1969 1970 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1971 ai = Aloc->i; aj = Aloc->j; 1972 bi = Bloc->i; bj = Bloc->j; 1973 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1974 PetscInt *d_nnz,*g_nnz,*o_nnz; 1975 PetscSFNode *oloc; 1976 PETSC_UNUSED PetscSF sf; 1977 1978 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1979 /* compute d_nnz for preallocation */ 1980 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1981 for (i=0; i<ai[ma]; i++) { 1982 d_nnz[aj[i]]++; 1983 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1984 } 1985 /* compute local off-diagonal contributions */ 1986 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1987 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1988 /* map those to global */ 1989 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1990 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1991 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1992 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1993 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1994 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1995 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1996 1997 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1998 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1999 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2000 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2001 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2002 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2003 } else { 2004 B = *matout; 2005 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2006 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2007 } 2008 2009 /* copy over the A part */ 2010 array = Aloc->a; 2011 row = A->rmap->rstart; 2012 for (i=0; i<ma; i++) { 2013 ncol = ai[i+1]-ai[i]; 2014 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2015 row++; 2016 array += ncol; aj += ncol; 2017 } 2018 aj = Aloc->j; 2019 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2020 2021 /* copy over the B part */ 2022 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2023 array = Bloc->a; 2024 row = A->rmap->rstart; 2025 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2026 cols_tmp = cols; 2027 for (i=0; i<mb; i++) { 2028 ncol = bi[i+1]-bi[i]; 2029 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2030 row++; 2031 array += ncol; cols_tmp += ncol; 2032 } 2033 ierr = PetscFree(cols);CHKERRQ(ierr); 2034 2035 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2036 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2037 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2038 *matout = B; 2039 } else { 2040 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 2041 } 2042 PetscFunctionReturn(0); 2043 } 2044 2045 #undef __FUNCT__ 2046 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2047 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2048 { 2049 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2050 Mat a = aij->A,b = aij->B; 2051 PetscErrorCode ierr; 2052 PetscInt s1,s2,s3; 2053 2054 PetscFunctionBegin; 2055 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2056 if (rr) { 2057 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2058 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2059 /* Overlap communication with computation. */ 2060 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2061 } 2062 if (ll) { 2063 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2064 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2065 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2066 } 2067 /* scale the diagonal block */ 2068 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2069 2070 if (rr) { 2071 /* Do a scatter end and then right scale the off-diagonal block */ 2072 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2073 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2074 } 2075 PetscFunctionReturn(0); 2076 } 2077 2078 #undef __FUNCT__ 2079 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2080 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2081 { 2082 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2083 PetscErrorCode ierr; 2084 2085 PetscFunctionBegin; 2086 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2087 PetscFunctionReturn(0); 2088 } 2089 2090 #undef __FUNCT__ 2091 #define __FUNCT__ "MatEqual_MPIAIJ" 2092 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2093 { 2094 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2095 Mat a,b,c,d; 2096 PetscBool flg; 2097 PetscErrorCode ierr; 2098 2099 PetscFunctionBegin; 2100 a = matA->A; b = matA->B; 2101 c = matB->A; d = matB->B; 2102 2103 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2104 if (flg) { 2105 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2106 } 2107 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2108 PetscFunctionReturn(0); 2109 } 2110 2111 #undef __FUNCT__ 2112 #define __FUNCT__ "MatCopy_MPIAIJ" 2113 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2114 { 2115 PetscErrorCode ierr; 2116 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2117 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2118 2119 PetscFunctionBegin; 2120 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2121 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2122 /* because of the column compression in the off-processor part of the matrix a->B, 2123 the number of columns in a->B and b->B may be different, hence we cannot call 2124 the MatCopy() directly on the two parts. If need be, we can provide a more 2125 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2126 then copying the submatrices */ 2127 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2128 } else { 2129 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2130 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2131 } 2132 PetscFunctionReturn(0); 2133 } 2134 2135 #undef __FUNCT__ 2136 #define __FUNCT__ "MatSetUp_MPIAIJ" 2137 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2138 { 2139 PetscErrorCode ierr; 2140 2141 PetscFunctionBegin; 2142 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2143 PetscFunctionReturn(0); 2144 } 2145 2146 /* 2147 Computes the number of nonzeros per row needed for preallocation when X and Y 2148 have different nonzero structure. 2149 */ 2150 #undef __FUNCT__ 2151 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2152 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2153 { 2154 PetscInt i,j,k,nzx,nzy; 2155 2156 PetscFunctionBegin; 2157 /* Set the number of nonzeros in the new matrix */ 2158 for (i=0; i<m; i++) { 2159 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2160 nzx = xi[i+1] - xi[i]; 2161 nzy = yi[i+1] - yi[i]; 2162 nnz[i] = 0; 2163 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2164 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2165 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2166 nnz[i]++; 2167 } 2168 for (; k<nzy; k++) nnz[i]++; 2169 } 2170 PetscFunctionReturn(0); 2171 } 2172 2173 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2174 #undef __FUNCT__ 2175 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2176 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2177 { 2178 PetscErrorCode ierr; 2179 PetscInt m = Y->rmap->N; 2180 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2181 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2182 2183 PetscFunctionBegin; 2184 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2185 PetscFunctionReturn(0); 2186 } 2187 2188 #undef __FUNCT__ 2189 #define __FUNCT__ "MatAXPY_MPIAIJ" 2190 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2191 { 2192 PetscErrorCode ierr; 2193 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2194 PetscBLASInt bnz,one=1; 2195 Mat_SeqAIJ *x,*y; 2196 2197 PetscFunctionBegin; 2198 if (str == SAME_NONZERO_PATTERN) { 2199 PetscScalar alpha = a; 2200 x = (Mat_SeqAIJ*)xx->A->data; 2201 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2202 y = (Mat_SeqAIJ*)yy->A->data; 2203 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2204 x = (Mat_SeqAIJ*)xx->B->data; 2205 y = (Mat_SeqAIJ*)yy->B->data; 2206 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2207 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2208 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2209 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2210 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2211 } else { 2212 Mat B; 2213 PetscInt *nnz_d,*nnz_o; 2214 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2215 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2216 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2217 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2218 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2219 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2220 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2221 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2222 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2223 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2224 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2225 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2226 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2227 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2228 } 2229 PetscFunctionReturn(0); 2230 } 2231 2232 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2233 2234 #undef __FUNCT__ 2235 #define __FUNCT__ "MatConjugate_MPIAIJ" 2236 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2237 { 2238 #if defined(PETSC_USE_COMPLEX) 2239 PetscErrorCode ierr; 2240 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2241 2242 PetscFunctionBegin; 2243 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2244 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2245 #else 2246 PetscFunctionBegin; 2247 #endif 2248 PetscFunctionReturn(0); 2249 } 2250 2251 #undef __FUNCT__ 2252 #define __FUNCT__ "MatRealPart_MPIAIJ" 2253 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2254 { 2255 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2256 PetscErrorCode ierr; 2257 2258 PetscFunctionBegin; 2259 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2260 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2261 PetscFunctionReturn(0); 2262 } 2263 2264 #undef __FUNCT__ 2265 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2266 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2267 { 2268 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2269 PetscErrorCode ierr; 2270 2271 PetscFunctionBegin; 2272 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2273 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2274 PetscFunctionReturn(0); 2275 } 2276 2277 #undef __FUNCT__ 2278 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2279 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2280 { 2281 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2282 PetscErrorCode ierr; 2283 PetscInt i,*idxb = 0; 2284 PetscScalar *va,*vb; 2285 Vec vtmp; 2286 2287 PetscFunctionBegin; 2288 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2289 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2290 if (idx) { 2291 for (i=0; i<A->rmap->n; i++) { 2292 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2293 } 2294 } 2295 2296 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2297 if (idx) { 2298 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2299 } 2300 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2301 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2302 2303 for (i=0; i<A->rmap->n; i++) { 2304 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2305 va[i] = vb[i]; 2306 if (idx) idx[i] = a->garray[idxb[i]]; 2307 } 2308 } 2309 2310 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2311 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2312 ierr = PetscFree(idxb);CHKERRQ(ierr); 2313 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2314 PetscFunctionReturn(0); 2315 } 2316 2317 #undef __FUNCT__ 2318 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2319 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2320 { 2321 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2322 PetscErrorCode ierr; 2323 PetscInt i,*idxb = 0; 2324 PetscScalar *va,*vb; 2325 Vec vtmp; 2326 2327 PetscFunctionBegin; 2328 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2329 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2330 if (idx) { 2331 for (i=0; i<A->cmap->n; i++) { 2332 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2333 } 2334 } 2335 2336 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2337 if (idx) { 2338 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2339 } 2340 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2341 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2342 2343 for (i=0; i<A->rmap->n; i++) { 2344 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2345 va[i] = vb[i]; 2346 if (idx) idx[i] = a->garray[idxb[i]]; 2347 } 2348 } 2349 2350 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2351 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2352 ierr = PetscFree(idxb);CHKERRQ(ierr); 2353 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2354 PetscFunctionReturn(0); 2355 } 2356 2357 #undef __FUNCT__ 2358 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2359 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2360 { 2361 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2362 PetscInt n = A->rmap->n; 2363 PetscInt cstart = A->cmap->rstart; 2364 PetscInt *cmap = mat->garray; 2365 PetscInt *diagIdx, *offdiagIdx; 2366 Vec diagV, offdiagV; 2367 PetscScalar *a, *diagA, *offdiagA; 2368 PetscInt r; 2369 PetscErrorCode ierr; 2370 2371 PetscFunctionBegin; 2372 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2373 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2374 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2375 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2376 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2377 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2378 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2379 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2380 for (r = 0; r < n; ++r) { 2381 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2382 a[r] = diagA[r]; 2383 idx[r] = cstart + diagIdx[r]; 2384 } else { 2385 a[r] = offdiagA[r]; 2386 idx[r] = cmap[offdiagIdx[r]]; 2387 } 2388 } 2389 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2390 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2391 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2392 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2393 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2394 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2395 PetscFunctionReturn(0); 2396 } 2397 2398 #undef __FUNCT__ 2399 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2400 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2401 { 2402 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2403 PetscInt n = A->rmap->n; 2404 PetscInt cstart = A->cmap->rstart; 2405 PetscInt *cmap = mat->garray; 2406 PetscInt *diagIdx, *offdiagIdx; 2407 Vec diagV, offdiagV; 2408 PetscScalar *a, *diagA, *offdiagA; 2409 PetscInt r; 2410 PetscErrorCode ierr; 2411 2412 PetscFunctionBegin; 2413 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2414 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2415 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2416 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2417 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2418 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2419 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2420 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2421 for (r = 0; r < n; ++r) { 2422 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2423 a[r] = diagA[r]; 2424 idx[r] = cstart + diagIdx[r]; 2425 } else { 2426 a[r] = offdiagA[r]; 2427 idx[r] = cmap[offdiagIdx[r]]; 2428 } 2429 } 2430 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2431 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2432 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2433 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2434 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2435 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2436 PetscFunctionReturn(0); 2437 } 2438 2439 #undef __FUNCT__ 2440 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2441 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2442 { 2443 PetscErrorCode ierr; 2444 Mat *dummy; 2445 2446 PetscFunctionBegin; 2447 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2448 *newmat = *dummy; 2449 ierr = PetscFree(dummy);CHKERRQ(ierr); 2450 PetscFunctionReturn(0); 2451 } 2452 2453 #undef __FUNCT__ 2454 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2455 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2456 { 2457 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2458 PetscErrorCode ierr; 2459 2460 PetscFunctionBegin; 2461 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2462 PetscFunctionReturn(0); 2463 } 2464 2465 #undef __FUNCT__ 2466 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2467 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2468 { 2469 PetscErrorCode ierr; 2470 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2471 2472 PetscFunctionBegin; 2473 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2474 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2475 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2476 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2477 PetscFunctionReturn(0); 2478 } 2479 2480 #undef __FUNCT__ 2481 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ" 2482 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2483 { 2484 PetscFunctionBegin; 2485 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2486 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2487 PetscFunctionReturn(0); 2488 } 2489 2490 #undef __FUNCT__ 2491 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap" 2492 /*@ 2493 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2494 2495 Collective on Mat 2496 2497 Input Parameters: 2498 + A - the matrix 2499 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2500 2501 @*/ 2502 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2503 { 2504 PetscErrorCode ierr; 2505 2506 PetscFunctionBegin; 2507 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2508 PetscFunctionReturn(0); 2509 } 2510 2511 #undef __FUNCT__ 2512 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2513 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptions *PetscOptionsObject,Mat A) 2514 { 2515 PetscErrorCode ierr; 2516 PetscBool sc = PETSC_FALSE,flg; 2517 2518 PetscFunctionBegin; 2519 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2520 ierr = PetscObjectOptionsBegin((PetscObject)A); 2521 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2522 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2523 if (flg) { 2524 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2525 } 2526 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2527 PetscFunctionReturn(0); 2528 } 2529 2530 #undef __FUNCT__ 2531 #define __FUNCT__ "MatShift_MPIAIJ" 2532 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2533 { 2534 PetscErrorCode ierr; 2535 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2536 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2537 2538 PetscFunctionBegin; 2539 if (!Y->preallocated) { 2540 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2541 } else if (!aij->nz) { 2542 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2543 } 2544 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2545 PetscFunctionReturn(0); 2546 } 2547 2548 #undef __FUNCT__ 2549 #define __FUNCT__ "MatMissingDiagonal_MPIAIJ" 2550 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2551 { 2552 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2553 PetscErrorCode ierr; 2554 2555 PetscFunctionBegin; 2556 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2557 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2558 if (d) { 2559 PetscInt rstart; 2560 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2561 *d += rstart; 2562 2563 } 2564 PetscFunctionReturn(0); 2565 } 2566 2567 2568 /* -------------------------------------------------------------------*/ 2569 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2570 MatGetRow_MPIAIJ, 2571 MatRestoreRow_MPIAIJ, 2572 MatMult_MPIAIJ, 2573 /* 4*/ MatMultAdd_MPIAIJ, 2574 MatMultTranspose_MPIAIJ, 2575 MatMultTransposeAdd_MPIAIJ, 2576 0, 2577 0, 2578 0, 2579 /*10*/ 0, 2580 0, 2581 0, 2582 MatSOR_MPIAIJ, 2583 MatTranspose_MPIAIJ, 2584 /*15*/ MatGetInfo_MPIAIJ, 2585 MatEqual_MPIAIJ, 2586 MatGetDiagonal_MPIAIJ, 2587 MatDiagonalScale_MPIAIJ, 2588 MatNorm_MPIAIJ, 2589 /*20*/ MatAssemblyBegin_MPIAIJ, 2590 MatAssemblyEnd_MPIAIJ, 2591 MatSetOption_MPIAIJ, 2592 MatZeroEntries_MPIAIJ, 2593 /*24*/ MatZeroRows_MPIAIJ, 2594 0, 2595 0, 2596 0, 2597 0, 2598 /*29*/ MatSetUp_MPIAIJ, 2599 0, 2600 0, 2601 0, 2602 0, 2603 /*34*/ MatDuplicate_MPIAIJ, 2604 0, 2605 0, 2606 0, 2607 0, 2608 /*39*/ MatAXPY_MPIAIJ, 2609 MatGetSubMatrices_MPIAIJ, 2610 MatIncreaseOverlap_MPIAIJ, 2611 MatGetValues_MPIAIJ, 2612 MatCopy_MPIAIJ, 2613 /*44*/ MatGetRowMax_MPIAIJ, 2614 MatScale_MPIAIJ, 2615 MatShift_MPIAIJ, 2616 MatDiagonalSet_MPIAIJ, 2617 MatZeroRowsColumns_MPIAIJ, 2618 /*49*/ MatSetRandom_MPIAIJ, 2619 0, 2620 0, 2621 0, 2622 0, 2623 /*54*/ MatFDColoringCreate_MPIXAIJ, 2624 0, 2625 MatSetUnfactored_MPIAIJ, 2626 MatPermute_MPIAIJ, 2627 0, 2628 /*59*/ MatGetSubMatrix_MPIAIJ, 2629 MatDestroy_MPIAIJ, 2630 MatView_MPIAIJ, 2631 0, 2632 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2633 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2634 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2635 0, 2636 0, 2637 0, 2638 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2639 MatGetRowMinAbs_MPIAIJ, 2640 0, 2641 MatSetColoring_MPIAIJ, 2642 0, 2643 MatSetValuesAdifor_MPIAIJ, 2644 /*75*/ MatFDColoringApply_AIJ, 2645 MatSetFromOptions_MPIAIJ, 2646 0, 2647 0, 2648 MatFindZeroDiagonals_MPIAIJ, 2649 /*80*/ 0, 2650 0, 2651 0, 2652 /*83*/ MatLoad_MPIAIJ, 2653 0, 2654 0, 2655 0, 2656 0, 2657 0, 2658 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2659 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2660 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2661 MatPtAP_MPIAIJ_MPIAIJ, 2662 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2663 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2664 0, 2665 0, 2666 0, 2667 0, 2668 /*99*/ 0, 2669 0, 2670 0, 2671 MatConjugate_MPIAIJ, 2672 0, 2673 /*104*/MatSetValuesRow_MPIAIJ, 2674 MatRealPart_MPIAIJ, 2675 MatImaginaryPart_MPIAIJ, 2676 0, 2677 0, 2678 /*109*/0, 2679 0, 2680 MatGetRowMin_MPIAIJ, 2681 0, 2682 MatMissingDiagonal_MPIAIJ, 2683 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2684 0, 2685 MatGetGhosts_MPIAIJ, 2686 0, 2687 0, 2688 /*119*/0, 2689 0, 2690 0, 2691 0, 2692 MatGetMultiProcBlock_MPIAIJ, 2693 /*124*/MatFindNonzeroRows_MPIAIJ, 2694 MatGetColumnNorms_MPIAIJ, 2695 MatInvertBlockDiagonal_MPIAIJ, 2696 0, 2697 MatGetSubMatricesMPI_MPIAIJ, 2698 /*129*/0, 2699 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2700 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2701 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2702 0, 2703 /*134*/0, 2704 0, 2705 0, 2706 0, 2707 0, 2708 /*139*/0, 2709 0, 2710 0, 2711 MatFDColoringSetUp_MPIXAIJ, 2712 MatFindOffBlockDiagonalEntries_MPIAIJ, 2713 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2714 }; 2715 2716 /* ----------------------------------------------------------------------------------------*/ 2717 2718 #undef __FUNCT__ 2719 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2720 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2721 { 2722 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2723 PetscErrorCode ierr; 2724 2725 PetscFunctionBegin; 2726 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2727 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2728 PetscFunctionReturn(0); 2729 } 2730 2731 #undef __FUNCT__ 2732 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2733 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2734 { 2735 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2736 PetscErrorCode ierr; 2737 2738 PetscFunctionBegin; 2739 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2740 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2741 PetscFunctionReturn(0); 2742 } 2743 2744 #undef __FUNCT__ 2745 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2746 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2747 { 2748 Mat_MPIAIJ *b; 2749 PetscErrorCode ierr; 2750 2751 PetscFunctionBegin; 2752 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2753 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2754 b = (Mat_MPIAIJ*)B->data; 2755 2756 if (!B->preallocated) { 2757 /* Explicitly create 2 MATSEQAIJ matrices. */ 2758 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2759 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2760 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2761 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2762 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2763 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2764 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2765 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2766 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2767 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2768 } 2769 2770 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2771 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2772 B->preallocated = PETSC_TRUE; 2773 PetscFunctionReturn(0); 2774 } 2775 2776 #undef __FUNCT__ 2777 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2778 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2779 { 2780 Mat mat; 2781 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2782 PetscErrorCode ierr; 2783 2784 PetscFunctionBegin; 2785 *newmat = 0; 2786 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2787 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2788 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2789 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2790 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2791 a = (Mat_MPIAIJ*)mat->data; 2792 2793 mat->factortype = matin->factortype; 2794 mat->assembled = PETSC_TRUE; 2795 mat->insertmode = NOT_SET_VALUES; 2796 mat->preallocated = PETSC_TRUE; 2797 2798 a->size = oldmat->size; 2799 a->rank = oldmat->rank; 2800 a->donotstash = oldmat->donotstash; 2801 a->roworiented = oldmat->roworiented; 2802 a->rowindices = 0; 2803 a->rowvalues = 0; 2804 a->getrowactive = PETSC_FALSE; 2805 2806 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2807 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2808 2809 if (oldmat->colmap) { 2810 #if defined(PETSC_USE_CTABLE) 2811 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2812 #else 2813 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2814 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2815 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2816 #endif 2817 } else a->colmap = 0; 2818 if (oldmat->garray) { 2819 PetscInt len; 2820 len = oldmat->B->cmap->n; 2821 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2822 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2823 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2824 } else a->garray = 0; 2825 2826 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2827 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2828 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2829 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2830 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2831 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2832 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2833 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2834 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2835 *newmat = mat; 2836 PetscFunctionReturn(0); 2837 } 2838 2839 2840 2841 #undef __FUNCT__ 2842 #define __FUNCT__ "MatLoad_MPIAIJ" 2843 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2844 { 2845 PetscScalar *vals,*svals; 2846 MPI_Comm comm; 2847 PetscErrorCode ierr; 2848 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2849 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2850 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2851 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2852 PetscInt cend,cstart,n,*rowners; 2853 int fd; 2854 PetscInt bs = newMat->rmap->bs; 2855 2856 PetscFunctionBegin; 2857 /* force binary viewer to load .info file if it has not yet done so */ 2858 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2859 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2860 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2861 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2862 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2863 if (!rank) { 2864 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2865 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2866 } 2867 2868 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2869 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2870 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2871 if (bs < 0) bs = 1; 2872 2873 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2874 M = header[1]; N = header[2]; 2875 2876 /* If global sizes are set, check if they are consistent with that given in the file */ 2877 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); 2878 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); 2879 2880 /* determine ownership of all (block) rows */ 2881 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2882 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2883 else m = newMat->rmap->n; /* Set by user */ 2884 2885 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2886 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2887 2888 /* First process needs enough room for process with most rows */ 2889 if (!rank) { 2890 mmax = rowners[1]; 2891 for (i=2; i<=size; i++) { 2892 mmax = PetscMax(mmax, rowners[i]); 2893 } 2894 } else mmax = -1; /* unused, but compilers complain */ 2895 2896 rowners[0] = 0; 2897 for (i=2; i<=size; i++) { 2898 rowners[i] += rowners[i-1]; 2899 } 2900 rstart = rowners[rank]; 2901 rend = rowners[rank+1]; 2902 2903 /* distribute row lengths to all processors */ 2904 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2905 if (!rank) { 2906 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2907 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2908 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2909 for (j=0; j<m; j++) { 2910 procsnz[0] += ourlens[j]; 2911 } 2912 for (i=1; i<size; i++) { 2913 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2914 /* calculate the number of nonzeros on each processor */ 2915 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2916 procsnz[i] += rowlengths[j]; 2917 } 2918 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2919 } 2920 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2921 } else { 2922 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2923 } 2924 2925 if (!rank) { 2926 /* determine max buffer needed and allocate it */ 2927 maxnz = 0; 2928 for (i=0; i<size; i++) { 2929 maxnz = PetscMax(maxnz,procsnz[i]); 2930 } 2931 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2932 2933 /* read in my part of the matrix column indices */ 2934 nz = procsnz[0]; 2935 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2936 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2937 2938 /* read in every one elses and ship off */ 2939 for (i=1; i<size; i++) { 2940 nz = procsnz[i]; 2941 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2942 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2943 } 2944 ierr = PetscFree(cols);CHKERRQ(ierr); 2945 } else { 2946 /* determine buffer space needed for message */ 2947 nz = 0; 2948 for (i=0; i<m; i++) { 2949 nz += ourlens[i]; 2950 } 2951 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2952 2953 /* receive message of column indices*/ 2954 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2955 } 2956 2957 /* determine column ownership if matrix is not square */ 2958 if (N != M) { 2959 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2960 else n = newMat->cmap->n; 2961 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2962 cstart = cend - n; 2963 } else { 2964 cstart = rstart; 2965 cend = rend; 2966 n = cend - cstart; 2967 } 2968 2969 /* loop over local rows, determining number of off diagonal entries */ 2970 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2971 jj = 0; 2972 for (i=0; i<m; i++) { 2973 for (j=0; j<ourlens[i]; j++) { 2974 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2975 jj++; 2976 } 2977 } 2978 2979 for (i=0; i<m; i++) { 2980 ourlens[i] -= offlens[i]; 2981 } 2982 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2983 2984 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2985 2986 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2987 2988 for (i=0; i<m; i++) { 2989 ourlens[i] += offlens[i]; 2990 } 2991 2992 if (!rank) { 2993 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2994 2995 /* read in my part of the matrix numerical values */ 2996 nz = procsnz[0]; 2997 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2998 2999 /* insert into matrix */ 3000 jj = rstart; 3001 smycols = mycols; 3002 svals = vals; 3003 for (i=0; i<m; i++) { 3004 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3005 smycols += ourlens[i]; 3006 svals += ourlens[i]; 3007 jj++; 3008 } 3009 3010 /* read in other processors and ship out */ 3011 for (i=1; i<size; i++) { 3012 nz = procsnz[i]; 3013 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3014 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3015 } 3016 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3017 } else { 3018 /* receive numeric values */ 3019 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3020 3021 /* receive message of values*/ 3022 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3023 3024 /* insert into matrix */ 3025 jj = rstart; 3026 smycols = mycols; 3027 svals = vals; 3028 for (i=0; i<m; i++) { 3029 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3030 smycols += ourlens[i]; 3031 svals += ourlens[i]; 3032 jj++; 3033 } 3034 } 3035 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3036 ierr = PetscFree(vals);CHKERRQ(ierr); 3037 ierr = PetscFree(mycols);CHKERRQ(ierr); 3038 ierr = PetscFree(rowners);CHKERRQ(ierr); 3039 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3040 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3041 PetscFunctionReturn(0); 3042 } 3043 3044 #undef __FUNCT__ 3045 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3046 /* TODO: Not scalable because of ISAllGather() unless getting all columns. */ 3047 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3048 { 3049 PetscErrorCode ierr; 3050 IS iscol_local; 3051 PetscInt csize; 3052 3053 PetscFunctionBegin; 3054 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3055 if (call == MAT_REUSE_MATRIX) { 3056 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3057 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3058 } else { 3059 /* check if we are grabbing all columns*/ 3060 PetscBool isstride; 3061 PetscMPIInt lisstride = 0,gisstride; 3062 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 3063 if (isstride) { 3064 PetscInt start,len,mstart,mlen; 3065 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 3066 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 3067 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 3068 if (mstart == start && mlen-mstart == len) lisstride = 1; 3069 } 3070 ierr = MPI_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 3071 if (gisstride) { 3072 PetscInt N; 3073 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 3074 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 3075 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 3076 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 3077 } else { 3078 PetscInt cbs; 3079 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3080 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3081 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3082 } 3083 } 3084 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3085 if (call == MAT_INITIAL_MATRIX) { 3086 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3087 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3088 } 3089 PetscFunctionReturn(0); 3090 } 3091 3092 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3093 #undef __FUNCT__ 3094 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3095 /* 3096 Not great since it makes two copies of the submatrix, first an SeqAIJ 3097 in local and then by concatenating the local matrices the end result. 3098 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3099 3100 Note: This requires a sequential iscol with all indices. 3101 */ 3102 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3103 { 3104 PetscErrorCode ierr; 3105 PetscMPIInt rank,size; 3106 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3107 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3108 PetscBool allcolumns, colflag; 3109 Mat M,Mreuse; 3110 MatScalar *vwork,*aa; 3111 MPI_Comm comm; 3112 Mat_SeqAIJ *aij; 3113 3114 PetscFunctionBegin; 3115 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3116 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3117 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3118 3119 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3120 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3121 if (colflag && ncol == mat->cmap->N) { 3122 allcolumns = PETSC_TRUE; 3123 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix\n");CHKERRQ(ierr); 3124 } else { 3125 allcolumns = PETSC_FALSE; 3126 } 3127 if (call == MAT_REUSE_MATRIX) { 3128 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3129 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3130 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3131 } else { 3132 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3133 } 3134 3135 /* 3136 m - number of local rows 3137 n - number of columns (same on all processors) 3138 rstart - first row in new global matrix generated 3139 */ 3140 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3141 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3142 if (call == MAT_INITIAL_MATRIX) { 3143 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3144 ii = aij->i; 3145 jj = aij->j; 3146 3147 /* 3148 Determine the number of non-zeros in the diagonal and off-diagonal 3149 portions of the matrix in order to do correct preallocation 3150 */ 3151 3152 /* first get start and end of "diagonal" columns */ 3153 if (csize == PETSC_DECIDE) { 3154 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3155 if (mglobal == n) { /* square matrix */ 3156 nlocal = m; 3157 } else { 3158 nlocal = n/size + ((n % size) > rank); 3159 } 3160 } else { 3161 nlocal = csize; 3162 } 3163 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3164 rstart = rend - nlocal; 3165 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); 3166 3167 /* next, compute all the lengths */ 3168 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3169 olens = dlens + m; 3170 for (i=0; i<m; i++) { 3171 jend = ii[i+1] - ii[i]; 3172 olen = 0; 3173 dlen = 0; 3174 for (j=0; j<jend; j++) { 3175 if (*jj < rstart || *jj >= rend) olen++; 3176 else dlen++; 3177 jj++; 3178 } 3179 olens[i] = olen; 3180 dlens[i] = dlen; 3181 } 3182 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3183 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3184 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3185 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3186 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3187 ierr = PetscFree(dlens);CHKERRQ(ierr); 3188 } else { 3189 PetscInt ml,nl; 3190 3191 M = *newmat; 3192 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3193 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3194 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3195 /* 3196 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3197 rather than the slower MatSetValues(). 3198 */ 3199 M->was_assembled = PETSC_TRUE; 3200 M->assembled = PETSC_FALSE; 3201 } 3202 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3203 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3204 ii = aij->i; 3205 jj = aij->j; 3206 aa = aij->a; 3207 for (i=0; i<m; i++) { 3208 row = rstart + i; 3209 nz = ii[i+1] - ii[i]; 3210 cwork = jj; jj += nz; 3211 vwork = aa; aa += nz; 3212 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3213 } 3214 3215 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3216 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3217 *newmat = M; 3218 3219 /* save submatrix used in processor for next request */ 3220 if (call == MAT_INITIAL_MATRIX) { 3221 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3222 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3223 } 3224 PetscFunctionReturn(0); 3225 } 3226 3227 #undef __FUNCT__ 3228 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3229 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3230 { 3231 PetscInt m,cstart, cend,j,nnz,i,d; 3232 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3233 const PetscInt *JJ; 3234 PetscScalar *values; 3235 PetscErrorCode ierr; 3236 3237 PetscFunctionBegin; 3238 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3239 3240 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3241 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3242 m = B->rmap->n; 3243 cstart = B->cmap->rstart; 3244 cend = B->cmap->rend; 3245 rstart = B->rmap->rstart; 3246 3247 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3248 3249 #if defined(PETSC_USE_DEBUGGING) 3250 for (i=0; i<m; i++) { 3251 nnz = Ii[i+1]- Ii[i]; 3252 JJ = J + Ii[i]; 3253 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3254 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3255 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); 3256 } 3257 #endif 3258 3259 for (i=0; i<m; i++) { 3260 nnz = Ii[i+1]- Ii[i]; 3261 JJ = J + Ii[i]; 3262 nnz_max = PetscMax(nnz_max,nnz); 3263 d = 0; 3264 for (j=0; j<nnz; j++) { 3265 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3266 } 3267 d_nnz[i] = d; 3268 o_nnz[i] = nnz - d; 3269 } 3270 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3271 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3272 3273 if (v) values = (PetscScalar*)v; 3274 else { 3275 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3276 } 3277 3278 for (i=0; i<m; i++) { 3279 ii = i + rstart; 3280 nnz = Ii[i+1]- Ii[i]; 3281 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3282 } 3283 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3284 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3285 3286 if (!v) { 3287 ierr = PetscFree(values);CHKERRQ(ierr); 3288 } 3289 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3290 PetscFunctionReturn(0); 3291 } 3292 3293 #undef __FUNCT__ 3294 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3295 /*@ 3296 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3297 (the default parallel PETSc format). 3298 3299 Collective on MPI_Comm 3300 3301 Input Parameters: 3302 + B - the matrix 3303 . i - the indices into j for the start of each local row (starts with zero) 3304 . j - the column indices for each local row (starts with zero) 3305 - v - optional values in the matrix 3306 3307 Level: developer 3308 3309 Notes: 3310 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3311 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3312 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3313 3314 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3315 3316 The format which is used for the sparse matrix input, is equivalent to a 3317 row-major ordering.. i.e for the following matrix, the input data expected is 3318 as shown 3319 3320 $ 1 0 0 3321 $ 2 0 3 P0 3322 $ ------- 3323 $ 4 5 6 P1 3324 $ 3325 $ Process0 [P0]: rows_owned=[0,1] 3326 $ i = {0,1,3} [size = nrow+1 = 2+1] 3327 $ j = {0,0,2} [size = 3] 3328 $ v = {1,2,3} [size = 3] 3329 $ 3330 $ Process1 [P1]: rows_owned=[2] 3331 $ i = {0,3} [size = nrow+1 = 1+1] 3332 $ j = {0,1,2} [size = 3] 3333 $ v = {4,5,6} [size = 3] 3334 3335 .keywords: matrix, aij, compressed row, sparse, parallel 3336 3337 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3338 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3339 @*/ 3340 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3341 { 3342 PetscErrorCode ierr; 3343 3344 PetscFunctionBegin; 3345 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3346 PetscFunctionReturn(0); 3347 } 3348 3349 #undef __FUNCT__ 3350 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3351 /*@C 3352 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3353 (the default parallel PETSc format). For good matrix assembly performance 3354 the user should preallocate the matrix storage by setting the parameters 3355 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3356 performance can be increased by more than a factor of 50. 3357 3358 Collective on MPI_Comm 3359 3360 Input Parameters: 3361 + B - the matrix 3362 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3363 (same value is used for all local rows) 3364 . d_nnz - array containing the number of nonzeros in the various rows of the 3365 DIAGONAL portion of the local submatrix (possibly different for each row) 3366 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3367 The size of this array is equal to the number of local rows, i.e 'm'. 3368 For matrices that will be factored, you must leave room for (and set) 3369 the diagonal entry even if it is zero. 3370 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3371 submatrix (same value is used for all local rows). 3372 - o_nnz - array containing the number of nonzeros in the various rows of the 3373 OFF-DIAGONAL portion of the local submatrix (possibly different for 3374 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3375 structure. The size of this array is equal to the number 3376 of local rows, i.e 'm'. 3377 3378 If the *_nnz parameter is given then the *_nz parameter is ignored 3379 3380 The AIJ format (also called the Yale sparse matrix format or 3381 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3382 storage. The stored row and column indices begin with zero. 3383 See Users-Manual: ch_mat for details. 3384 3385 The parallel matrix is partitioned such that the first m0 rows belong to 3386 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3387 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3388 3389 The DIAGONAL portion of the local submatrix of a processor can be defined 3390 as the submatrix which is obtained by extraction the part corresponding to 3391 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3392 first row that belongs to the processor, r2 is the last row belonging to 3393 the this processor, and c1-c2 is range of indices of the local part of a 3394 vector suitable for applying the matrix to. This is an mxn matrix. In the 3395 common case of a square matrix, the row and column ranges are the same and 3396 the DIAGONAL part is also square. The remaining portion of the local 3397 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3398 3399 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3400 3401 You can call MatGetInfo() to get information on how effective the preallocation was; 3402 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3403 You can also run with the option -info and look for messages with the string 3404 malloc in them to see if additional memory allocation was needed. 3405 3406 Example usage: 3407 3408 Consider the following 8x8 matrix with 34 non-zero values, that is 3409 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3410 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3411 as follows: 3412 3413 .vb 3414 1 2 0 | 0 3 0 | 0 4 3415 Proc0 0 5 6 | 7 0 0 | 8 0 3416 9 0 10 | 11 0 0 | 12 0 3417 ------------------------------------- 3418 13 0 14 | 15 16 17 | 0 0 3419 Proc1 0 18 0 | 19 20 21 | 0 0 3420 0 0 0 | 22 23 0 | 24 0 3421 ------------------------------------- 3422 Proc2 25 26 27 | 0 0 28 | 29 0 3423 30 0 0 | 31 32 33 | 0 34 3424 .ve 3425 3426 This can be represented as a collection of submatrices as: 3427 3428 .vb 3429 A B C 3430 D E F 3431 G H I 3432 .ve 3433 3434 Where the submatrices A,B,C are owned by proc0, D,E,F are 3435 owned by proc1, G,H,I are owned by proc2. 3436 3437 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3438 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3439 The 'M','N' parameters are 8,8, and have the same values on all procs. 3440 3441 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3442 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3443 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3444 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3445 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3446 matrix, ans [DF] as another SeqAIJ matrix. 3447 3448 When d_nz, o_nz parameters are specified, d_nz storage elements are 3449 allocated for every row of the local diagonal submatrix, and o_nz 3450 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3451 One way to choose d_nz and o_nz is to use the max nonzerors per local 3452 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3453 In this case, the values of d_nz,o_nz are: 3454 .vb 3455 proc0 : dnz = 2, o_nz = 2 3456 proc1 : dnz = 3, o_nz = 2 3457 proc2 : dnz = 1, o_nz = 4 3458 .ve 3459 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3460 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3461 for proc3. i.e we are using 12+15+10=37 storage locations to store 3462 34 values. 3463 3464 When d_nnz, o_nnz parameters are specified, the storage is specified 3465 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3466 In the above case the values for d_nnz,o_nnz are: 3467 .vb 3468 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3469 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3470 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3471 .ve 3472 Here the space allocated is sum of all the above values i.e 34, and 3473 hence pre-allocation is perfect. 3474 3475 Level: intermediate 3476 3477 .keywords: matrix, aij, compressed row, sparse, parallel 3478 3479 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3480 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3481 @*/ 3482 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3483 { 3484 PetscErrorCode ierr; 3485 3486 PetscFunctionBegin; 3487 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3488 PetscValidType(B,1); 3489 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3490 PetscFunctionReturn(0); 3491 } 3492 3493 #undef __FUNCT__ 3494 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3495 /*@ 3496 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3497 CSR format the local rows. 3498 3499 Collective on MPI_Comm 3500 3501 Input Parameters: 3502 + comm - MPI communicator 3503 . m - number of local rows (Cannot be PETSC_DECIDE) 3504 . n - This value should be the same as the local size used in creating the 3505 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3506 calculated if N is given) For square matrices n is almost always m. 3507 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3508 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3509 . i - row indices 3510 . j - column indices 3511 - a - matrix values 3512 3513 Output Parameter: 3514 . mat - the matrix 3515 3516 Level: intermediate 3517 3518 Notes: 3519 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3520 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3521 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3522 3523 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3524 3525 The format which is used for the sparse matrix input, is equivalent to a 3526 row-major ordering.. i.e for the following matrix, the input data expected is 3527 as shown 3528 3529 $ 1 0 0 3530 $ 2 0 3 P0 3531 $ ------- 3532 $ 4 5 6 P1 3533 $ 3534 $ Process0 [P0]: rows_owned=[0,1] 3535 $ i = {0,1,3} [size = nrow+1 = 2+1] 3536 $ j = {0,0,2} [size = 3] 3537 $ v = {1,2,3} [size = 3] 3538 $ 3539 $ Process1 [P1]: rows_owned=[2] 3540 $ i = {0,3} [size = nrow+1 = 1+1] 3541 $ j = {0,1,2} [size = 3] 3542 $ v = {4,5,6} [size = 3] 3543 3544 .keywords: matrix, aij, compressed row, sparse, parallel 3545 3546 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3547 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3548 @*/ 3549 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3550 { 3551 PetscErrorCode ierr; 3552 3553 PetscFunctionBegin; 3554 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3555 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3556 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3557 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3558 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3559 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3560 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3561 PetscFunctionReturn(0); 3562 } 3563 3564 #undef __FUNCT__ 3565 #define __FUNCT__ "MatCreateAIJ" 3566 /*@C 3567 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3568 (the default parallel PETSc format). For good matrix assembly performance 3569 the user should preallocate the matrix storage by setting the parameters 3570 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3571 performance can be increased by more than a factor of 50. 3572 3573 Collective on MPI_Comm 3574 3575 Input Parameters: 3576 + comm - MPI communicator 3577 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3578 This value should be the same as the local size used in creating the 3579 y vector for the matrix-vector product y = Ax. 3580 . n - This value should be the same as the local size used in creating the 3581 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3582 calculated if N is given) For square matrices n is almost always m. 3583 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3584 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3585 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3586 (same value is used for all local rows) 3587 . d_nnz - array containing the number of nonzeros in the various rows of the 3588 DIAGONAL portion of the local submatrix (possibly different for each row) 3589 or NULL, if d_nz is used to specify the nonzero structure. 3590 The size of this array is equal to the number of local rows, i.e 'm'. 3591 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3592 submatrix (same value is used for all local rows). 3593 - o_nnz - array containing the number of nonzeros in the various rows of the 3594 OFF-DIAGONAL portion of the local submatrix (possibly different for 3595 each row) or NULL, if o_nz is used to specify the nonzero 3596 structure. The size of this array is equal to the number 3597 of local rows, i.e 'm'. 3598 3599 Output Parameter: 3600 . A - the matrix 3601 3602 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3603 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3604 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3605 3606 Notes: 3607 If the *_nnz parameter is given then the *_nz parameter is ignored 3608 3609 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3610 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3611 storage requirements for this matrix. 3612 3613 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3614 processor than it must be used on all processors that share the object for 3615 that argument. 3616 3617 The user MUST specify either the local or global matrix dimensions 3618 (possibly both). 3619 3620 The parallel matrix is partitioned across processors such that the 3621 first m0 rows belong to process 0, the next m1 rows belong to 3622 process 1, the next m2 rows belong to process 2 etc.. where 3623 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3624 values corresponding to [m x N] submatrix. 3625 3626 The columns are logically partitioned with the n0 columns belonging 3627 to 0th partition, the next n1 columns belonging to the next 3628 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3629 3630 The DIAGONAL portion of the local submatrix on any given processor 3631 is the submatrix corresponding to the rows and columns m,n 3632 corresponding to the given processor. i.e diagonal matrix on 3633 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3634 etc. The remaining portion of the local submatrix [m x (N-n)] 3635 constitute the OFF-DIAGONAL portion. The example below better 3636 illustrates this concept. 3637 3638 For a square global matrix we define each processor's diagonal portion 3639 to be its local rows and the corresponding columns (a square submatrix); 3640 each processor's off-diagonal portion encompasses the remainder of the 3641 local matrix (a rectangular submatrix). 3642 3643 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3644 3645 When calling this routine with a single process communicator, a matrix of 3646 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3647 type of communicator, use the construction mechanism: 3648 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3649 3650 By default, this format uses inodes (identical nodes) when possible. 3651 We search for consecutive rows with the same nonzero structure, thereby 3652 reusing matrix information to achieve increased efficiency. 3653 3654 Options Database Keys: 3655 + -mat_no_inode - Do not use inodes 3656 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3657 - -mat_aij_oneindex - Internally use indexing starting at 1 3658 rather than 0. Note that when calling MatSetValues(), 3659 the user still MUST index entries starting at 0! 3660 3661 3662 Example usage: 3663 3664 Consider the following 8x8 matrix with 34 non-zero values, that is 3665 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3666 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3667 as follows: 3668 3669 .vb 3670 1 2 0 | 0 3 0 | 0 4 3671 Proc0 0 5 6 | 7 0 0 | 8 0 3672 9 0 10 | 11 0 0 | 12 0 3673 ------------------------------------- 3674 13 0 14 | 15 16 17 | 0 0 3675 Proc1 0 18 0 | 19 20 21 | 0 0 3676 0 0 0 | 22 23 0 | 24 0 3677 ------------------------------------- 3678 Proc2 25 26 27 | 0 0 28 | 29 0 3679 30 0 0 | 31 32 33 | 0 34 3680 .ve 3681 3682 This can be represented as a collection of submatrices as: 3683 3684 .vb 3685 A B C 3686 D E F 3687 G H I 3688 .ve 3689 3690 Where the submatrices A,B,C are owned by proc0, D,E,F are 3691 owned by proc1, G,H,I are owned by proc2. 3692 3693 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3694 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3695 The 'M','N' parameters are 8,8, and have the same values on all procs. 3696 3697 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3698 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3699 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3700 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3701 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3702 matrix, ans [DF] as another SeqAIJ matrix. 3703 3704 When d_nz, o_nz parameters are specified, d_nz storage elements are 3705 allocated for every row of the local diagonal submatrix, and o_nz 3706 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3707 One way to choose d_nz and o_nz is to use the max nonzerors per local 3708 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3709 In this case, the values of d_nz,o_nz are: 3710 .vb 3711 proc0 : dnz = 2, o_nz = 2 3712 proc1 : dnz = 3, o_nz = 2 3713 proc2 : dnz = 1, o_nz = 4 3714 .ve 3715 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3716 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3717 for proc3. i.e we are using 12+15+10=37 storage locations to store 3718 34 values. 3719 3720 When d_nnz, o_nnz parameters are specified, the storage is specified 3721 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3722 In the above case the values for d_nnz,o_nnz are: 3723 .vb 3724 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3725 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3726 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3727 .ve 3728 Here the space allocated is sum of all the above values i.e 34, and 3729 hence pre-allocation is perfect. 3730 3731 Level: intermediate 3732 3733 .keywords: matrix, aij, compressed row, sparse, parallel 3734 3735 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3736 MPIAIJ, MatCreateMPIAIJWithArrays() 3737 @*/ 3738 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) 3739 { 3740 PetscErrorCode ierr; 3741 PetscMPIInt size; 3742 3743 PetscFunctionBegin; 3744 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3745 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3746 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3747 if (size > 1) { 3748 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3749 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3750 } else { 3751 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3752 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3753 } 3754 PetscFunctionReturn(0); 3755 } 3756 3757 #undef __FUNCT__ 3758 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3759 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3760 { 3761 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3762 3763 PetscFunctionBegin; 3764 if (Ad) *Ad = a->A; 3765 if (Ao) *Ao = a->B; 3766 if (colmap) *colmap = a->garray; 3767 PetscFunctionReturn(0); 3768 } 3769 3770 #undef __FUNCT__ 3771 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3772 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3773 { 3774 PetscErrorCode ierr; 3775 PetscInt i; 3776 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3777 3778 PetscFunctionBegin; 3779 if (coloring->ctype == IS_COLORING_GLOBAL) { 3780 ISColoringValue *allcolors,*colors; 3781 ISColoring ocoloring; 3782 3783 /* set coloring for diagonal portion */ 3784 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3785 3786 /* set coloring for off-diagonal portion */ 3787 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3788 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3789 for (i=0; i<a->B->cmap->n; i++) { 3790 colors[i] = allcolors[a->garray[i]]; 3791 } 3792 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3793 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3794 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3795 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3796 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3797 ISColoringValue *colors; 3798 PetscInt *larray; 3799 ISColoring ocoloring; 3800 3801 /* set coloring for diagonal portion */ 3802 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3803 for (i=0; i<a->A->cmap->n; i++) { 3804 larray[i] = i + A->cmap->rstart; 3805 } 3806 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3807 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3808 for (i=0; i<a->A->cmap->n; i++) { 3809 colors[i] = coloring->colors[larray[i]]; 3810 } 3811 ierr = PetscFree(larray);CHKERRQ(ierr); 3812 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3813 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3814 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3815 3816 /* set coloring for off-diagonal portion */ 3817 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3818 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3819 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3820 for (i=0; i<a->B->cmap->n; i++) { 3821 colors[i] = coloring->colors[larray[i]]; 3822 } 3823 ierr = PetscFree(larray);CHKERRQ(ierr); 3824 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3825 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3826 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3827 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3828 PetscFunctionReturn(0); 3829 } 3830 3831 #undef __FUNCT__ 3832 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3833 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3834 { 3835 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3836 PetscErrorCode ierr; 3837 3838 PetscFunctionBegin; 3839 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3840 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3841 PetscFunctionReturn(0); 3842 } 3843 3844 #undef __FUNCT__ 3845 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3846 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3847 { 3848 PetscErrorCode ierr; 3849 PetscInt m,N,i,rstart,nnz,Ii; 3850 PetscInt *indx; 3851 PetscScalar *values; 3852 3853 PetscFunctionBegin; 3854 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3855 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3856 PetscInt *dnz,*onz,sum,bs,cbs; 3857 3858 if (n == PETSC_DECIDE) { 3859 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3860 } 3861 /* Check sum(n) = N */ 3862 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3863 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3864 3865 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3866 rstart -= m; 3867 3868 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3869 for (i=0; i<m; i++) { 3870 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3871 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3872 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3873 } 3874 3875 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3876 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3877 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3878 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3879 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3880 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3881 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3882 } 3883 3884 /* numeric phase */ 3885 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3886 for (i=0; i<m; i++) { 3887 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3888 Ii = i + rstart; 3889 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3890 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3891 } 3892 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3893 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3894 PetscFunctionReturn(0); 3895 } 3896 3897 #undef __FUNCT__ 3898 #define __FUNCT__ "MatFileSplit" 3899 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3900 { 3901 PetscErrorCode ierr; 3902 PetscMPIInt rank; 3903 PetscInt m,N,i,rstart,nnz; 3904 size_t len; 3905 const PetscInt *indx; 3906 PetscViewer out; 3907 char *name; 3908 Mat B; 3909 const PetscScalar *values; 3910 3911 PetscFunctionBegin; 3912 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3913 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3914 /* Should this be the type of the diagonal block of A? */ 3915 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3916 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3917 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3918 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3919 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3920 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3921 for (i=0; i<m; i++) { 3922 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3923 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3924 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3925 } 3926 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3927 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3928 3929 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3930 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3931 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3932 sprintf(name,"%s.%d",outfile,rank); 3933 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3934 ierr = PetscFree(name);CHKERRQ(ierr); 3935 ierr = MatView(B,out);CHKERRQ(ierr); 3936 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3937 ierr = MatDestroy(&B);CHKERRQ(ierr); 3938 PetscFunctionReturn(0); 3939 } 3940 3941 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3942 #undef __FUNCT__ 3943 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3944 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3945 { 3946 PetscErrorCode ierr; 3947 Mat_Merge_SeqsToMPI *merge; 3948 PetscContainer container; 3949 3950 PetscFunctionBegin; 3951 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3952 if (container) { 3953 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3954 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3955 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3956 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3957 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3958 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3959 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3960 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3961 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3962 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3963 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3964 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3965 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3966 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3967 ierr = PetscFree(merge);CHKERRQ(ierr); 3968 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3969 } 3970 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3971 PetscFunctionReturn(0); 3972 } 3973 3974 #include <../src/mat/utils/freespace.h> 3975 #include <petscbt.h> 3976 3977 #undef __FUNCT__ 3978 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 3979 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 3980 { 3981 PetscErrorCode ierr; 3982 MPI_Comm comm; 3983 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 3984 PetscMPIInt size,rank,taga,*len_s; 3985 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 3986 PetscInt proc,m; 3987 PetscInt **buf_ri,**buf_rj; 3988 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3989 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3990 MPI_Request *s_waits,*r_waits; 3991 MPI_Status *status; 3992 MatScalar *aa=a->a; 3993 MatScalar **abuf_r,*ba_i; 3994 Mat_Merge_SeqsToMPI *merge; 3995 PetscContainer container; 3996 3997 PetscFunctionBegin; 3998 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 3999 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4000 4001 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4002 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4003 4004 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4005 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4006 4007 bi = merge->bi; 4008 bj = merge->bj; 4009 buf_ri = merge->buf_ri; 4010 buf_rj = merge->buf_rj; 4011 4012 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4013 owners = merge->rowmap->range; 4014 len_s = merge->len_s; 4015 4016 /* send and recv matrix values */ 4017 /*-----------------------------*/ 4018 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4019 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4020 4021 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4022 for (proc=0,k=0; proc<size; proc++) { 4023 if (!len_s[proc]) continue; 4024 i = owners[proc]; 4025 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4026 k++; 4027 } 4028 4029 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4030 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4031 ierr = PetscFree(status);CHKERRQ(ierr); 4032 4033 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4034 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4035 4036 /* insert mat values of mpimat */ 4037 /*----------------------------*/ 4038 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4039 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4040 4041 for (k=0; k<merge->nrecv; k++) { 4042 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4043 nrows = *(buf_ri_k[k]); 4044 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4045 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4046 } 4047 4048 /* set values of ba */ 4049 m = merge->rowmap->n; 4050 for (i=0; i<m; i++) { 4051 arow = owners[rank] + i; 4052 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4053 bnzi = bi[i+1] - bi[i]; 4054 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4055 4056 /* add local non-zero vals of this proc's seqmat into ba */ 4057 anzi = ai[arow+1] - ai[arow]; 4058 aj = a->j + ai[arow]; 4059 aa = a->a + ai[arow]; 4060 nextaj = 0; 4061 for (j=0; nextaj<anzi; j++) { 4062 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4063 ba_i[j] += aa[nextaj++]; 4064 } 4065 } 4066 4067 /* add received vals into ba */ 4068 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4069 /* i-th row */ 4070 if (i == *nextrow[k]) { 4071 anzi = *(nextai[k]+1) - *nextai[k]; 4072 aj = buf_rj[k] + *(nextai[k]); 4073 aa = abuf_r[k] + *(nextai[k]); 4074 nextaj = 0; 4075 for (j=0; nextaj<anzi; j++) { 4076 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4077 ba_i[j] += aa[nextaj++]; 4078 } 4079 } 4080 nextrow[k]++; nextai[k]++; 4081 } 4082 } 4083 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4084 } 4085 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4086 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4087 4088 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4089 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4090 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4091 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4092 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4093 PetscFunctionReturn(0); 4094 } 4095 4096 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4097 4098 #undef __FUNCT__ 4099 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4100 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4101 { 4102 PetscErrorCode ierr; 4103 Mat B_mpi; 4104 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4105 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4106 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4107 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4108 PetscInt len,proc,*dnz,*onz,bs,cbs; 4109 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4110 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4111 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4112 MPI_Status *status; 4113 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4114 PetscBT lnkbt; 4115 Mat_Merge_SeqsToMPI *merge; 4116 PetscContainer container; 4117 4118 PetscFunctionBegin; 4119 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4120 4121 /* make sure it is a PETSc comm */ 4122 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4123 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4124 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4125 4126 ierr = PetscNew(&merge);CHKERRQ(ierr); 4127 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4128 4129 /* determine row ownership */ 4130 /*---------------------------------------------------------*/ 4131 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4132 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4133 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4134 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4135 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4136 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4137 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4138 4139 m = merge->rowmap->n; 4140 owners = merge->rowmap->range; 4141 4142 /* determine the number of messages to send, their lengths */ 4143 /*---------------------------------------------------------*/ 4144 len_s = merge->len_s; 4145 4146 len = 0; /* length of buf_si[] */ 4147 merge->nsend = 0; 4148 for (proc=0; proc<size; proc++) { 4149 len_si[proc] = 0; 4150 if (proc == rank) { 4151 len_s[proc] = 0; 4152 } else { 4153 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4154 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4155 } 4156 if (len_s[proc]) { 4157 merge->nsend++; 4158 nrows = 0; 4159 for (i=owners[proc]; i<owners[proc+1]; i++) { 4160 if (ai[i+1] > ai[i]) nrows++; 4161 } 4162 len_si[proc] = 2*(nrows+1); 4163 len += len_si[proc]; 4164 } 4165 } 4166 4167 /* determine the number and length of messages to receive for ij-structure */ 4168 /*-------------------------------------------------------------------------*/ 4169 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4170 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4171 4172 /* post the Irecv of j-structure */ 4173 /*-------------------------------*/ 4174 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4175 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4176 4177 /* post the Isend of j-structure */ 4178 /*--------------------------------*/ 4179 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4180 4181 for (proc=0, k=0; proc<size; proc++) { 4182 if (!len_s[proc]) continue; 4183 i = owners[proc]; 4184 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4185 k++; 4186 } 4187 4188 /* receives and sends of j-structure are complete */ 4189 /*------------------------------------------------*/ 4190 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4191 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4192 4193 /* send and recv i-structure */ 4194 /*---------------------------*/ 4195 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4196 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4197 4198 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4199 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4200 for (proc=0,k=0; proc<size; proc++) { 4201 if (!len_s[proc]) continue; 4202 /* form outgoing message for i-structure: 4203 buf_si[0]: nrows to be sent 4204 [1:nrows]: row index (global) 4205 [nrows+1:2*nrows+1]: i-structure index 4206 */ 4207 /*-------------------------------------------*/ 4208 nrows = len_si[proc]/2 - 1; 4209 buf_si_i = buf_si + nrows+1; 4210 buf_si[0] = nrows; 4211 buf_si_i[0] = 0; 4212 nrows = 0; 4213 for (i=owners[proc]; i<owners[proc+1]; i++) { 4214 anzi = ai[i+1] - ai[i]; 4215 if (anzi) { 4216 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4217 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4218 nrows++; 4219 } 4220 } 4221 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4222 k++; 4223 buf_si += len_si[proc]; 4224 } 4225 4226 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4227 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4228 4229 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4230 for (i=0; i<merge->nrecv; i++) { 4231 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); 4232 } 4233 4234 ierr = PetscFree(len_si);CHKERRQ(ierr); 4235 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4236 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4237 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4238 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4239 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4240 ierr = PetscFree(status);CHKERRQ(ierr); 4241 4242 /* compute a local seq matrix in each processor */ 4243 /*----------------------------------------------*/ 4244 /* allocate bi array and free space for accumulating nonzero column info */ 4245 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4246 bi[0] = 0; 4247 4248 /* create and initialize a linked list */ 4249 nlnk = N+1; 4250 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4251 4252 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4253 len = ai[owners[rank+1]] - ai[owners[rank]]; 4254 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4255 4256 current_space = free_space; 4257 4258 /* determine symbolic info for each local row */ 4259 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4260 4261 for (k=0; k<merge->nrecv; k++) { 4262 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4263 nrows = *buf_ri_k[k]; 4264 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4265 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4266 } 4267 4268 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4269 len = 0; 4270 for (i=0; i<m; i++) { 4271 bnzi = 0; 4272 /* add local non-zero cols of this proc's seqmat into lnk */ 4273 arow = owners[rank] + i; 4274 anzi = ai[arow+1] - ai[arow]; 4275 aj = a->j + ai[arow]; 4276 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4277 bnzi += nlnk; 4278 /* add received col data into lnk */ 4279 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4280 if (i == *nextrow[k]) { /* i-th row */ 4281 anzi = *(nextai[k]+1) - *nextai[k]; 4282 aj = buf_rj[k] + *nextai[k]; 4283 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4284 bnzi += nlnk; 4285 nextrow[k]++; nextai[k]++; 4286 } 4287 } 4288 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4289 4290 /* if free space is not available, make more free space */ 4291 if (current_space->local_remaining<bnzi) { 4292 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4293 nspacedouble++; 4294 } 4295 /* copy data into free space, then initialize lnk */ 4296 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4297 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4298 4299 current_space->array += bnzi; 4300 current_space->local_used += bnzi; 4301 current_space->local_remaining -= bnzi; 4302 4303 bi[i+1] = bi[i] + bnzi; 4304 } 4305 4306 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4307 4308 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4309 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4310 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4311 4312 /* create symbolic parallel matrix B_mpi */ 4313 /*---------------------------------------*/ 4314 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4315 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4316 if (n==PETSC_DECIDE) { 4317 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4318 } else { 4319 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4320 } 4321 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4322 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4323 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4324 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4325 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4326 4327 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4328 B_mpi->assembled = PETSC_FALSE; 4329 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4330 merge->bi = bi; 4331 merge->bj = bj; 4332 merge->buf_ri = buf_ri; 4333 merge->buf_rj = buf_rj; 4334 merge->coi = NULL; 4335 merge->coj = NULL; 4336 merge->owners_co = NULL; 4337 4338 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4339 4340 /* attach the supporting struct to B_mpi for reuse */ 4341 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4342 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4343 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4344 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4345 *mpimat = B_mpi; 4346 4347 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4348 PetscFunctionReturn(0); 4349 } 4350 4351 #undef __FUNCT__ 4352 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4353 /*@C 4354 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4355 matrices from each processor 4356 4357 Collective on MPI_Comm 4358 4359 Input Parameters: 4360 + comm - the communicators the parallel matrix will live on 4361 . seqmat - the input sequential matrices 4362 . m - number of local rows (or PETSC_DECIDE) 4363 . n - number of local columns (or PETSC_DECIDE) 4364 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4365 4366 Output Parameter: 4367 . mpimat - the parallel matrix generated 4368 4369 Level: advanced 4370 4371 Notes: 4372 The dimensions of the sequential matrix in each processor MUST be the same. 4373 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4374 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4375 @*/ 4376 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4377 { 4378 PetscErrorCode ierr; 4379 PetscMPIInt size; 4380 4381 PetscFunctionBegin; 4382 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4383 if (size == 1) { 4384 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4385 if (scall == MAT_INITIAL_MATRIX) { 4386 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4387 } else { 4388 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4389 } 4390 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4391 PetscFunctionReturn(0); 4392 } 4393 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4394 if (scall == MAT_INITIAL_MATRIX) { 4395 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4396 } 4397 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4398 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4399 PetscFunctionReturn(0); 4400 } 4401 4402 #undef __FUNCT__ 4403 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4404 /*@ 4405 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4406 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4407 with MatGetSize() 4408 4409 Not Collective 4410 4411 Input Parameters: 4412 + A - the matrix 4413 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4414 4415 Output Parameter: 4416 . A_loc - the local sequential matrix generated 4417 4418 Level: developer 4419 4420 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4421 4422 @*/ 4423 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4424 { 4425 PetscErrorCode ierr; 4426 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4427 Mat_SeqAIJ *mat,*a,*b; 4428 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4429 MatScalar *aa,*ba,*cam; 4430 PetscScalar *ca; 4431 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4432 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4433 PetscBool match; 4434 MPI_Comm comm; 4435 PetscMPIInt size; 4436 4437 PetscFunctionBegin; 4438 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4439 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4440 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4441 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4442 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4443 4444 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4445 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4446 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4447 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4448 aa = a->a; ba = b->a; 4449 if (scall == MAT_INITIAL_MATRIX) { 4450 if (size == 1) { 4451 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4452 PetscFunctionReturn(0); 4453 } 4454 4455 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4456 ci[0] = 0; 4457 for (i=0; i<am; i++) { 4458 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4459 } 4460 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4461 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4462 k = 0; 4463 for (i=0; i<am; i++) { 4464 ncols_o = bi[i+1] - bi[i]; 4465 ncols_d = ai[i+1] - ai[i]; 4466 /* off-diagonal portion of A */ 4467 for (jo=0; jo<ncols_o; jo++) { 4468 col = cmap[*bj]; 4469 if (col >= cstart) break; 4470 cj[k] = col; bj++; 4471 ca[k++] = *ba++; 4472 } 4473 /* diagonal portion of A */ 4474 for (j=0; j<ncols_d; j++) { 4475 cj[k] = cstart + *aj++; 4476 ca[k++] = *aa++; 4477 } 4478 /* off-diagonal portion of A */ 4479 for (j=jo; j<ncols_o; j++) { 4480 cj[k] = cmap[*bj++]; 4481 ca[k++] = *ba++; 4482 } 4483 } 4484 /* put together the new matrix */ 4485 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4486 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4487 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4488 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4489 mat->free_a = PETSC_TRUE; 4490 mat->free_ij = PETSC_TRUE; 4491 mat->nonew = 0; 4492 } else if (scall == MAT_REUSE_MATRIX) { 4493 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4494 ci = mat->i; cj = mat->j; cam = mat->a; 4495 for (i=0; i<am; i++) { 4496 /* off-diagonal portion of A */ 4497 ncols_o = bi[i+1] - bi[i]; 4498 for (jo=0; jo<ncols_o; jo++) { 4499 col = cmap[*bj]; 4500 if (col >= cstart) break; 4501 *cam++ = *ba++; bj++; 4502 } 4503 /* diagonal portion of A */ 4504 ncols_d = ai[i+1] - ai[i]; 4505 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4506 /* off-diagonal portion of A */ 4507 for (j=jo; j<ncols_o; j++) { 4508 *cam++ = *ba++; bj++; 4509 } 4510 } 4511 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4512 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4513 PetscFunctionReturn(0); 4514 } 4515 4516 #undef __FUNCT__ 4517 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4518 /*@C 4519 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4520 4521 Not Collective 4522 4523 Input Parameters: 4524 + A - the matrix 4525 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4526 - row, col - index sets of rows and columns to extract (or NULL) 4527 4528 Output Parameter: 4529 . A_loc - the local sequential matrix generated 4530 4531 Level: developer 4532 4533 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4534 4535 @*/ 4536 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4537 { 4538 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4539 PetscErrorCode ierr; 4540 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4541 IS isrowa,iscola; 4542 Mat *aloc; 4543 PetscBool match; 4544 4545 PetscFunctionBegin; 4546 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4547 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4548 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4549 if (!row) { 4550 start = A->rmap->rstart; end = A->rmap->rend; 4551 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4552 } else { 4553 isrowa = *row; 4554 } 4555 if (!col) { 4556 start = A->cmap->rstart; 4557 cmap = a->garray; 4558 nzA = a->A->cmap->n; 4559 nzB = a->B->cmap->n; 4560 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4561 ncols = 0; 4562 for (i=0; i<nzB; i++) { 4563 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4564 else break; 4565 } 4566 imark = i; 4567 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4568 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4569 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4570 } else { 4571 iscola = *col; 4572 } 4573 if (scall != MAT_INITIAL_MATRIX) { 4574 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4575 aloc[0] = *A_loc; 4576 } 4577 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4578 *A_loc = aloc[0]; 4579 ierr = PetscFree(aloc);CHKERRQ(ierr); 4580 if (!row) { 4581 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4582 } 4583 if (!col) { 4584 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4585 } 4586 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4587 PetscFunctionReturn(0); 4588 } 4589 4590 #undef __FUNCT__ 4591 #define __FUNCT__ "MatGetBrowsOfAcols" 4592 /*@C 4593 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4594 4595 Collective on Mat 4596 4597 Input Parameters: 4598 + A,B - the matrices in mpiaij format 4599 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4600 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4601 4602 Output Parameter: 4603 + rowb, colb - index sets of rows and columns of B to extract 4604 - B_seq - the sequential matrix generated 4605 4606 Level: developer 4607 4608 @*/ 4609 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4610 { 4611 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4612 PetscErrorCode ierr; 4613 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4614 IS isrowb,iscolb; 4615 Mat *bseq=NULL; 4616 4617 PetscFunctionBegin; 4618 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4619 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); 4620 } 4621 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4622 4623 if (scall == MAT_INITIAL_MATRIX) { 4624 start = A->cmap->rstart; 4625 cmap = a->garray; 4626 nzA = a->A->cmap->n; 4627 nzB = a->B->cmap->n; 4628 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4629 ncols = 0; 4630 for (i=0; i<nzB; i++) { /* row < local row index */ 4631 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4632 else break; 4633 } 4634 imark = i; 4635 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4636 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4637 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4638 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4639 } else { 4640 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4641 isrowb = *rowb; iscolb = *colb; 4642 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4643 bseq[0] = *B_seq; 4644 } 4645 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4646 *B_seq = bseq[0]; 4647 ierr = PetscFree(bseq);CHKERRQ(ierr); 4648 if (!rowb) { 4649 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4650 } else { 4651 *rowb = isrowb; 4652 } 4653 if (!colb) { 4654 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4655 } else { 4656 *colb = iscolb; 4657 } 4658 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4659 PetscFunctionReturn(0); 4660 } 4661 4662 #undef __FUNCT__ 4663 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4664 /* 4665 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4666 of the OFF-DIAGONAL portion of local A 4667 4668 Collective on Mat 4669 4670 Input Parameters: 4671 + A,B - the matrices in mpiaij format 4672 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4673 4674 Output Parameter: 4675 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4676 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4677 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4678 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4679 4680 Level: developer 4681 4682 */ 4683 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4684 { 4685 VecScatter_MPI_General *gen_to,*gen_from; 4686 PetscErrorCode ierr; 4687 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4688 Mat_SeqAIJ *b_oth; 4689 VecScatter ctx =a->Mvctx; 4690 MPI_Comm comm; 4691 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4692 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4693 PetscScalar *rvalues,*svalues; 4694 MatScalar *b_otha,*bufa,*bufA; 4695 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4696 MPI_Request *rwaits = NULL,*swaits = NULL; 4697 MPI_Status *sstatus,rstatus; 4698 PetscMPIInt jj,size; 4699 PetscInt *cols,sbs,rbs; 4700 PetscScalar *vals; 4701 4702 PetscFunctionBegin; 4703 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4704 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4705 4706 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4707 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); 4708 } 4709 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4710 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4711 4712 gen_to = (VecScatter_MPI_General*)ctx->todata; 4713 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4714 rvalues = gen_from->values; /* holds the length of receiving row */ 4715 svalues = gen_to->values; /* holds the length of sending row */ 4716 nrecvs = gen_from->n; 4717 nsends = gen_to->n; 4718 4719 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4720 srow = gen_to->indices; /* local row index to be sent */ 4721 sstarts = gen_to->starts; 4722 sprocs = gen_to->procs; 4723 sstatus = gen_to->sstatus; 4724 sbs = gen_to->bs; 4725 rstarts = gen_from->starts; 4726 rprocs = gen_from->procs; 4727 rbs = gen_from->bs; 4728 4729 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4730 if (scall == MAT_INITIAL_MATRIX) { 4731 /* i-array */ 4732 /*---------*/ 4733 /* post receives */ 4734 for (i=0; i<nrecvs; i++) { 4735 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4736 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4737 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4738 } 4739 4740 /* pack the outgoing message */ 4741 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4742 4743 sstartsj[0] = 0; 4744 rstartsj[0] = 0; 4745 len = 0; /* total length of j or a array to be sent */ 4746 k = 0; 4747 for (i=0; i<nsends; i++) { 4748 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4749 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4750 for (j=0; j<nrows; j++) { 4751 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4752 for (l=0; l<sbs; l++) { 4753 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4754 4755 rowlen[j*sbs+l] = ncols; 4756 4757 len += ncols; 4758 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4759 } 4760 k++; 4761 } 4762 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4763 4764 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4765 } 4766 /* recvs and sends of i-array are completed */ 4767 i = nrecvs; 4768 while (i--) { 4769 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4770 } 4771 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4772 4773 /* allocate buffers for sending j and a arrays */ 4774 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4775 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4776 4777 /* create i-array of B_oth */ 4778 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4779 4780 b_othi[0] = 0; 4781 len = 0; /* total length of j or a array to be received */ 4782 k = 0; 4783 for (i=0; i<nrecvs; i++) { 4784 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4785 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4786 for (j=0; j<nrows; j++) { 4787 b_othi[k+1] = b_othi[k] + rowlen[j]; 4788 len += rowlen[j]; k++; 4789 } 4790 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4791 } 4792 4793 /* allocate space for j and a arrrays of B_oth */ 4794 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4795 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4796 4797 /* j-array */ 4798 /*---------*/ 4799 /* post receives of j-array */ 4800 for (i=0; i<nrecvs; i++) { 4801 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4802 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4803 } 4804 4805 /* pack the outgoing message j-array */ 4806 k = 0; 4807 for (i=0; i<nsends; i++) { 4808 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4809 bufJ = bufj+sstartsj[i]; 4810 for (j=0; j<nrows; j++) { 4811 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4812 for (ll=0; ll<sbs; ll++) { 4813 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4814 for (l=0; l<ncols; l++) { 4815 *bufJ++ = cols[l]; 4816 } 4817 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4818 } 4819 } 4820 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4821 } 4822 4823 /* recvs and sends of j-array are completed */ 4824 i = nrecvs; 4825 while (i--) { 4826 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4827 } 4828 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4829 } else if (scall == MAT_REUSE_MATRIX) { 4830 sstartsj = *startsj_s; 4831 rstartsj = *startsj_r; 4832 bufa = *bufa_ptr; 4833 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4834 b_otha = b_oth->a; 4835 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4836 4837 /* a-array */ 4838 /*---------*/ 4839 /* post receives of a-array */ 4840 for (i=0; i<nrecvs; i++) { 4841 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4842 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4843 } 4844 4845 /* pack the outgoing message a-array */ 4846 k = 0; 4847 for (i=0; i<nsends; i++) { 4848 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4849 bufA = bufa+sstartsj[i]; 4850 for (j=0; j<nrows; j++) { 4851 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4852 for (ll=0; ll<sbs; ll++) { 4853 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4854 for (l=0; l<ncols; l++) { 4855 *bufA++ = vals[l]; 4856 } 4857 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4858 } 4859 } 4860 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4861 } 4862 /* recvs and sends of a-array are completed */ 4863 i = nrecvs; 4864 while (i--) { 4865 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4866 } 4867 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4868 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4869 4870 if (scall == MAT_INITIAL_MATRIX) { 4871 /* put together the new matrix */ 4872 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4873 4874 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4875 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4876 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4877 b_oth->free_a = PETSC_TRUE; 4878 b_oth->free_ij = PETSC_TRUE; 4879 b_oth->nonew = 0; 4880 4881 ierr = PetscFree(bufj);CHKERRQ(ierr); 4882 if (!startsj_s || !bufa_ptr) { 4883 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4884 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4885 } else { 4886 *startsj_s = sstartsj; 4887 *startsj_r = rstartsj; 4888 *bufa_ptr = bufa; 4889 } 4890 } 4891 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4892 PetscFunctionReturn(0); 4893 } 4894 4895 #undef __FUNCT__ 4896 #define __FUNCT__ "MatGetCommunicationStructs" 4897 /*@C 4898 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4899 4900 Not Collective 4901 4902 Input Parameters: 4903 . A - The matrix in mpiaij format 4904 4905 Output Parameter: 4906 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4907 . colmap - A map from global column index to local index into lvec 4908 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4909 4910 Level: developer 4911 4912 @*/ 4913 #if defined(PETSC_USE_CTABLE) 4914 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4915 #else 4916 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4917 #endif 4918 { 4919 Mat_MPIAIJ *a; 4920 4921 PetscFunctionBegin; 4922 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4923 PetscValidPointer(lvec, 2); 4924 PetscValidPointer(colmap, 3); 4925 PetscValidPointer(multScatter, 4); 4926 a = (Mat_MPIAIJ*) A->data; 4927 if (lvec) *lvec = a->lvec; 4928 if (colmap) *colmap = a->colmap; 4929 if (multScatter) *multScatter = a->Mvctx; 4930 PetscFunctionReturn(0); 4931 } 4932 4933 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4934 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4935 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4936 #if defined(PETSC_HAVE_ELEMENTAL) 4937 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4938 #endif 4939 4940 #undef __FUNCT__ 4941 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4942 /* 4943 Computes (B'*A')' since computing B*A directly is untenable 4944 4945 n p p 4946 ( ) ( ) ( ) 4947 m ( A ) * n ( B ) = m ( C ) 4948 ( ) ( ) ( ) 4949 4950 */ 4951 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4952 { 4953 PetscErrorCode ierr; 4954 Mat At,Bt,Ct; 4955 4956 PetscFunctionBegin; 4957 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4958 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4959 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4960 ierr = MatDestroy(&At);CHKERRQ(ierr); 4961 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4962 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4963 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4964 PetscFunctionReturn(0); 4965 } 4966 4967 #undef __FUNCT__ 4968 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4969 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4970 { 4971 PetscErrorCode ierr; 4972 PetscInt m=A->rmap->n,n=B->cmap->n; 4973 Mat Cmat; 4974 4975 PetscFunctionBegin; 4976 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); 4977 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4978 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4979 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4980 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4981 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4982 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4983 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4984 4985 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 4986 4987 *C = Cmat; 4988 PetscFunctionReturn(0); 4989 } 4990 4991 /* ----------------------------------------------------------------*/ 4992 #undef __FUNCT__ 4993 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4994 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4995 { 4996 PetscErrorCode ierr; 4997 4998 PetscFunctionBegin; 4999 if (scall == MAT_INITIAL_MATRIX) { 5000 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5001 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5002 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5003 } 5004 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5005 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5006 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5007 PetscFunctionReturn(0); 5008 } 5009 5010 /*MC 5011 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5012 5013 Options Database Keys: 5014 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5015 5016 Level: beginner 5017 5018 .seealso: MatCreateAIJ() 5019 M*/ 5020 5021 #undef __FUNCT__ 5022 #define __FUNCT__ "MatCreate_MPIAIJ" 5023 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5024 { 5025 Mat_MPIAIJ *b; 5026 PetscErrorCode ierr; 5027 PetscMPIInt size; 5028 5029 PetscFunctionBegin; 5030 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5031 5032 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5033 B->data = (void*)b; 5034 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5035 B->assembled = PETSC_FALSE; 5036 B->insertmode = NOT_SET_VALUES; 5037 b->size = size; 5038 5039 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5040 5041 /* build cache for off array entries formed */ 5042 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5043 5044 b->donotstash = PETSC_FALSE; 5045 b->colmap = 0; 5046 b->garray = 0; 5047 b->roworiented = PETSC_TRUE; 5048 5049 /* stuff used for matrix vector multiply */ 5050 b->lvec = NULL; 5051 b->Mvctx = NULL; 5052 5053 /* stuff for MatGetRow() */ 5054 b->rowindices = 0; 5055 b->rowvalues = 0; 5056 b->getrowactive = PETSC_FALSE; 5057 5058 /* flexible pointer used in CUSP/CUSPARSE classes */ 5059 b->spptr = NULL; 5060 5061 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5062 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5063 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5064 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5065 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5066 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5067 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5068 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5069 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5070 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5071 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5072 #if defined(PETSC_HAVE_ELEMENTAL) 5073 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5074 #endif 5075 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5076 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5077 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5078 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5079 PetscFunctionReturn(0); 5080 } 5081 5082 #undef __FUNCT__ 5083 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5084 /*@C 5085 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5086 and "off-diagonal" part of the matrix in CSR format. 5087 5088 Collective on MPI_Comm 5089 5090 Input Parameters: 5091 + comm - MPI communicator 5092 . m - number of local rows (Cannot be PETSC_DECIDE) 5093 . n - This value should be the same as the local size used in creating the 5094 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5095 calculated if N is given) For square matrices n is almost always m. 5096 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5097 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5098 . i - row indices for "diagonal" portion of matrix 5099 . j - column indices 5100 . a - matrix values 5101 . oi - row indices for "off-diagonal" portion of matrix 5102 . oj - column indices 5103 - oa - matrix values 5104 5105 Output Parameter: 5106 . mat - the matrix 5107 5108 Level: advanced 5109 5110 Notes: 5111 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5112 must free the arrays once the matrix has been destroyed and not before. 5113 5114 The i and j indices are 0 based 5115 5116 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5117 5118 This sets local rows and cannot be used to set off-processor values. 5119 5120 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5121 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5122 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5123 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5124 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5125 communication if it is known that only local entries will be set. 5126 5127 .keywords: matrix, aij, compressed row, sparse, parallel 5128 5129 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5130 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5131 @*/ 5132 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) 5133 { 5134 PetscErrorCode ierr; 5135 Mat_MPIAIJ *maij; 5136 5137 PetscFunctionBegin; 5138 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5139 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5140 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5141 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5142 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5143 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5144 maij = (Mat_MPIAIJ*) (*mat)->data; 5145 5146 (*mat)->preallocated = PETSC_TRUE; 5147 5148 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5149 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5150 5151 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5152 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5153 5154 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5155 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5156 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5157 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5158 5159 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5160 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5161 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5162 PetscFunctionReturn(0); 5163 } 5164 5165 /* 5166 Special version for direct calls from Fortran 5167 */ 5168 #include <petsc/private/fortranimpl.h> 5169 5170 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5171 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5172 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5173 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5174 #endif 5175 5176 /* Change these macros so can be used in void function */ 5177 #undef CHKERRQ 5178 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5179 #undef SETERRQ2 5180 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5181 #undef SETERRQ3 5182 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5183 #undef SETERRQ 5184 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5185 5186 #undef __FUNCT__ 5187 #define __FUNCT__ "matsetvaluesmpiaij_" 5188 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) 5189 { 5190 Mat mat = *mmat; 5191 PetscInt m = *mm, n = *mn; 5192 InsertMode addv = *maddv; 5193 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5194 PetscScalar value; 5195 PetscErrorCode ierr; 5196 5197 MatCheckPreallocated(mat,1); 5198 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5199 5200 #if defined(PETSC_USE_DEBUG) 5201 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5202 #endif 5203 { 5204 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5205 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5206 PetscBool roworiented = aij->roworiented; 5207 5208 /* Some Variables required in the macro */ 5209 Mat A = aij->A; 5210 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5211 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5212 MatScalar *aa = a->a; 5213 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5214 Mat B = aij->B; 5215 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5216 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5217 MatScalar *ba = b->a; 5218 5219 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5220 PetscInt nonew = a->nonew; 5221 MatScalar *ap1,*ap2; 5222 5223 PetscFunctionBegin; 5224 for (i=0; i<m; i++) { 5225 if (im[i] < 0) continue; 5226 #if defined(PETSC_USE_DEBUG) 5227 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); 5228 #endif 5229 if (im[i] >= rstart && im[i] < rend) { 5230 row = im[i] - rstart; 5231 lastcol1 = -1; 5232 rp1 = aj + ai[row]; 5233 ap1 = aa + ai[row]; 5234 rmax1 = aimax[row]; 5235 nrow1 = ailen[row]; 5236 low1 = 0; 5237 high1 = nrow1; 5238 lastcol2 = -1; 5239 rp2 = bj + bi[row]; 5240 ap2 = ba + bi[row]; 5241 rmax2 = bimax[row]; 5242 nrow2 = bilen[row]; 5243 low2 = 0; 5244 high2 = nrow2; 5245 5246 for (j=0; j<n; j++) { 5247 if (roworiented) value = v[i*n+j]; 5248 else value = v[i+j*m]; 5249 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5250 if (in[j] >= cstart && in[j] < cend) { 5251 col = in[j] - cstart; 5252 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5253 } else if (in[j] < 0) continue; 5254 #if defined(PETSC_USE_DEBUG) 5255 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); 5256 #endif 5257 else { 5258 if (mat->was_assembled) { 5259 if (!aij->colmap) { 5260 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5261 } 5262 #if defined(PETSC_USE_CTABLE) 5263 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5264 col--; 5265 #else 5266 col = aij->colmap[in[j]] - 1; 5267 #endif 5268 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5269 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5270 col = in[j]; 5271 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5272 B = aij->B; 5273 b = (Mat_SeqAIJ*)B->data; 5274 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5275 rp2 = bj + bi[row]; 5276 ap2 = ba + bi[row]; 5277 rmax2 = bimax[row]; 5278 nrow2 = bilen[row]; 5279 low2 = 0; 5280 high2 = nrow2; 5281 bm = aij->B->rmap->n; 5282 ba = b->a; 5283 } 5284 } else col = in[j]; 5285 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5286 } 5287 } 5288 } else if (!aij->donotstash) { 5289 if (roworiented) { 5290 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5291 } else { 5292 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5293 } 5294 } 5295 } 5296 } 5297 PetscFunctionReturnVoid(); 5298 } 5299 5300