1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 12 and MATMPIAIJ otherwise. As a result, for single process communicators, 13 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 19 20 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 21 enough exist. 22 23 Level: beginner 24 25 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 26 M*/ 27 28 /*MC 29 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 30 31 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 32 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 33 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 34 for communicators controlling multiple processes. It is recommended that you call both of 35 the above preallocation routines for simplicity. 36 37 Options Database Keys: 38 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 39 40 Level: beginner 41 42 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 43 M*/ 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 47 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 48 { 49 PetscErrorCode ierr; 50 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 52 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 53 const PetscInt *ia,*ib; 54 const MatScalar *aa,*bb; 55 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 56 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 57 58 PetscFunctionBegin; 59 *keptrows = 0; 60 ia = a->i; 61 ib = b->i; 62 for (i=0; i<m; i++) { 63 na = ia[i+1] - ia[i]; 64 nb = ib[i+1] - ib[i]; 65 if (!na && !nb) { 66 cnt++; 67 goto ok1; 68 } 69 aa = a->a + ia[i]; 70 for (j=0; j<na; j++) { 71 if (aa[j] != 0.0) goto ok1; 72 } 73 bb = b->a + ib[i]; 74 for (j=0; j <nb; j++) { 75 if (bb[j] != 0.0) goto ok1; 76 } 77 cnt++; 78 ok1:; 79 } 80 ierr = MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 81 if (!n0rows) PetscFunctionReturn(0); 82 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 83 cnt = 0; 84 for (i=0; i<m; i++) { 85 na = ia[i+1] - ia[i]; 86 nb = ib[i+1] - ib[i]; 87 if (!na && !nb) continue; 88 aa = a->a + ia[i]; 89 for (j=0; j<na;j++) { 90 if (aa[j] != 0.0) { 91 rows[cnt++] = rstart + i; 92 goto ok2; 93 } 94 } 95 bb = b->a + ib[i]; 96 for (j=0; j<nb; j++) { 97 if (bb[j] != 0.0) { 98 rows[cnt++] = rstart + i; 99 goto ok2; 100 } 101 } 102 ok2:; 103 } 104 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 105 PetscFunctionReturn(0); 106 } 107 108 #undef __FUNCT__ 109 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 110 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 111 { 112 PetscErrorCode ierr; 113 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 114 115 PetscFunctionBegin; 116 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 117 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 118 } else { 119 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 120 } 121 PetscFunctionReturn(0); 122 } 123 124 125 #undef __FUNCT__ 126 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 127 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 128 { 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 130 PetscErrorCode ierr; 131 PetscInt i,rstart,nrows,*rows; 132 133 PetscFunctionBegin; 134 *zrows = NULL; 135 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 136 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 137 for (i=0; i<nrows; i++) rows[i] += rstart; 138 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 #undef __FUNCT__ 143 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 144 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 145 { 146 PetscErrorCode ierr; 147 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 148 PetscInt i,n,*garray = aij->garray; 149 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 150 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 151 PetscReal *work; 152 153 PetscFunctionBegin; 154 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 155 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 156 if (type == NORM_2) { 157 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 158 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 159 } 160 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 161 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 162 } 163 } else if (type == NORM_1) { 164 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 165 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 166 } 167 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 168 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 169 } 170 } else if (type == NORM_INFINITY) { 171 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 172 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 173 } 174 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 175 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 176 } 177 178 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 179 if (type == NORM_INFINITY) { 180 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 181 } else { 182 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 183 } 184 ierr = PetscFree(work);CHKERRQ(ierr); 185 if (type == NORM_2) { 186 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 187 } 188 PetscFunctionReturn(0); 189 } 190 191 #undef __FUNCT__ 192 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_MPIAIJ" 193 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 194 { 195 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 196 IS sis,gis; 197 PetscErrorCode ierr; 198 const PetscInt *isis,*igis; 199 PetscInt n,*iis,nsis,ngis,rstart,i; 200 201 PetscFunctionBegin; 202 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 203 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 204 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 205 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 206 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 207 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 208 209 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 210 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 211 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 212 n = ngis + nsis; 213 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 214 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 215 for (i=0; i<n; i++) iis[i] += rstart; 216 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 217 218 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 219 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 220 ierr = ISDestroy(&sis);CHKERRQ(ierr); 221 ierr = ISDestroy(&gis);CHKERRQ(ierr); 222 PetscFunctionReturn(0); 223 } 224 225 #undef __FUNCT__ 226 #define __FUNCT__ "MatDistribute_MPIAIJ" 227 /* 228 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 229 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 230 231 Only for square matrices 232 233 Used by a preconditioner, hence PETSC_EXTERN 234 */ 235 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 236 { 237 PetscMPIInt rank,size; 238 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 239 PetscErrorCode ierr; 240 Mat mat; 241 Mat_SeqAIJ *gmata; 242 PetscMPIInt tag; 243 MPI_Status status; 244 PetscBool aij; 245 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 246 247 PetscFunctionBegin; 248 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 249 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 250 if (!rank) { 251 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 252 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 253 } 254 if (reuse == MAT_INITIAL_MATRIX) { 255 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 256 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 257 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 258 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 259 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 260 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 261 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 262 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 263 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 264 265 rowners[0] = 0; 266 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 267 rstart = rowners[rank]; 268 rend = rowners[rank+1]; 269 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 270 if (!rank) { 271 gmata = (Mat_SeqAIJ*) gmat->data; 272 /* send row lengths to all processors */ 273 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 274 for (i=1; i<size; i++) { 275 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 276 } 277 /* determine number diagonal and off-diagonal counts */ 278 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 279 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 280 jj = 0; 281 for (i=0; i<m; i++) { 282 for (j=0; j<dlens[i]; j++) { 283 if (gmata->j[jj] < rstart) ld[i]++; 284 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 285 jj++; 286 } 287 } 288 /* send column indices to other processes */ 289 for (i=1; i<size; i++) { 290 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 291 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 292 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 } 294 295 /* send numerical values to other processes */ 296 for (i=1; i<size; i++) { 297 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 298 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 299 } 300 gmataa = gmata->a; 301 gmataj = gmata->j; 302 303 } else { 304 /* receive row lengths */ 305 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 306 /* receive column indices */ 307 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 309 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 /* determine number diagonal and off-diagonal counts */ 311 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 312 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 313 jj = 0; 314 for (i=0; i<m; i++) { 315 for (j=0; j<dlens[i]; j++) { 316 if (gmataj[jj] < rstart) ld[i]++; 317 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 318 jj++; 319 } 320 } 321 /* receive numerical values */ 322 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* set preallocation */ 326 for (i=0; i<m; i++) { 327 dlens[i] -= olens[i]; 328 } 329 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 330 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 331 332 for (i=0; i<m; i++) { 333 dlens[i] += olens[i]; 334 } 335 cnt = 0; 336 for (i=0; i<m; i++) { 337 row = rstart + i; 338 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 339 cnt += dlens[i]; 340 } 341 if (rank) { 342 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 343 } 344 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 345 ierr = PetscFree(rowners);CHKERRQ(ierr); 346 347 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 348 349 *inmat = mat; 350 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 351 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 352 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 353 mat = *inmat; 354 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 355 if (!rank) { 356 /* send numerical values to other processes */ 357 gmata = (Mat_SeqAIJ*) gmat->data; 358 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 359 gmataa = gmata->a; 360 for (i=1; i<size; i++) { 361 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 362 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 363 } 364 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 365 } else { 366 /* receive numerical values from process 0*/ 367 nz = Ad->nz + Ao->nz; 368 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 369 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 370 } 371 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 372 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 373 ad = Ad->a; 374 ao = Ao->a; 375 if (mat->rmap->n) { 376 i = 0; 377 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 378 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 379 } 380 for (i=1; i<mat->rmap->n; i++) { 381 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 382 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 383 } 384 i--; 385 if (mat->rmap->n) { 386 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 387 } 388 if (rank) { 389 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 390 } 391 } 392 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 393 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 /* 398 Local utility routine that creates a mapping from the global column 399 number to the local number in the off-diagonal part of the local 400 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 401 a slightly higher hash table cost; without it it is not scalable (each processor 402 has an order N integer array but is fast to acess. 403 */ 404 #undef __FUNCT__ 405 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 406 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 407 { 408 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 409 PetscErrorCode ierr; 410 PetscInt n = aij->B->cmap->n,i; 411 412 PetscFunctionBegin; 413 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 414 #if defined(PETSC_USE_CTABLE) 415 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 416 for (i=0; i<n; i++) { 417 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 418 } 419 #else 420 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 421 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 422 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 423 #endif 424 PetscFunctionReturn(0); 425 } 426 427 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 428 { \ 429 if (col <= lastcol1) low1 = 0; \ 430 else high1 = nrow1; \ 431 lastcol1 = col;\ 432 while (high1-low1 > 5) { \ 433 t = (low1+high1)/2; \ 434 if (rp1[t] > col) high1 = t; \ 435 else low1 = t; \ 436 } \ 437 for (_i=low1; _i<high1; _i++) { \ 438 if (rp1[_i] > col) break; \ 439 if (rp1[_i] == col) { \ 440 if (addv == ADD_VALUES) ap1[_i] += value; \ 441 else ap1[_i] = value; \ 442 goto a_noinsert; \ 443 } \ 444 } \ 445 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 446 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 447 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 448 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 449 N = nrow1++ - 1; a->nz++; high1++; \ 450 /* shift up all the later entries in this row */ \ 451 for (ii=N; ii>=_i; ii--) { \ 452 rp1[ii+1] = rp1[ii]; \ 453 ap1[ii+1] = ap1[ii]; \ 454 } \ 455 rp1[_i] = col; \ 456 ap1[_i] = value; \ 457 A->nonzerostate++;\ 458 a_noinsert: ; \ 459 ailen[row] = nrow1; \ 460 } 461 462 463 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 464 { \ 465 if (col <= lastcol2) low2 = 0; \ 466 else high2 = nrow2; \ 467 lastcol2 = col; \ 468 while (high2-low2 > 5) { \ 469 t = (low2+high2)/2; \ 470 if (rp2[t] > col) high2 = t; \ 471 else low2 = t; \ 472 } \ 473 for (_i=low2; _i<high2; _i++) { \ 474 if (rp2[_i] > col) break; \ 475 if (rp2[_i] == col) { \ 476 if (addv == ADD_VALUES) ap2[_i] += value; \ 477 else ap2[_i] = value; \ 478 goto b_noinsert; \ 479 } \ 480 } \ 481 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 482 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 483 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 484 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 485 N = nrow2++ - 1; b->nz++; high2++; \ 486 /* shift up all the later entries in this row */ \ 487 for (ii=N; ii>=_i; ii--) { \ 488 rp2[ii+1] = rp2[ii]; \ 489 ap2[ii+1] = ap2[ii]; \ 490 } \ 491 rp2[_i] = col; \ 492 ap2[_i] = value; \ 493 B->nonzerostate++; \ 494 b_noinsert: ; \ 495 bilen[row] = nrow2; \ 496 } 497 498 #undef __FUNCT__ 499 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 500 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 501 { 502 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 504 PetscErrorCode ierr; 505 PetscInt l,*garray = mat->garray,diag; 506 507 PetscFunctionBegin; 508 /* code only works for square matrices A */ 509 510 /* find size of row to the left of the diagonal part */ 511 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 512 row = row - diag; 513 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 514 if (garray[b->j[b->i[row]+l]] > diag) break; 515 } 516 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 517 518 /* diagonal part */ 519 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 520 521 /* right of diagonal part */ 522 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 523 PetscFunctionReturn(0); 524 } 525 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatSetValues_MPIAIJ" 528 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 529 { 530 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 531 PetscScalar value; 532 PetscErrorCode ierr; 533 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 534 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 535 PetscBool roworiented = aij->roworiented; 536 537 /* Some Variables required in the macro */ 538 Mat A = aij->A; 539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 540 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 541 MatScalar *aa = a->a; 542 PetscBool ignorezeroentries = a->ignorezeroentries; 543 Mat B = aij->B; 544 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 545 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 546 MatScalar *ba = b->a; 547 548 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 549 PetscInt nonew; 550 MatScalar *ap1,*ap2; 551 552 PetscFunctionBegin; 553 for (i=0; i<m; i++) { 554 if (im[i] < 0) continue; 555 #if defined(PETSC_USE_DEBUG) 556 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 557 #endif 558 if (im[i] >= rstart && im[i] < rend) { 559 row = im[i] - rstart; 560 lastcol1 = -1; 561 rp1 = aj + ai[row]; 562 ap1 = aa + ai[row]; 563 rmax1 = aimax[row]; 564 nrow1 = ailen[row]; 565 low1 = 0; 566 high1 = nrow1; 567 lastcol2 = -1; 568 rp2 = bj + bi[row]; 569 ap2 = ba + bi[row]; 570 rmax2 = bimax[row]; 571 nrow2 = bilen[row]; 572 low2 = 0; 573 high2 = nrow2; 574 575 for (j=0; j<n; j++) { 576 if (roworiented) value = v[i*n+j]; 577 else value = v[i+j*m]; 578 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 579 if (in[j] >= cstart && in[j] < cend) { 580 col = in[j] - cstart; 581 nonew = a->nonew; 582 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 583 } else if (in[j] < 0) continue; 584 #if defined(PETSC_USE_DEBUG) 585 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 586 #endif 587 else { 588 if (mat->was_assembled) { 589 if (!aij->colmap) { 590 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 591 } 592 #if defined(PETSC_USE_CTABLE) 593 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 594 col--; 595 #else 596 col = aij->colmap[in[j]] - 1; 597 #endif 598 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 599 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 600 col = in[j]; 601 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 602 B = aij->B; 603 b = (Mat_SeqAIJ*)B->data; 604 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 605 rp2 = bj + bi[row]; 606 ap2 = ba + bi[row]; 607 rmax2 = bimax[row]; 608 nrow2 = bilen[row]; 609 low2 = 0; 610 high2 = nrow2; 611 bm = aij->B->rmap->n; 612 ba = b->a; 613 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]); 614 } else col = in[j]; 615 nonew = b->nonew; 616 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 617 } 618 } 619 } else { 620 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 621 if (!aij->donotstash) { 622 mat->assembled = PETSC_FALSE; 623 if (roworiented) { 624 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 625 } else { 626 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 627 } 628 } 629 } 630 } 631 PetscFunctionReturn(0); 632 } 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatGetValues_MPIAIJ" 636 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 641 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 642 643 PetscFunctionBegin; 644 for (i=0; i<m; i++) { 645 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 646 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 647 if (idxm[i] >= rstart && idxm[i] < rend) { 648 row = idxm[i] - rstart; 649 for (j=0; j<n; j++) { 650 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 651 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 652 if (idxn[j] >= cstart && idxn[j] < cend) { 653 col = idxn[j] - cstart; 654 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 655 } else { 656 if (!aij->colmap) { 657 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 658 } 659 #if defined(PETSC_USE_CTABLE) 660 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 661 col--; 662 #else 663 col = aij->colmap[idxn[j]] - 1; 664 #endif 665 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 666 else { 667 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 668 } 669 } 670 } 671 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 672 } 673 PetscFunctionReturn(0); 674 } 675 676 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 677 678 #undef __FUNCT__ 679 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 680 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 681 { 682 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 683 PetscErrorCode ierr; 684 PetscInt nstash,reallocs; 685 686 PetscFunctionBegin; 687 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 688 689 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 690 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 691 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 692 PetscFunctionReturn(0); 693 } 694 695 #undef __FUNCT__ 696 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 697 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 698 { 699 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 700 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 701 PetscErrorCode ierr; 702 PetscMPIInt n; 703 PetscInt i,j,rstart,ncols,flg; 704 PetscInt *row,*col; 705 PetscBool other_disassembled; 706 PetscScalar *val; 707 708 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 709 710 PetscFunctionBegin; 711 if (!aij->donotstash && !mat->nooffprocentries) { 712 while (1) { 713 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 714 if (!flg) break; 715 716 for (i=0; i<n; ) { 717 /* Now identify the consecutive vals belonging to the same row */ 718 for (j=i,rstart=row[j]; j<n; j++) { 719 if (row[j] != rstart) break; 720 } 721 if (j < n) ncols = j-i; 722 else ncols = n-i; 723 /* Now assemble all these values with a single function call */ 724 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 725 726 i = j; 727 } 728 } 729 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 730 } 731 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 732 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 733 734 /* determine if any processor has disassembled, if so we must 735 also disassemble ourselfs, in order that we may reassemble. */ 736 /* 737 if nonzero structure of submatrix B cannot change then we know that 738 no processor disassembled thus we can skip this stuff 739 */ 740 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 741 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 742 if (mat->was_assembled && !other_disassembled) { 743 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 744 } 745 } 746 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 747 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 748 } 749 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 750 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 751 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 752 753 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 754 755 aij->rowvalues = 0; 756 757 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 758 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 759 760 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 761 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 762 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 763 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 764 } 765 PetscFunctionReturn(0); 766 } 767 768 #undef __FUNCT__ 769 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 770 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 771 { 772 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 773 PetscErrorCode ierr; 774 775 PetscFunctionBegin; 776 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 777 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 778 PetscFunctionReturn(0); 779 } 780 781 #undef __FUNCT__ 782 #define __FUNCT__ "MatZeroRows_MPIAIJ" 783 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 784 { 785 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 786 PetscInt *owners = A->rmap->range; 787 PetscInt n = A->rmap->n; 788 PetscSF sf; 789 PetscInt *lrows; 790 PetscSFNode *rrows; 791 PetscInt r, p = 0, len = 0; 792 PetscErrorCode ierr; 793 794 PetscFunctionBegin; 795 /* Create SF where leaves are input rows and roots are owned rows */ 796 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 797 for (r = 0; r < n; ++r) lrows[r] = -1; 798 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 799 for (r = 0; r < N; ++r) { 800 const PetscInt idx = rows[r]; 801 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 802 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 803 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 804 } 805 if (A->nooffproczerorows) { 806 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 807 lrows[len++] = idx - owners[p]; 808 } else { 809 rrows[r].rank = p; 810 rrows[r].index = rows[r] - owners[p]; 811 } 812 } 813 if (!A->nooffproczerorows) { 814 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 815 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 816 /* Collect flags for rows to be zeroed */ 817 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 818 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 819 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 820 /* Compress and put in row numbers */ 821 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 822 } 823 /* fix right hand side if needed */ 824 if (x && b) { 825 const PetscScalar *xx; 826 PetscScalar *bb; 827 828 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 829 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 830 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 831 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 832 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 833 } 834 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 835 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 836 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 837 PetscBool cong; 838 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 839 if (cong) A->congruentlayouts = 1; 840 else A->congruentlayouts = 0; 841 } 842 if ((diag != 0.0) && A->congruentlayouts) { 843 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 844 } else if (diag != 0.0) { 845 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 846 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"); 847 for (r = 0; r < len; ++r) { 848 const PetscInt row = lrows[r] + A->rmap->rstart; 849 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 850 } 851 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 852 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 853 } else { 854 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 855 } 856 ierr = PetscFree(lrows);CHKERRQ(ierr); 857 858 /* only change matrix nonzero state if pattern was allowed to be changed */ 859 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 860 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 861 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 862 } 863 PetscFunctionReturn(0); 864 } 865 866 #undef __FUNCT__ 867 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 868 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 869 { 870 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 871 PetscErrorCode ierr; 872 PetscMPIInt n = A->rmap->n; 873 PetscInt i,j,r,m,p = 0,len = 0; 874 PetscInt *lrows,*owners = A->rmap->range; 875 PetscSFNode *rrows; 876 PetscSF sf; 877 const PetscScalar *xx; 878 PetscScalar *bb,*mask; 879 Vec xmask,lmask; 880 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 881 const PetscInt *aj, *ii,*ridx; 882 PetscScalar *aa; 883 884 PetscFunctionBegin; 885 /* Create SF where leaves are input rows and roots are owned rows */ 886 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 887 for (r = 0; r < n; ++r) lrows[r] = -1; 888 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 889 for (r = 0; r < N; ++r) { 890 const PetscInt idx = rows[r]; 891 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); 892 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 893 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 894 } 895 rrows[r].rank = p; 896 rrows[r].index = rows[r] - owners[p]; 897 } 898 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 899 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 900 /* Collect flags for rows to be zeroed */ 901 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 902 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 903 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 904 /* Compress and put in row numbers */ 905 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 906 /* zero diagonal part of matrix */ 907 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 908 /* handle off diagonal part of matrix */ 909 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 910 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 911 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 912 for (i=0; i<len; i++) bb[lrows[i]] = 1; 913 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 914 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 915 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 916 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 917 if (x) { 918 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 919 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 920 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 921 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 922 } 923 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 924 /* remove zeroed rows of off diagonal matrix */ 925 ii = aij->i; 926 for (i=0; i<len; i++) { 927 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 928 } 929 /* loop over all elements of off process part of matrix zeroing removed columns*/ 930 if (aij->compressedrow.use) { 931 m = aij->compressedrow.nrows; 932 ii = aij->compressedrow.i; 933 ridx = aij->compressedrow.rindex; 934 for (i=0; i<m; i++) { 935 n = ii[i+1] - ii[i]; 936 aj = aij->j + ii[i]; 937 aa = aij->a + ii[i]; 938 939 for (j=0; j<n; j++) { 940 if (PetscAbsScalar(mask[*aj])) { 941 if (b) bb[*ridx] -= *aa*xx[*aj]; 942 *aa = 0.0; 943 } 944 aa++; 945 aj++; 946 } 947 ridx++; 948 } 949 } else { /* do not use compressed row format */ 950 m = l->B->rmap->n; 951 for (i=0; i<m; i++) { 952 n = ii[i+1] - ii[i]; 953 aj = aij->j + ii[i]; 954 aa = aij->a + ii[i]; 955 for (j=0; j<n; j++) { 956 if (PetscAbsScalar(mask[*aj])) { 957 if (b) bb[i] -= *aa*xx[*aj]; 958 *aa = 0.0; 959 } 960 aa++; 961 aj++; 962 } 963 } 964 } 965 if (x) { 966 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 967 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 968 } 969 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 970 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 971 ierr = PetscFree(lrows);CHKERRQ(ierr); 972 973 /* only change matrix nonzero state if pattern was allowed to be changed */ 974 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 975 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 976 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 977 } 978 PetscFunctionReturn(0); 979 } 980 981 #undef __FUNCT__ 982 #define __FUNCT__ "MatMult_MPIAIJ" 983 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 984 { 985 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 986 PetscErrorCode ierr; 987 PetscInt nt; 988 989 PetscFunctionBegin; 990 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 991 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); 992 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 993 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 994 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 995 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 996 PetscFunctionReturn(0); 997 } 998 999 #undef __FUNCT__ 1000 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1001 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1002 { 1003 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1004 PetscErrorCode ierr; 1005 1006 PetscFunctionBegin; 1007 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1008 PetscFunctionReturn(0); 1009 } 1010 1011 #undef __FUNCT__ 1012 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1013 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1014 { 1015 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1016 PetscErrorCode ierr; 1017 1018 PetscFunctionBegin; 1019 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1020 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1021 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1022 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1023 PetscFunctionReturn(0); 1024 } 1025 1026 #undef __FUNCT__ 1027 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1028 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1029 { 1030 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1031 PetscErrorCode ierr; 1032 PetscBool merged; 1033 1034 PetscFunctionBegin; 1035 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1036 /* do nondiagonal part */ 1037 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1038 if (!merged) { 1039 /* send it on its way */ 1040 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1041 /* do local part */ 1042 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1043 /* receive remote parts: note this assumes the values are not actually */ 1044 /* added in yy until the next line, */ 1045 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1046 } else { 1047 /* do local part */ 1048 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1049 /* send it on its way */ 1050 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1051 /* values actually were received in the Begin() but we need to call this nop */ 1052 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1053 } 1054 PetscFunctionReturn(0); 1055 } 1056 1057 #undef __FUNCT__ 1058 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1059 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1060 { 1061 MPI_Comm comm; 1062 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1063 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1064 IS Me,Notme; 1065 PetscErrorCode ierr; 1066 PetscInt M,N,first,last,*notme,i; 1067 PetscMPIInt size; 1068 1069 PetscFunctionBegin; 1070 /* Easy test: symmetric diagonal block */ 1071 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1072 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1073 if (!*f) PetscFunctionReturn(0); 1074 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1075 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1076 if (size == 1) PetscFunctionReturn(0); 1077 1078 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1079 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1080 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1081 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1082 for (i=0; i<first; i++) notme[i] = i; 1083 for (i=last; i<M; i++) notme[i-last+first] = i; 1084 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1085 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1086 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1087 Aoff = Aoffs[0]; 1088 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1089 Boff = Boffs[0]; 1090 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1091 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1092 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1093 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1094 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1095 ierr = PetscFree(notme);CHKERRQ(ierr); 1096 PetscFunctionReturn(0); 1097 } 1098 1099 #undef __FUNCT__ 1100 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1101 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1102 { 1103 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1104 PetscErrorCode ierr; 1105 1106 PetscFunctionBegin; 1107 /* do nondiagonal part */ 1108 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1109 /* send it on its way */ 1110 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1111 /* do local part */ 1112 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1113 /* receive remote parts */ 1114 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 /* 1119 This only works correctly for square matrices where the subblock A->A is the 1120 diagonal block 1121 */ 1122 #undef __FUNCT__ 1123 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1124 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1125 { 1126 PetscErrorCode ierr; 1127 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1128 1129 PetscFunctionBegin; 1130 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1131 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"); 1132 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1133 PetscFunctionReturn(0); 1134 } 1135 1136 #undef __FUNCT__ 1137 #define __FUNCT__ "MatScale_MPIAIJ" 1138 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1139 { 1140 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1141 PetscErrorCode ierr; 1142 1143 PetscFunctionBegin; 1144 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1145 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1146 PetscFunctionReturn(0); 1147 } 1148 1149 #undef __FUNCT__ 1150 #define __FUNCT__ "MatDestroy_MPIAIJ" 1151 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1152 { 1153 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1154 PetscErrorCode ierr; 1155 1156 PetscFunctionBegin; 1157 #if defined(PETSC_USE_LOG) 1158 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1159 #endif 1160 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1161 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1162 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1163 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1164 #if defined(PETSC_USE_CTABLE) 1165 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1166 #else 1167 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1168 #endif 1169 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1170 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1171 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1172 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1173 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1174 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1175 1176 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1177 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1178 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1179 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1180 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1181 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1182 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1184 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1185 #if defined(PETSC_HAVE_ELEMENTAL) 1186 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1187 #endif 1188 PetscFunctionReturn(0); 1189 } 1190 1191 #undef __FUNCT__ 1192 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1193 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1194 { 1195 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1196 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1197 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1198 PetscErrorCode ierr; 1199 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1200 int fd; 1201 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1202 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1203 PetscScalar *column_values; 1204 PetscInt message_count,flowcontrolcount; 1205 FILE *file; 1206 1207 PetscFunctionBegin; 1208 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1209 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1210 nz = A->nz + B->nz; 1211 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1212 if (!rank) { 1213 header[0] = MAT_FILE_CLASSID; 1214 header[1] = mat->rmap->N; 1215 header[2] = mat->cmap->N; 1216 1217 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1218 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1219 /* get largest number of rows any processor has */ 1220 rlen = mat->rmap->n; 1221 range = mat->rmap->range; 1222 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1223 } else { 1224 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1225 rlen = mat->rmap->n; 1226 } 1227 1228 /* load up the local row counts */ 1229 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1230 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]; 1231 1232 /* store the row lengths to the file */ 1233 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1234 if (!rank) { 1235 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1236 for (i=1; i<size; i++) { 1237 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1238 rlen = range[i+1] - range[i]; 1239 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1240 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1241 } 1242 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1243 } else { 1244 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1245 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1247 } 1248 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1249 1250 /* load up the local column indices */ 1251 nzmax = nz; /* th processor needs space a largest processor needs */ 1252 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1253 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1254 cnt = 0; 1255 for (i=0; i<mat->rmap->n; i++) { 1256 for (j=B->i[i]; j<B->i[i+1]; j++) { 1257 if ((col = garray[B->j[j]]) > cstart) break; 1258 column_indices[cnt++] = col; 1259 } 1260 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1261 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1262 } 1263 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); 1264 1265 /* store the column indices to the file */ 1266 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1267 if (!rank) { 1268 MPI_Status status; 1269 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1270 for (i=1; i<size; i++) { 1271 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1272 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1273 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1274 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1275 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1276 } 1277 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1278 } else { 1279 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1280 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1281 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1282 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1283 } 1284 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1285 1286 /* load up the local column values */ 1287 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1288 cnt = 0; 1289 for (i=0; i<mat->rmap->n; i++) { 1290 for (j=B->i[i]; j<B->i[i+1]; j++) { 1291 if (garray[B->j[j]] > cstart) break; 1292 column_values[cnt++] = B->a[j]; 1293 } 1294 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1295 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1296 } 1297 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); 1298 1299 /* store the column values to the file */ 1300 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1301 if (!rank) { 1302 MPI_Status status; 1303 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1304 for (i=1; i<size; i++) { 1305 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1306 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1307 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1308 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1309 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1310 } 1311 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1312 } else { 1313 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1314 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1315 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1316 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1317 } 1318 ierr = PetscFree(column_values);CHKERRQ(ierr); 1319 1320 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1321 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1322 PetscFunctionReturn(0); 1323 } 1324 1325 #include <petscdraw.h> 1326 #undef __FUNCT__ 1327 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1328 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1329 { 1330 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1331 PetscErrorCode ierr; 1332 PetscMPIInt rank = aij->rank,size = aij->size; 1333 PetscBool isdraw,iascii,isbinary; 1334 PetscViewer sviewer; 1335 PetscViewerFormat format; 1336 1337 PetscFunctionBegin; 1338 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1339 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1340 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1341 if (iascii) { 1342 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1343 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1344 MatInfo info; 1345 PetscBool inodes; 1346 1347 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1348 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1349 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1350 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1351 if (!inodes) { 1352 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1353 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1354 } else { 1355 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1356 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1357 } 1358 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1359 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1360 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1361 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1362 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1363 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1364 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1365 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1366 PetscFunctionReturn(0); 1367 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1368 PetscInt inodecount,inodelimit,*inodes; 1369 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1370 if (inodes) { 1371 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1372 } else { 1373 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1374 } 1375 PetscFunctionReturn(0); 1376 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1377 PetscFunctionReturn(0); 1378 } 1379 } else if (isbinary) { 1380 if (size == 1) { 1381 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1382 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1383 } else { 1384 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1385 } 1386 PetscFunctionReturn(0); 1387 } else if (isdraw) { 1388 PetscDraw draw; 1389 PetscBool isnull; 1390 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1391 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1392 if (isnull) PetscFunctionReturn(0); 1393 } 1394 1395 { 1396 /* assemble the entire matrix onto first processor. */ 1397 Mat A; 1398 Mat_SeqAIJ *Aloc; 1399 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1400 MatScalar *a; 1401 1402 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1403 if (!rank) { 1404 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1405 } else { 1406 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1407 } 1408 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1409 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1410 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1411 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1412 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1413 1414 /* copy over the A part */ 1415 Aloc = (Mat_SeqAIJ*)aij->A->data; 1416 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1417 row = mat->rmap->rstart; 1418 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1419 for (i=0; i<m; i++) { 1420 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1421 row++; 1422 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1423 } 1424 aj = Aloc->j; 1425 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1426 1427 /* copy over the B part */ 1428 Aloc = (Mat_SeqAIJ*)aij->B->data; 1429 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1430 row = mat->rmap->rstart; 1431 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1432 ct = cols; 1433 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1434 for (i=0; i<m; i++) { 1435 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1436 row++; 1437 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1438 } 1439 ierr = PetscFree(ct);CHKERRQ(ierr); 1440 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1441 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1442 /* 1443 Everyone has to call to draw the matrix since the graphics waits are 1444 synchronized across all processors that share the PetscDraw object 1445 */ 1446 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1447 if (!rank) { 1448 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1449 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1450 } 1451 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1452 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1453 ierr = MatDestroy(&A);CHKERRQ(ierr); 1454 } 1455 PetscFunctionReturn(0); 1456 } 1457 1458 #undef __FUNCT__ 1459 #define __FUNCT__ "MatView_MPIAIJ" 1460 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1461 { 1462 PetscErrorCode ierr; 1463 PetscBool iascii,isdraw,issocket,isbinary; 1464 1465 PetscFunctionBegin; 1466 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1467 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1468 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1469 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1470 if (iascii || isdraw || isbinary || issocket) { 1471 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1472 } 1473 PetscFunctionReturn(0); 1474 } 1475 1476 #undef __FUNCT__ 1477 #define __FUNCT__ "MatSOR_MPIAIJ" 1478 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1479 { 1480 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1481 PetscErrorCode ierr; 1482 Vec bb1 = 0; 1483 PetscBool hasop; 1484 1485 PetscFunctionBegin; 1486 if (flag == SOR_APPLY_UPPER) { 1487 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1488 PetscFunctionReturn(0); 1489 } 1490 1491 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1492 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1493 } 1494 1495 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1496 if (flag & SOR_ZERO_INITIAL_GUESS) { 1497 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1498 its--; 1499 } 1500 1501 while (its--) { 1502 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1503 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1504 1505 /* update rhs: bb1 = bb - B*x */ 1506 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1507 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1508 1509 /* local sweep */ 1510 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1511 } 1512 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1513 if (flag & SOR_ZERO_INITIAL_GUESS) { 1514 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1515 its--; 1516 } 1517 while (its--) { 1518 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1519 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1520 1521 /* update rhs: bb1 = bb - B*x */ 1522 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1523 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1524 1525 /* local sweep */ 1526 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1527 } 1528 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1529 if (flag & SOR_ZERO_INITIAL_GUESS) { 1530 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1531 its--; 1532 } 1533 while (its--) { 1534 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1535 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1536 1537 /* update rhs: bb1 = bb - B*x */ 1538 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1539 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1540 1541 /* local sweep */ 1542 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1543 } 1544 } else if (flag & SOR_EISENSTAT) { 1545 Vec xx1; 1546 1547 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1548 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1549 1550 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1551 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1552 if (!mat->diag) { 1553 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1554 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1555 } 1556 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1557 if (hasop) { 1558 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1559 } else { 1560 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1561 } 1562 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1563 1564 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1565 1566 /* local sweep */ 1567 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1568 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1569 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1570 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1571 1572 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1573 1574 matin->errortype = mat->A->errortype; 1575 PetscFunctionReturn(0); 1576 } 1577 1578 #undef __FUNCT__ 1579 #define __FUNCT__ "MatPermute_MPIAIJ" 1580 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1581 { 1582 Mat aA,aB,Aperm; 1583 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1584 PetscScalar *aa,*ba; 1585 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1586 PetscSF rowsf,sf; 1587 IS parcolp = NULL; 1588 PetscBool done; 1589 PetscErrorCode ierr; 1590 1591 PetscFunctionBegin; 1592 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1593 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1594 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1595 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1596 1597 /* Invert row permutation to find out where my rows should go */ 1598 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1599 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1600 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1601 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1602 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1603 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1604 1605 /* Invert column permutation to find out where my columns should go */ 1606 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1607 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1608 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1609 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1610 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1611 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1612 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1613 1614 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1615 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1616 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1617 1618 /* Find out where my gcols should go */ 1619 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1620 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1621 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1622 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1623 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1624 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1625 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1626 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1627 1628 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1629 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1630 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1631 for (i=0; i<m; i++) { 1632 PetscInt row = rdest[i],rowner; 1633 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1634 for (j=ai[i]; j<ai[i+1]; j++) { 1635 PetscInt cowner,col = cdest[aj[j]]; 1636 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1637 if (rowner == cowner) dnnz[i]++; 1638 else onnz[i]++; 1639 } 1640 for (j=bi[i]; j<bi[i+1]; j++) { 1641 PetscInt cowner,col = gcdest[bj[j]]; 1642 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1643 if (rowner == cowner) dnnz[i]++; 1644 else onnz[i]++; 1645 } 1646 } 1647 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1648 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1649 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1650 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1651 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1652 1653 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1654 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1655 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1656 for (i=0; i<m; i++) { 1657 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1658 PetscInt j0,rowlen; 1659 rowlen = ai[i+1] - ai[i]; 1660 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1661 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1662 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1663 } 1664 rowlen = bi[i+1] - bi[i]; 1665 for (j0=j=0; j<rowlen; j0=j) { 1666 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1667 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1668 } 1669 } 1670 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1671 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1672 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1673 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1674 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1675 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1676 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1677 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1678 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1679 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1680 *B = Aperm; 1681 PetscFunctionReturn(0); 1682 } 1683 1684 #undef __FUNCT__ 1685 #define __FUNCT__ "MatGetGhosts_MPIAIJ" 1686 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1687 { 1688 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1689 PetscErrorCode ierr; 1690 1691 PetscFunctionBegin; 1692 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1693 if (ghosts) *ghosts = aij->garray; 1694 PetscFunctionReturn(0); 1695 } 1696 1697 #undef __FUNCT__ 1698 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1699 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1700 { 1701 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1702 Mat A = mat->A,B = mat->B; 1703 PetscErrorCode ierr; 1704 PetscReal isend[5],irecv[5]; 1705 1706 PetscFunctionBegin; 1707 info->block_size = 1.0; 1708 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1709 1710 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1711 isend[3] = info->memory; isend[4] = info->mallocs; 1712 1713 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1714 1715 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1716 isend[3] += info->memory; isend[4] += info->mallocs; 1717 if (flag == MAT_LOCAL) { 1718 info->nz_used = isend[0]; 1719 info->nz_allocated = isend[1]; 1720 info->nz_unneeded = isend[2]; 1721 info->memory = isend[3]; 1722 info->mallocs = isend[4]; 1723 } else if (flag == MAT_GLOBAL_MAX) { 1724 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1725 1726 info->nz_used = irecv[0]; 1727 info->nz_allocated = irecv[1]; 1728 info->nz_unneeded = irecv[2]; 1729 info->memory = irecv[3]; 1730 info->mallocs = irecv[4]; 1731 } else if (flag == MAT_GLOBAL_SUM) { 1732 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1733 1734 info->nz_used = irecv[0]; 1735 info->nz_allocated = irecv[1]; 1736 info->nz_unneeded = irecv[2]; 1737 info->memory = irecv[3]; 1738 info->mallocs = irecv[4]; 1739 } 1740 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1741 info->fill_ratio_needed = 0; 1742 info->factor_mallocs = 0; 1743 PetscFunctionReturn(0); 1744 } 1745 1746 #undef __FUNCT__ 1747 #define __FUNCT__ "MatSetOption_MPIAIJ" 1748 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1749 { 1750 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1751 PetscErrorCode ierr; 1752 1753 PetscFunctionBegin; 1754 switch (op) { 1755 case MAT_NEW_NONZERO_LOCATIONS: 1756 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1757 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1758 case MAT_KEEP_NONZERO_PATTERN: 1759 case MAT_NEW_NONZERO_LOCATION_ERR: 1760 case MAT_USE_INODES: 1761 case MAT_IGNORE_ZERO_ENTRIES: 1762 MatCheckPreallocated(A,1); 1763 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1764 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1765 break; 1766 case MAT_ROW_ORIENTED: 1767 MatCheckPreallocated(A,1); 1768 a->roworiented = flg; 1769 1770 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1771 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1772 break; 1773 case MAT_NEW_DIAGONALS: 1774 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1775 break; 1776 case MAT_IGNORE_OFF_PROC_ENTRIES: 1777 a->donotstash = flg; 1778 break; 1779 case MAT_SPD: 1780 A->spd_set = PETSC_TRUE; 1781 A->spd = flg; 1782 if (flg) { 1783 A->symmetric = PETSC_TRUE; 1784 A->structurally_symmetric = PETSC_TRUE; 1785 A->symmetric_set = PETSC_TRUE; 1786 A->structurally_symmetric_set = PETSC_TRUE; 1787 } 1788 break; 1789 case MAT_SYMMETRIC: 1790 MatCheckPreallocated(A,1); 1791 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1792 break; 1793 case MAT_STRUCTURALLY_SYMMETRIC: 1794 MatCheckPreallocated(A,1); 1795 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1796 break; 1797 case MAT_HERMITIAN: 1798 MatCheckPreallocated(A,1); 1799 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1800 break; 1801 case MAT_SYMMETRY_ETERNAL: 1802 MatCheckPreallocated(A,1); 1803 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1804 break; 1805 default: 1806 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1807 } 1808 PetscFunctionReturn(0); 1809 } 1810 1811 #undef __FUNCT__ 1812 #define __FUNCT__ "MatGetRow_MPIAIJ" 1813 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1814 { 1815 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1816 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1817 PetscErrorCode ierr; 1818 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1819 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1820 PetscInt *cmap,*idx_p; 1821 1822 PetscFunctionBegin; 1823 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1824 mat->getrowactive = PETSC_TRUE; 1825 1826 if (!mat->rowvalues && (idx || v)) { 1827 /* 1828 allocate enough space to hold information from the longest row. 1829 */ 1830 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1831 PetscInt max = 1,tmp; 1832 for (i=0; i<matin->rmap->n; i++) { 1833 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1834 if (max < tmp) max = tmp; 1835 } 1836 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1837 } 1838 1839 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1840 lrow = row - rstart; 1841 1842 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1843 if (!v) {pvA = 0; pvB = 0;} 1844 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1845 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1846 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1847 nztot = nzA + nzB; 1848 1849 cmap = mat->garray; 1850 if (v || idx) { 1851 if (nztot) { 1852 /* Sort by increasing column numbers, assuming A and B already sorted */ 1853 PetscInt imark = -1; 1854 if (v) { 1855 *v = v_p = mat->rowvalues; 1856 for (i=0; i<nzB; i++) { 1857 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1858 else break; 1859 } 1860 imark = i; 1861 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1862 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1863 } 1864 if (idx) { 1865 *idx = idx_p = mat->rowindices; 1866 if (imark > -1) { 1867 for (i=0; i<imark; i++) { 1868 idx_p[i] = cmap[cworkB[i]]; 1869 } 1870 } else { 1871 for (i=0; i<nzB; i++) { 1872 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1873 else break; 1874 } 1875 imark = i; 1876 } 1877 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1878 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1879 } 1880 } else { 1881 if (idx) *idx = 0; 1882 if (v) *v = 0; 1883 } 1884 } 1885 *nz = nztot; 1886 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1887 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1888 PetscFunctionReturn(0); 1889 } 1890 1891 #undef __FUNCT__ 1892 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1893 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1894 { 1895 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1896 1897 PetscFunctionBegin; 1898 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1899 aij->getrowactive = PETSC_FALSE; 1900 PetscFunctionReturn(0); 1901 } 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "MatNorm_MPIAIJ" 1905 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1906 { 1907 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1908 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1909 PetscErrorCode ierr; 1910 PetscInt i,j,cstart = mat->cmap->rstart; 1911 PetscReal sum = 0.0; 1912 MatScalar *v; 1913 1914 PetscFunctionBegin; 1915 if (aij->size == 1) { 1916 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1917 } else { 1918 if (type == NORM_FROBENIUS) { 1919 v = amat->a; 1920 for (i=0; i<amat->nz; i++) { 1921 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1922 } 1923 v = bmat->a; 1924 for (i=0; i<bmat->nz; i++) { 1925 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1926 } 1927 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1928 *norm = PetscSqrtReal(*norm); 1929 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1930 } else if (type == NORM_1) { /* max column norm */ 1931 PetscReal *tmp,*tmp2; 1932 PetscInt *jj,*garray = aij->garray; 1933 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1934 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1935 *norm = 0.0; 1936 v = amat->a; jj = amat->j; 1937 for (j=0; j<amat->nz; j++) { 1938 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1939 } 1940 v = bmat->a; jj = bmat->j; 1941 for (j=0; j<bmat->nz; j++) { 1942 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1943 } 1944 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1945 for (j=0; j<mat->cmap->N; j++) { 1946 if (tmp2[j] > *norm) *norm = tmp2[j]; 1947 } 1948 ierr = PetscFree(tmp);CHKERRQ(ierr); 1949 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1950 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1951 } else if (type == NORM_INFINITY) { /* max row norm */ 1952 PetscReal ntemp = 0.0; 1953 for (j=0; j<aij->A->rmap->n; j++) { 1954 v = amat->a + amat->i[j]; 1955 sum = 0.0; 1956 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1957 sum += PetscAbsScalar(*v); v++; 1958 } 1959 v = bmat->a + bmat->i[j]; 1960 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1961 sum += PetscAbsScalar(*v); v++; 1962 } 1963 if (sum > ntemp) ntemp = sum; 1964 } 1965 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1966 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1967 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1968 } 1969 PetscFunctionReturn(0); 1970 } 1971 1972 #undef __FUNCT__ 1973 #define __FUNCT__ "MatTranspose_MPIAIJ" 1974 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1975 { 1976 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1977 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1978 PetscErrorCode ierr; 1979 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1980 PetscInt cstart = A->cmap->rstart,ncol; 1981 Mat B; 1982 MatScalar *array; 1983 1984 PetscFunctionBegin; 1985 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1986 1987 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1988 ai = Aloc->i; aj = Aloc->j; 1989 bi = Bloc->i; bj = Bloc->j; 1990 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1991 PetscInt *d_nnz,*g_nnz,*o_nnz; 1992 PetscSFNode *oloc; 1993 PETSC_UNUSED PetscSF sf; 1994 1995 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1996 /* compute d_nnz for preallocation */ 1997 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1998 for (i=0; i<ai[ma]; i++) { 1999 d_nnz[aj[i]]++; 2000 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2001 } 2002 /* compute local off-diagonal contributions */ 2003 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2004 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2005 /* map those to global */ 2006 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2007 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2008 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2009 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2010 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2011 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2012 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2013 2014 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2015 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2016 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2017 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2018 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2019 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2020 } else { 2021 B = *matout; 2022 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2023 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2024 } 2025 2026 /* copy over the A part */ 2027 array = Aloc->a; 2028 row = A->rmap->rstart; 2029 for (i=0; i<ma; i++) { 2030 ncol = ai[i+1]-ai[i]; 2031 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2032 row++; 2033 array += ncol; aj += ncol; 2034 } 2035 aj = Aloc->j; 2036 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2037 2038 /* copy over the B part */ 2039 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2040 array = Bloc->a; 2041 row = A->rmap->rstart; 2042 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2043 cols_tmp = cols; 2044 for (i=0; i<mb; i++) { 2045 ncol = bi[i+1]-bi[i]; 2046 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2047 row++; 2048 array += ncol; cols_tmp += ncol; 2049 } 2050 ierr = PetscFree(cols);CHKERRQ(ierr); 2051 2052 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2053 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2054 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2055 *matout = B; 2056 } else { 2057 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 2058 } 2059 PetscFunctionReturn(0); 2060 } 2061 2062 #undef __FUNCT__ 2063 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2064 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2065 { 2066 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2067 Mat a = aij->A,b = aij->B; 2068 PetscErrorCode ierr; 2069 PetscInt s1,s2,s3; 2070 2071 PetscFunctionBegin; 2072 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2073 if (rr) { 2074 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2075 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2076 /* Overlap communication with computation. */ 2077 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2078 } 2079 if (ll) { 2080 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2081 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2082 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2083 } 2084 /* scale the diagonal block */ 2085 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2086 2087 if (rr) { 2088 /* Do a scatter end and then right scale the off-diagonal block */ 2089 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2090 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2091 } 2092 PetscFunctionReturn(0); 2093 } 2094 2095 #undef __FUNCT__ 2096 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2097 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2098 { 2099 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2100 PetscErrorCode ierr; 2101 2102 PetscFunctionBegin; 2103 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2104 PetscFunctionReturn(0); 2105 } 2106 2107 #undef __FUNCT__ 2108 #define __FUNCT__ "MatEqual_MPIAIJ" 2109 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2110 { 2111 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2112 Mat a,b,c,d; 2113 PetscBool flg; 2114 PetscErrorCode ierr; 2115 2116 PetscFunctionBegin; 2117 a = matA->A; b = matA->B; 2118 c = matB->A; d = matB->B; 2119 2120 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2121 if (flg) { 2122 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2123 } 2124 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatCopy_MPIAIJ" 2130 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2131 { 2132 PetscErrorCode ierr; 2133 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2134 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2135 2136 PetscFunctionBegin; 2137 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2138 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2139 /* because of the column compression in the off-processor part of the matrix a->B, 2140 the number of columns in a->B and b->B may be different, hence we cannot call 2141 the MatCopy() directly on the two parts. If need be, we can provide a more 2142 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2143 then copying the submatrices */ 2144 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2145 } else { 2146 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2147 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2148 } 2149 PetscFunctionReturn(0); 2150 } 2151 2152 #undef __FUNCT__ 2153 #define __FUNCT__ "MatSetUp_MPIAIJ" 2154 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2155 { 2156 PetscErrorCode ierr; 2157 2158 PetscFunctionBegin; 2159 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2160 PetscFunctionReturn(0); 2161 } 2162 2163 /* 2164 Computes the number of nonzeros per row needed for preallocation when X and Y 2165 have different nonzero structure. 2166 */ 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2169 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) 2170 { 2171 PetscInt i,j,k,nzx,nzy; 2172 2173 PetscFunctionBegin; 2174 /* Set the number of nonzeros in the new matrix */ 2175 for (i=0; i<m; i++) { 2176 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2177 nzx = xi[i+1] - xi[i]; 2178 nzy = yi[i+1] - yi[i]; 2179 nnz[i] = 0; 2180 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2181 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2182 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2183 nnz[i]++; 2184 } 2185 for (; k<nzy; k++) nnz[i]++; 2186 } 2187 PetscFunctionReturn(0); 2188 } 2189 2190 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2191 #undef __FUNCT__ 2192 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2193 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2194 { 2195 PetscErrorCode ierr; 2196 PetscInt m = Y->rmap->N; 2197 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2198 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2199 2200 PetscFunctionBegin; 2201 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2202 PetscFunctionReturn(0); 2203 } 2204 2205 #undef __FUNCT__ 2206 #define __FUNCT__ "MatAXPY_MPIAIJ" 2207 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2208 { 2209 PetscErrorCode ierr; 2210 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2211 PetscBLASInt bnz,one=1; 2212 Mat_SeqAIJ *x,*y; 2213 2214 PetscFunctionBegin; 2215 if (str == SAME_NONZERO_PATTERN) { 2216 PetscScalar alpha = a; 2217 x = (Mat_SeqAIJ*)xx->A->data; 2218 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2219 y = (Mat_SeqAIJ*)yy->A->data; 2220 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2221 x = (Mat_SeqAIJ*)xx->B->data; 2222 y = (Mat_SeqAIJ*)yy->B->data; 2223 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2224 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2225 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2226 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2227 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2228 } else { 2229 Mat B; 2230 PetscInt *nnz_d,*nnz_o; 2231 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2232 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2233 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2234 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2235 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2236 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2237 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2238 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2239 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2240 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2241 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2242 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2243 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2244 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2245 } 2246 PetscFunctionReturn(0); 2247 } 2248 2249 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2250 2251 #undef __FUNCT__ 2252 #define __FUNCT__ "MatConjugate_MPIAIJ" 2253 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2254 { 2255 #if defined(PETSC_USE_COMPLEX) 2256 PetscErrorCode ierr; 2257 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2258 2259 PetscFunctionBegin; 2260 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2261 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2262 #else 2263 PetscFunctionBegin; 2264 #endif 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatRealPart_MPIAIJ" 2270 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2271 { 2272 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2273 PetscErrorCode ierr; 2274 2275 PetscFunctionBegin; 2276 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2277 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2278 PetscFunctionReturn(0); 2279 } 2280 2281 #undef __FUNCT__ 2282 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2283 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2284 { 2285 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2286 PetscErrorCode ierr; 2287 2288 PetscFunctionBegin; 2289 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2290 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2296 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2297 { 2298 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2299 PetscErrorCode ierr; 2300 PetscInt i,*idxb = 0; 2301 PetscScalar *va,*vb; 2302 Vec vtmp; 2303 2304 PetscFunctionBegin; 2305 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2306 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2307 if (idx) { 2308 for (i=0; i<A->rmap->n; i++) { 2309 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2310 } 2311 } 2312 2313 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2314 if (idx) { 2315 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2316 } 2317 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2318 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2319 2320 for (i=0; i<A->rmap->n; i++) { 2321 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2322 va[i] = vb[i]; 2323 if (idx) idx[i] = a->garray[idxb[i]]; 2324 } 2325 } 2326 2327 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2328 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2329 ierr = PetscFree(idxb);CHKERRQ(ierr); 2330 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2331 PetscFunctionReturn(0); 2332 } 2333 2334 #undef __FUNCT__ 2335 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2336 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2337 { 2338 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2339 PetscErrorCode ierr; 2340 PetscInt i,*idxb = 0; 2341 PetscScalar *va,*vb; 2342 Vec vtmp; 2343 2344 PetscFunctionBegin; 2345 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2346 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2347 if (idx) { 2348 for (i=0; i<A->cmap->n; i++) { 2349 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2350 } 2351 } 2352 2353 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2354 if (idx) { 2355 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2356 } 2357 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2358 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2359 2360 for (i=0; i<A->rmap->n; i++) { 2361 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2362 va[i] = vb[i]; 2363 if (idx) idx[i] = a->garray[idxb[i]]; 2364 } 2365 } 2366 2367 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2368 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2369 ierr = PetscFree(idxb);CHKERRQ(ierr); 2370 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2371 PetscFunctionReturn(0); 2372 } 2373 2374 #undef __FUNCT__ 2375 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2376 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2377 { 2378 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2379 PetscInt n = A->rmap->n; 2380 PetscInt cstart = A->cmap->rstart; 2381 PetscInt *cmap = mat->garray; 2382 PetscInt *diagIdx, *offdiagIdx; 2383 Vec diagV, offdiagV; 2384 PetscScalar *a, *diagA, *offdiagA; 2385 PetscInt r; 2386 PetscErrorCode ierr; 2387 2388 PetscFunctionBegin; 2389 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2390 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2391 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2392 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2393 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2394 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2395 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2396 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2397 for (r = 0; r < n; ++r) { 2398 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2399 a[r] = diagA[r]; 2400 idx[r] = cstart + diagIdx[r]; 2401 } else { 2402 a[r] = offdiagA[r]; 2403 idx[r] = cmap[offdiagIdx[r]]; 2404 } 2405 } 2406 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2407 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2408 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2409 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2410 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2411 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2412 PetscFunctionReturn(0); 2413 } 2414 2415 #undef __FUNCT__ 2416 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2417 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2418 { 2419 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2420 PetscInt n = A->rmap->n; 2421 PetscInt cstart = A->cmap->rstart; 2422 PetscInt *cmap = mat->garray; 2423 PetscInt *diagIdx, *offdiagIdx; 2424 Vec diagV, offdiagV; 2425 PetscScalar *a, *diagA, *offdiagA; 2426 PetscInt r; 2427 PetscErrorCode ierr; 2428 2429 PetscFunctionBegin; 2430 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2431 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2432 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2433 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2434 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2435 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2436 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2437 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2438 for (r = 0; r < n; ++r) { 2439 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2440 a[r] = diagA[r]; 2441 idx[r] = cstart + diagIdx[r]; 2442 } else { 2443 a[r] = offdiagA[r]; 2444 idx[r] = cmap[offdiagIdx[r]]; 2445 } 2446 } 2447 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2448 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2449 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2450 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2451 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2452 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2458 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2459 { 2460 PetscErrorCode ierr; 2461 Mat *dummy; 2462 2463 PetscFunctionBegin; 2464 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2465 *newmat = *dummy; 2466 ierr = PetscFree(dummy);CHKERRQ(ierr); 2467 PetscFunctionReturn(0); 2468 } 2469 2470 #undef __FUNCT__ 2471 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2472 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2473 { 2474 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2475 PetscErrorCode ierr; 2476 2477 PetscFunctionBegin; 2478 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2479 A->errortype = a->A->errortype; 2480 PetscFunctionReturn(0); 2481 } 2482 2483 #undef __FUNCT__ 2484 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2485 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2486 { 2487 PetscErrorCode ierr; 2488 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2489 2490 PetscFunctionBegin; 2491 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2492 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2493 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2494 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2495 PetscFunctionReturn(0); 2496 } 2497 2498 #undef __FUNCT__ 2499 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ" 2500 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2501 { 2502 PetscFunctionBegin; 2503 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2504 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2505 PetscFunctionReturn(0); 2506 } 2507 2508 #undef __FUNCT__ 2509 #define __FUNCT__ "MatMPIAIJSetUseScalableIncreaseOverlap" 2510 /*@ 2511 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2512 2513 Collective on Mat 2514 2515 Input Parameters: 2516 + A - the matrix 2517 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2518 2519 Level: advanced 2520 2521 @*/ 2522 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2523 { 2524 PetscErrorCode ierr; 2525 2526 PetscFunctionBegin; 2527 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2528 PetscFunctionReturn(0); 2529 } 2530 2531 #undef __FUNCT__ 2532 #define __FUNCT__ "MatSetFromOptions_MPIAIJ" 2533 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2534 { 2535 PetscErrorCode ierr; 2536 PetscBool sc = PETSC_FALSE,flg; 2537 2538 PetscFunctionBegin; 2539 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2540 ierr = PetscObjectOptionsBegin((PetscObject)A); 2541 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2542 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2543 if (flg) { 2544 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2545 } 2546 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2547 PetscFunctionReturn(0); 2548 } 2549 2550 #undef __FUNCT__ 2551 #define __FUNCT__ "MatShift_MPIAIJ" 2552 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2553 { 2554 PetscErrorCode ierr; 2555 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2556 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2557 2558 PetscFunctionBegin; 2559 if (!Y->preallocated) { 2560 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2561 } else if (!aij->nz) { 2562 PetscInt nonew = aij->nonew; 2563 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2564 aij->nonew = nonew; 2565 } 2566 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2567 PetscFunctionReturn(0); 2568 } 2569 2570 #undef __FUNCT__ 2571 #define __FUNCT__ "MatMissingDiagonal_MPIAIJ" 2572 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2573 { 2574 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2575 PetscErrorCode ierr; 2576 2577 PetscFunctionBegin; 2578 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2579 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2580 if (d) { 2581 PetscInt rstart; 2582 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2583 *d += rstart; 2584 2585 } 2586 PetscFunctionReturn(0); 2587 } 2588 2589 2590 /* -------------------------------------------------------------------*/ 2591 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2592 MatGetRow_MPIAIJ, 2593 MatRestoreRow_MPIAIJ, 2594 MatMult_MPIAIJ, 2595 /* 4*/ MatMultAdd_MPIAIJ, 2596 MatMultTranspose_MPIAIJ, 2597 MatMultTransposeAdd_MPIAIJ, 2598 0, 2599 0, 2600 0, 2601 /*10*/ 0, 2602 0, 2603 0, 2604 MatSOR_MPIAIJ, 2605 MatTranspose_MPIAIJ, 2606 /*15*/ MatGetInfo_MPIAIJ, 2607 MatEqual_MPIAIJ, 2608 MatGetDiagonal_MPIAIJ, 2609 MatDiagonalScale_MPIAIJ, 2610 MatNorm_MPIAIJ, 2611 /*20*/ MatAssemblyBegin_MPIAIJ, 2612 MatAssemblyEnd_MPIAIJ, 2613 MatSetOption_MPIAIJ, 2614 MatZeroEntries_MPIAIJ, 2615 /*24*/ MatZeroRows_MPIAIJ, 2616 0, 2617 0, 2618 0, 2619 0, 2620 /*29*/ MatSetUp_MPIAIJ, 2621 0, 2622 0, 2623 0, 2624 0, 2625 /*34*/ MatDuplicate_MPIAIJ, 2626 0, 2627 0, 2628 0, 2629 0, 2630 /*39*/ MatAXPY_MPIAIJ, 2631 MatGetSubMatrices_MPIAIJ, 2632 MatIncreaseOverlap_MPIAIJ, 2633 MatGetValues_MPIAIJ, 2634 MatCopy_MPIAIJ, 2635 /*44*/ MatGetRowMax_MPIAIJ, 2636 MatScale_MPIAIJ, 2637 MatShift_MPIAIJ, 2638 MatDiagonalSet_MPIAIJ, 2639 MatZeroRowsColumns_MPIAIJ, 2640 /*49*/ MatSetRandom_MPIAIJ, 2641 0, 2642 0, 2643 0, 2644 0, 2645 /*54*/ MatFDColoringCreate_MPIXAIJ, 2646 0, 2647 MatSetUnfactored_MPIAIJ, 2648 MatPermute_MPIAIJ, 2649 0, 2650 /*59*/ MatGetSubMatrix_MPIAIJ, 2651 MatDestroy_MPIAIJ, 2652 MatView_MPIAIJ, 2653 0, 2654 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2655 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2656 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2657 0, 2658 0, 2659 0, 2660 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2661 MatGetRowMinAbs_MPIAIJ, 2662 0, 2663 MatSetColoring_MPIAIJ, 2664 0, 2665 MatSetValuesAdifor_MPIAIJ, 2666 /*75*/ MatFDColoringApply_AIJ, 2667 MatSetFromOptions_MPIAIJ, 2668 0, 2669 0, 2670 MatFindZeroDiagonals_MPIAIJ, 2671 /*80*/ 0, 2672 0, 2673 0, 2674 /*83*/ MatLoad_MPIAIJ, 2675 0, 2676 0, 2677 0, 2678 0, 2679 0, 2680 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2681 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2682 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2683 MatPtAP_MPIAIJ_MPIAIJ, 2684 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2685 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2686 0, 2687 0, 2688 0, 2689 0, 2690 /*99*/ 0, 2691 0, 2692 0, 2693 MatConjugate_MPIAIJ, 2694 0, 2695 /*104*/MatSetValuesRow_MPIAIJ, 2696 MatRealPart_MPIAIJ, 2697 MatImaginaryPart_MPIAIJ, 2698 0, 2699 0, 2700 /*109*/0, 2701 0, 2702 MatGetRowMin_MPIAIJ, 2703 0, 2704 MatMissingDiagonal_MPIAIJ, 2705 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2706 0, 2707 MatGetGhosts_MPIAIJ, 2708 0, 2709 0, 2710 /*119*/0, 2711 0, 2712 0, 2713 0, 2714 MatGetMultiProcBlock_MPIAIJ, 2715 /*124*/MatFindNonzeroRows_MPIAIJ, 2716 MatGetColumnNorms_MPIAIJ, 2717 MatInvertBlockDiagonal_MPIAIJ, 2718 0, 2719 MatGetSubMatricesMPI_MPIAIJ, 2720 /*129*/0, 2721 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2722 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2723 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2724 0, 2725 /*134*/0, 2726 0, 2727 0, 2728 0, 2729 0, 2730 /*139*/0, 2731 0, 2732 0, 2733 MatFDColoringSetUp_MPIXAIJ, 2734 MatFindOffBlockDiagonalEntries_MPIAIJ, 2735 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2736 }; 2737 2738 /* ----------------------------------------------------------------------------------------*/ 2739 2740 #undef __FUNCT__ 2741 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2742 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2743 { 2744 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2745 PetscErrorCode ierr; 2746 2747 PetscFunctionBegin; 2748 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2749 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2750 PetscFunctionReturn(0); 2751 } 2752 2753 #undef __FUNCT__ 2754 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2755 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2756 { 2757 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2758 PetscErrorCode ierr; 2759 2760 PetscFunctionBegin; 2761 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2762 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2763 PetscFunctionReturn(0); 2764 } 2765 2766 #undef __FUNCT__ 2767 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2768 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2769 { 2770 Mat_MPIAIJ *b; 2771 PetscErrorCode ierr; 2772 2773 PetscFunctionBegin; 2774 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2775 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2776 b = (Mat_MPIAIJ*)B->data; 2777 2778 if (!B->preallocated) { 2779 /* Explicitly create 2 MATSEQAIJ matrices. */ 2780 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2781 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2782 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2783 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2784 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2785 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2786 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2787 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2788 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2789 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2790 } 2791 2792 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2793 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2794 B->preallocated = PETSC_TRUE; 2795 PetscFunctionReturn(0); 2796 } 2797 2798 #undef __FUNCT__ 2799 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2800 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2801 { 2802 Mat mat; 2803 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2804 PetscErrorCode ierr; 2805 2806 PetscFunctionBegin; 2807 *newmat = 0; 2808 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2809 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2810 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2811 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2812 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2813 a = (Mat_MPIAIJ*)mat->data; 2814 2815 mat->factortype = matin->factortype; 2816 mat->assembled = PETSC_TRUE; 2817 mat->insertmode = NOT_SET_VALUES; 2818 mat->preallocated = PETSC_TRUE; 2819 2820 a->size = oldmat->size; 2821 a->rank = oldmat->rank; 2822 a->donotstash = oldmat->donotstash; 2823 a->roworiented = oldmat->roworiented; 2824 a->rowindices = 0; 2825 a->rowvalues = 0; 2826 a->getrowactive = PETSC_FALSE; 2827 2828 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2829 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2830 2831 if (oldmat->colmap) { 2832 #if defined(PETSC_USE_CTABLE) 2833 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2834 #else 2835 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2836 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2837 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2838 #endif 2839 } else a->colmap = 0; 2840 if (oldmat->garray) { 2841 PetscInt len; 2842 len = oldmat->B->cmap->n; 2843 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2844 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2845 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2846 } else a->garray = 0; 2847 2848 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2849 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2850 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2851 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2852 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2853 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2854 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2855 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2856 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2857 *newmat = mat; 2858 PetscFunctionReturn(0); 2859 } 2860 2861 2862 2863 #undef __FUNCT__ 2864 #define __FUNCT__ "MatLoad_MPIAIJ" 2865 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2866 { 2867 PetscScalar *vals,*svals; 2868 MPI_Comm comm; 2869 PetscErrorCode ierr; 2870 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2871 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2872 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2873 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2874 PetscInt cend,cstart,n,*rowners; 2875 int fd; 2876 PetscInt bs = newMat->rmap->bs; 2877 2878 PetscFunctionBegin; 2879 /* force binary viewer to load .info file if it has not yet done so */ 2880 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2881 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2882 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2883 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2884 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2885 if (!rank) { 2886 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2887 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2888 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MPIAIJ"); 2889 } 2890 2891 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");CHKERRQ(ierr); 2892 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2893 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2894 if (bs < 0) bs = 1; 2895 2896 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2897 M = header[1]; N = header[2]; 2898 2899 /* If global sizes are set, check if they are consistent with that given in the file */ 2900 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); 2901 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); 2902 2903 /* determine ownership of all (block) rows */ 2904 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2905 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2906 else m = newMat->rmap->n; /* Set by user */ 2907 2908 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2909 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2910 2911 /* First process needs enough room for process with most rows */ 2912 if (!rank) { 2913 mmax = rowners[1]; 2914 for (i=2; i<=size; i++) { 2915 mmax = PetscMax(mmax, rowners[i]); 2916 } 2917 } else mmax = -1; /* unused, but compilers complain */ 2918 2919 rowners[0] = 0; 2920 for (i=2; i<=size; i++) { 2921 rowners[i] += rowners[i-1]; 2922 } 2923 rstart = rowners[rank]; 2924 rend = rowners[rank+1]; 2925 2926 /* distribute row lengths to all processors */ 2927 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2928 if (!rank) { 2929 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2930 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2931 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2932 for (j=0; j<m; j++) { 2933 procsnz[0] += ourlens[j]; 2934 } 2935 for (i=1; i<size; i++) { 2936 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2937 /* calculate the number of nonzeros on each processor */ 2938 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2939 procsnz[i] += rowlengths[j]; 2940 } 2941 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2942 } 2943 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2944 } else { 2945 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2946 } 2947 2948 if (!rank) { 2949 /* determine max buffer needed and allocate it */ 2950 maxnz = 0; 2951 for (i=0; i<size; i++) { 2952 maxnz = PetscMax(maxnz,procsnz[i]); 2953 } 2954 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2955 2956 /* read in my part of the matrix column indices */ 2957 nz = procsnz[0]; 2958 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2959 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2960 2961 /* read in every one elses and ship off */ 2962 for (i=1; i<size; i++) { 2963 nz = procsnz[i]; 2964 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2965 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2966 } 2967 ierr = PetscFree(cols);CHKERRQ(ierr); 2968 } else { 2969 /* determine buffer space needed for message */ 2970 nz = 0; 2971 for (i=0; i<m; i++) { 2972 nz += ourlens[i]; 2973 } 2974 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2975 2976 /* receive message of column indices*/ 2977 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2978 } 2979 2980 /* determine column ownership if matrix is not square */ 2981 if (N != M) { 2982 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2983 else n = newMat->cmap->n; 2984 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2985 cstart = cend - n; 2986 } else { 2987 cstart = rstart; 2988 cend = rend; 2989 n = cend - cstart; 2990 } 2991 2992 /* loop over local rows, determining number of off diagonal entries */ 2993 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2994 jj = 0; 2995 for (i=0; i<m; i++) { 2996 for (j=0; j<ourlens[i]; j++) { 2997 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2998 jj++; 2999 } 3000 } 3001 3002 for (i=0; i<m; i++) { 3003 ourlens[i] -= offlens[i]; 3004 } 3005 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3006 3007 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3008 3009 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3010 3011 for (i=0; i<m; i++) { 3012 ourlens[i] += offlens[i]; 3013 } 3014 3015 if (!rank) { 3016 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 3017 3018 /* read in my part of the matrix numerical values */ 3019 nz = procsnz[0]; 3020 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3021 3022 /* insert into matrix */ 3023 jj = rstart; 3024 smycols = mycols; 3025 svals = vals; 3026 for (i=0; i<m; i++) { 3027 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3028 smycols += ourlens[i]; 3029 svals += ourlens[i]; 3030 jj++; 3031 } 3032 3033 /* read in other processors and ship out */ 3034 for (i=1; i<size; i++) { 3035 nz = procsnz[i]; 3036 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3037 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3038 } 3039 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3040 } else { 3041 /* receive numeric values */ 3042 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 3043 3044 /* receive message of values*/ 3045 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3046 3047 /* insert into matrix */ 3048 jj = rstart; 3049 smycols = mycols; 3050 svals = vals; 3051 for (i=0; i<m; i++) { 3052 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3053 smycols += ourlens[i]; 3054 svals += ourlens[i]; 3055 jj++; 3056 } 3057 } 3058 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3059 ierr = PetscFree(vals);CHKERRQ(ierr); 3060 ierr = PetscFree(mycols);CHKERRQ(ierr); 3061 ierr = PetscFree(rowners);CHKERRQ(ierr); 3062 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3063 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3064 PetscFunctionReturn(0); 3065 } 3066 3067 #undef __FUNCT__ 3068 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3069 /* TODO: Not scalable because of ISAllGather() unless getting all columns. */ 3070 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3071 { 3072 PetscErrorCode ierr; 3073 IS iscol_local; 3074 PetscInt csize; 3075 3076 PetscFunctionBegin; 3077 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3078 if (call == MAT_REUSE_MATRIX) { 3079 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3080 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3081 } else { 3082 /* check if we are grabbing all columns*/ 3083 PetscBool isstride; 3084 PetscMPIInt lisstride = 0,gisstride; 3085 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 3086 if (isstride) { 3087 PetscInt start,len,mstart,mlen; 3088 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 3089 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 3090 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 3091 if (mstart == start && mlen-mstart == len) lisstride = 1; 3092 } 3093 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 3094 if (gisstride) { 3095 PetscInt N; 3096 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 3097 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 3098 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 3099 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 3100 } else { 3101 PetscInt cbs; 3102 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3103 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3104 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3105 } 3106 } 3107 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3108 if (call == MAT_INITIAL_MATRIX) { 3109 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3110 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3111 } 3112 PetscFunctionReturn(0); 3113 } 3114 3115 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3116 #undef __FUNCT__ 3117 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3118 /* 3119 Not great since it makes two copies of the submatrix, first an SeqAIJ 3120 in local and then by concatenating the local matrices the end result. 3121 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3122 3123 Note: This requires a sequential iscol with all indices. 3124 */ 3125 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3126 { 3127 PetscErrorCode ierr; 3128 PetscMPIInt rank,size; 3129 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3130 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3131 PetscBool allcolumns, colflag; 3132 Mat M,Mreuse; 3133 MatScalar *vwork,*aa; 3134 MPI_Comm comm; 3135 Mat_SeqAIJ *aij; 3136 3137 PetscFunctionBegin; 3138 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3139 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3140 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3141 3142 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3143 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3144 if (colflag && ncol == mat->cmap->N) { 3145 allcolumns = PETSC_TRUE; 3146 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix\n");CHKERRQ(ierr); 3147 } else { 3148 allcolumns = PETSC_FALSE; 3149 } 3150 if (call == MAT_REUSE_MATRIX) { 3151 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3152 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3153 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3154 } else { 3155 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3156 } 3157 3158 /* 3159 m - number of local rows 3160 n - number of columns (same on all processors) 3161 rstart - first row in new global matrix generated 3162 */ 3163 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3164 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3165 if (call == MAT_INITIAL_MATRIX) { 3166 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3167 ii = aij->i; 3168 jj = aij->j; 3169 3170 /* 3171 Determine the number of non-zeros in the diagonal and off-diagonal 3172 portions of the matrix in order to do correct preallocation 3173 */ 3174 3175 /* first get start and end of "diagonal" columns */ 3176 if (csize == PETSC_DECIDE) { 3177 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3178 if (mglobal == n) { /* square matrix */ 3179 nlocal = m; 3180 } else { 3181 nlocal = n/size + ((n % size) > rank); 3182 } 3183 } else { 3184 nlocal = csize; 3185 } 3186 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3187 rstart = rend - nlocal; 3188 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); 3189 3190 /* next, compute all the lengths */ 3191 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3192 olens = dlens + m; 3193 for (i=0; i<m; i++) { 3194 jend = ii[i+1] - ii[i]; 3195 olen = 0; 3196 dlen = 0; 3197 for (j=0; j<jend; j++) { 3198 if (*jj < rstart || *jj >= rend) olen++; 3199 else dlen++; 3200 jj++; 3201 } 3202 olens[i] = olen; 3203 dlens[i] = dlen; 3204 } 3205 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3206 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3207 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3208 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3209 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3210 ierr = PetscFree(dlens);CHKERRQ(ierr); 3211 } else { 3212 PetscInt ml,nl; 3213 3214 M = *newmat; 3215 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3216 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3217 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3218 /* 3219 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3220 rather than the slower MatSetValues(). 3221 */ 3222 M->was_assembled = PETSC_TRUE; 3223 M->assembled = PETSC_FALSE; 3224 } 3225 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3226 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3227 ii = aij->i; 3228 jj = aij->j; 3229 aa = aij->a; 3230 for (i=0; i<m; i++) { 3231 row = rstart + i; 3232 nz = ii[i+1] - ii[i]; 3233 cwork = jj; jj += nz; 3234 vwork = aa; aa += nz; 3235 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3236 } 3237 3238 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3239 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3240 *newmat = M; 3241 3242 /* save submatrix used in processor for next request */ 3243 if (call == MAT_INITIAL_MATRIX) { 3244 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3245 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3246 } 3247 PetscFunctionReturn(0); 3248 } 3249 3250 #undef __FUNCT__ 3251 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3252 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3253 { 3254 PetscInt m,cstart, cend,j,nnz,i,d; 3255 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3256 const PetscInt *JJ; 3257 PetscScalar *values; 3258 PetscErrorCode ierr; 3259 3260 PetscFunctionBegin; 3261 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3262 3263 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3264 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3265 m = B->rmap->n; 3266 cstart = B->cmap->rstart; 3267 cend = B->cmap->rend; 3268 rstart = B->rmap->rstart; 3269 3270 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3271 3272 #if defined(PETSC_USE_DEBUGGING) 3273 for (i=0; i<m; i++) { 3274 nnz = Ii[i+1]- Ii[i]; 3275 JJ = J + Ii[i]; 3276 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3277 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3278 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); 3279 } 3280 #endif 3281 3282 for (i=0; i<m; i++) { 3283 nnz = Ii[i+1]- Ii[i]; 3284 JJ = J + Ii[i]; 3285 nnz_max = PetscMax(nnz_max,nnz); 3286 d = 0; 3287 for (j=0; j<nnz; j++) { 3288 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3289 } 3290 d_nnz[i] = d; 3291 o_nnz[i] = nnz - d; 3292 } 3293 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3294 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3295 3296 if (v) values = (PetscScalar*)v; 3297 else { 3298 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3299 } 3300 3301 for (i=0; i<m; i++) { 3302 ii = i + rstart; 3303 nnz = Ii[i+1]- Ii[i]; 3304 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3305 } 3306 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3307 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3308 3309 if (!v) { 3310 ierr = PetscFree(values);CHKERRQ(ierr); 3311 } 3312 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3313 PetscFunctionReturn(0); 3314 } 3315 3316 #undef __FUNCT__ 3317 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3318 /*@ 3319 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3320 (the default parallel PETSc format). 3321 3322 Collective on MPI_Comm 3323 3324 Input Parameters: 3325 + B - the matrix 3326 . i - the indices into j for the start of each local row (starts with zero) 3327 . j - the column indices for each local row (starts with zero) 3328 - v - optional values in the matrix 3329 3330 Level: developer 3331 3332 Notes: 3333 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3334 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3335 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3336 3337 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3338 3339 The format which is used for the sparse matrix input, is equivalent to a 3340 row-major ordering.. i.e for the following matrix, the input data expected is 3341 as shown 3342 3343 $ 1 0 0 3344 $ 2 0 3 P0 3345 $ ------- 3346 $ 4 5 6 P1 3347 $ 3348 $ Process0 [P0]: rows_owned=[0,1] 3349 $ i = {0,1,3} [size = nrow+1 = 2+1] 3350 $ j = {0,0,2} [size = 3] 3351 $ v = {1,2,3} [size = 3] 3352 $ 3353 $ Process1 [P1]: rows_owned=[2] 3354 $ i = {0,3} [size = nrow+1 = 1+1] 3355 $ j = {0,1,2} [size = 3] 3356 $ v = {4,5,6} [size = 3] 3357 3358 .keywords: matrix, aij, compressed row, sparse, parallel 3359 3360 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3361 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3362 @*/ 3363 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3364 { 3365 PetscErrorCode ierr; 3366 3367 PetscFunctionBegin; 3368 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3369 PetscFunctionReturn(0); 3370 } 3371 3372 #undef __FUNCT__ 3373 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3374 /*@C 3375 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3376 (the default parallel PETSc format). For good matrix assembly performance 3377 the user should preallocate the matrix storage by setting the parameters 3378 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3379 performance can be increased by more than a factor of 50. 3380 3381 Collective on MPI_Comm 3382 3383 Input Parameters: 3384 + B - the matrix 3385 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3386 (same value is used for all local rows) 3387 . d_nnz - array containing the number of nonzeros in the various rows of the 3388 DIAGONAL portion of the local submatrix (possibly different for each row) 3389 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3390 The size of this array is equal to the number of local rows, i.e 'm'. 3391 For matrices that will be factored, you must leave room for (and set) 3392 the diagonal entry even if it is zero. 3393 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3394 submatrix (same value is used for all local rows). 3395 - o_nnz - array containing the number of nonzeros in the various rows of the 3396 OFF-DIAGONAL portion of the local submatrix (possibly different for 3397 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3398 structure. The size of this array is equal to the number 3399 of local rows, i.e 'm'. 3400 3401 If the *_nnz parameter is given then the *_nz parameter is ignored 3402 3403 The AIJ format (also called the Yale sparse matrix format or 3404 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3405 storage. The stored row and column indices begin with zero. 3406 See Users-Manual: ch_mat for details. 3407 3408 The parallel matrix is partitioned such that the first m0 rows belong to 3409 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3410 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3411 3412 The DIAGONAL portion of the local submatrix of a processor can be defined 3413 as the submatrix which is obtained by extraction the part corresponding to 3414 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3415 first row that belongs to the processor, r2 is the last row belonging to 3416 the this processor, and c1-c2 is range of indices of the local part of a 3417 vector suitable for applying the matrix to. This is an mxn matrix. In the 3418 common case of a square matrix, the row and column ranges are the same and 3419 the DIAGONAL part is also square. The remaining portion of the local 3420 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3421 3422 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3423 3424 You can call MatGetInfo() to get information on how effective the preallocation was; 3425 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3426 You can also run with the option -info and look for messages with the string 3427 malloc in them to see if additional memory allocation was needed. 3428 3429 Example usage: 3430 3431 Consider the following 8x8 matrix with 34 non-zero values, that is 3432 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3433 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3434 as follows: 3435 3436 .vb 3437 1 2 0 | 0 3 0 | 0 4 3438 Proc0 0 5 6 | 7 0 0 | 8 0 3439 9 0 10 | 11 0 0 | 12 0 3440 ------------------------------------- 3441 13 0 14 | 15 16 17 | 0 0 3442 Proc1 0 18 0 | 19 20 21 | 0 0 3443 0 0 0 | 22 23 0 | 24 0 3444 ------------------------------------- 3445 Proc2 25 26 27 | 0 0 28 | 29 0 3446 30 0 0 | 31 32 33 | 0 34 3447 .ve 3448 3449 This can be represented as a collection of submatrices as: 3450 3451 .vb 3452 A B C 3453 D E F 3454 G H I 3455 .ve 3456 3457 Where the submatrices A,B,C are owned by proc0, D,E,F are 3458 owned by proc1, G,H,I are owned by proc2. 3459 3460 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3461 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3462 The 'M','N' parameters are 8,8, and have the same values on all procs. 3463 3464 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3465 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3466 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3467 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3468 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3469 matrix, ans [DF] as another SeqAIJ matrix. 3470 3471 When d_nz, o_nz parameters are specified, d_nz storage elements are 3472 allocated for every row of the local diagonal submatrix, and o_nz 3473 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3474 One way to choose d_nz and o_nz is to use the max nonzerors per local 3475 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3476 In this case, the values of d_nz,o_nz are: 3477 .vb 3478 proc0 : dnz = 2, o_nz = 2 3479 proc1 : dnz = 3, o_nz = 2 3480 proc2 : dnz = 1, o_nz = 4 3481 .ve 3482 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3483 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3484 for proc3. i.e we are using 12+15+10=37 storage locations to store 3485 34 values. 3486 3487 When d_nnz, o_nnz parameters are specified, the storage is specified 3488 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3489 In the above case the values for d_nnz,o_nnz are: 3490 .vb 3491 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3492 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3493 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3494 .ve 3495 Here the space allocated is sum of all the above values i.e 34, and 3496 hence pre-allocation is perfect. 3497 3498 Level: intermediate 3499 3500 .keywords: matrix, aij, compressed row, sparse, parallel 3501 3502 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3503 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3504 @*/ 3505 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3506 { 3507 PetscErrorCode ierr; 3508 3509 PetscFunctionBegin; 3510 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3511 PetscValidType(B,1); 3512 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3513 PetscFunctionReturn(0); 3514 } 3515 3516 #undef __FUNCT__ 3517 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3518 /*@ 3519 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3520 CSR format the local rows. 3521 3522 Collective on MPI_Comm 3523 3524 Input Parameters: 3525 + comm - MPI communicator 3526 . m - number of local rows (Cannot be PETSC_DECIDE) 3527 . n - This value should be the same as the local size used in creating the 3528 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3529 calculated if N is given) For square matrices n is almost always m. 3530 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3531 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3532 . i - row indices 3533 . j - column indices 3534 - a - matrix values 3535 3536 Output Parameter: 3537 . mat - the matrix 3538 3539 Level: intermediate 3540 3541 Notes: 3542 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3543 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3544 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3545 3546 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3547 3548 The format which is used for the sparse matrix input, is equivalent to a 3549 row-major ordering.. i.e for the following matrix, the input data expected is 3550 as shown 3551 3552 $ 1 0 0 3553 $ 2 0 3 P0 3554 $ ------- 3555 $ 4 5 6 P1 3556 $ 3557 $ Process0 [P0]: rows_owned=[0,1] 3558 $ i = {0,1,3} [size = nrow+1 = 2+1] 3559 $ j = {0,0,2} [size = 3] 3560 $ v = {1,2,3} [size = 3] 3561 $ 3562 $ Process1 [P1]: rows_owned=[2] 3563 $ i = {0,3} [size = nrow+1 = 1+1] 3564 $ j = {0,1,2} [size = 3] 3565 $ v = {4,5,6} [size = 3] 3566 3567 .keywords: matrix, aij, compressed row, sparse, parallel 3568 3569 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3570 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3571 @*/ 3572 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3573 { 3574 PetscErrorCode ierr; 3575 3576 PetscFunctionBegin; 3577 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3578 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3579 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3580 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3581 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3582 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3583 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3584 PetscFunctionReturn(0); 3585 } 3586 3587 #undef __FUNCT__ 3588 #define __FUNCT__ "MatCreateAIJ" 3589 /*@C 3590 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3591 (the default parallel PETSc format). For good matrix assembly performance 3592 the user should preallocate the matrix storage by setting the parameters 3593 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3594 performance can be increased by more than a factor of 50. 3595 3596 Collective on MPI_Comm 3597 3598 Input Parameters: 3599 + comm - MPI communicator 3600 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3601 This value should be the same as the local size used in creating the 3602 y vector for the matrix-vector product y = Ax. 3603 . n - This value should be the same as the local size used in creating the 3604 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3605 calculated if N is given) For square matrices n is almost always m. 3606 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3607 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3608 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3609 (same value is used for all local rows) 3610 . d_nnz - array containing the number of nonzeros in the various rows of the 3611 DIAGONAL portion of the local submatrix (possibly different for each row) 3612 or NULL, if d_nz is used to specify the nonzero structure. 3613 The size of this array is equal to the number of local rows, i.e 'm'. 3614 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3615 submatrix (same value is used for all local rows). 3616 - o_nnz - array containing the number of nonzeros in the various rows of the 3617 OFF-DIAGONAL portion of the local submatrix (possibly different for 3618 each row) or NULL, if o_nz is used to specify the nonzero 3619 structure. The size of this array is equal to the number 3620 of local rows, i.e 'm'. 3621 3622 Output Parameter: 3623 . A - the matrix 3624 3625 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3626 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3627 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3628 3629 Notes: 3630 If the *_nnz parameter is given then the *_nz parameter is ignored 3631 3632 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3633 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3634 storage requirements for this matrix. 3635 3636 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3637 processor than it must be used on all processors that share the object for 3638 that argument. 3639 3640 The user MUST specify either the local or global matrix dimensions 3641 (possibly both). 3642 3643 The parallel matrix is partitioned across processors such that the 3644 first m0 rows belong to process 0, the next m1 rows belong to 3645 process 1, the next m2 rows belong to process 2 etc.. where 3646 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3647 values corresponding to [m x N] submatrix. 3648 3649 The columns are logically partitioned with the n0 columns belonging 3650 to 0th partition, the next n1 columns belonging to the next 3651 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3652 3653 The DIAGONAL portion of the local submatrix on any given processor 3654 is the submatrix corresponding to the rows and columns m,n 3655 corresponding to the given processor. i.e diagonal matrix on 3656 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3657 etc. The remaining portion of the local submatrix [m x (N-n)] 3658 constitute the OFF-DIAGONAL portion. The example below better 3659 illustrates this concept. 3660 3661 For a square global matrix we define each processor's diagonal portion 3662 to be its local rows and the corresponding columns (a square submatrix); 3663 each processor's off-diagonal portion encompasses the remainder of the 3664 local matrix (a rectangular submatrix). 3665 3666 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3667 3668 When calling this routine with a single process communicator, a matrix of 3669 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3670 type of communicator, use the construction mechanism: 3671 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3672 3673 By default, this format uses inodes (identical nodes) when possible. 3674 We search for consecutive rows with the same nonzero structure, thereby 3675 reusing matrix information to achieve increased efficiency. 3676 3677 Options Database Keys: 3678 + -mat_no_inode - Do not use inodes 3679 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3680 - -mat_aij_oneindex - Internally use indexing starting at 1 3681 rather than 0. Note that when calling MatSetValues(), 3682 the user still MUST index entries starting at 0! 3683 3684 3685 Example usage: 3686 3687 Consider the following 8x8 matrix with 34 non-zero values, that is 3688 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3689 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3690 as follows: 3691 3692 .vb 3693 1 2 0 | 0 3 0 | 0 4 3694 Proc0 0 5 6 | 7 0 0 | 8 0 3695 9 0 10 | 11 0 0 | 12 0 3696 ------------------------------------- 3697 13 0 14 | 15 16 17 | 0 0 3698 Proc1 0 18 0 | 19 20 21 | 0 0 3699 0 0 0 | 22 23 0 | 24 0 3700 ------------------------------------- 3701 Proc2 25 26 27 | 0 0 28 | 29 0 3702 30 0 0 | 31 32 33 | 0 34 3703 .ve 3704 3705 This can be represented as a collection of submatrices as: 3706 3707 .vb 3708 A B C 3709 D E F 3710 G H I 3711 .ve 3712 3713 Where the submatrices A,B,C are owned by proc0, D,E,F are 3714 owned by proc1, G,H,I are owned by proc2. 3715 3716 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3717 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3718 The 'M','N' parameters are 8,8, and have the same values on all procs. 3719 3720 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3721 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3722 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3723 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3724 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3725 matrix, ans [DF] as another SeqAIJ matrix. 3726 3727 When d_nz, o_nz parameters are specified, d_nz storage elements are 3728 allocated for every row of the local diagonal submatrix, and o_nz 3729 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3730 One way to choose d_nz and o_nz is to use the max nonzerors per local 3731 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3732 In this case, the values of d_nz,o_nz are: 3733 .vb 3734 proc0 : dnz = 2, o_nz = 2 3735 proc1 : dnz = 3, o_nz = 2 3736 proc2 : dnz = 1, o_nz = 4 3737 .ve 3738 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3739 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3740 for proc3. i.e we are using 12+15+10=37 storage locations to store 3741 34 values. 3742 3743 When d_nnz, o_nnz parameters are specified, the storage is specified 3744 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3745 In the above case the values for d_nnz,o_nnz are: 3746 .vb 3747 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3748 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3749 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3750 .ve 3751 Here the space allocated is sum of all the above values i.e 34, and 3752 hence pre-allocation is perfect. 3753 3754 Level: intermediate 3755 3756 .keywords: matrix, aij, compressed row, sparse, parallel 3757 3758 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3759 MPIAIJ, MatCreateMPIAIJWithArrays() 3760 @*/ 3761 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) 3762 { 3763 PetscErrorCode ierr; 3764 PetscMPIInt size; 3765 3766 PetscFunctionBegin; 3767 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3768 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3769 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3770 if (size > 1) { 3771 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3772 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3773 } else { 3774 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3775 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3776 } 3777 PetscFunctionReturn(0); 3778 } 3779 3780 #undef __FUNCT__ 3781 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3782 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3783 { 3784 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3785 PetscBool flg; 3786 PetscErrorCode ierr; 3787 3788 PetscFunctionBegin; 3789 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 3790 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MPIAIJ matrix as input"); 3791 if (Ad) *Ad = a->A; 3792 if (Ao) *Ao = a->B; 3793 if (colmap) *colmap = a->garray; 3794 PetscFunctionReturn(0); 3795 } 3796 3797 #undef __FUNCT__ 3798 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3799 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3800 { 3801 PetscErrorCode ierr; 3802 PetscInt i; 3803 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3804 3805 PetscFunctionBegin; 3806 if (coloring->ctype == IS_COLORING_GLOBAL) { 3807 ISColoringValue *allcolors,*colors; 3808 ISColoring ocoloring; 3809 3810 /* set coloring for diagonal portion */ 3811 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3812 3813 /* set coloring for off-diagonal portion */ 3814 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3815 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3816 for (i=0; i<a->B->cmap->n; i++) { 3817 colors[i] = allcolors[a->garray[i]]; 3818 } 3819 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3820 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3821 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3822 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3823 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3824 ISColoringValue *colors; 3825 PetscInt *larray; 3826 ISColoring ocoloring; 3827 3828 /* set coloring for diagonal portion */ 3829 ierr = PetscMalloc1(a->A->cmap->n+1,&larray);CHKERRQ(ierr); 3830 for (i=0; i<a->A->cmap->n; i++) { 3831 larray[i] = i + A->cmap->rstart; 3832 } 3833 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3834 ierr = PetscMalloc1(a->A->cmap->n+1,&colors);CHKERRQ(ierr); 3835 for (i=0; i<a->A->cmap->n; i++) { 3836 colors[i] = coloring->colors[larray[i]]; 3837 } 3838 ierr = PetscFree(larray);CHKERRQ(ierr); 3839 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3840 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3841 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3842 3843 /* set coloring for off-diagonal portion */ 3844 ierr = PetscMalloc1(a->B->cmap->n+1,&larray);CHKERRQ(ierr); 3845 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3846 ierr = PetscMalloc1(a->B->cmap->n+1,&colors);CHKERRQ(ierr); 3847 for (i=0; i<a->B->cmap->n; i++) { 3848 colors[i] = coloring->colors[larray[i]]; 3849 } 3850 ierr = PetscFree(larray);CHKERRQ(ierr); 3851 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); 3852 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3853 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3854 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3855 PetscFunctionReturn(0); 3856 } 3857 3858 #undef __FUNCT__ 3859 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3860 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3861 { 3862 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3863 PetscErrorCode ierr; 3864 3865 PetscFunctionBegin; 3866 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3867 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3868 PetscFunctionReturn(0); 3869 } 3870 3871 #undef __FUNCT__ 3872 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3873 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3874 { 3875 PetscErrorCode ierr; 3876 PetscInt m,N,i,rstart,nnz,Ii; 3877 PetscInt *indx; 3878 PetscScalar *values; 3879 3880 PetscFunctionBegin; 3881 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3882 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3883 PetscInt *dnz,*onz,sum,bs,cbs; 3884 3885 if (n == PETSC_DECIDE) { 3886 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3887 } 3888 /* Check sum(n) = N */ 3889 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3890 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3891 3892 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3893 rstart -= m; 3894 3895 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3896 for (i=0; i<m; i++) { 3897 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3898 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3899 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3900 } 3901 3902 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3903 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3904 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3905 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3906 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3907 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3908 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3909 } 3910 3911 /* numeric phase */ 3912 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3913 for (i=0; i<m; i++) { 3914 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3915 Ii = i + rstart; 3916 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3917 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3918 } 3919 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3920 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3921 PetscFunctionReturn(0); 3922 } 3923 3924 #undef __FUNCT__ 3925 #define __FUNCT__ "MatFileSplit" 3926 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3927 { 3928 PetscErrorCode ierr; 3929 PetscMPIInt rank; 3930 PetscInt m,N,i,rstart,nnz; 3931 size_t len; 3932 const PetscInt *indx; 3933 PetscViewer out; 3934 char *name; 3935 Mat B; 3936 const PetscScalar *values; 3937 3938 PetscFunctionBegin; 3939 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3940 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3941 /* Should this be the type of the diagonal block of A? */ 3942 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3943 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3944 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3945 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3946 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3947 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3948 for (i=0; i<m; i++) { 3949 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3950 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3951 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3952 } 3953 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3954 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3955 3956 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3957 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3958 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 3959 sprintf(name,"%s.%d",outfile,rank); 3960 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3961 ierr = PetscFree(name);CHKERRQ(ierr); 3962 ierr = MatView(B,out);CHKERRQ(ierr); 3963 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3964 ierr = MatDestroy(&B);CHKERRQ(ierr); 3965 PetscFunctionReturn(0); 3966 } 3967 3968 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3969 #undef __FUNCT__ 3970 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3971 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3972 { 3973 PetscErrorCode ierr; 3974 Mat_Merge_SeqsToMPI *merge; 3975 PetscContainer container; 3976 3977 PetscFunctionBegin; 3978 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3979 if (container) { 3980 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3981 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3982 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3983 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3984 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3985 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3986 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3987 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3988 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3989 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3990 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3991 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3992 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3993 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 3994 ierr = PetscFree(merge);CHKERRQ(ierr); 3995 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3996 } 3997 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3998 PetscFunctionReturn(0); 3999 } 4000 4001 #include <../src/mat/utils/freespace.h> 4002 #include <petscbt.h> 4003 4004 #undef __FUNCT__ 4005 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4006 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4007 { 4008 PetscErrorCode ierr; 4009 MPI_Comm comm; 4010 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4011 PetscMPIInt size,rank,taga,*len_s; 4012 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4013 PetscInt proc,m; 4014 PetscInt **buf_ri,**buf_rj; 4015 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4016 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4017 MPI_Request *s_waits,*r_waits; 4018 MPI_Status *status; 4019 MatScalar *aa=a->a; 4020 MatScalar **abuf_r,*ba_i; 4021 Mat_Merge_SeqsToMPI *merge; 4022 PetscContainer container; 4023 4024 PetscFunctionBegin; 4025 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4026 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4027 4028 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4029 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4030 4031 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4032 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4033 4034 bi = merge->bi; 4035 bj = merge->bj; 4036 buf_ri = merge->buf_ri; 4037 buf_rj = merge->buf_rj; 4038 4039 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4040 owners = merge->rowmap->range; 4041 len_s = merge->len_s; 4042 4043 /* send and recv matrix values */ 4044 /*-----------------------------*/ 4045 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4046 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4047 4048 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4049 for (proc=0,k=0; proc<size; proc++) { 4050 if (!len_s[proc]) continue; 4051 i = owners[proc]; 4052 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4053 k++; 4054 } 4055 4056 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4057 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4058 ierr = PetscFree(status);CHKERRQ(ierr); 4059 4060 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4061 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4062 4063 /* insert mat values of mpimat */ 4064 /*----------------------------*/ 4065 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4066 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4067 4068 for (k=0; k<merge->nrecv; k++) { 4069 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4070 nrows = *(buf_ri_k[k]); 4071 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4072 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4073 } 4074 4075 /* set values of ba */ 4076 m = merge->rowmap->n; 4077 for (i=0; i<m; i++) { 4078 arow = owners[rank] + i; 4079 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4080 bnzi = bi[i+1] - bi[i]; 4081 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4082 4083 /* add local non-zero vals of this proc's seqmat into ba */ 4084 anzi = ai[arow+1] - ai[arow]; 4085 aj = a->j + ai[arow]; 4086 aa = a->a + ai[arow]; 4087 nextaj = 0; 4088 for (j=0; nextaj<anzi; j++) { 4089 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4090 ba_i[j] += aa[nextaj++]; 4091 } 4092 } 4093 4094 /* add received vals into ba */ 4095 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4096 /* i-th row */ 4097 if (i == *nextrow[k]) { 4098 anzi = *(nextai[k]+1) - *nextai[k]; 4099 aj = buf_rj[k] + *(nextai[k]); 4100 aa = abuf_r[k] + *(nextai[k]); 4101 nextaj = 0; 4102 for (j=0; nextaj<anzi; j++) { 4103 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4104 ba_i[j] += aa[nextaj++]; 4105 } 4106 } 4107 nextrow[k]++; nextai[k]++; 4108 } 4109 } 4110 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4111 } 4112 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4113 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4114 4115 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4116 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4117 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4118 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4119 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4120 PetscFunctionReturn(0); 4121 } 4122 4123 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4124 4125 #undef __FUNCT__ 4126 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4127 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4128 { 4129 PetscErrorCode ierr; 4130 Mat B_mpi; 4131 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4132 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4133 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4134 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4135 PetscInt len,proc,*dnz,*onz,bs,cbs; 4136 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4137 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4138 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4139 MPI_Status *status; 4140 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4141 PetscBT lnkbt; 4142 Mat_Merge_SeqsToMPI *merge; 4143 PetscContainer container; 4144 4145 PetscFunctionBegin; 4146 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4147 4148 /* make sure it is a PETSc comm */ 4149 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4150 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4151 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4152 4153 ierr = PetscNew(&merge);CHKERRQ(ierr); 4154 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4155 4156 /* determine row ownership */ 4157 /*---------------------------------------------------------*/ 4158 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4159 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4160 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4161 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4162 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4163 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4164 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4165 4166 m = merge->rowmap->n; 4167 owners = merge->rowmap->range; 4168 4169 /* determine the number of messages to send, their lengths */ 4170 /*---------------------------------------------------------*/ 4171 len_s = merge->len_s; 4172 4173 len = 0; /* length of buf_si[] */ 4174 merge->nsend = 0; 4175 for (proc=0; proc<size; proc++) { 4176 len_si[proc] = 0; 4177 if (proc == rank) { 4178 len_s[proc] = 0; 4179 } else { 4180 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4181 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4182 } 4183 if (len_s[proc]) { 4184 merge->nsend++; 4185 nrows = 0; 4186 for (i=owners[proc]; i<owners[proc+1]; i++) { 4187 if (ai[i+1] > ai[i]) nrows++; 4188 } 4189 len_si[proc] = 2*(nrows+1); 4190 len += len_si[proc]; 4191 } 4192 } 4193 4194 /* determine the number and length of messages to receive for ij-structure */ 4195 /*-------------------------------------------------------------------------*/ 4196 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4197 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4198 4199 /* post the Irecv of j-structure */ 4200 /*-------------------------------*/ 4201 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4202 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4203 4204 /* post the Isend of j-structure */ 4205 /*--------------------------------*/ 4206 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4207 4208 for (proc=0, k=0; proc<size; proc++) { 4209 if (!len_s[proc]) continue; 4210 i = owners[proc]; 4211 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4212 k++; 4213 } 4214 4215 /* receives and sends of j-structure are complete */ 4216 /*------------------------------------------------*/ 4217 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4218 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4219 4220 /* send and recv i-structure */ 4221 /*---------------------------*/ 4222 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4223 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4224 4225 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4226 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4227 for (proc=0,k=0; proc<size; proc++) { 4228 if (!len_s[proc]) continue; 4229 /* form outgoing message for i-structure: 4230 buf_si[0]: nrows to be sent 4231 [1:nrows]: row index (global) 4232 [nrows+1:2*nrows+1]: i-structure index 4233 */ 4234 /*-------------------------------------------*/ 4235 nrows = len_si[proc]/2 - 1; 4236 buf_si_i = buf_si + nrows+1; 4237 buf_si[0] = nrows; 4238 buf_si_i[0] = 0; 4239 nrows = 0; 4240 for (i=owners[proc]; i<owners[proc+1]; i++) { 4241 anzi = ai[i+1] - ai[i]; 4242 if (anzi) { 4243 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4244 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4245 nrows++; 4246 } 4247 } 4248 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4249 k++; 4250 buf_si += len_si[proc]; 4251 } 4252 4253 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4254 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4255 4256 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4257 for (i=0; i<merge->nrecv; i++) { 4258 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); 4259 } 4260 4261 ierr = PetscFree(len_si);CHKERRQ(ierr); 4262 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4263 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4264 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4265 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4266 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4267 ierr = PetscFree(status);CHKERRQ(ierr); 4268 4269 /* compute a local seq matrix in each processor */ 4270 /*----------------------------------------------*/ 4271 /* allocate bi array and free space for accumulating nonzero column info */ 4272 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4273 bi[0] = 0; 4274 4275 /* create and initialize a linked list */ 4276 nlnk = N+1; 4277 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4278 4279 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4280 len = ai[owners[rank+1]] - ai[owners[rank]]; 4281 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4282 4283 current_space = free_space; 4284 4285 /* determine symbolic info for each local row */ 4286 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4287 4288 for (k=0; k<merge->nrecv; k++) { 4289 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4290 nrows = *buf_ri_k[k]; 4291 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4292 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4293 } 4294 4295 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4296 len = 0; 4297 for (i=0; i<m; i++) { 4298 bnzi = 0; 4299 /* add local non-zero cols of this proc's seqmat into lnk */ 4300 arow = owners[rank] + i; 4301 anzi = ai[arow+1] - ai[arow]; 4302 aj = a->j + ai[arow]; 4303 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4304 bnzi += nlnk; 4305 /* add received col data into lnk */ 4306 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4307 if (i == *nextrow[k]) { /* i-th row */ 4308 anzi = *(nextai[k]+1) - *nextai[k]; 4309 aj = buf_rj[k] + *nextai[k]; 4310 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4311 bnzi += nlnk; 4312 nextrow[k]++; nextai[k]++; 4313 } 4314 } 4315 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4316 4317 /* if free space is not available, make more free space */ 4318 if (current_space->local_remaining<bnzi) { 4319 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4320 nspacedouble++; 4321 } 4322 /* copy data into free space, then initialize lnk */ 4323 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4324 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4325 4326 current_space->array += bnzi; 4327 current_space->local_used += bnzi; 4328 current_space->local_remaining -= bnzi; 4329 4330 bi[i+1] = bi[i] + bnzi; 4331 } 4332 4333 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4334 4335 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4336 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4337 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4338 4339 /* create symbolic parallel matrix B_mpi */ 4340 /*---------------------------------------*/ 4341 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4342 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4343 if (n==PETSC_DECIDE) { 4344 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4345 } else { 4346 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4347 } 4348 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4349 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4350 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4351 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4352 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4353 4354 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4355 B_mpi->assembled = PETSC_FALSE; 4356 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4357 merge->bi = bi; 4358 merge->bj = bj; 4359 merge->buf_ri = buf_ri; 4360 merge->buf_rj = buf_rj; 4361 merge->coi = NULL; 4362 merge->coj = NULL; 4363 merge->owners_co = NULL; 4364 4365 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4366 4367 /* attach the supporting struct to B_mpi for reuse */ 4368 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4369 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4370 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4371 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4372 *mpimat = B_mpi; 4373 4374 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4375 PetscFunctionReturn(0); 4376 } 4377 4378 #undef __FUNCT__ 4379 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4380 /*@C 4381 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4382 matrices from each processor 4383 4384 Collective on MPI_Comm 4385 4386 Input Parameters: 4387 + comm - the communicators the parallel matrix will live on 4388 . seqmat - the input sequential matrices 4389 . m - number of local rows (or PETSC_DECIDE) 4390 . n - number of local columns (or PETSC_DECIDE) 4391 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4392 4393 Output Parameter: 4394 . mpimat - the parallel matrix generated 4395 4396 Level: advanced 4397 4398 Notes: 4399 The dimensions of the sequential matrix in each processor MUST be the same. 4400 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4401 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4402 @*/ 4403 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4404 { 4405 PetscErrorCode ierr; 4406 PetscMPIInt size; 4407 4408 PetscFunctionBegin; 4409 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4410 if (size == 1) { 4411 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4412 if (scall == MAT_INITIAL_MATRIX) { 4413 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4414 } else { 4415 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4416 } 4417 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4418 PetscFunctionReturn(0); 4419 } 4420 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4421 if (scall == MAT_INITIAL_MATRIX) { 4422 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4423 } 4424 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4425 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4426 PetscFunctionReturn(0); 4427 } 4428 4429 #undef __FUNCT__ 4430 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4431 /*@ 4432 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4433 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4434 with MatGetSize() 4435 4436 Not Collective 4437 4438 Input Parameters: 4439 + A - the matrix 4440 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4441 4442 Output Parameter: 4443 . A_loc - the local sequential matrix generated 4444 4445 Level: developer 4446 4447 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4448 4449 @*/ 4450 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4451 { 4452 PetscErrorCode ierr; 4453 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4454 Mat_SeqAIJ *mat,*a,*b; 4455 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4456 MatScalar *aa,*ba,*cam; 4457 PetscScalar *ca; 4458 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4459 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4460 PetscBool match; 4461 MPI_Comm comm; 4462 PetscMPIInt size; 4463 4464 PetscFunctionBegin; 4465 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4466 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4467 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4468 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4469 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4470 4471 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4472 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4473 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4474 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4475 aa = a->a; ba = b->a; 4476 if (scall == MAT_INITIAL_MATRIX) { 4477 if (size == 1) { 4478 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4479 PetscFunctionReturn(0); 4480 } 4481 4482 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4483 ci[0] = 0; 4484 for (i=0; i<am; i++) { 4485 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4486 } 4487 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4488 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4489 k = 0; 4490 for (i=0; i<am; i++) { 4491 ncols_o = bi[i+1] - bi[i]; 4492 ncols_d = ai[i+1] - ai[i]; 4493 /* off-diagonal portion of A */ 4494 for (jo=0; jo<ncols_o; jo++) { 4495 col = cmap[*bj]; 4496 if (col >= cstart) break; 4497 cj[k] = col; bj++; 4498 ca[k++] = *ba++; 4499 } 4500 /* diagonal portion of A */ 4501 for (j=0; j<ncols_d; j++) { 4502 cj[k] = cstart + *aj++; 4503 ca[k++] = *aa++; 4504 } 4505 /* off-diagonal portion of A */ 4506 for (j=jo; j<ncols_o; j++) { 4507 cj[k] = cmap[*bj++]; 4508 ca[k++] = *ba++; 4509 } 4510 } 4511 /* put together the new matrix */ 4512 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4513 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4514 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4515 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4516 mat->free_a = PETSC_TRUE; 4517 mat->free_ij = PETSC_TRUE; 4518 mat->nonew = 0; 4519 } else if (scall == MAT_REUSE_MATRIX) { 4520 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4521 ci = mat->i; cj = mat->j; cam = mat->a; 4522 for (i=0; i<am; i++) { 4523 /* off-diagonal portion of A */ 4524 ncols_o = bi[i+1] - bi[i]; 4525 for (jo=0; jo<ncols_o; jo++) { 4526 col = cmap[*bj]; 4527 if (col >= cstart) break; 4528 *cam++ = *ba++; bj++; 4529 } 4530 /* diagonal portion of A */ 4531 ncols_d = ai[i+1] - ai[i]; 4532 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4533 /* off-diagonal portion of A */ 4534 for (j=jo; j<ncols_o; j++) { 4535 *cam++ = *ba++; bj++; 4536 } 4537 } 4538 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4539 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4540 PetscFunctionReturn(0); 4541 } 4542 4543 #undef __FUNCT__ 4544 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4545 /*@C 4546 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4547 4548 Not Collective 4549 4550 Input Parameters: 4551 + A - the matrix 4552 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4553 - row, col - index sets of rows and columns to extract (or NULL) 4554 4555 Output Parameter: 4556 . A_loc - the local sequential matrix generated 4557 4558 Level: developer 4559 4560 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4561 4562 @*/ 4563 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4564 { 4565 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4566 PetscErrorCode ierr; 4567 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4568 IS isrowa,iscola; 4569 Mat *aloc; 4570 PetscBool match; 4571 4572 PetscFunctionBegin; 4573 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4574 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4575 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4576 if (!row) { 4577 start = A->rmap->rstart; end = A->rmap->rend; 4578 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4579 } else { 4580 isrowa = *row; 4581 } 4582 if (!col) { 4583 start = A->cmap->rstart; 4584 cmap = a->garray; 4585 nzA = a->A->cmap->n; 4586 nzB = a->B->cmap->n; 4587 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4588 ncols = 0; 4589 for (i=0; i<nzB; i++) { 4590 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4591 else break; 4592 } 4593 imark = i; 4594 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4595 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4596 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4597 } else { 4598 iscola = *col; 4599 } 4600 if (scall != MAT_INITIAL_MATRIX) { 4601 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4602 aloc[0] = *A_loc; 4603 } 4604 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4605 *A_loc = aloc[0]; 4606 ierr = PetscFree(aloc);CHKERRQ(ierr); 4607 if (!row) { 4608 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4609 } 4610 if (!col) { 4611 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4612 } 4613 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4614 PetscFunctionReturn(0); 4615 } 4616 4617 #undef __FUNCT__ 4618 #define __FUNCT__ "MatGetBrowsOfAcols" 4619 /*@C 4620 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4621 4622 Collective on Mat 4623 4624 Input Parameters: 4625 + A,B - the matrices in mpiaij format 4626 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4627 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4628 4629 Output Parameter: 4630 + rowb, colb - index sets of rows and columns of B to extract 4631 - B_seq - the sequential matrix generated 4632 4633 Level: developer 4634 4635 @*/ 4636 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4637 { 4638 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4639 PetscErrorCode ierr; 4640 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4641 IS isrowb,iscolb; 4642 Mat *bseq=NULL; 4643 4644 PetscFunctionBegin; 4645 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4646 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); 4647 } 4648 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4649 4650 if (scall == MAT_INITIAL_MATRIX) { 4651 start = A->cmap->rstart; 4652 cmap = a->garray; 4653 nzA = a->A->cmap->n; 4654 nzB = a->B->cmap->n; 4655 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4656 ncols = 0; 4657 for (i=0; i<nzB; i++) { /* row < local row index */ 4658 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4659 else break; 4660 } 4661 imark = i; 4662 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4663 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4664 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4665 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4666 } else { 4667 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4668 isrowb = *rowb; iscolb = *colb; 4669 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4670 bseq[0] = *B_seq; 4671 } 4672 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4673 *B_seq = bseq[0]; 4674 ierr = PetscFree(bseq);CHKERRQ(ierr); 4675 if (!rowb) { 4676 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4677 } else { 4678 *rowb = isrowb; 4679 } 4680 if (!colb) { 4681 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4682 } else { 4683 *colb = iscolb; 4684 } 4685 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4686 PetscFunctionReturn(0); 4687 } 4688 4689 #undef __FUNCT__ 4690 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4691 /* 4692 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4693 of the OFF-DIAGONAL portion of local A 4694 4695 Collective on Mat 4696 4697 Input Parameters: 4698 + A,B - the matrices in mpiaij format 4699 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4700 4701 Output Parameter: 4702 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4703 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4704 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4705 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4706 4707 Level: developer 4708 4709 */ 4710 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4711 { 4712 VecScatter_MPI_General *gen_to,*gen_from; 4713 PetscErrorCode ierr; 4714 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4715 Mat_SeqAIJ *b_oth; 4716 VecScatter ctx =a->Mvctx; 4717 MPI_Comm comm; 4718 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4719 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4720 PetscScalar *rvalues,*svalues; 4721 MatScalar *b_otha,*bufa,*bufA; 4722 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4723 MPI_Request *rwaits = NULL,*swaits = NULL; 4724 MPI_Status *sstatus,rstatus; 4725 PetscMPIInt jj,size; 4726 PetscInt *cols,sbs,rbs; 4727 PetscScalar *vals; 4728 4729 PetscFunctionBegin; 4730 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4731 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4732 4733 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4734 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); 4735 } 4736 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4737 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4738 4739 gen_to = (VecScatter_MPI_General*)ctx->todata; 4740 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4741 rvalues = gen_from->values; /* holds the length of receiving row */ 4742 svalues = gen_to->values; /* holds the length of sending row */ 4743 nrecvs = gen_from->n; 4744 nsends = gen_to->n; 4745 4746 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4747 srow = gen_to->indices; /* local row index to be sent */ 4748 sstarts = gen_to->starts; 4749 sprocs = gen_to->procs; 4750 sstatus = gen_to->sstatus; 4751 sbs = gen_to->bs; 4752 rstarts = gen_from->starts; 4753 rprocs = gen_from->procs; 4754 rbs = gen_from->bs; 4755 4756 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4757 if (scall == MAT_INITIAL_MATRIX) { 4758 /* i-array */ 4759 /*---------*/ 4760 /* post receives */ 4761 for (i=0; i<nrecvs; i++) { 4762 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4763 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4764 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4765 } 4766 4767 /* pack the outgoing message */ 4768 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4769 4770 sstartsj[0] = 0; 4771 rstartsj[0] = 0; 4772 len = 0; /* total length of j or a array to be sent */ 4773 k = 0; 4774 for (i=0; i<nsends; i++) { 4775 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4776 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4777 for (j=0; j<nrows; j++) { 4778 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4779 for (l=0; l<sbs; l++) { 4780 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4781 4782 rowlen[j*sbs+l] = ncols; 4783 4784 len += ncols; 4785 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4786 } 4787 k++; 4788 } 4789 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4790 4791 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4792 } 4793 /* recvs and sends of i-array are completed */ 4794 i = nrecvs; 4795 while (i--) { 4796 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4797 } 4798 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4799 4800 /* allocate buffers for sending j and a arrays */ 4801 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4802 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4803 4804 /* create i-array of B_oth */ 4805 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4806 4807 b_othi[0] = 0; 4808 len = 0; /* total length of j or a array to be received */ 4809 k = 0; 4810 for (i=0; i<nrecvs; i++) { 4811 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4812 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4813 for (j=0; j<nrows; j++) { 4814 b_othi[k+1] = b_othi[k] + rowlen[j]; 4815 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4816 k++; 4817 } 4818 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4819 } 4820 4821 /* allocate space for j and a arrrays of B_oth */ 4822 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4823 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4824 4825 /* j-array */ 4826 /*---------*/ 4827 /* post receives of j-array */ 4828 for (i=0; i<nrecvs; i++) { 4829 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4830 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4831 } 4832 4833 /* pack the outgoing message j-array */ 4834 k = 0; 4835 for (i=0; i<nsends; i++) { 4836 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4837 bufJ = bufj+sstartsj[i]; 4838 for (j=0; j<nrows; j++) { 4839 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4840 for (ll=0; ll<sbs; ll++) { 4841 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4842 for (l=0; l<ncols; l++) { 4843 *bufJ++ = cols[l]; 4844 } 4845 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4846 } 4847 } 4848 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4849 } 4850 4851 /* recvs and sends of j-array are completed */ 4852 i = nrecvs; 4853 while (i--) { 4854 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4855 } 4856 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4857 } else if (scall == MAT_REUSE_MATRIX) { 4858 sstartsj = *startsj_s; 4859 rstartsj = *startsj_r; 4860 bufa = *bufa_ptr; 4861 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4862 b_otha = b_oth->a; 4863 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4864 4865 /* a-array */ 4866 /*---------*/ 4867 /* post receives of a-array */ 4868 for (i=0; i<nrecvs; i++) { 4869 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4870 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4871 } 4872 4873 /* pack the outgoing message a-array */ 4874 k = 0; 4875 for (i=0; i<nsends; i++) { 4876 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4877 bufA = bufa+sstartsj[i]; 4878 for (j=0; j<nrows; j++) { 4879 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4880 for (ll=0; ll<sbs; ll++) { 4881 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4882 for (l=0; l<ncols; l++) { 4883 *bufA++ = vals[l]; 4884 } 4885 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4886 } 4887 } 4888 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4889 } 4890 /* recvs and sends of a-array are completed */ 4891 i = nrecvs; 4892 while (i--) { 4893 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4894 } 4895 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4896 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4897 4898 if (scall == MAT_INITIAL_MATRIX) { 4899 /* put together the new matrix */ 4900 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4901 4902 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4903 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4904 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4905 b_oth->free_a = PETSC_TRUE; 4906 b_oth->free_ij = PETSC_TRUE; 4907 b_oth->nonew = 0; 4908 4909 ierr = PetscFree(bufj);CHKERRQ(ierr); 4910 if (!startsj_s || !bufa_ptr) { 4911 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4912 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4913 } else { 4914 *startsj_s = sstartsj; 4915 *startsj_r = rstartsj; 4916 *bufa_ptr = bufa; 4917 } 4918 } 4919 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4920 PetscFunctionReturn(0); 4921 } 4922 4923 #undef __FUNCT__ 4924 #define __FUNCT__ "MatGetCommunicationStructs" 4925 /*@C 4926 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4927 4928 Not Collective 4929 4930 Input Parameters: 4931 . A - The matrix in mpiaij format 4932 4933 Output Parameter: 4934 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4935 . colmap - A map from global column index to local index into lvec 4936 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4937 4938 Level: developer 4939 4940 @*/ 4941 #if defined(PETSC_USE_CTABLE) 4942 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4943 #else 4944 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4945 #endif 4946 { 4947 Mat_MPIAIJ *a; 4948 4949 PetscFunctionBegin; 4950 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4951 PetscValidPointer(lvec, 2); 4952 PetscValidPointer(colmap, 3); 4953 PetscValidPointer(multScatter, 4); 4954 a = (Mat_MPIAIJ*) A->data; 4955 if (lvec) *lvec = a->lvec; 4956 if (colmap) *colmap = a->colmap; 4957 if (multScatter) *multScatter = a->Mvctx; 4958 PetscFunctionReturn(0); 4959 } 4960 4961 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4962 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4963 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4964 #if defined(PETSC_HAVE_ELEMENTAL) 4965 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4966 #endif 4967 4968 #undef __FUNCT__ 4969 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4970 /* 4971 Computes (B'*A')' since computing B*A directly is untenable 4972 4973 n p p 4974 ( ) ( ) ( ) 4975 m ( A ) * n ( B ) = m ( C ) 4976 ( ) ( ) ( ) 4977 4978 */ 4979 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4980 { 4981 PetscErrorCode ierr; 4982 Mat At,Bt,Ct; 4983 4984 PetscFunctionBegin; 4985 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4986 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4987 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4988 ierr = MatDestroy(&At);CHKERRQ(ierr); 4989 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4990 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4991 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 4992 PetscFunctionReturn(0); 4993 } 4994 4995 #undef __FUNCT__ 4996 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4997 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4998 { 4999 PetscErrorCode ierr; 5000 PetscInt m=A->rmap->n,n=B->cmap->n; 5001 Mat Cmat; 5002 5003 PetscFunctionBegin; 5004 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); 5005 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5006 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5007 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5008 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5009 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5010 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5011 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5012 5013 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5014 5015 *C = Cmat; 5016 PetscFunctionReturn(0); 5017 } 5018 5019 /* ----------------------------------------------------------------*/ 5020 #undef __FUNCT__ 5021 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5022 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5023 { 5024 PetscErrorCode ierr; 5025 5026 PetscFunctionBegin; 5027 if (scall == MAT_INITIAL_MATRIX) { 5028 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5029 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5030 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5031 } 5032 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5033 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5034 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5035 PetscFunctionReturn(0); 5036 } 5037 5038 /*MC 5039 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5040 5041 Options Database Keys: 5042 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5043 5044 Level: beginner 5045 5046 .seealso: MatCreateAIJ() 5047 M*/ 5048 5049 #undef __FUNCT__ 5050 #define __FUNCT__ "MatCreate_MPIAIJ" 5051 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5052 { 5053 Mat_MPIAIJ *b; 5054 PetscErrorCode ierr; 5055 PetscMPIInt size; 5056 5057 PetscFunctionBegin; 5058 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5059 5060 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5061 B->data = (void*)b; 5062 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5063 B->assembled = PETSC_FALSE; 5064 B->insertmode = NOT_SET_VALUES; 5065 b->size = size; 5066 5067 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5068 5069 /* build cache for off array entries formed */ 5070 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5071 5072 b->donotstash = PETSC_FALSE; 5073 b->colmap = 0; 5074 b->garray = 0; 5075 b->roworiented = PETSC_TRUE; 5076 5077 /* stuff used for matrix vector multiply */ 5078 b->lvec = NULL; 5079 b->Mvctx = NULL; 5080 5081 /* stuff for MatGetRow() */ 5082 b->rowindices = 0; 5083 b->rowvalues = 0; 5084 b->getrowactive = PETSC_FALSE; 5085 5086 /* flexible pointer used in CUSP/CUSPARSE classes */ 5087 b->spptr = NULL; 5088 5089 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5091 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5092 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5093 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5094 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5095 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5096 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5097 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5098 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5099 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5100 #if defined(PETSC_HAVE_ELEMENTAL) 5101 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5102 #endif 5103 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5104 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5105 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5106 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5107 PetscFunctionReturn(0); 5108 } 5109 5110 #undef __FUNCT__ 5111 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5112 /*@C 5113 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5114 and "off-diagonal" part of the matrix in CSR format. 5115 5116 Collective on MPI_Comm 5117 5118 Input Parameters: 5119 + comm - MPI communicator 5120 . m - number of local rows (Cannot be PETSC_DECIDE) 5121 . n - This value should be the same as the local size used in creating the 5122 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5123 calculated if N is given) For square matrices n is almost always m. 5124 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5125 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5126 . i - row indices for "diagonal" portion of matrix 5127 . j - column indices 5128 . a - matrix values 5129 . oi - row indices for "off-diagonal" portion of matrix 5130 . oj - column indices 5131 - oa - matrix values 5132 5133 Output Parameter: 5134 . mat - the matrix 5135 5136 Level: advanced 5137 5138 Notes: 5139 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5140 must free the arrays once the matrix has been destroyed and not before. 5141 5142 The i and j indices are 0 based 5143 5144 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5145 5146 This sets local rows and cannot be used to set off-processor values. 5147 5148 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5149 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5150 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5151 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5152 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5153 communication if it is known that only local entries will be set. 5154 5155 .keywords: matrix, aij, compressed row, sparse, parallel 5156 5157 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5158 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5159 @*/ 5160 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) 5161 { 5162 PetscErrorCode ierr; 5163 Mat_MPIAIJ *maij; 5164 5165 PetscFunctionBegin; 5166 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5167 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5168 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5169 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5170 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5171 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5172 maij = (Mat_MPIAIJ*) (*mat)->data; 5173 5174 (*mat)->preallocated = PETSC_TRUE; 5175 5176 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5177 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5178 5179 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5180 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5181 5182 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5183 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5184 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5185 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5186 5187 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5188 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5189 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5190 PetscFunctionReturn(0); 5191 } 5192 5193 /* 5194 Special version for direct calls from Fortran 5195 */ 5196 #include <petsc/private/fortranimpl.h> 5197 5198 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5199 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5200 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5201 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5202 #endif 5203 5204 /* Change these macros so can be used in void function */ 5205 #undef CHKERRQ 5206 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5207 #undef SETERRQ2 5208 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5209 #undef SETERRQ3 5210 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5211 #undef SETERRQ 5212 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5213 5214 #undef __FUNCT__ 5215 #define __FUNCT__ "matsetvaluesmpiaij_" 5216 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) 5217 { 5218 Mat mat = *mmat; 5219 PetscInt m = *mm, n = *mn; 5220 InsertMode addv = *maddv; 5221 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5222 PetscScalar value; 5223 PetscErrorCode ierr; 5224 5225 MatCheckPreallocated(mat,1); 5226 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5227 5228 #if defined(PETSC_USE_DEBUG) 5229 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5230 #endif 5231 { 5232 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5233 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5234 PetscBool roworiented = aij->roworiented; 5235 5236 /* Some Variables required in the macro */ 5237 Mat A = aij->A; 5238 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5239 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5240 MatScalar *aa = a->a; 5241 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5242 Mat B = aij->B; 5243 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5244 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5245 MatScalar *ba = b->a; 5246 5247 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5248 PetscInt nonew = a->nonew; 5249 MatScalar *ap1,*ap2; 5250 5251 PetscFunctionBegin; 5252 for (i=0; i<m; i++) { 5253 if (im[i] < 0) continue; 5254 #if defined(PETSC_USE_DEBUG) 5255 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); 5256 #endif 5257 if (im[i] >= rstart && im[i] < rend) { 5258 row = im[i] - rstart; 5259 lastcol1 = -1; 5260 rp1 = aj + ai[row]; 5261 ap1 = aa + ai[row]; 5262 rmax1 = aimax[row]; 5263 nrow1 = ailen[row]; 5264 low1 = 0; 5265 high1 = nrow1; 5266 lastcol2 = -1; 5267 rp2 = bj + bi[row]; 5268 ap2 = ba + bi[row]; 5269 rmax2 = bimax[row]; 5270 nrow2 = bilen[row]; 5271 low2 = 0; 5272 high2 = nrow2; 5273 5274 for (j=0; j<n; j++) { 5275 if (roworiented) value = v[i*n+j]; 5276 else value = v[i+j*m]; 5277 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5278 if (in[j] >= cstart && in[j] < cend) { 5279 col = in[j] - cstart; 5280 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5281 } else if (in[j] < 0) continue; 5282 #if defined(PETSC_USE_DEBUG) 5283 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); 5284 #endif 5285 else { 5286 if (mat->was_assembled) { 5287 if (!aij->colmap) { 5288 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5289 } 5290 #if defined(PETSC_USE_CTABLE) 5291 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5292 col--; 5293 #else 5294 col = aij->colmap[in[j]] - 1; 5295 #endif 5296 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5297 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5298 col = in[j]; 5299 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5300 B = aij->B; 5301 b = (Mat_SeqAIJ*)B->data; 5302 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5303 rp2 = bj + bi[row]; 5304 ap2 = ba + bi[row]; 5305 rmax2 = bimax[row]; 5306 nrow2 = bilen[row]; 5307 low2 = 0; 5308 high2 = nrow2; 5309 bm = aij->B->rmap->n; 5310 ba = b->a; 5311 } 5312 } else col = in[j]; 5313 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5314 } 5315 } 5316 } else if (!aij->donotstash) { 5317 if (roworiented) { 5318 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5319 } else { 5320 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5321 } 5322 } 5323 } 5324 } 5325 PetscFunctionReturnVoid(); 5326 } 5327 5328