1 2 3 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 4 #include <petsc/private/vecimpl.h> 5 #include <petsc/private/isimpl.h> 6 #include <petscblaslapack.h> 7 #include <petscsf.h> 8 9 /*MC 10 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 11 12 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 13 and MATMPIAIJ otherwise. As a result, for single process communicators, 14 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 15 for communicators controlling multiple processes. It is recommended that you call both of 16 the above preallocation routines for simplicity. 17 18 Options Database Keys: 19 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 20 21 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 22 enough exist. 23 24 Level: beginner 25 26 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ 27 M*/ 28 29 /*MC 30 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 31 32 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 33 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 34 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 35 for communicators controlling multiple processes. It is recommended that you call both of 36 the above preallocation routines for simplicity. 37 38 Options Database Keys: 39 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 40 41 Level: beginner 42 43 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 44 M*/ 45 46 PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 51 PetscFunctionBegin; 52 if (mat->A) { 53 ierr = MatSetBlockSizes(mat->A,rbs,cbs);CHKERRQ(ierr); 54 ierr = MatSetBlockSizes(mat->B,rbs,1);CHKERRQ(ierr); 55 } 56 PetscFunctionReturn(0); 57 } 58 59 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 60 { 61 PetscErrorCode ierr; 62 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 63 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 64 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 65 const PetscInt *ia,*ib; 66 const MatScalar *aa,*bb; 67 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 68 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 69 70 PetscFunctionBegin; 71 *keptrows = 0; 72 ia = a->i; 73 ib = b->i; 74 for (i=0; i<m; i++) { 75 na = ia[i+1] - ia[i]; 76 nb = ib[i+1] - ib[i]; 77 if (!na && !nb) { 78 cnt++; 79 goto ok1; 80 } 81 aa = a->a + ia[i]; 82 for (j=0; j<na; j++) { 83 if (aa[j] != 0.0) goto ok1; 84 } 85 bb = b->a + ib[i]; 86 for (j=0; j <nb; j++) { 87 if (bb[j] != 0.0) goto ok1; 88 } 89 cnt++; 90 ok1:; 91 } 92 ierr = MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 93 if (!n0rows) PetscFunctionReturn(0); 94 ierr = PetscMalloc1(M->rmap->n-cnt,&rows);CHKERRQ(ierr); 95 cnt = 0; 96 for (i=0; i<m; i++) { 97 na = ia[i+1] - ia[i]; 98 nb = ib[i+1] - ib[i]; 99 if (!na && !nb) continue; 100 aa = a->a + ia[i]; 101 for (j=0; j<na;j++) { 102 if (aa[j] != 0.0) { 103 rows[cnt++] = rstart + i; 104 goto ok2; 105 } 106 } 107 bb = b->a + ib[i]; 108 for (j=0; j<nb; j++) { 109 if (bb[j] != 0.0) { 110 rows[cnt++] = rstart + i; 111 goto ok2; 112 } 113 } 114 ok2:; 115 } 116 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 117 PetscFunctionReturn(0); 118 } 119 120 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 121 { 122 PetscErrorCode ierr; 123 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 124 125 PetscFunctionBegin; 126 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 127 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 128 } else { 129 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 130 } 131 PetscFunctionReturn(0); 132 } 133 134 135 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 136 { 137 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 138 PetscErrorCode ierr; 139 PetscInt i,rstart,nrows,*rows; 140 141 PetscFunctionBegin; 142 *zrows = NULL; 143 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 144 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 145 for (i=0; i<nrows; i++) rows[i] += rstart; 146 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 147 PetscFunctionReturn(0); 148 } 149 150 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 151 { 152 PetscErrorCode ierr; 153 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 154 PetscInt i,n,*garray = aij->garray; 155 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 156 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 157 PetscReal *work; 158 159 PetscFunctionBegin; 160 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 161 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 162 if (type == NORM_2) { 163 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 164 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 165 } 166 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 167 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 168 } 169 } else if (type == NORM_1) { 170 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 171 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 172 } 173 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 174 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 175 } 176 } else if (type == NORM_INFINITY) { 177 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 178 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 179 } 180 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 181 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 182 } 183 184 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 185 if (type == NORM_INFINITY) { 186 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 187 } else { 188 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 189 } 190 ierr = PetscFree(work);CHKERRQ(ierr); 191 if (type == NORM_2) { 192 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 193 } 194 PetscFunctionReturn(0); 195 } 196 197 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 198 { 199 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 200 IS sis,gis; 201 PetscErrorCode ierr; 202 const PetscInt *isis,*igis; 203 PetscInt n,*iis,nsis,ngis,rstart,i; 204 205 PetscFunctionBegin; 206 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 207 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 208 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 209 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 210 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 211 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 212 213 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 215 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 216 n = ngis + nsis; 217 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 218 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 219 for (i=0; i<n; i++) iis[i] += rstart; 220 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 221 222 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 223 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 224 ierr = ISDestroy(&sis);CHKERRQ(ierr); 225 ierr = ISDestroy(&gis);CHKERRQ(ierr); 226 PetscFunctionReturn(0); 227 } 228 229 /* 230 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 231 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 232 233 Only for square matrices 234 235 Used by a preconditioner, hence PETSC_EXTERN 236 */ 237 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 238 { 239 PetscMPIInt rank,size; 240 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 241 PetscErrorCode ierr; 242 Mat mat; 243 Mat_SeqAIJ *gmata; 244 PetscMPIInt tag; 245 MPI_Status status; 246 PetscBool aij; 247 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 248 249 PetscFunctionBegin; 250 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 252 if (!rank) { 253 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 254 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 255 } 256 if (reuse == MAT_INITIAL_MATRIX) { 257 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 258 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 259 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 260 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 261 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 262 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 263 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 264 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 265 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 266 267 rowners[0] = 0; 268 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 269 rstart = rowners[rank]; 270 rend = rowners[rank+1]; 271 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 272 if (!rank) { 273 gmata = (Mat_SeqAIJ*) gmat->data; 274 /* send row lengths to all processors */ 275 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 276 for (i=1; i<size; i++) { 277 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 278 } 279 /* determine number diagonal and off-diagonal counts */ 280 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 281 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 282 jj = 0; 283 for (i=0; i<m; i++) { 284 for (j=0; j<dlens[i]; j++) { 285 if (gmata->j[jj] < rstart) ld[i]++; 286 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 287 jj++; 288 } 289 } 290 /* send column indices to other processes */ 291 for (i=1; i<size; i++) { 292 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 293 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 295 } 296 297 /* send numerical values to other processes */ 298 for (i=1; i<size; i++) { 299 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 300 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 301 } 302 gmataa = gmata->a; 303 gmataj = gmata->j; 304 305 } else { 306 /* receive row lengths */ 307 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 308 /* receive column indices */ 309 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 310 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 311 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 312 /* determine number diagonal and off-diagonal counts */ 313 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 314 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 315 jj = 0; 316 for (i=0; i<m; i++) { 317 for (j=0; j<dlens[i]; j++) { 318 if (gmataj[jj] < rstart) ld[i]++; 319 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 320 jj++; 321 } 322 } 323 /* receive numerical values */ 324 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 325 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 326 } 327 /* set preallocation */ 328 for (i=0; i<m; i++) { 329 dlens[i] -= olens[i]; 330 } 331 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 332 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 333 334 for (i=0; i<m; i++) { 335 dlens[i] += olens[i]; 336 } 337 cnt = 0; 338 for (i=0; i<m; i++) { 339 row = rstart + i; 340 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 341 cnt += dlens[i]; 342 } 343 if (rank) { 344 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 345 } 346 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 347 ierr = PetscFree(rowners);CHKERRQ(ierr); 348 349 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 350 351 *inmat = mat; 352 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 353 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 354 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 355 mat = *inmat; 356 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 357 if (!rank) { 358 /* send numerical values to other processes */ 359 gmata = (Mat_SeqAIJ*) gmat->data; 360 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 361 gmataa = gmata->a; 362 for (i=1; i<size; i++) { 363 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 364 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 365 } 366 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 367 } else { 368 /* receive numerical values from process 0*/ 369 nz = Ad->nz + Ao->nz; 370 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 371 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 372 } 373 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 374 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 375 ad = Ad->a; 376 ao = Ao->a; 377 if (mat->rmap->n) { 378 i = 0; 379 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 380 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 381 } 382 for (i=1; i<mat->rmap->n; i++) { 383 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; 384 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 385 } 386 i--; 387 if (mat->rmap->n) { 388 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 389 } 390 if (rank) { 391 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 392 } 393 } 394 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 396 PetscFunctionReturn(0); 397 } 398 399 /* 400 Local utility routine that creates a mapping from the global column 401 number to the local number in the off-diagonal part of the local 402 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 403 a slightly higher hash table cost; without it it is not scalable (each processor 404 has an order N integer array but is fast to acess. 405 */ 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 && row != col) {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 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 499 { 500 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 501 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 502 PetscErrorCode ierr; 503 PetscInt l,*garray = mat->garray,diag; 504 505 PetscFunctionBegin; 506 /* code only works for square matrices A */ 507 508 /* find size of row to the left of the diagonal part */ 509 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 510 row = row - diag; 511 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 512 if (garray[b->j[b->i[row]+l]] > diag) break; 513 } 514 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 515 516 /* diagonal part */ 517 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 518 519 /* right of diagonal part */ 520 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); 521 PetscFunctionReturn(0); 522 } 523 524 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 525 { 526 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 527 PetscScalar value; 528 PetscErrorCode ierr; 529 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 530 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 531 PetscBool roworiented = aij->roworiented; 532 533 /* Some Variables required in the macro */ 534 Mat A = aij->A; 535 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 536 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 537 MatScalar *aa = a->a; 538 PetscBool ignorezeroentries = a->ignorezeroentries; 539 Mat B = aij->B; 540 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 541 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 542 MatScalar *ba = b->a; 543 544 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 545 PetscInt nonew; 546 MatScalar *ap1,*ap2; 547 548 PetscFunctionBegin; 549 for (i=0; i<m; i++) { 550 if (im[i] < 0) continue; 551 #if defined(PETSC_USE_DEBUG) 552 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); 553 #endif 554 if (im[i] >= rstart && im[i] < rend) { 555 row = im[i] - rstart; 556 lastcol1 = -1; 557 rp1 = aj + ai[row]; 558 ap1 = aa + ai[row]; 559 rmax1 = aimax[row]; 560 nrow1 = ailen[row]; 561 low1 = 0; 562 high1 = nrow1; 563 lastcol2 = -1; 564 rp2 = bj + bi[row]; 565 ap2 = ba + bi[row]; 566 rmax2 = bimax[row]; 567 nrow2 = bilen[row]; 568 low2 = 0; 569 high2 = nrow2; 570 571 for (j=0; j<n; j++) { 572 if (roworiented) value = v[i*n+j]; 573 else value = v[i+j*m]; 574 if (in[j] >= cstart && in[j] < cend) { 575 col = in[j] - cstart; 576 nonew = a->nonew; 577 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 578 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 579 } else if (in[j] < 0) continue; 580 #if defined(PETSC_USE_DEBUG) 581 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); 582 #endif 583 else { 584 if (mat->was_assembled) { 585 if (!aij->colmap) { 586 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 587 } 588 #if defined(PETSC_USE_CTABLE) 589 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 590 col--; 591 #else 592 col = aij->colmap[in[j]] - 1; 593 #endif 594 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 595 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 596 col = in[j]; 597 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 598 B = aij->B; 599 b = (Mat_SeqAIJ*)B->data; 600 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 601 rp2 = bj + bi[row]; 602 ap2 = ba + bi[row]; 603 rmax2 = bimax[row]; 604 nrow2 = bilen[row]; 605 low2 = 0; 606 high2 = nrow2; 607 bm = aij->B->rmap->n; 608 ba = b->a; 609 } 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]); 610 } else col = in[j]; 611 nonew = b->nonew; 612 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 613 } 614 } 615 } else { 616 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]); 617 if (!aij->donotstash) { 618 mat->assembled = PETSC_FALSE; 619 if (roworiented) { 620 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } else { 622 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 623 } 624 } 625 } 626 } 627 PetscFunctionReturn(0); 628 } 629 630 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 631 { 632 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 633 PetscErrorCode ierr; 634 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 635 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 636 637 PetscFunctionBegin; 638 for (i=0; i<m; i++) { 639 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 640 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); 641 if (idxm[i] >= rstart && idxm[i] < rend) { 642 row = idxm[i] - rstart; 643 for (j=0; j<n; j++) { 644 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 645 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); 646 if (idxn[j] >= cstart && idxn[j] < cend) { 647 col = idxn[j] - cstart; 648 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 649 } else { 650 if (!aij->colmap) { 651 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 652 } 653 #if defined(PETSC_USE_CTABLE) 654 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 655 col--; 656 #else 657 col = aij->colmap[idxn[j]] - 1; 658 #endif 659 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 660 else { 661 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 662 } 663 } 664 } 665 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 666 } 667 PetscFunctionReturn(0); 668 } 669 670 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 671 672 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 673 { 674 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 675 PetscErrorCode ierr; 676 PetscInt nstash,reallocs; 677 678 PetscFunctionBegin; 679 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 680 681 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 682 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 683 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 684 PetscFunctionReturn(0); 685 } 686 687 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 688 { 689 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 690 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 691 PetscErrorCode ierr; 692 PetscMPIInt n; 693 PetscInt i,j,rstart,ncols,flg; 694 PetscInt *row,*col; 695 PetscBool other_disassembled; 696 PetscScalar *val; 697 698 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 699 700 PetscFunctionBegin; 701 if (!aij->donotstash && !mat->nooffprocentries) { 702 while (1) { 703 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 704 if (!flg) break; 705 706 for (i=0; i<n; ) { 707 /* Now identify the consecutive vals belonging to the same row */ 708 for (j=i,rstart=row[j]; j<n; j++) { 709 if (row[j] != rstart) break; 710 } 711 if (j < n) ncols = j-i; 712 else ncols = n-i; 713 /* Now assemble all these values with a single function call */ 714 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 715 716 i = j; 717 } 718 } 719 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 720 } 721 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 722 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 723 724 /* determine if any processor has disassembled, if so we must 725 also disassemble ourselfs, in order that we may reassemble. */ 726 /* 727 if nonzero structure of submatrix B cannot change then we know that 728 no processor disassembled thus we can skip this stuff 729 */ 730 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 731 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 732 if (mat->was_assembled && !other_disassembled) { 733 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 734 } 735 } 736 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 737 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 738 } 739 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 740 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 741 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 742 743 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 744 745 aij->rowvalues = 0; 746 747 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 748 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 749 750 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 751 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 752 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 753 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 754 } 755 PetscFunctionReturn(0); 756 } 757 758 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 759 { 760 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 761 PetscErrorCode ierr; 762 763 PetscFunctionBegin; 764 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 765 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 766 PetscFunctionReturn(0); 767 } 768 769 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 770 { 771 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 772 PetscInt *lrows; 773 PetscInt r, len; 774 PetscErrorCode ierr; 775 776 PetscFunctionBegin; 777 /* get locally owned rows */ 778 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 779 /* fix right hand side if needed */ 780 if (x && b) { 781 const PetscScalar *xx; 782 PetscScalar *bb; 783 784 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 785 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 786 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 787 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 788 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 789 } 790 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 791 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 792 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 793 PetscBool cong; 794 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 795 if (cong) A->congruentlayouts = 1; 796 else A->congruentlayouts = 0; 797 } 798 if ((diag != 0.0) && A->congruentlayouts) { 799 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 800 } else if (diag != 0.0) { 801 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 802 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"); 803 for (r = 0; r < len; ++r) { 804 const PetscInt row = lrows[r] + A->rmap->rstart; 805 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 806 } 807 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 808 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 809 } else { 810 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 811 } 812 ierr = PetscFree(lrows);CHKERRQ(ierr); 813 814 /* only change matrix nonzero state if pattern was allowed to be changed */ 815 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 816 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 817 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 818 } 819 PetscFunctionReturn(0); 820 } 821 822 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 823 { 824 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 825 PetscErrorCode ierr; 826 PetscMPIInt n = A->rmap->n; 827 PetscInt i,j,r,m,p = 0,len = 0; 828 PetscInt *lrows,*owners = A->rmap->range; 829 PetscSFNode *rrows; 830 PetscSF sf; 831 const PetscScalar *xx; 832 PetscScalar *bb,*mask; 833 Vec xmask,lmask; 834 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 835 const PetscInt *aj, *ii,*ridx; 836 PetscScalar *aa; 837 838 PetscFunctionBegin; 839 /* Create SF where leaves are input rows and roots are owned rows */ 840 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 841 for (r = 0; r < n; ++r) lrows[r] = -1; 842 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 843 for (r = 0; r < N; ++r) { 844 const PetscInt idx = rows[r]; 845 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); 846 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 847 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 848 } 849 rrows[r].rank = p; 850 rrows[r].index = rows[r] - owners[p]; 851 } 852 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 853 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 854 /* Collect flags for rows to be zeroed */ 855 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 856 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 857 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 858 /* Compress and put in row numbers */ 859 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 860 /* zero diagonal part of matrix */ 861 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 862 /* handle off diagonal part of matrix */ 863 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 864 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 865 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 866 for (i=0; i<len; i++) bb[lrows[i]] = 1; 867 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 868 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 869 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 870 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 871 if (x) { 872 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 873 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 874 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 875 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 876 } 877 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 878 /* remove zeroed rows of off diagonal matrix */ 879 ii = aij->i; 880 for (i=0; i<len; i++) { 881 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 882 } 883 /* loop over all elements of off process part of matrix zeroing removed columns*/ 884 if (aij->compressedrow.use) { 885 m = aij->compressedrow.nrows; 886 ii = aij->compressedrow.i; 887 ridx = aij->compressedrow.rindex; 888 for (i=0; i<m; i++) { 889 n = ii[i+1] - ii[i]; 890 aj = aij->j + ii[i]; 891 aa = aij->a + ii[i]; 892 893 for (j=0; j<n; j++) { 894 if (PetscAbsScalar(mask[*aj])) { 895 if (b) bb[*ridx] -= *aa*xx[*aj]; 896 *aa = 0.0; 897 } 898 aa++; 899 aj++; 900 } 901 ridx++; 902 } 903 } else { /* do not use compressed row format */ 904 m = l->B->rmap->n; 905 for (i=0; i<m; i++) { 906 n = ii[i+1] - ii[i]; 907 aj = aij->j + ii[i]; 908 aa = aij->a + ii[i]; 909 for (j=0; j<n; j++) { 910 if (PetscAbsScalar(mask[*aj])) { 911 if (b) bb[i] -= *aa*xx[*aj]; 912 *aa = 0.0; 913 } 914 aa++; 915 aj++; 916 } 917 } 918 } 919 if (x) { 920 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 921 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 922 } 923 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 924 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 925 ierr = PetscFree(lrows);CHKERRQ(ierr); 926 927 /* only change matrix nonzero state if pattern was allowed to be changed */ 928 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 929 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 930 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 931 } 932 PetscFunctionReturn(0); 933 } 934 935 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 936 { 937 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 938 PetscErrorCode ierr; 939 PetscInt nt; 940 941 PetscFunctionBegin; 942 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 943 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); 944 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 946 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 947 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 948 PetscFunctionReturn(0); 949 } 950 951 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 952 { 953 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 954 PetscErrorCode ierr; 955 956 PetscFunctionBegin; 957 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 962 { 963 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 964 PetscErrorCode ierr; 965 966 PetscFunctionBegin; 967 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 969 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 970 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 975 { 976 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 977 PetscErrorCode ierr; 978 PetscBool merged; 979 980 PetscFunctionBegin; 981 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 982 /* do nondiagonal part */ 983 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 984 if (!merged) { 985 /* send it on its way */ 986 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 987 /* do local part */ 988 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 989 /* receive remote parts: note this assumes the values are not actually */ 990 /* added in yy until the next line, */ 991 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 992 } else { 993 /* do local part */ 994 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 995 /* send it on its way */ 996 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 /* values actually were received in the Begin() but we need to call this nop */ 998 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 999 } 1000 PetscFunctionReturn(0); 1001 } 1002 1003 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1004 { 1005 MPI_Comm comm; 1006 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1007 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1008 IS Me,Notme; 1009 PetscErrorCode ierr; 1010 PetscInt M,N,first,last,*notme,i; 1011 PetscMPIInt size; 1012 1013 PetscFunctionBegin; 1014 /* Easy test: symmetric diagonal block */ 1015 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1016 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1017 if (!*f) PetscFunctionReturn(0); 1018 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1019 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1020 if (size == 1) PetscFunctionReturn(0); 1021 1022 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1023 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1024 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1025 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1026 for (i=0; i<first; i++) notme[i] = i; 1027 for (i=last; i<M; i++) notme[i-last+first] = i; 1028 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1029 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1030 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1031 Aoff = Aoffs[0]; 1032 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1033 Boff = Boffs[0]; 1034 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1035 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1036 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1037 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1038 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1039 ierr = PetscFree(notme);CHKERRQ(ierr); 1040 PetscFunctionReturn(0); 1041 } 1042 1043 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1044 { 1045 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1046 PetscErrorCode ierr; 1047 1048 PetscFunctionBegin; 1049 /* do nondiagonal part */ 1050 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1051 /* send it on its way */ 1052 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1053 /* do local part */ 1054 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1055 /* receive remote parts */ 1056 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1057 PetscFunctionReturn(0); 1058 } 1059 1060 /* 1061 This only works correctly for square matrices where the subblock A->A is the 1062 diagonal block 1063 */ 1064 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1065 { 1066 PetscErrorCode ierr; 1067 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1068 1069 PetscFunctionBegin; 1070 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1071 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"); 1072 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1073 PetscFunctionReturn(0); 1074 } 1075 1076 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1077 { 1078 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1079 PetscErrorCode ierr; 1080 1081 PetscFunctionBegin; 1082 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1083 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1084 PetscFunctionReturn(0); 1085 } 1086 1087 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1088 { 1089 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1090 PetscErrorCode ierr; 1091 1092 PetscFunctionBegin; 1093 #if defined(PETSC_USE_LOG) 1094 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1095 #endif 1096 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1097 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1098 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1099 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1100 #if defined(PETSC_USE_CTABLE) 1101 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1102 #else 1103 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1104 #endif 1105 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1106 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1107 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1108 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1109 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1110 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1111 1112 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1118 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1120 #if defined(PETSC_HAVE_ELEMENTAL) 1121 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1122 #endif 1123 #if defined(PETSC_HAVE_HYPRE) 1124 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1126 #endif 1127 PetscFunctionReturn(0); 1128 } 1129 1130 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1131 { 1132 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1133 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1134 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1135 PetscErrorCode ierr; 1136 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1137 int fd; 1138 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1139 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1140 PetscScalar *column_values; 1141 PetscInt message_count,flowcontrolcount; 1142 FILE *file; 1143 1144 PetscFunctionBegin; 1145 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1146 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1147 nz = A->nz + B->nz; 1148 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1149 if (!rank) { 1150 header[0] = MAT_FILE_CLASSID; 1151 header[1] = mat->rmap->N; 1152 header[2] = mat->cmap->N; 1153 1154 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1155 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1156 /* get largest number of rows any processor has */ 1157 rlen = mat->rmap->n; 1158 range = mat->rmap->range; 1159 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1160 } else { 1161 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1162 rlen = mat->rmap->n; 1163 } 1164 1165 /* load up the local row counts */ 1166 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1167 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]; 1168 1169 /* store the row lengths to the file */ 1170 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1171 if (!rank) { 1172 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1173 for (i=1; i<size; i++) { 1174 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1175 rlen = range[i+1] - range[i]; 1176 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1177 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1178 } 1179 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1180 } else { 1181 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1182 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1183 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1184 } 1185 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1186 1187 /* load up the local column indices */ 1188 nzmax = nz; /* th processor needs space a largest processor needs */ 1189 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1190 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1191 cnt = 0; 1192 for (i=0; i<mat->rmap->n; i++) { 1193 for (j=B->i[i]; j<B->i[i+1]; j++) { 1194 if ((col = garray[B->j[j]]) > cstart) break; 1195 column_indices[cnt++] = col; 1196 } 1197 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1198 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1199 } 1200 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); 1201 1202 /* store the column indices to the file */ 1203 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1204 if (!rank) { 1205 MPI_Status status; 1206 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1207 for (i=1; i<size; i++) { 1208 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1209 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1210 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1211 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1212 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1213 } 1214 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1215 } else { 1216 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1217 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1218 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1219 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1220 } 1221 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1222 1223 /* load up the local column values */ 1224 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1225 cnt = 0; 1226 for (i=0; i<mat->rmap->n; i++) { 1227 for (j=B->i[i]; j<B->i[i+1]; j++) { 1228 if (garray[B->j[j]] > cstart) break; 1229 column_values[cnt++] = B->a[j]; 1230 } 1231 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1232 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1233 } 1234 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); 1235 1236 /* store the column values to the file */ 1237 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1238 if (!rank) { 1239 MPI_Status status; 1240 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1241 for (i=1; i<size; i++) { 1242 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1243 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1244 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1245 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1247 } 1248 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1249 } else { 1250 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1251 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1252 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1253 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1254 } 1255 ierr = PetscFree(column_values);CHKERRQ(ierr); 1256 1257 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1258 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #include <petscdraw.h> 1263 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1264 { 1265 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1266 PetscErrorCode ierr; 1267 PetscMPIInt rank = aij->rank,size = aij->size; 1268 PetscBool isdraw,iascii,isbinary; 1269 PetscViewer sviewer; 1270 PetscViewerFormat format; 1271 1272 PetscFunctionBegin; 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1274 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1275 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1276 if (iascii) { 1277 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1278 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1279 MatInfo info; 1280 PetscBool inodes; 1281 1282 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1283 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1284 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1285 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1286 if (!inodes) { 1287 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1288 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1289 } else { 1290 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1291 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1292 } 1293 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1297 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1298 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1299 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1300 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1301 PetscFunctionReturn(0); 1302 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1303 PetscInt inodecount,inodelimit,*inodes; 1304 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1305 if (inodes) { 1306 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1307 } else { 1308 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1309 } 1310 PetscFunctionReturn(0); 1311 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1312 PetscFunctionReturn(0); 1313 } 1314 } else if (isbinary) { 1315 if (size == 1) { 1316 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1317 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1318 } else { 1319 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1320 } 1321 PetscFunctionReturn(0); 1322 } else if (isdraw) { 1323 PetscDraw draw; 1324 PetscBool isnull; 1325 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1326 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1327 if (isnull) PetscFunctionReturn(0); 1328 } 1329 1330 { 1331 /* assemble the entire matrix onto first processor. */ 1332 Mat A; 1333 Mat_SeqAIJ *Aloc; 1334 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1335 MatScalar *a; 1336 1337 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1338 if (!rank) { 1339 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1340 } else { 1341 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1342 } 1343 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1344 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1345 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1346 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1347 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1348 1349 /* copy over the A part */ 1350 Aloc = (Mat_SeqAIJ*)aij->A->data; 1351 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1352 row = mat->rmap->rstart; 1353 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1354 for (i=0; i<m; i++) { 1355 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1356 row++; 1357 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1358 } 1359 aj = Aloc->j; 1360 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1361 1362 /* copy over the B part */ 1363 Aloc = (Mat_SeqAIJ*)aij->B->data; 1364 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1365 row = mat->rmap->rstart; 1366 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1367 ct = cols; 1368 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1369 for (i=0; i<m; i++) { 1370 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1371 row++; 1372 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1373 } 1374 ierr = PetscFree(ct);CHKERRQ(ierr); 1375 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1376 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1377 /* 1378 Everyone has to call to draw the matrix since the graphics waits are 1379 synchronized across all processors that share the PetscDraw object 1380 */ 1381 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1382 if (!rank) { 1383 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1384 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1385 } 1386 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1387 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1388 ierr = MatDestroy(&A);CHKERRQ(ierr); 1389 } 1390 PetscFunctionReturn(0); 1391 } 1392 1393 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1394 { 1395 PetscErrorCode ierr; 1396 PetscBool iascii,isdraw,issocket,isbinary; 1397 1398 PetscFunctionBegin; 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1401 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1402 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1403 if (iascii || isdraw || isbinary || issocket) { 1404 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1405 } 1406 PetscFunctionReturn(0); 1407 } 1408 1409 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1410 { 1411 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1412 PetscErrorCode ierr; 1413 Vec bb1 = 0; 1414 PetscBool hasop; 1415 1416 PetscFunctionBegin; 1417 if (flag == SOR_APPLY_UPPER) { 1418 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1419 PetscFunctionReturn(0); 1420 } 1421 1422 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1423 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1424 } 1425 1426 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1427 if (flag & SOR_ZERO_INITIAL_GUESS) { 1428 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1429 its--; 1430 } 1431 1432 while (its--) { 1433 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1434 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1435 1436 /* update rhs: bb1 = bb - B*x */ 1437 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1438 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1439 1440 /* local sweep */ 1441 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1442 } 1443 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1444 if (flag & SOR_ZERO_INITIAL_GUESS) { 1445 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1446 its--; 1447 } 1448 while (its--) { 1449 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1450 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1451 1452 /* update rhs: bb1 = bb - B*x */ 1453 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1454 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1455 1456 /* local sweep */ 1457 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1458 } 1459 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1460 if (flag & SOR_ZERO_INITIAL_GUESS) { 1461 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1462 its--; 1463 } 1464 while (its--) { 1465 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1466 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1467 1468 /* update rhs: bb1 = bb - B*x */ 1469 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1470 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1471 1472 /* local sweep */ 1473 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1474 } 1475 } else if (flag & SOR_EISENSTAT) { 1476 Vec xx1; 1477 1478 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1479 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1480 1481 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1482 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1483 if (!mat->diag) { 1484 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1485 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1486 } 1487 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1488 if (hasop) { 1489 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1490 } else { 1491 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1492 } 1493 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1494 1495 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1496 1497 /* local sweep */ 1498 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1499 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1500 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1501 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1502 1503 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1504 1505 matin->factorerrortype = mat->A->factorerrortype; 1506 PetscFunctionReturn(0); 1507 } 1508 1509 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1510 { 1511 Mat aA,aB,Aperm; 1512 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1513 PetscScalar *aa,*ba; 1514 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1515 PetscSF rowsf,sf; 1516 IS parcolp = NULL; 1517 PetscBool done; 1518 PetscErrorCode ierr; 1519 1520 PetscFunctionBegin; 1521 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1522 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1523 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1524 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1525 1526 /* Invert row permutation to find out where my rows should go */ 1527 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1528 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1529 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1530 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1531 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1532 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1533 1534 /* Invert column permutation to find out where my columns should go */ 1535 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1536 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1537 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1538 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1539 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1540 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1541 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1542 1543 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1544 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1545 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1546 1547 /* Find out where my gcols should go */ 1548 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1549 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1550 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1551 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1552 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1553 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1554 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1555 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1556 1557 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1558 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1559 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1560 for (i=0; i<m; i++) { 1561 PetscInt row = rdest[i],rowner; 1562 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1563 for (j=ai[i]; j<ai[i+1]; j++) { 1564 PetscInt cowner,col = cdest[aj[j]]; 1565 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1566 if (rowner == cowner) dnnz[i]++; 1567 else onnz[i]++; 1568 } 1569 for (j=bi[i]; j<bi[i+1]; j++) { 1570 PetscInt cowner,col = gcdest[bj[j]]; 1571 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1572 if (rowner == cowner) dnnz[i]++; 1573 else onnz[i]++; 1574 } 1575 } 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1578 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1579 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1580 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1581 1582 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1583 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1584 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1585 for (i=0; i<m; i++) { 1586 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1587 PetscInt j0,rowlen; 1588 rowlen = ai[i+1] - ai[i]; 1589 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1590 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1591 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1592 } 1593 rowlen = bi[i+1] - bi[i]; 1594 for (j0=j=0; j<rowlen; j0=j) { 1595 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1596 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1597 } 1598 } 1599 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1600 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1601 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1602 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1603 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1604 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1605 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1606 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1607 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1608 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1609 *B = Aperm; 1610 PetscFunctionReturn(0); 1611 } 1612 1613 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1614 { 1615 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1616 PetscErrorCode ierr; 1617 1618 PetscFunctionBegin; 1619 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1620 if (ghosts) *ghosts = aij->garray; 1621 PetscFunctionReturn(0); 1622 } 1623 1624 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1625 { 1626 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1627 Mat A = mat->A,B = mat->B; 1628 PetscErrorCode ierr; 1629 PetscReal isend[5],irecv[5]; 1630 1631 PetscFunctionBegin; 1632 info->block_size = 1.0; 1633 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1634 1635 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1636 isend[3] = info->memory; isend[4] = info->mallocs; 1637 1638 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1639 1640 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1641 isend[3] += info->memory; isend[4] += info->mallocs; 1642 if (flag == MAT_LOCAL) { 1643 info->nz_used = isend[0]; 1644 info->nz_allocated = isend[1]; 1645 info->nz_unneeded = isend[2]; 1646 info->memory = isend[3]; 1647 info->mallocs = isend[4]; 1648 } else if (flag == MAT_GLOBAL_MAX) { 1649 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1650 1651 info->nz_used = irecv[0]; 1652 info->nz_allocated = irecv[1]; 1653 info->nz_unneeded = irecv[2]; 1654 info->memory = irecv[3]; 1655 info->mallocs = irecv[4]; 1656 } else if (flag == MAT_GLOBAL_SUM) { 1657 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1658 1659 info->nz_used = irecv[0]; 1660 info->nz_allocated = irecv[1]; 1661 info->nz_unneeded = irecv[2]; 1662 info->memory = irecv[3]; 1663 info->mallocs = irecv[4]; 1664 } 1665 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1666 info->fill_ratio_needed = 0; 1667 info->factor_mallocs = 0; 1668 PetscFunctionReturn(0); 1669 } 1670 1671 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1672 { 1673 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1674 PetscErrorCode ierr; 1675 1676 PetscFunctionBegin; 1677 switch (op) { 1678 case MAT_NEW_NONZERO_LOCATIONS: 1679 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1680 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1681 case MAT_KEEP_NONZERO_PATTERN: 1682 case MAT_NEW_NONZERO_LOCATION_ERR: 1683 case MAT_USE_INODES: 1684 case MAT_IGNORE_ZERO_ENTRIES: 1685 MatCheckPreallocated(A,1); 1686 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1687 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1688 break; 1689 case MAT_ROW_ORIENTED: 1690 MatCheckPreallocated(A,1); 1691 a->roworiented = flg; 1692 1693 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1694 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1695 break; 1696 case MAT_NEW_DIAGONALS: 1697 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1698 break; 1699 case MAT_IGNORE_OFF_PROC_ENTRIES: 1700 a->donotstash = flg; 1701 break; 1702 case MAT_SPD: 1703 A->spd_set = PETSC_TRUE; 1704 A->spd = flg; 1705 if (flg) { 1706 A->symmetric = PETSC_TRUE; 1707 A->structurally_symmetric = PETSC_TRUE; 1708 A->symmetric_set = PETSC_TRUE; 1709 A->structurally_symmetric_set = PETSC_TRUE; 1710 } 1711 break; 1712 case MAT_SYMMETRIC: 1713 MatCheckPreallocated(A,1); 1714 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1715 break; 1716 case MAT_STRUCTURALLY_SYMMETRIC: 1717 MatCheckPreallocated(A,1); 1718 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1719 break; 1720 case MAT_HERMITIAN: 1721 MatCheckPreallocated(A,1); 1722 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1723 break; 1724 case MAT_SYMMETRY_ETERNAL: 1725 MatCheckPreallocated(A,1); 1726 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1727 break; 1728 case MAT_SUBMAT_SINGLEIS: 1729 A->submat_singleis = flg; 1730 break; 1731 default: 1732 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1733 } 1734 PetscFunctionReturn(0); 1735 } 1736 1737 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1738 { 1739 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1740 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1741 PetscErrorCode ierr; 1742 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1743 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1744 PetscInt *cmap,*idx_p; 1745 1746 PetscFunctionBegin; 1747 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1748 mat->getrowactive = PETSC_TRUE; 1749 1750 if (!mat->rowvalues && (idx || v)) { 1751 /* 1752 allocate enough space to hold information from the longest row. 1753 */ 1754 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1755 PetscInt max = 1,tmp; 1756 for (i=0; i<matin->rmap->n; i++) { 1757 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1758 if (max < tmp) max = tmp; 1759 } 1760 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1761 } 1762 1763 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1764 lrow = row - rstart; 1765 1766 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1767 if (!v) {pvA = 0; pvB = 0;} 1768 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1769 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1770 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1771 nztot = nzA + nzB; 1772 1773 cmap = mat->garray; 1774 if (v || idx) { 1775 if (nztot) { 1776 /* Sort by increasing column numbers, assuming A and B already sorted */ 1777 PetscInt imark = -1; 1778 if (v) { 1779 *v = v_p = mat->rowvalues; 1780 for (i=0; i<nzB; i++) { 1781 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1782 else break; 1783 } 1784 imark = i; 1785 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1786 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1787 } 1788 if (idx) { 1789 *idx = idx_p = mat->rowindices; 1790 if (imark > -1) { 1791 for (i=0; i<imark; i++) { 1792 idx_p[i] = cmap[cworkB[i]]; 1793 } 1794 } else { 1795 for (i=0; i<nzB; i++) { 1796 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1797 else break; 1798 } 1799 imark = i; 1800 } 1801 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1802 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1803 } 1804 } else { 1805 if (idx) *idx = 0; 1806 if (v) *v = 0; 1807 } 1808 } 1809 *nz = nztot; 1810 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1811 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1812 PetscFunctionReturn(0); 1813 } 1814 1815 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1816 { 1817 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1818 1819 PetscFunctionBegin; 1820 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1821 aij->getrowactive = PETSC_FALSE; 1822 PetscFunctionReturn(0); 1823 } 1824 1825 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1826 { 1827 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1828 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1829 PetscErrorCode ierr; 1830 PetscInt i,j,cstart = mat->cmap->rstart; 1831 PetscReal sum = 0.0; 1832 MatScalar *v; 1833 1834 PetscFunctionBegin; 1835 if (aij->size == 1) { 1836 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1837 } else { 1838 if (type == NORM_FROBENIUS) { 1839 v = amat->a; 1840 for (i=0; i<amat->nz; i++) { 1841 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1842 } 1843 v = bmat->a; 1844 for (i=0; i<bmat->nz; i++) { 1845 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1846 } 1847 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1848 *norm = PetscSqrtReal(*norm); 1849 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1850 } else if (type == NORM_1) { /* max column norm */ 1851 PetscReal *tmp,*tmp2; 1852 PetscInt *jj,*garray = aij->garray; 1853 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1854 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1855 *norm = 0.0; 1856 v = amat->a; jj = amat->j; 1857 for (j=0; j<amat->nz; j++) { 1858 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1859 } 1860 v = bmat->a; jj = bmat->j; 1861 for (j=0; j<bmat->nz; j++) { 1862 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1863 } 1864 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1865 for (j=0; j<mat->cmap->N; j++) { 1866 if (tmp2[j] > *norm) *norm = tmp2[j]; 1867 } 1868 ierr = PetscFree(tmp);CHKERRQ(ierr); 1869 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1870 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1871 } else if (type == NORM_INFINITY) { /* max row norm */ 1872 PetscReal ntemp = 0.0; 1873 for (j=0; j<aij->A->rmap->n; j++) { 1874 v = amat->a + amat->i[j]; 1875 sum = 0.0; 1876 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1877 sum += PetscAbsScalar(*v); v++; 1878 } 1879 v = bmat->a + bmat->i[j]; 1880 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1881 sum += PetscAbsScalar(*v); v++; 1882 } 1883 if (sum > ntemp) ntemp = sum; 1884 } 1885 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1886 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1887 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1888 } 1889 PetscFunctionReturn(0); 1890 } 1891 1892 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1893 { 1894 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1895 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1896 PetscErrorCode ierr; 1897 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1898 PetscInt cstart = A->cmap->rstart,ncol; 1899 Mat B; 1900 MatScalar *array; 1901 1902 PetscFunctionBegin; 1903 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1904 1905 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1906 ai = Aloc->i; aj = Aloc->j; 1907 bi = Bloc->i; bj = Bloc->j; 1908 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1909 PetscInt *d_nnz,*g_nnz,*o_nnz; 1910 PetscSFNode *oloc; 1911 PETSC_UNUSED PetscSF sf; 1912 1913 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1914 /* compute d_nnz for preallocation */ 1915 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1916 for (i=0; i<ai[ma]; i++) { 1917 d_nnz[aj[i]]++; 1918 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1919 } 1920 /* compute local off-diagonal contributions */ 1921 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1922 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1923 /* map those to global */ 1924 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1925 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1926 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1927 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1928 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1929 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1930 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1931 1932 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1933 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1934 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1935 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1936 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1937 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1938 } else { 1939 B = *matout; 1940 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1941 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1942 } 1943 1944 /* copy over the A part */ 1945 array = Aloc->a; 1946 row = A->rmap->rstart; 1947 for (i=0; i<ma; i++) { 1948 ncol = ai[i+1]-ai[i]; 1949 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1950 row++; 1951 array += ncol; aj += ncol; 1952 } 1953 aj = Aloc->j; 1954 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1955 1956 /* copy over the B part */ 1957 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1958 array = Bloc->a; 1959 row = A->rmap->rstart; 1960 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1961 cols_tmp = cols; 1962 for (i=0; i<mb; i++) { 1963 ncol = bi[i+1]-bi[i]; 1964 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1965 row++; 1966 array += ncol; cols_tmp += ncol; 1967 } 1968 ierr = PetscFree(cols);CHKERRQ(ierr); 1969 1970 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1971 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1972 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1973 *matout = B; 1974 } else { 1975 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1976 } 1977 PetscFunctionReturn(0); 1978 } 1979 1980 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1981 { 1982 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1983 Mat a = aij->A,b = aij->B; 1984 PetscErrorCode ierr; 1985 PetscInt s1,s2,s3; 1986 1987 PetscFunctionBegin; 1988 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1989 if (rr) { 1990 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1991 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1992 /* Overlap communication with computation. */ 1993 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1994 } 1995 if (ll) { 1996 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1997 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1998 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1999 } 2000 /* scale the diagonal block */ 2001 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2002 2003 if (rr) { 2004 /* Do a scatter end and then right scale the off-diagonal block */ 2005 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2006 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2007 } 2008 PetscFunctionReturn(0); 2009 } 2010 2011 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2012 { 2013 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2014 PetscErrorCode ierr; 2015 2016 PetscFunctionBegin; 2017 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2018 PetscFunctionReturn(0); 2019 } 2020 2021 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2022 { 2023 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2024 Mat a,b,c,d; 2025 PetscBool flg; 2026 PetscErrorCode ierr; 2027 2028 PetscFunctionBegin; 2029 a = matA->A; b = matA->B; 2030 c = matB->A; d = matB->B; 2031 2032 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2033 if (flg) { 2034 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2035 } 2036 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2037 PetscFunctionReturn(0); 2038 } 2039 2040 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2041 { 2042 PetscErrorCode ierr; 2043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2044 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2045 2046 PetscFunctionBegin; 2047 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2048 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2049 /* because of the column compression in the off-processor part of the matrix a->B, 2050 the number of columns in a->B and b->B may be different, hence we cannot call 2051 the MatCopy() directly on the two parts. If need be, we can provide a more 2052 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2053 then copying the submatrices */ 2054 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2055 } else { 2056 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2057 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2058 } 2059 PetscFunctionReturn(0); 2060 } 2061 2062 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2063 { 2064 PetscErrorCode ierr; 2065 2066 PetscFunctionBegin; 2067 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2068 PetscFunctionReturn(0); 2069 } 2070 2071 /* 2072 Computes the number of nonzeros per row needed for preallocation when X and Y 2073 have different nonzero structure. 2074 */ 2075 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) 2076 { 2077 PetscInt i,j,k,nzx,nzy; 2078 2079 PetscFunctionBegin; 2080 /* Set the number of nonzeros in the new matrix */ 2081 for (i=0; i<m; i++) { 2082 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2083 nzx = xi[i+1] - xi[i]; 2084 nzy = yi[i+1] - yi[i]; 2085 nnz[i] = 0; 2086 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2087 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2088 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2089 nnz[i]++; 2090 } 2091 for (; k<nzy; k++) nnz[i]++; 2092 } 2093 PetscFunctionReturn(0); 2094 } 2095 2096 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2097 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2098 { 2099 PetscErrorCode ierr; 2100 PetscInt m = Y->rmap->N; 2101 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2102 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2103 2104 PetscFunctionBegin; 2105 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2106 PetscFunctionReturn(0); 2107 } 2108 2109 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2110 { 2111 PetscErrorCode ierr; 2112 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2113 PetscBLASInt bnz,one=1; 2114 Mat_SeqAIJ *x,*y; 2115 2116 PetscFunctionBegin; 2117 if (str == SAME_NONZERO_PATTERN) { 2118 PetscScalar alpha = a; 2119 x = (Mat_SeqAIJ*)xx->A->data; 2120 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2121 y = (Mat_SeqAIJ*)yy->A->data; 2122 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2123 x = (Mat_SeqAIJ*)xx->B->data; 2124 y = (Mat_SeqAIJ*)yy->B->data; 2125 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2126 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2127 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2128 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2129 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2130 } else { 2131 Mat B; 2132 PetscInt *nnz_d,*nnz_o; 2133 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2134 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2135 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2136 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2137 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2138 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2139 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2140 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2141 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2142 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2143 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2144 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2145 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2146 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2147 } 2148 PetscFunctionReturn(0); 2149 } 2150 2151 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2152 2153 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2154 { 2155 #if defined(PETSC_USE_COMPLEX) 2156 PetscErrorCode ierr; 2157 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2158 2159 PetscFunctionBegin; 2160 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2161 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2162 #else 2163 PetscFunctionBegin; 2164 #endif 2165 PetscFunctionReturn(0); 2166 } 2167 2168 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2169 { 2170 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2171 PetscErrorCode ierr; 2172 2173 PetscFunctionBegin; 2174 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2175 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2176 PetscFunctionReturn(0); 2177 } 2178 2179 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2180 { 2181 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2182 PetscErrorCode ierr; 2183 2184 PetscFunctionBegin; 2185 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2186 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2187 PetscFunctionReturn(0); 2188 } 2189 2190 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2191 { 2192 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2193 PetscErrorCode ierr; 2194 PetscInt i,*idxb = 0; 2195 PetscScalar *va,*vb; 2196 Vec vtmp; 2197 2198 PetscFunctionBegin; 2199 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2200 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2201 if (idx) { 2202 for (i=0; i<A->rmap->n; i++) { 2203 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2204 } 2205 } 2206 2207 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2208 if (idx) { 2209 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2210 } 2211 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2212 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2213 2214 for (i=0; i<A->rmap->n; i++) { 2215 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2216 va[i] = vb[i]; 2217 if (idx) idx[i] = a->garray[idxb[i]]; 2218 } 2219 } 2220 2221 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2222 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2223 ierr = PetscFree(idxb);CHKERRQ(ierr); 2224 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2225 PetscFunctionReturn(0); 2226 } 2227 2228 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2229 { 2230 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2231 PetscErrorCode ierr; 2232 PetscInt i,*idxb = 0; 2233 PetscScalar *va,*vb; 2234 Vec vtmp; 2235 2236 PetscFunctionBegin; 2237 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2238 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2239 if (idx) { 2240 for (i=0; i<A->cmap->n; i++) { 2241 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2242 } 2243 } 2244 2245 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2246 if (idx) { 2247 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2248 } 2249 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2250 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2251 2252 for (i=0; i<A->rmap->n; i++) { 2253 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2254 va[i] = vb[i]; 2255 if (idx) idx[i] = a->garray[idxb[i]]; 2256 } 2257 } 2258 2259 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2260 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2261 ierr = PetscFree(idxb);CHKERRQ(ierr); 2262 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2263 PetscFunctionReturn(0); 2264 } 2265 2266 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2267 { 2268 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2269 PetscInt n = A->rmap->n; 2270 PetscInt cstart = A->cmap->rstart; 2271 PetscInt *cmap = mat->garray; 2272 PetscInt *diagIdx, *offdiagIdx; 2273 Vec diagV, offdiagV; 2274 PetscScalar *a, *diagA, *offdiagA; 2275 PetscInt r; 2276 PetscErrorCode ierr; 2277 2278 PetscFunctionBegin; 2279 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2280 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2281 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2282 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2283 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2284 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2285 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2286 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2287 for (r = 0; r < n; ++r) { 2288 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2289 a[r] = diagA[r]; 2290 idx[r] = cstart + diagIdx[r]; 2291 } else { 2292 a[r] = offdiagA[r]; 2293 idx[r] = cmap[offdiagIdx[r]]; 2294 } 2295 } 2296 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2297 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2298 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2299 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2300 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2301 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2302 PetscFunctionReturn(0); 2303 } 2304 2305 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2306 { 2307 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2308 PetscInt n = A->rmap->n; 2309 PetscInt cstart = A->cmap->rstart; 2310 PetscInt *cmap = mat->garray; 2311 PetscInt *diagIdx, *offdiagIdx; 2312 Vec diagV, offdiagV; 2313 PetscScalar *a, *diagA, *offdiagA; 2314 PetscInt r; 2315 PetscErrorCode ierr; 2316 2317 PetscFunctionBegin; 2318 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2319 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2320 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2321 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2322 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2323 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2324 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2325 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2326 for (r = 0; r < n; ++r) { 2327 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2328 a[r] = diagA[r]; 2329 idx[r] = cstart + diagIdx[r]; 2330 } else { 2331 a[r] = offdiagA[r]; 2332 idx[r] = cmap[offdiagIdx[r]]; 2333 } 2334 } 2335 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2336 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2337 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2338 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2339 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2340 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2341 PetscFunctionReturn(0); 2342 } 2343 2344 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2345 { 2346 PetscErrorCode ierr; 2347 Mat *dummy; 2348 2349 PetscFunctionBegin; 2350 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2351 *newmat = *dummy; 2352 ierr = PetscFree(dummy);CHKERRQ(ierr); 2353 PetscFunctionReturn(0); 2354 } 2355 2356 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2357 { 2358 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2359 PetscErrorCode ierr; 2360 2361 PetscFunctionBegin; 2362 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2363 A->factorerrortype = a->A->factorerrortype; 2364 PetscFunctionReturn(0); 2365 } 2366 2367 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2368 { 2369 PetscErrorCode ierr; 2370 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2371 2372 PetscFunctionBegin; 2373 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2374 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2375 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2376 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2377 PetscFunctionReturn(0); 2378 } 2379 2380 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2381 { 2382 PetscFunctionBegin; 2383 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2384 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2385 PetscFunctionReturn(0); 2386 } 2387 2388 /*@ 2389 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2390 2391 Collective on Mat 2392 2393 Input Parameters: 2394 + A - the matrix 2395 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2396 2397 Level: advanced 2398 2399 @*/ 2400 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2401 { 2402 PetscErrorCode ierr; 2403 2404 PetscFunctionBegin; 2405 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2406 PetscFunctionReturn(0); 2407 } 2408 2409 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2410 { 2411 PetscErrorCode ierr; 2412 PetscBool sc = PETSC_FALSE,flg; 2413 2414 PetscFunctionBegin; 2415 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2416 ierr = PetscObjectOptionsBegin((PetscObject)A); 2417 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2418 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2419 if (flg) { 2420 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2421 } 2422 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2423 PetscFunctionReturn(0); 2424 } 2425 2426 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2427 { 2428 PetscErrorCode ierr; 2429 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2430 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2431 2432 PetscFunctionBegin; 2433 if (!Y->preallocated) { 2434 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2435 } else if (!aij->nz) { 2436 PetscInt nonew = aij->nonew; 2437 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2438 aij->nonew = nonew; 2439 } 2440 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2441 PetscFunctionReturn(0); 2442 } 2443 2444 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2445 { 2446 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2447 PetscErrorCode ierr; 2448 2449 PetscFunctionBegin; 2450 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2451 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2452 if (d) { 2453 PetscInt rstart; 2454 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2455 *d += rstart; 2456 2457 } 2458 PetscFunctionReturn(0); 2459 } 2460 2461 2462 /* -------------------------------------------------------------------*/ 2463 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2464 MatGetRow_MPIAIJ, 2465 MatRestoreRow_MPIAIJ, 2466 MatMult_MPIAIJ, 2467 /* 4*/ MatMultAdd_MPIAIJ, 2468 MatMultTranspose_MPIAIJ, 2469 MatMultTransposeAdd_MPIAIJ, 2470 0, 2471 0, 2472 0, 2473 /*10*/ 0, 2474 0, 2475 0, 2476 MatSOR_MPIAIJ, 2477 MatTranspose_MPIAIJ, 2478 /*15*/ MatGetInfo_MPIAIJ, 2479 MatEqual_MPIAIJ, 2480 MatGetDiagonal_MPIAIJ, 2481 MatDiagonalScale_MPIAIJ, 2482 MatNorm_MPIAIJ, 2483 /*20*/ MatAssemblyBegin_MPIAIJ, 2484 MatAssemblyEnd_MPIAIJ, 2485 MatSetOption_MPIAIJ, 2486 MatZeroEntries_MPIAIJ, 2487 /*24*/ MatZeroRows_MPIAIJ, 2488 0, 2489 0, 2490 0, 2491 0, 2492 /*29*/ MatSetUp_MPIAIJ, 2493 0, 2494 0, 2495 MatGetDiagonalBlock_MPIAIJ, 2496 0, 2497 /*34*/ MatDuplicate_MPIAIJ, 2498 0, 2499 0, 2500 0, 2501 0, 2502 /*39*/ MatAXPY_MPIAIJ, 2503 MatCreateSubMatrices_MPIAIJ, 2504 MatIncreaseOverlap_MPIAIJ, 2505 MatGetValues_MPIAIJ, 2506 MatCopy_MPIAIJ, 2507 /*44*/ MatGetRowMax_MPIAIJ, 2508 MatScale_MPIAIJ, 2509 MatShift_MPIAIJ, 2510 MatDiagonalSet_MPIAIJ, 2511 MatZeroRowsColumns_MPIAIJ, 2512 /*49*/ MatSetRandom_MPIAIJ, 2513 0, 2514 0, 2515 0, 2516 0, 2517 /*54*/ MatFDColoringCreate_MPIXAIJ, 2518 0, 2519 MatSetUnfactored_MPIAIJ, 2520 MatPermute_MPIAIJ, 2521 0, 2522 /*59*/ MatCreateSubMatrix_MPIAIJ, 2523 MatDestroy_MPIAIJ, 2524 MatView_MPIAIJ, 2525 0, 2526 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2527 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2528 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2529 0, 2530 0, 2531 0, 2532 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2533 MatGetRowMinAbs_MPIAIJ, 2534 0, 2535 0, 2536 0, 2537 0, 2538 /*75*/ MatFDColoringApply_AIJ, 2539 MatSetFromOptions_MPIAIJ, 2540 0, 2541 0, 2542 MatFindZeroDiagonals_MPIAIJ, 2543 /*80*/ 0, 2544 0, 2545 0, 2546 /*83*/ MatLoad_MPIAIJ, 2547 0, 2548 0, 2549 0, 2550 0, 2551 0, 2552 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2553 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2554 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2555 MatPtAP_MPIAIJ_MPIAIJ, 2556 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2557 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2558 0, 2559 0, 2560 0, 2561 0, 2562 /*99*/ 0, 2563 0, 2564 0, 2565 MatConjugate_MPIAIJ, 2566 0, 2567 /*104*/MatSetValuesRow_MPIAIJ, 2568 MatRealPart_MPIAIJ, 2569 MatImaginaryPart_MPIAIJ, 2570 0, 2571 0, 2572 /*109*/0, 2573 0, 2574 MatGetRowMin_MPIAIJ, 2575 0, 2576 MatMissingDiagonal_MPIAIJ, 2577 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2578 0, 2579 MatGetGhosts_MPIAIJ, 2580 0, 2581 0, 2582 /*119*/0, 2583 0, 2584 0, 2585 0, 2586 MatGetMultiProcBlock_MPIAIJ, 2587 /*124*/MatFindNonzeroRows_MPIAIJ, 2588 MatGetColumnNorms_MPIAIJ, 2589 MatInvertBlockDiagonal_MPIAIJ, 2590 0, 2591 MatCreateSubMatricesMPI_MPIAIJ, 2592 /*129*/0, 2593 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2594 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2595 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2596 0, 2597 /*134*/0, 2598 0, 2599 0, 2600 0, 2601 0, 2602 /*139*/MatSetBlockSizes_MPIAIJ, 2603 0, 2604 0, 2605 MatFDColoringSetUp_MPIXAIJ, 2606 MatFindOffBlockDiagonalEntries_MPIAIJ, 2607 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2608 }; 2609 2610 /* ----------------------------------------------------------------------------------------*/ 2611 2612 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2613 { 2614 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2615 PetscErrorCode ierr; 2616 2617 PetscFunctionBegin; 2618 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2619 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2620 PetscFunctionReturn(0); 2621 } 2622 2623 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2624 { 2625 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2626 PetscErrorCode ierr; 2627 2628 PetscFunctionBegin; 2629 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2630 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2631 PetscFunctionReturn(0); 2632 } 2633 2634 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2635 { 2636 Mat_MPIAIJ *b; 2637 PetscErrorCode ierr; 2638 2639 PetscFunctionBegin; 2640 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2641 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2642 b = (Mat_MPIAIJ*)B->data; 2643 2644 #if defined(PETSC_USE_CTABLE) 2645 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2646 #else 2647 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2648 #endif 2649 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2650 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2651 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2652 2653 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2654 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2655 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2656 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2657 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2658 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2659 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2660 2661 if (!B->preallocated) { 2662 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2663 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2664 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2665 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2666 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2667 } 2668 2669 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2670 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2671 B->preallocated = PETSC_TRUE; 2672 B->was_assembled = PETSC_FALSE; 2673 B->assembled = PETSC_FALSE;; 2674 PetscFunctionReturn(0); 2675 } 2676 2677 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2678 { 2679 Mat mat; 2680 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2681 PetscErrorCode ierr; 2682 2683 PetscFunctionBegin; 2684 *newmat = 0; 2685 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2686 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2687 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2688 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2689 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2690 a = (Mat_MPIAIJ*)mat->data; 2691 2692 mat->factortype = matin->factortype; 2693 mat->assembled = PETSC_TRUE; 2694 mat->insertmode = NOT_SET_VALUES; 2695 mat->preallocated = PETSC_TRUE; 2696 2697 a->size = oldmat->size; 2698 a->rank = oldmat->rank; 2699 a->donotstash = oldmat->donotstash; 2700 a->roworiented = oldmat->roworiented; 2701 a->rowindices = 0; 2702 a->rowvalues = 0; 2703 a->getrowactive = PETSC_FALSE; 2704 2705 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2706 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2707 2708 if (oldmat->colmap) { 2709 #if defined(PETSC_USE_CTABLE) 2710 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2711 #else 2712 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2713 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2714 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2715 #endif 2716 } else a->colmap = 0; 2717 if (oldmat->garray) { 2718 PetscInt len; 2719 len = oldmat->B->cmap->n; 2720 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2721 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2722 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2723 } else a->garray = 0; 2724 2725 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2727 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2731 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2732 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2733 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2734 *newmat = mat; 2735 PetscFunctionReturn(0); 2736 } 2737 2738 2739 2740 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2741 { 2742 PetscScalar *vals,*svals; 2743 MPI_Comm comm; 2744 PetscErrorCode ierr; 2745 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2746 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2747 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2748 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2749 PetscInt cend,cstart,n,*rowners; 2750 int fd; 2751 PetscInt bs = newMat->rmap->bs; 2752 2753 PetscFunctionBegin; 2754 /* force binary viewer to load .info file if it has not yet done so */ 2755 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2756 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2757 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2758 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2759 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2760 if (!rank) { 2761 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2762 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2763 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2764 } 2765 2766 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2767 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2768 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2769 if (bs < 0) bs = 1; 2770 2771 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2772 M = header[1]; N = header[2]; 2773 2774 /* If global sizes are set, check if they are consistent with that given in the file */ 2775 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); 2776 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); 2777 2778 /* determine ownership of all (block) rows */ 2779 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2780 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2781 else m = newMat->rmap->n; /* Set by user */ 2782 2783 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2784 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2785 2786 /* First process needs enough room for process with most rows */ 2787 if (!rank) { 2788 mmax = rowners[1]; 2789 for (i=2; i<=size; i++) { 2790 mmax = PetscMax(mmax, rowners[i]); 2791 } 2792 } else mmax = -1; /* unused, but compilers complain */ 2793 2794 rowners[0] = 0; 2795 for (i=2; i<=size; i++) { 2796 rowners[i] += rowners[i-1]; 2797 } 2798 rstart = rowners[rank]; 2799 rend = rowners[rank+1]; 2800 2801 /* distribute row lengths to all processors */ 2802 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2803 if (!rank) { 2804 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2805 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2806 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2807 for (j=0; j<m; j++) { 2808 procsnz[0] += ourlens[j]; 2809 } 2810 for (i=1; i<size; i++) { 2811 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2812 /* calculate the number of nonzeros on each processor */ 2813 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2814 procsnz[i] += rowlengths[j]; 2815 } 2816 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2817 } 2818 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2819 } else { 2820 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2821 } 2822 2823 if (!rank) { 2824 /* determine max buffer needed and allocate it */ 2825 maxnz = 0; 2826 for (i=0; i<size; i++) { 2827 maxnz = PetscMax(maxnz,procsnz[i]); 2828 } 2829 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2830 2831 /* read in my part of the matrix column indices */ 2832 nz = procsnz[0]; 2833 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2834 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2835 2836 /* read in every one elses and ship off */ 2837 for (i=1; i<size; i++) { 2838 nz = procsnz[i]; 2839 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2840 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2841 } 2842 ierr = PetscFree(cols);CHKERRQ(ierr); 2843 } else { 2844 /* determine buffer space needed for message */ 2845 nz = 0; 2846 for (i=0; i<m; i++) { 2847 nz += ourlens[i]; 2848 } 2849 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2850 2851 /* receive message of column indices*/ 2852 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2853 } 2854 2855 /* determine column ownership if matrix is not square */ 2856 if (N != M) { 2857 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2858 else n = newMat->cmap->n; 2859 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2860 cstart = cend - n; 2861 } else { 2862 cstart = rstart; 2863 cend = rend; 2864 n = cend - cstart; 2865 } 2866 2867 /* loop over local rows, determining number of off diagonal entries */ 2868 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2869 jj = 0; 2870 for (i=0; i<m; i++) { 2871 for (j=0; j<ourlens[i]; j++) { 2872 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2873 jj++; 2874 } 2875 } 2876 2877 for (i=0; i<m; i++) { 2878 ourlens[i] -= offlens[i]; 2879 } 2880 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2881 2882 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2883 2884 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2885 2886 for (i=0; i<m; i++) { 2887 ourlens[i] += offlens[i]; 2888 } 2889 2890 if (!rank) { 2891 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2892 2893 /* read in my part of the matrix numerical values */ 2894 nz = procsnz[0]; 2895 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2896 2897 /* insert into matrix */ 2898 jj = rstart; 2899 smycols = mycols; 2900 svals = vals; 2901 for (i=0; i<m; i++) { 2902 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2903 smycols += ourlens[i]; 2904 svals += ourlens[i]; 2905 jj++; 2906 } 2907 2908 /* read in other processors and ship out */ 2909 for (i=1; i<size; i++) { 2910 nz = procsnz[i]; 2911 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2912 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2913 } 2914 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2915 } else { 2916 /* receive numeric values */ 2917 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2918 2919 /* receive message of values*/ 2920 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2921 2922 /* insert into matrix */ 2923 jj = rstart; 2924 smycols = mycols; 2925 svals = vals; 2926 for (i=0; i<m; i++) { 2927 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2928 smycols += ourlens[i]; 2929 svals += ourlens[i]; 2930 jj++; 2931 } 2932 } 2933 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2934 ierr = PetscFree(vals);CHKERRQ(ierr); 2935 ierr = PetscFree(mycols);CHKERRQ(ierr); 2936 ierr = PetscFree(rowners);CHKERRQ(ierr); 2937 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2938 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2939 PetscFunctionReturn(0); 2940 } 2941 2942 /* Not scalable because of ISAllGather() unless getting all columns. */ 2943 PetscErrorCode ISGetISseq_Private(Mat mat,IS iscol,IS *isseq) 2944 { 2945 PetscErrorCode ierr; 2946 IS iscol_local; 2947 PetscBool isstride; 2948 PetscMPIInt lisstride=0,gisstride; 2949 2950 PetscFunctionBegin; 2951 /* check if we are grabbing all columns*/ 2952 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2953 2954 if (isstride) { 2955 PetscInt start,len,mstart,mlen; 2956 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2957 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2958 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2959 if (mstart == start && mlen-mstart == len) lisstride = 1; 2960 } 2961 2962 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2963 if (gisstride) { 2964 PetscInt N; 2965 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2966 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2967 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2968 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2969 } else { 2970 PetscInt cbs; 2971 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2972 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2973 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2974 } 2975 2976 *isseq = iscol_local; 2977 PetscFunctionReturn(0); 2978 } 2979 2980 extern PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private_SameDist(Mat,IS,IS,PetscInt,MatReuse,Mat*); 2981 2982 /* isrow has same processor distribution as mat, avoid iscol_local which uses O(mat->cmap->N) ctable */ 2983 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2984 { 2985 PetscErrorCode ierr; 2986 IS iscol_local; 2987 PetscInt csize; 2988 PetscInt n,i,j,rstart,rend; 2989 PetscBool sameDist=PETSC_FALSE,tsameDist; 2990 //MPI_Comm comm; 2991 //PetscMPIInt rank; 2992 2993 PetscFunctionBegin; 2994 //ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2995 //ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2996 //if (!rank) printf("MatCreateSubMatrix_MPIAIJ_SameDist ...reuse %d \n",call); 2997 2998 /* Get nonscalable iscol_local -- will replace it with iscol_sub! */ 2999 if (call == MAT_REUSE_MATRIX) { 3000 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3001 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3002 } else { 3003 ierr = ISGetISseq_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3004 } 3005 3006 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3007 ierr = MatCreateSubMatrix_MPIAIJ_Private_SameDist(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3008 3009 if (call == MAT_INITIAL_MATRIX) { 3010 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3011 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3012 } 3013 PetscFunctionReturn(0); 3014 } 3015 3016 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3017 { 3018 PetscErrorCode ierr; 3019 IS iscol_local; 3020 PetscInt csize; 3021 PetscInt n,i,j,rstart,rend; 3022 PetscBool sameDist=PETSC_FALSE,tsameDist; 3023 MPI_Comm comm; 3024 3025 PetscFunctionBegin; 3026 /* If isrow has same processor distribution as mat, then use a scalable routine */ 3027 if (call == MAT_REUSE_MATRIX) { 3028 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3029 if (iscol_local) tsameDist = PETSC_TRUE; 3030 } else { 3031 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3032 if (!n) { 3033 sameDist = PETSC_TRUE; 3034 } else { 3035 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3036 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3037 if (i >= rstart && j < rend) sameDist = PETSC_TRUE; 3038 } 3039 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3040 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3041 } 3042 3043 if (tsameDist) { 3044 ierr = MatCreateSubMatrix_MPIAIJ_SameDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3045 PetscFunctionReturn(0); 3046 } 3047 3048 /* General case */ 3049 /* --------------------------------------- */ 3050 if (call == MAT_REUSE_MATRIX) { 3051 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3052 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3053 } else { 3054 ierr = ISGetISseq_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3055 } 3056 3057 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3058 ierr = MatCreateSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3059 3060 if (call == MAT_INITIAL_MATRIX) { 3061 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3062 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3063 } 3064 PetscFunctionReturn(0); 3065 } 3066 3067 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,Mat*); 3068 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3069 3070 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private_SameDist(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3071 { 3072 PetscErrorCode ierr; 3073 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3074 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3075 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3076 Mat M,Msub,B=a->B; 3077 MatScalar *aa; 3078 Mat_SeqAIJ *aij; 3079 PetscInt *garray = a->garray,*colsub; 3080 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3081 IS iscol_sub,iscmap; 3082 const PetscInt *is_idx,*cmap; 3083 3084 PetscFunctionBegin; 3085 //printf("SubMatrix_MPIAIJ_Private_SameDist ...\n"); 3086 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); /* iscol should be sequential */ 3087 3088 if (call == MAT_INITIAL_MATRIX) { 3089 /* create scalable iscol_sub (a subset of iscol) */ 3090 PetscInt *idx,*cmap1; 3091 3092 ierr = PetscMalloc2(n,&idx,n,&cmap1);CHKERRQ(ierr); 3093 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3094 count = 0; 3095 3096 /* A part */ 3097 j = cstart; 3098 for (i=0; i<n; i++) { 3099 if (j >= cend) break; 3100 if (is_idx[i] == j) { 3101 idx[count] = j; 3102 cmap1[count] = i; /* column index in submat */ 3103 count++; j++; 3104 } else if (is_idx[i] > j) { 3105 while (is_idx[i] > j && j < cend-1) j++; 3106 if (is_idx[i] == j) { 3107 idx[count] = j; 3108 cmap1[count] = i; /* column index in submat */ 3109 count++; j++; 3110 } 3111 } 3112 } 3113 3114 /* B part */ 3115 j = 0; 3116 for (i=0; i<n; i++) { 3117 if (j >= Bn) break; 3118 if (is_idx[i] == garray[j]) { 3119 idx[count] = garray[j]; 3120 cmap1[count] = i; /* column index in submat */ 3121 count++; j++; 3122 } else if (is_idx[i] > garray[j]) { 3123 while (is_idx[i] > garray[j] && j < Bn-1) j++; 3124 if (is_idx[i] == garray[j]) { 3125 idx[count] = garray[j]; 3126 cmap1[count] = i; /* column index in submat */ 3127 count++; j++; 3128 } 3129 } 3130 } 3131 ierr = PetscSortInt(count,cmap1);CHKERRQ(ierr); 3132 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3133 3134 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,idx,PETSC_COPY_VALUES,&iscol_sub);CHKERRQ(ierr); 3135 ierr = ISSort(iscol_sub);CHKERRQ(ierr); 3136 3137 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol),count,cmap1,PETSC_COPY_VALUES,&iscmap);CHKERRQ(ierr); 3138 ierr = PetscFree2(idx,cmap1);CHKERRQ(ierr); 3139 3140 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3141 3142 } else { /* call == MAT_REUSE_MATRIX */ 3143 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3144 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3145 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3146 3147 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3148 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3149 3150 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3151 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3152 3153 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3154 } 3155 3156 aij = (Mat_SeqAIJ*)(Msub)->data; 3157 ii = aij->i; 3158 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3159 3160 /* 3161 m - number of local rows 3162 n - number of columns (same on all processors) 3163 rstart - first row in new global matrix generated 3164 */ 3165 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3166 3167 if (call == MAT_INITIAL_MATRIX) { 3168 MPI_Comm comm; 3169 PetscMPIInt rank,size; 3170 3171 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3172 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3173 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3174 3175 /* 3176 Determine the number of non-zeros in the diagonal and off-diagonal 3177 portions of the matrix in order to do correct preallocation 3178 */ 3179 3180 /* first get start and end of "diagonal" columns */ 3181 if (csize == PETSC_DECIDE) { 3182 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3183 if (mglobal == n) { /* square matrix */ 3184 nlocal = m; 3185 } else { 3186 nlocal = n/size + ((n % size) > rank); 3187 } 3188 } else { 3189 nlocal = csize; 3190 } 3191 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3192 rstart = rend - nlocal; 3193 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); 3194 3195 /* next, compute all the lengths */ 3196 jj = aij->j; 3197 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3198 olens = dlens + m; 3199 for (i=0; i<m; i++) { 3200 jend = ii[i+1] - ii[i]; 3201 olen = 0; 3202 dlen = 0; 3203 for (j=0; j<jend; j++) { 3204 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3205 else dlen++; 3206 jj++; 3207 } 3208 olens[i] = olen; 3209 dlens[i] = dlen; 3210 } 3211 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3212 3213 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3214 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3215 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3216 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3217 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3218 ierr = PetscFree(dlens);CHKERRQ(ierr); 3219 } else { 3220 M = *newmat; 3221 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3222 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3223 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3224 /* 3225 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3226 rather than the slower MatSetValues(). 3227 */ 3228 M->was_assembled = PETSC_TRUE; 3229 M->assembled = PETSC_FALSE; 3230 } 3231 3232 /* set values of Msub to *newmat */ 3233 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3234 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3235 3236 jj = aij->j; 3237 aa = aij->a; 3238 for (i=0; i<m; i++) { 3239 row = rstart + i; 3240 nz = ii[i+1] - ii[i]; 3241 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3242 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3243 jj += nz; aa += nz; 3244 } 3245 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3246 3247 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3248 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3249 *newmat = M; 3250 3251 ierr = PetscFree(colsub);CHKERRQ(ierr); 3252 3253 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3254 if (call == MAT_INITIAL_MATRIX) { 3255 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3256 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3257 3258 ierr = PetscObjectCompose((PetscObject)M,"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3259 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3260 3261 ierr = PetscObjectCompose((PetscObject)M,"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3262 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3263 } 3264 PetscFunctionReturn(0); 3265 } 3266 3267 /* 3268 Not great since it makes two copies of the submatrix, first an SeqAIJ 3269 in local and then by concatenating the local matrices the end result. 3270 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3271 3272 Note: This requires a sequential iscol with all indices. 3273 */ 3274 PetscErrorCode MatCreateSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3275 { 3276 PetscErrorCode ierr; 3277 PetscMPIInt rank,size; 3278 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3279 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3280 Mat M,Mreuse; 3281 MatScalar *aa,*vwork; 3282 MPI_Comm comm; 3283 Mat_SeqAIJ *aij; 3284 //PetscBool sameDist=PETSC_FALSE,tsameDist; 3285 3286 PetscFunctionBegin; 3287 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3288 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3289 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3290 #if 0 3291 /* If isrow has same processor distribution as mat, then use a scalable routine */ 3292 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3293 if (!n) { 3294 sameDist=PETSC_TRUE; 3295 } else { 3296 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3297 ierr = MatGetOwnershipRange(mat,&rstart,&rend);CHKERRQ(ierr); 3298 if (i >= rstart && j < rend) sameDist=PETSC_TRUE; 3299 } 3300 ierr = MPIU_Allreduce(&sameDist,&tsameDist,1,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3301 if (tsameDist) { 3302 ierr = MatCreateSubMatrix_MPIAIJ_Private_SameDist(mat,isrow,iscol,csize,call,newmat);CHKERRQ(ierr); 3303 PetscFunctionReturn(0); 3304 } 3305 #endif 3306 3307 if (call == MAT_REUSE_MATRIX) { 3308 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3309 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3310 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&Mreuse);CHKERRQ(ierr); 3311 } else { 3312 ierr = MatCreateSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&Mreuse);CHKERRQ(ierr); 3313 } 3314 3315 /* 3316 m - number of local rows 3317 n - number of columns (same on all processors) 3318 rstart - first row in new global matrix generated 3319 */ 3320 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3321 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3322 if (call == MAT_INITIAL_MATRIX) { 3323 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3324 ii = aij->i; 3325 jj = aij->j; 3326 3327 /* 3328 Determine the number of non-zeros in the diagonal and off-diagonal 3329 portions of the matrix in order to do correct preallocation 3330 */ 3331 3332 /* first get start and end of "diagonal" columns */ 3333 if (csize == PETSC_DECIDE) { 3334 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3335 if (mglobal == n) { /* square matrix */ 3336 nlocal = m; 3337 } else { 3338 nlocal = n/size + ((n % size) > rank); 3339 } 3340 } else { 3341 nlocal = csize; 3342 } 3343 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3344 rstart = rend - nlocal; 3345 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); 3346 3347 /* next, compute all the lengths */ 3348 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3349 olens = dlens + m; 3350 for (i=0; i<m; i++) { 3351 jend = ii[i+1] - ii[i]; 3352 olen = 0; 3353 dlen = 0; 3354 for (j=0; j<jend; j++) { 3355 if (*jj < rstart || *jj >= rend) olen++; 3356 else dlen++; 3357 jj++; 3358 } 3359 olens[i] = olen; 3360 dlens[i] = dlen; 3361 } 3362 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3363 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3364 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3365 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3366 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3367 ierr = PetscFree(dlens);CHKERRQ(ierr); 3368 } else { 3369 PetscInt ml,nl; 3370 3371 M = *newmat; 3372 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3373 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3374 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3375 /* 3376 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3377 rather than the slower MatSetValues(). 3378 */ 3379 M->was_assembled = PETSC_TRUE; 3380 M->assembled = PETSC_FALSE; 3381 } 3382 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3383 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3384 ii = aij->i; 3385 jj = aij->j; 3386 aa = aij->a; 3387 for (i=0; i<m; i++) { 3388 row = rstart + i; 3389 nz = ii[i+1] - ii[i]; 3390 cwork = jj; jj += nz; 3391 vwork = aa; aa += nz; 3392 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3393 } 3394 3395 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3396 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3397 *newmat = M; 3398 3399 /* save submatrix used in processor for next request */ 3400 if (call == MAT_INITIAL_MATRIX) { 3401 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3402 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3403 } 3404 PetscFunctionReturn(0); 3405 } 3406 3407 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3408 { 3409 PetscInt m,cstart, cend,j,nnz,i,d; 3410 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3411 const PetscInt *JJ; 3412 PetscScalar *values; 3413 PetscErrorCode ierr; 3414 PetscBool nooffprocentries; 3415 3416 PetscFunctionBegin; 3417 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3418 3419 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3420 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3421 m = B->rmap->n; 3422 cstart = B->cmap->rstart; 3423 cend = B->cmap->rend; 3424 rstart = B->rmap->rstart; 3425 3426 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3427 3428 #if defined(PETSC_USE_DEBUGGING) 3429 for (i=0; i<m; i++) { 3430 nnz = Ii[i+1]- Ii[i]; 3431 JJ = J + Ii[i]; 3432 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3433 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3434 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); 3435 } 3436 #endif 3437 3438 for (i=0; i<m; i++) { 3439 nnz = Ii[i+1]- Ii[i]; 3440 JJ = J + Ii[i]; 3441 nnz_max = PetscMax(nnz_max,nnz); 3442 d = 0; 3443 for (j=0; j<nnz; j++) { 3444 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3445 } 3446 d_nnz[i] = d; 3447 o_nnz[i] = nnz - d; 3448 } 3449 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3450 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3451 3452 if (v) values = (PetscScalar*)v; 3453 else { 3454 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3455 } 3456 3457 for (i=0; i<m; i++) { 3458 ii = i + rstart; 3459 nnz = Ii[i+1]- Ii[i]; 3460 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3461 } 3462 nooffprocentries = B->nooffprocentries; 3463 B->nooffprocentries = PETSC_TRUE; 3464 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3465 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3466 B->nooffprocentries = nooffprocentries; 3467 3468 if (!v) { 3469 ierr = PetscFree(values);CHKERRQ(ierr); 3470 } 3471 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3472 PetscFunctionReturn(0); 3473 } 3474 3475 /*@ 3476 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3477 (the default parallel PETSc format). 3478 3479 Collective on MPI_Comm 3480 3481 Input Parameters: 3482 + B - the matrix 3483 . i - the indices into j for the start of each local row (starts with zero) 3484 . j - the column indices for each local row (starts with zero) 3485 - v - optional values in the matrix 3486 3487 Level: developer 3488 3489 Notes: 3490 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3491 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3492 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3493 3494 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3495 3496 The format which is used for the sparse matrix input, is equivalent to a 3497 row-major ordering.. i.e for the following matrix, the input data expected is 3498 as shown 3499 3500 $ 1 0 0 3501 $ 2 0 3 P0 3502 $ ------- 3503 $ 4 5 6 P1 3504 $ 3505 $ Process0 [P0]: rows_owned=[0,1] 3506 $ i = {0,1,3} [size = nrow+1 = 2+1] 3507 $ j = {0,0,2} [size = 3] 3508 $ v = {1,2,3} [size = 3] 3509 $ 3510 $ Process1 [P1]: rows_owned=[2] 3511 $ i = {0,3} [size = nrow+1 = 1+1] 3512 $ j = {0,1,2} [size = 3] 3513 $ v = {4,5,6} [size = 3] 3514 3515 .keywords: matrix, aij, compressed row, sparse, parallel 3516 3517 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3518 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3519 @*/ 3520 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3521 { 3522 PetscErrorCode ierr; 3523 3524 PetscFunctionBegin; 3525 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3526 PetscFunctionReturn(0); 3527 } 3528 3529 /*@C 3530 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3531 (the default parallel PETSc format). For good matrix assembly performance 3532 the user should preallocate the matrix storage by setting the parameters 3533 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3534 performance can be increased by more than a factor of 50. 3535 3536 Collective on MPI_Comm 3537 3538 Input Parameters: 3539 + B - the matrix 3540 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3541 (same value is used for all local rows) 3542 . d_nnz - array containing the number of nonzeros in the various rows of the 3543 DIAGONAL portion of the local submatrix (possibly different for each row) 3544 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3545 The size of this array is equal to the number of local rows, i.e 'm'. 3546 For matrices that will be factored, you must leave room for (and set) 3547 the diagonal entry even if it is zero. 3548 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3549 submatrix (same value is used for all local rows). 3550 - o_nnz - array containing the number of nonzeros in the various rows of the 3551 OFF-DIAGONAL portion of the local submatrix (possibly different for 3552 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3553 structure. The size of this array is equal to the number 3554 of local rows, i.e 'm'. 3555 3556 If the *_nnz parameter is given then the *_nz parameter is ignored 3557 3558 The AIJ format (also called the Yale sparse matrix format or 3559 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3560 storage. The stored row and column indices begin with zero. 3561 See Users-Manual: ch_mat for details. 3562 3563 The parallel matrix is partitioned such that the first m0 rows belong to 3564 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3565 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3566 3567 The DIAGONAL portion of the local submatrix of a processor can be defined 3568 as the submatrix which is obtained by extraction the part corresponding to 3569 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3570 first row that belongs to the processor, r2 is the last row belonging to 3571 the this processor, and c1-c2 is range of indices of the local part of a 3572 vector suitable for applying the matrix to. This is an mxn matrix. In the 3573 common case of a square matrix, the row and column ranges are the same and 3574 the DIAGONAL part is also square. The remaining portion of the local 3575 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3576 3577 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3578 3579 You can call MatGetInfo() to get information on how effective the preallocation was; 3580 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3581 You can also run with the option -info and look for messages with the string 3582 malloc in them to see if additional memory allocation was needed. 3583 3584 Example usage: 3585 3586 Consider the following 8x8 matrix with 34 non-zero values, that is 3587 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3588 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3589 as follows: 3590 3591 .vb 3592 1 2 0 | 0 3 0 | 0 4 3593 Proc0 0 5 6 | 7 0 0 | 8 0 3594 9 0 10 | 11 0 0 | 12 0 3595 ------------------------------------- 3596 13 0 14 | 15 16 17 | 0 0 3597 Proc1 0 18 0 | 19 20 21 | 0 0 3598 0 0 0 | 22 23 0 | 24 0 3599 ------------------------------------- 3600 Proc2 25 26 27 | 0 0 28 | 29 0 3601 30 0 0 | 31 32 33 | 0 34 3602 .ve 3603 3604 This can be represented as a collection of submatrices as: 3605 3606 .vb 3607 A B C 3608 D E F 3609 G H I 3610 .ve 3611 3612 Where the submatrices A,B,C are owned by proc0, D,E,F are 3613 owned by proc1, G,H,I are owned by proc2. 3614 3615 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3616 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3617 The 'M','N' parameters are 8,8, and have the same values on all procs. 3618 3619 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3620 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3621 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3622 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3623 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3624 matrix, ans [DF] as another SeqAIJ matrix. 3625 3626 When d_nz, o_nz parameters are specified, d_nz storage elements are 3627 allocated for every row of the local diagonal submatrix, and o_nz 3628 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3629 One way to choose d_nz and o_nz is to use the max nonzerors per local 3630 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3631 In this case, the values of d_nz,o_nz are: 3632 .vb 3633 proc0 : dnz = 2, o_nz = 2 3634 proc1 : dnz = 3, o_nz = 2 3635 proc2 : dnz = 1, o_nz = 4 3636 .ve 3637 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3638 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3639 for proc3. i.e we are using 12+15+10=37 storage locations to store 3640 34 values. 3641 3642 When d_nnz, o_nnz parameters are specified, the storage is specified 3643 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3644 In the above case the values for d_nnz,o_nnz are: 3645 .vb 3646 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3647 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3648 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3649 .ve 3650 Here the space allocated is sum of all the above values i.e 34, and 3651 hence pre-allocation is perfect. 3652 3653 Level: intermediate 3654 3655 .keywords: matrix, aij, compressed row, sparse, parallel 3656 3657 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3658 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3659 @*/ 3660 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3661 { 3662 PetscErrorCode ierr; 3663 3664 PetscFunctionBegin; 3665 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3666 PetscValidType(B,1); 3667 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3668 PetscFunctionReturn(0); 3669 } 3670 3671 /*@ 3672 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3673 CSR format the local rows. 3674 3675 Collective on MPI_Comm 3676 3677 Input Parameters: 3678 + comm - MPI communicator 3679 . m - number of local rows (Cannot be PETSC_DECIDE) 3680 . n - This value should be the same as the local size used in creating the 3681 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3682 calculated if N is given) For square matrices n is almost always m. 3683 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3684 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3685 . i - row indices 3686 . j - column indices 3687 - a - matrix values 3688 3689 Output Parameter: 3690 . mat - the matrix 3691 3692 Level: intermediate 3693 3694 Notes: 3695 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3696 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3697 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3698 3699 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3700 3701 The format which is used for the sparse matrix input, is equivalent to a 3702 row-major ordering.. i.e for the following matrix, the input data expected is 3703 as shown 3704 3705 $ 1 0 0 3706 $ 2 0 3 P0 3707 $ ------- 3708 $ 4 5 6 P1 3709 $ 3710 $ Process0 [P0]: rows_owned=[0,1] 3711 $ i = {0,1,3} [size = nrow+1 = 2+1] 3712 $ j = {0,0,2} [size = 3] 3713 $ v = {1,2,3} [size = 3] 3714 $ 3715 $ Process1 [P1]: rows_owned=[2] 3716 $ i = {0,3} [size = nrow+1 = 1+1] 3717 $ j = {0,1,2} [size = 3] 3718 $ v = {4,5,6} [size = 3] 3719 3720 .keywords: matrix, aij, compressed row, sparse, parallel 3721 3722 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3723 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3724 @*/ 3725 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3726 { 3727 PetscErrorCode ierr; 3728 3729 PetscFunctionBegin; 3730 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3731 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3732 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3733 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3734 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3735 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3736 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3737 PetscFunctionReturn(0); 3738 } 3739 3740 /*@C 3741 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3742 (the default parallel PETSc format). For good matrix assembly performance 3743 the user should preallocate the matrix storage by setting the parameters 3744 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3745 performance can be increased by more than a factor of 50. 3746 3747 Collective on MPI_Comm 3748 3749 Input Parameters: 3750 + comm - MPI communicator 3751 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3752 This value should be the same as the local size used in creating the 3753 y vector for the matrix-vector product y = Ax. 3754 . n - This value should be the same as the local size used in creating the 3755 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3756 calculated if N is given) For square matrices n is almost always m. 3757 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3758 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3759 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3760 (same value is used for all local rows) 3761 . d_nnz - array containing the number of nonzeros in the various rows of the 3762 DIAGONAL portion of the local submatrix (possibly different for each row) 3763 or NULL, if d_nz is used to specify the nonzero structure. 3764 The size of this array is equal to the number of local rows, i.e 'm'. 3765 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3766 submatrix (same value is used for all local rows). 3767 - o_nnz - array containing the number of nonzeros in the various rows of the 3768 OFF-DIAGONAL portion of the local submatrix (possibly different for 3769 each row) or NULL, if o_nz is used to specify the nonzero 3770 structure. The size of this array is equal to the number 3771 of local rows, i.e 'm'. 3772 3773 Output Parameter: 3774 . A - the matrix 3775 3776 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3777 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3778 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3779 3780 Notes: 3781 If the *_nnz parameter is given then the *_nz parameter is ignored 3782 3783 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3784 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3785 storage requirements for this matrix. 3786 3787 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3788 processor than it must be used on all processors that share the object for 3789 that argument. 3790 3791 The user MUST specify either the local or global matrix dimensions 3792 (possibly both). 3793 3794 The parallel matrix is partitioned across processors such that the 3795 first m0 rows belong to process 0, the next m1 rows belong to 3796 process 1, the next m2 rows belong to process 2 etc.. where 3797 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3798 values corresponding to [m x N] submatrix. 3799 3800 The columns are logically partitioned with the n0 columns belonging 3801 to 0th partition, the next n1 columns belonging to the next 3802 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3803 3804 The DIAGONAL portion of the local submatrix on any given processor 3805 is the submatrix corresponding to the rows and columns m,n 3806 corresponding to the given processor. i.e diagonal matrix on 3807 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3808 etc. The remaining portion of the local submatrix [m x (N-n)] 3809 constitute the OFF-DIAGONAL portion. The example below better 3810 illustrates this concept. 3811 3812 For a square global matrix we define each processor's diagonal portion 3813 to be its local rows and the corresponding columns (a square submatrix); 3814 each processor's off-diagonal portion encompasses the remainder of the 3815 local matrix (a rectangular submatrix). 3816 3817 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3818 3819 When calling this routine with a single process communicator, a matrix of 3820 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 3821 type of communicator, use the construction mechanism: 3822 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3823 3824 By default, this format uses inodes (identical nodes) when possible. 3825 We search for consecutive rows with the same nonzero structure, thereby 3826 reusing matrix information to achieve increased efficiency. 3827 3828 Options Database Keys: 3829 + -mat_no_inode - Do not use inodes 3830 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3831 - -mat_aij_oneindex - Internally use indexing starting at 1 3832 rather than 0. Note that when calling MatSetValues(), 3833 the user still MUST index entries starting at 0! 3834 3835 3836 Example usage: 3837 3838 Consider the following 8x8 matrix with 34 non-zero values, that is 3839 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3840 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3841 as follows: 3842 3843 .vb 3844 1 2 0 | 0 3 0 | 0 4 3845 Proc0 0 5 6 | 7 0 0 | 8 0 3846 9 0 10 | 11 0 0 | 12 0 3847 ------------------------------------- 3848 13 0 14 | 15 16 17 | 0 0 3849 Proc1 0 18 0 | 19 20 21 | 0 0 3850 0 0 0 | 22 23 0 | 24 0 3851 ------------------------------------- 3852 Proc2 25 26 27 | 0 0 28 | 29 0 3853 30 0 0 | 31 32 33 | 0 34 3854 .ve 3855 3856 This can be represented as a collection of submatrices as: 3857 3858 .vb 3859 A B C 3860 D E F 3861 G H I 3862 .ve 3863 3864 Where the submatrices A,B,C are owned by proc0, D,E,F are 3865 owned by proc1, G,H,I are owned by proc2. 3866 3867 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3868 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3869 The 'M','N' parameters are 8,8, and have the same values on all procs. 3870 3871 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3872 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3873 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3874 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3875 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3876 matrix, ans [DF] as another SeqAIJ matrix. 3877 3878 When d_nz, o_nz parameters are specified, d_nz storage elements are 3879 allocated for every row of the local diagonal submatrix, and o_nz 3880 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3881 One way to choose d_nz and o_nz is to use the max nonzerors per local 3882 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3883 In this case, the values of d_nz,o_nz are: 3884 .vb 3885 proc0 : dnz = 2, o_nz = 2 3886 proc1 : dnz = 3, o_nz = 2 3887 proc2 : dnz = 1, o_nz = 4 3888 .ve 3889 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3890 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3891 for proc3. i.e we are using 12+15+10=37 storage locations to store 3892 34 values. 3893 3894 When d_nnz, o_nnz parameters are specified, the storage is specified 3895 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3896 In the above case the values for d_nnz,o_nnz are: 3897 .vb 3898 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3899 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3900 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3901 .ve 3902 Here the space allocated is sum of all the above values i.e 34, and 3903 hence pre-allocation is perfect. 3904 3905 Level: intermediate 3906 3907 .keywords: matrix, aij, compressed row, sparse, parallel 3908 3909 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3910 MATMPIAIJ, MatCreateMPIAIJWithArrays() 3911 @*/ 3912 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) 3913 { 3914 PetscErrorCode ierr; 3915 PetscMPIInt size; 3916 3917 PetscFunctionBegin; 3918 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3919 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3920 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3921 if (size > 1) { 3922 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3923 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3924 } else { 3925 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3926 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3927 } 3928 PetscFunctionReturn(0); 3929 } 3930 3931 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3932 { 3933 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3934 PetscBool flg; 3935 PetscErrorCode ierr; 3936 3937 PetscFunctionBegin; 3938 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 3939 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 3940 if (Ad) *Ad = a->A; 3941 if (Ao) *Ao = a->B; 3942 if (colmap) *colmap = a->garray; 3943 PetscFunctionReturn(0); 3944 } 3945 3946 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3947 { 3948 PetscErrorCode ierr; 3949 PetscInt m,N,i,rstart,nnz,Ii; 3950 PetscInt *indx; 3951 PetscScalar *values; 3952 3953 PetscFunctionBegin; 3954 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3955 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3956 PetscInt *dnz,*onz,sum,bs,cbs; 3957 3958 if (n == PETSC_DECIDE) { 3959 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3960 } 3961 /* Check sum(n) = N */ 3962 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3963 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3964 3965 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3966 rstart -= m; 3967 3968 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3969 for (i=0; i<m; i++) { 3970 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3971 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3972 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3973 } 3974 3975 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3976 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3977 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3978 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3979 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 3980 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 3981 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3982 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3983 } 3984 3985 /* numeric phase */ 3986 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3987 for (i=0; i<m; i++) { 3988 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3989 Ii = i + rstart; 3990 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3991 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3992 } 3993 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3994 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3995 PetscFunctionReturn(0); 3996 } 3997 3998 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3999 { 4000 PetscErrorCode ierr; 4001 PetscMPIInt rank; 4002 PetscInt m,N,i,rstart,nnz; 4003 size_t len; 4004 const PetscInt *indx; 4005 PetscViewer out; 4006 char *name; 4007 Mat B; 4008 const PetscScalar *values; 4009 4010 PetscFunctionBegin; 4011 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4012 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4013 /* Should this be the type of the diagonal block of A? */ 4014 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4015 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4016 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4017 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4018 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4019 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4020 for (i=0; i<m; i++) { 4021 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4022 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4023 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4024 } 4025 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4026 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4027 4028 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4029 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4030 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4031 sprintf(name,"%s.%d",outfile,rank); 4032 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4033 ierr = PetscFree(name);CHKERRQ(ierr); 4034 ierr = MatView(B,out);CHKERRQ(ierr); 4035 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4036 ierr = MatDestroy(&B);CHKERRQ(ierr); 4037 PetscFunctionReturn(0); 4038 } 4039 4040 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4041 { 4042 PetscErrorCode ierr; 4043 Mat_Merge_SeqsToMPI *merge; 4044 PetscContainer container; 4045 4046 PetscFunctionBegin; 4047 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4048 if (container) { 4049 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4050 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4051 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4052 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4053 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4054 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4055 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4056 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4057 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4058 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4059 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4060 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4061 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4062 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4063 ierr = PetscFree(merge);CHKERRQ(ierr); 4064 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4065 } 4066 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4067 PetscFunctionReturn(0); 4068 } 4069 4070 #include <../src/mat/utils/freespace.h> 4071 #include <petscbt.h> 4072 4073 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4074 { 4075 PetscErrorCode ierr; 4076 MPI_Comm comm; 4077 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4078 PetscMPIInt size,rank,taga,*len_s; 4079 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4080 PetscInt proc,m; 4081 PetscInt **buf_ri,**buf_rj; 4082 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4083 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4084 MPI_Request *s_waits,*r_waits; 4085 MPI_Status *status; 4086 MatScalar *aa=a->a; 4087 MatScalar **abuf_r,*ba_i; 4088 Mat_Merge_SeqsToMPI *merge; 4089 PetscContainer container; 4090 4091 PetscFunctionBegin; 4092 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4093 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4094 4095 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4096 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4097 4098 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4099 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4100 4101 bi = merge->bi; 4102 bj = merge->bj; 4103 buf_ri = merge->buf_ri; 4104 buf_rj = merge->buf_rj; 4105 4106 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4107 owners = merge->rowmap->range; 4108 len_s = merge->len_s; 4109 4110 /* send and recv matrix values */ 4111 /*-----------------------------*/ 4112 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4113 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4114 4115 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4116 for (proc=0,k=0; proc<size; proc++) { 4117 if (!len_s[proc]) continue; 4118 i = owners[proc]; 4119 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4120 k++; 4121 } 4122 4123 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4124 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4125 ierr = PetscFree(status);CHKERRQ(ierr); 4126 4127 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4128 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4129 4130 /* insert mat values of mpimat */ 4131 /*----------------------------*/ 4132 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4133 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4134 4135 for (k=0; k<merge->nrecv; k++) { 4136 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4137 nrows = *(buf_ri_k[k]); 4138 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4139 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4140 } 4141 4142 /* set values of ba */ 4143 m = merge->rowmap->n; 4144 for (i=0; i<m; i++) { 4145 arow = owners[rank] + i; 4146 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4147 bnzi = bi[i+1] - bi[i]; 4148 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4149 4150 /* add local non-zero vals of this proc's seqmat into ba */ 4151 anzi = ai[arow+1] - ai[arow]; 4152 aj = a->j + ai[arow]; 4153 aa = a->a + ai[arow]; 4154 nextaj = 0; 4155 for (j=0; nextaj<anzi; j++) { 4156 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4157 ba_i[j] += aa[nextaj++]; 4158 } 4159 } 4160 4161 /* add received vals into ba */ 4162 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4163 /* i-th row */ 4164 if (i == *nextrow[k]) { 4165 anzi = *(nextai[k]+1) - *nextai[k]; 4166 aj = buf_rj[k] + *(nextai[k]); 4167 aa = abuf_r[k] + *(nextai[k]); 4168 nextaj = 0; 4169 for (j=0; nextaj<anzi; j++) { 4170 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4171 ba_i[j] += aa[nextaj++]; 4172 } 4173 } 4174 nextrow[k]++; nextai[k]++; 4175 } 4176 } 4177 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4178 } 4179 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4180 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4181 4182 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4183 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4184 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4185 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4186 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4187 PetscFunctionReturn(0); 4188 } 4189 4190 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4191 { 4192 PetscErrorCode ierr; 4193 Mat B_mpi; 4194 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4195 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4196 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4197 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4198 PetscInt len,proc,*dnz,*onz,bs,cbs; 4199 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4200 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4201 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4202 MPI_Status *status; 4203 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4204 PetscBT lnkbt; 4205 Mat_Merge_SeqsToMPI *merge; 4206 PetscContainer container; 4207 4208 PetscFunctionBegin; 4209 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4210 4211 /* make sure it is a PETSc comm */ 4212 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4213 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4214 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4215 4216 ierr = PetscNew(&merge);CHKERRQ(ierr); 4217 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4218 4219 /* determine row ownership */ 4220 /*---------------------------------------------------------*/ 4221 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4222 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4223 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4224 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4225 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4226 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4227 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4228 4229 m = merge->rowmap->n; 4230 owners = merge->rowmap->range; 4231 4232 /* determine the number of messages to send, their lengths */ 4233 /*---------------------------------------------------------*/ 4234 len_s = merge->len_s; 4235 4236 len = 0; /* length of buf_si[] */ 4237 merge->nsend = 0; 4238 for (proc=0; proc<size; proc++) { 4239 len_si[proc] = 0; 4240 if (proc == rank) { 4241 len_s[proc] = 0; 4242 } else { 4243 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4244 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4245 } 4246 if (len_s[proc]) { 4247 merge->nsend++; 4248 nrows = 0; 4249 for (i=owners[proc]; i<owners[proc+1]; i++) { 4250 if (ai[i+1] > ai[i]) nrows++; 4251 } 4252 len_si[proc] = 2*(nrows+1); 4253 len += len_si[proc]; 4254 } 4255 } 4256 4257 /* determine the number and length of messages to receive for ij-structure */ 4258 /*-------------------------------------------------------------------------*/ 4259 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4260 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4261 4262 /* post the Irecv of j-structure */ 4263 /*-------------------------------*/ 4264 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4265 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4266 4267 /* post the Isend of j-structure */ 4268 /*--------------------------------*/ 4269 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4270 4271 for (proc=0, k=0; proc<size; proc++) { 4272 if (!len_s[proc]) continue; 4273 i = owners[proc]; 4274 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4275 k++; 4276 } 4277 4278 /* receives and sends of j-structure are complete */ 4279 /*------------------------------------------------*/ 4280 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4281 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4282 4283 /* send and recv i-structure */ 4284 /*---------------------------*/ 4285 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4286 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4287 4288 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4289 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4290 for (proc=0,k=0; proc<size; proc++) { 4291 if (!len_s[proc]) continue; 4292 /* form outgoing message for i-structure: 4293 buf_si[0]: nrows to be sent 4294 [1:nrows]: row index (global) 4295 [nrows+1:2*nrows+1]: i-structure index 4296 */ 4297 /*-------------------------------------------*/ 4298 nrows = len_si[proc]/2 - 1; 4299 buf_si_i = buf_si + nrows+1; 4300 buf_si[0] = nrows; 4301 buf_si_i[0] = 0; 4302 nrows = 0; 4303 for (i=owners[proc]; i<owners[proc+1]; i++) { 4304 anzi = ai[i+1] - ai[i]; 4305 if (anzi) { 4306 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4307 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4308 nrows++; 4309 } 4310 } 4311 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4312 k++; 4313 buf_si += len_si[proc]; 4314 } 4315 4316 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4317 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4318 4319 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4320 for (i=0; i<merge->nrecv; i++) { 4321 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); 4322 } 4323 4324 ierr = PetscFree(len_si);CHKERRQ(ierr); 4325 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4326 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4327 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4328 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4329 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4330 ierr = PetscFree(status);CHKERRQ(ierr); 4331 4332 /* compute a local seq matrix in each processor */ 4333 /*----------------------------------------------*/ 4334 /* allocate bi array and free space for accumulating nonzero column info */ 4335 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4336 bi[0] = 0; 4337 4338 /* create and initialize a linked list */ 4339 nlnk = N+1; 4340 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4341 4342 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4343 len = ai[owners[rank+1]] - ai[owners[rank]]; 4344 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4345 4346 current_space = free_space; 4347 4348 /* determine symbolic info for each local row */ 4349 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4350 4351 for (k=0; k<merge->nrecv; k++) { 4352 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4353 nrows = *buf_ri_k[k]; 4354 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4355 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4356 } 4357 4358 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4359 len = 0; 4360 for (i=0; i<m; i++) { 4361 bnzi = 0; 4362 /* add local non-zero cols of this proc's seqmat into lnk */ 4363 arow = owners[rank] + i; 4364 anzi = ai[arow+1] - ai[arow]; 4365 aj = a->j + ai[arow]; 4366 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4367 bnzi += nlnk; 4368 /* add received col data into lnk */ 4369 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4370 if (i == *nextrow[k]) { /* i-th row */ 4371 anzi = *(nextai[k]+1) - *nextai[k]; 4372 aj = buf_rj[k] + *nextai[k]; 4373 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4374 bnzi += nlnk; 4375 nextrow[k]++; nextai[k]++; 4376 } 4377 } 4378 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4379 4380 /* if free space is not available, make more free space */ 4381 if (current_space->local_remaining<bnzi) { 4382 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4383 nspacedouble++; 4384 } 4385 /* copy data into free space, then initialize lnk */ 4386 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4387 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4388 4389 current_space->array += bnzi; 4390 current_space->local_used += bnzi; 4391 current_space->local_remaining -= bnzi; 4392 4393 bi[i+1] = bi[i] + bnzi; 4394 } 4395 4396 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4397 4398 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4399 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4400 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4401 4402 /* create symbolic parallel matrix B_mpi */ 4403 /*---------------------------------------*/ 4404 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4405 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4406 if (n==PETSC_DECIDE) { 4407 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4408 } else { 4409 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4410 } 4411 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4412 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4413 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4414 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4415 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4416 4417 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4418 B_mpi->assembled = PETSC_FALSE; 4419 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4420 merge->bi = bi; 4421 merge->bj = bj; 4422 merge->buf_ri = buf_ri; 4423 merge->buf_rj = buf_rj; 4424 merge->coi = NULL; 4425 merge->coj = NULL; 4426 merge->owners_co = NULL; 4427 4428 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4429 4430 /* attach the supporting struct to B_mpi for reuse */ 4431 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4432 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4433 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4434 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4435 *mpimat = B_mpi; 4436 4437 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4438 PetscFunctionReturn(0); 4439 } 4440 4441 /*@C 4442 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4443 matrices from each processor 4444 4445 Collective on MPI_Comm 4446 4447 Input Parameters: 4448 + comm - the communicators the parallel matrix will live on 4449 . seqmat - the input sequential matrices 4450 . m - number of local rows (or PETSC_DECIDE) 4451 . n - number of local columns (or PETSC_DECIDE) 4452 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4453 4454 Output Parameter: 4455 . mpimat - the parallel matrix generated 4456 4457 Level: advanced 4458 4459 Notes: 4460 The dimensions of the sequential matrix in each processor MUST be the same. 4461 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4462 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4463 @*/ 4464 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4465 { 4466 PetscErrorCode ierr; 4467 PetscMPIInt size; 4468 4469 PetscFunctionBegin; 4470 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4471 if (size == 1) { 4472 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4473 if (scall == MAT_INITIAL_MATRIX) { 4474 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4475 } else { 4476 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4477 } 4478 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4479 PetscFunctionReturn(0); 4480 } 4481 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4482 if (scall == MAT_INITIAL_MATRIX) { 4483 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4484 } 4485 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4486 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4487 PetscFunctionReturn(0); 4488 } 4489 4490 /*@ 4491 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4492 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4493 with MatGetSize() 4494 4495 Not Collective 4496 4497 Input Parameters: 4498 + A - the matrix 4499 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4500 4501 Output Parameter: 4502 . A_loc - the local sequential matrix generated 4503 4504 Level: developer 4505 4506 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4507 4508 @*/ 4509 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4510 { 4511 PetscErrorCode ierr; 4512 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4513 Mat_SeqAIJ *mat,*a,*b; 4514 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4515 MatScalar *aa,*ba,*cam; 4516 PetscScalar *ca; 4517 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4518 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4519 PetscBool match; 4520 MPI_Comm comm; 4521 PetscMPIInt size; 4522 4523 PetscFunctionBegin; 4524 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4525 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4526 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4527 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4528 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4529 4530 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4531 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4532 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4533 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4534 aa = a->a; ba = b->a; 4535 if (scall == MAT_INITIAL_MATRIX) { 4536 if (size == 1) { 4537 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4538 PetscFunctionReturn(0); 4539 } 4540 4541 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4542 ci[0] = 0; 4543 for (i=0; i<am; i++) { 4544 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4545 } 4546 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4547 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4548 k = 0; 4549 for (i=0; i<am; i++) { 4550 ncols_o = bi[i+1] - bi[i]; 4551 ncols_d = ai[i+1] - ai[i]; 4552 /* off-diagonal portion of A */ 4553 for (jo=0; jo<ncols_o; jo++) { 4554 col = cmap[*bj]; 4555 if (col >= cstart) break; 4556 cj[k] = col; bj++; 4557 ca[k++] = *ba++; 4558 } 4559 /* diagonal portion of A */ 4560 for (j=0; j<ncols_d; j++) { 4561 cj[k] = cstart + *aj++; 4562 ca[k++] = *aa++; 4563 } 4564 /* off-diagonal portion of A */ 4565 for (j=jo; j<ncols_o; j++) { 4566 cj[k] = cmap[*bj++]; 4567 ca[k++] = *ba++; 4568 } 4569 } 4570 /* put together the new matrix */ 4571 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4572 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4573 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4574 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4575 mat->free_a = PETSC_TRUE; 4576 mat->free_ij = PETSC_TRUE; 4577 mat->nonew = 0; 4578 } else if (scall == MAT_REUSE_MATRIX) { 4579 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4580 ci = mat->i; cj = mat->j; cam = mat->a; 4581 for (i=0; i<am; i++) { 4582 /* off-diagonal portion of A */ 4583 ncols_o = bi[i+1] - bi[i]; 4584 for (jo=0; jo<ncols_o; jo++) { 4585 col = cmap[*bj]; 4586 if (col >= cstart) break; 4587 *cam++ = *ba++; bj++; 4588 } 4589 /* diagonal portion of A */ 4590 ncols_d = ai[i+1] - ai[i]; 4591 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4592 /* off-diagonal portion of A */ 4593 for (j=jo; j<ncols_o; j++) { 4594 *cam++ = *ba++; bj++; 4595 } 4596 } 4597 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4598 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4599 PetscFunctionReturn(0); 4600 } 4601 4602 /*@C 4603 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4604 4605 Not Collective 4606 4607 Input Parameters: 4608 + A - the matrix 4609 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4610 - row, col - index sets of rows and columns to extract (or NULL) 4611 4612 Output Parameter: 4613 . A_loc - the local sequential matrix generated 4614 4615 Level: developer 4616 4617 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4618 4619 @*/ 4620 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4621 { 4622 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4623 PetscErrorCode ierr; 4624 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4625 IS isrowa,iscola; 4626 Mat *aloc; 4627 PetscBool match; 4628 4629 PetscFunctionBegin; 4630 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4631 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4632 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4633 if (!row) { 4634 start = A->rmap->rstart; end = A->rmap->rend; 4635 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4636 } else { 4637 isrowa = *row; 4638 } 4639 if (!col) { 4640 start = A->cmap->rstart; 4641 cmap = a->garray; 4642 nzA = a->A->cmap->n; 4643 nzB = a->B->cmap->n; 4644 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4645 ncols = 0; 4646 for (i=0; i<nzB; i++) { 4647 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4648 else break; 4649 } 4650 imark = i; 4651 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4652 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4653 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4654 } else { 4655 iscola = *col; 4656 } 4657 if (scall != MAT_INITIAL_MATRIX) { 4658 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4659 aloc[0] = *A_loc; 4660 } 4661 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4662 *A_loc = aloc[0]; 4663 ierr = PetscFree(aloc);CHKERRQ(ierr); 4664 if (!row) { 4665 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4666 } 4667 if (!col) { 4668 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4669 } 4670 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4671 PetscFunctionReturn(0); 4672 } 4673 4674 /*@C 4675 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4676 4677 Collective on Mat 4678 4679 Input Parameters: 4680 + A,B - the matrices in mpiaij format 4681 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4682 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4683 4684 Output Parameter: 4685 + rowb, colb - index sets of rows and columns of B to extract 4686 - B_seq - the sequential matrix generated 4687 4688 Level: developer 4689 4690 @*/ 4691 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4692 { 4693 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4694 PetscErrorCode ierr; 4695 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4696 IS isrowb,iscolb; 4697 Mat *bseq=NULL; 4698 4699 PetscFunctionBegin; 4700 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4701 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); 4702 } 4703 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4704 4705 if (scall == MAT_INITIAL_MATRIX) { 4706 start = A->cmap->rstart; 4707 cmap = a->garray; 4708 nzA = a->A->cmap->n; 4709 nzB = a->B->cmap->n; 4710 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4711 ncols = 0; 4712 for (i=0; i<nzB; i++) { /* row < local row index */ 4713 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4714 else break; 4715 } 4716 imark = i; 4717 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4718 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4719 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4720 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4721 } else { 4722 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4723 isrowb = *rowb; iscolb = *colb; 4724 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 4725 bseq[0] = *B_seq; 4726 } 4727 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4728 *B_seq = bseq[0]; 4729 ierr = PetscFree(bseq);CHKERRQ(ierr); 4730 if (!rowb) { 4731 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4732 } else { 4733 *rowb = isrowb; 4734 } 4735 if (!colb) { 4736 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4737 } else { 4738 *colb = iscolb; 4739 } 4740 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4741 PetscFunctionReturn(0); 4742 } 4743 4744 /* 4745 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4746 of the OFF-DIAGONAL portion of local A 4747 4748 Collective on Mat 4749 4750 Input Parameters: 4751 + A,B - the matrices in mpiaij format 4752 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4753 4754 Output Parameter: 4755 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4756 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4757 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4758 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4759 4760 Level: developer 4761 4762 */ 4763 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4764 { 4765 VecScatter_MPI_General *gen_to,*gen_from; 4766 PetscErrorCode ierr; 4767 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4768 Mat_SeqAIJ *b_oth; 4769 VecScatter ctx =a->Mvctx; 4770 MPI_Comm comm; 4771 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4772 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4773 PetscInt *rvalues,*svalues; 4774 MatScalar *b_otha,*bufa,*bufA; 4775 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4776 MPI_Request *rwaits = NULL,*swaits = NULL; 4777 MPI_Status *sstatus,rstatus; 4778 PetscMPIInt jj,size; 4779 PetscInt *cols,sbs,rbs; 4780 PetscScalar *vals; 4781 4782 PetscFunctionBegin; 4783 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4784 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4785 4786 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4787 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); 4788 } 4789 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4790 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4791 4792 if (size == 1) { 4793 startsj_s = NULL; 4794 bufa_ptr = NULL; 4795 *B_oth = NULL; 4796 PetscFunctionReturn(0); 4797 } 4798 4799 gen_to = (VecScatter_MPI_General*)ctx->todata; 4800 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4801 nrecvs = gen_from->n; 4802 nsends = gen_to->n; 4803 4804 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4805 srow = gen_to->indices; /* local row index to be sent */ 4806 sstarts = gen_to->starts; 4807 sprocs = gen_to->procs; 4808 sstatus = gen_to->sstatus; 4809 sbs = gen_to->bs; 4810 rstarts = gen_from->starts; 4811 rprocs = gen_from->procs; 4812 rbs = gen_from->bs; 4813 4814 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4815 if (scall == MAT_INITIAL_MATRIX) { 4816 /* i-array */ 4817 /*---------*/ 4818 /* post receives */ 4819 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 4820 for (i=0; i<nrecvs; i++) { 4821 rowlen = rvalues + rstarts[i]*rbs; 4822 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4823 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4824 } 4825 4826 /* pack the outgoing message */ 4827 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4828 4829 sstartsj[0] = 0; 4830 rstartsj[0] = 0; 4831 len = 0; /* total length of j or a array to be sent */ 4832 k = 0; 4833 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 4834 for (i=0; i<nsends; i++) { 4835 rowlen = svalues + sstarts[i]*sbs; 4836 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4837 for (j=0; j<nrows; j++) { 4838 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4839 for (l=0; l<sbs; l++) { 4840 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4841 4842 rowlen[j*sbs+l] = ncols; 4843 4844 len += ncols; 4845 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4846 } 4847 k++; 4848 } 4849 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4850 4851 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4852 } 4853 /* recvs and sends of i-array are completed */ 4854 i = nrecvs; 4855 while (i--) { 4856 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4857 } 4858 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4859 ierr = PetscFree(svalues);CHKERRQ(ierr); 4860 4861 /* allocate buffers for sending j and a arrays */ 4862 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 4863 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 4864 4865 /* create i-array of B_oth */ 4866 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 4867 4868 b_othi[0] = 0; 4869 len = 0; /* total length of j or a array to be received */ 4870 k = 0; 4871 for (i=0; i<nrecvs; i++) { 4872 rowlen = rvalues + rstarts[i]*rbs; 4873 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 4874 for (j=0; j<nrows; j++) { 4875 b_othi[k+1] = b_othi[k] + rowlen[j]; 4876 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 4877 k++; 4878 } 4879 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4880 } 4881 ierr = PetscFree(rvalues);CHKERRQ(ierr); 4882 4883 /* allocate space for j and a arrrays of B_oth */ 4884 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 4885 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 4886 4887 /* j-array */ 4888 /*---------*/ 4889 /* post receives of j-array */ 4890 for (i=0; i<nrecvs; i++) { 4891 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4892 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4893 } 4894 4895 /* pack the outgoing message j-array */ 4896 k = 0; 4897 for (i=0; i<nsends; i++) { 4898 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4899 bufJ = bufj+sstartsj[i]; 4900 for (j=0; j<nrows; j++) { 4901 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4902 for (ll=0; ll<sbs; ll++) { 4903 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4904 for (l=0; l<ncols; l++) { 4905 *bufJ++ = cols[l]; 4906 } 4907 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4908 } 4909 } 4910 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4911 } 4912 4913 /* recvs and sends of j-array are completed */ 4914 i = nrecvs; 4915 while (i--) { 4916 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4917 } 4918 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4919 } else if (scall == MAT_REUSE_MATRIX) { 4920 sstartsj = *startsj_s; 4921 rstartsj = *startsj_r; 4922 bufa = *bufa_ptr; 4923 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4924 b_otha = b_oth->a; 4925 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4926 4927 /* a-array */ 4928 /*---------*/ 4929 /* post receives of a-array */ 4930 for (i=0; i<nrecvs; i++) { 4931 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4932 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4933 } 4934 4935 /* pack the outgoing message a-array */ 4936 k = 0; 4937 for (i=0; i<nsends; i++) { 4938 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4939 bufA = bufa+sstartsj[i]; 4940 for (j=0; j<nrows; j++) { 4941 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4942 for (ll=0; ll<sbs; ll++) { 4943 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4944 for (l=0; l<ncols; l++) { 4945 *bufA++ = vals[l]; 4946 } 4947 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4948 } 4949 } 4950 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4951 } 4952 /* recvs and sends of a-array are completed */ 4953 i = nrecvs; 4954 while (i--) { 4955 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4956 } 4957 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4958 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4959 4960 if (scall == MAT_INITIAL_MATRIX) { 4961 /* put together the new matrix */ 4962 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4963 4964 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4965 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4966 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4967 b_oth->free_a = PETSC_TRUE; 4968 b_oth->free_ij = PETSC_TRUE; 4969 b_oth->nonew = 0; 4970 4971 ierr = PetscFree(bufj);CHKERRQ(ierr); 4972 if (!startsj_s || !bufa_ptr) { 4973 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4974 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4975 } else { 4976 *startsj_s = sstartsj; 4977 *startsj_r = rstartsj; 4978 *bufa_ptr = bufa; 4979 } 4980 } 4981 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4982 PetscFunctionReturn(0); 4983 } 4984 4985 /*@C 4986 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4987 4988 Not Collective 4989 4990 Input Parameters: 4991 . A - The matrix in mpiaij format 4992 4993 Output Parameter: 4994 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4995 . colmap - A map from global column index to local index into lvec 4996 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4997 4998 Level: developer 4999 5000 @*/ 5001 #if defined(PETSC_USE_CTABLE) 5002 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5003 #else 5004 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5005 #endif 5006 { 5007 Mat_MPIAIJ *a; 5008 5009 PetscFunctionBegin; 5010 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5011 PetscValidPointer(lvec, 2); 5012 PetscValidPointer(colmap, 3); 5013 PetscValidPointer(multScatter, 4); 5014 a = (Mat_MPIAIJ*) A->data; 5015 if (lvec) *lvec = a->lvec; 5016 if (colmap) *colmap = a->colmap; 5017 if (multScatter) *multScatter = a->Mvctx; 5018 PetscFunctionReturn(0); 5019 } 5020 5021 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5022 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5023 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5024 #if defined(PETSC_HAVE_ELEMENTAL) 5025 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5026 #endif 5027 #if defined(PETSC_HAVE_HYPRE) 5028 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5029 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5030 #endif 5031 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5032 5033 /* 5034 Computes (B'*A')' since computing B*A directly is untenable 5035 5036 n p p 5037 ( ) ( ) ( ) 5038 m ( A ) * n ( B ) = m ( C ) 5039 ( ) ( ) ( ) 5040 5041 */ 5042 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5043 { 5044 PetscErrorCode ierr; 5045 Mat At,Bt,Ct; 5046 5047 PetscFunctionBegin; 5048 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5049 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5050 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5051 ierr = MatDestroy(&At);CHKERRQ(ierr); 5052 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5053 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5054 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5055 PetscFunctionReturn(0); 5056 } 5057 5058 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5059 { 5060 PetscErrorCode ierr; 5061 PetscInt m=A->rmap->n,n=B->cmap->n; 5062 Mat Cmat; 5063 5064 PetscFunctionBegin; 5065 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); 5066 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5067 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5068 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5069 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5070 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5071 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5072 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5073 5074 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5075 5076 *C = Cmat; 5077 PetscFunctionReturn(0); 5078 } 5079 5080 /* ----------------------------------------------------------------*/ 5081 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5082 { 5083 PetscErrorCode ierr; 5084 5085 PetscFunctionBegin; 5086 if (scall == MAT_INITIAL_MATRIX) { 5087 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5088 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5089 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5090 } 5091 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5092 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5093 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5094 PetscFunctionReturn(0); 5095 } 5096 5097 /*MC 5098 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5099 5100 Options Database Keys: 5101 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5102 5103 Level: beginner 5104 5105 .seealso: MatCreateAIJ() 5106 M*/ 5107 5108 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5109 { 5110 Mat_MPIAIJ *b; 5111 PetscErrorCode ierr; 5112 PetscMPIInt size; 5113 5114 PetscFunctionBegin; 5115 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5116 5117 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5118 B->data = (void*)b; 5119 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5120 B->assembled = PETSC_FALSE; 5121 B->insertmode = NOT_SET_VALUES; 5122 b->size = size; 5123 5124 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5125 5126 /* build cache for off array entries formed */ 5127 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5128 5129 b->donotstash = PETSC_FALSE; 5130 b->colmap = 0; 5131 b->garray = 0; 5132 b->roworiented = PETSC_TRUE; 5133 5134 /* stuff used for matrix vector multiply */ 5135 b->lvec = NULL; 5136 b->Mvctx = NULL; 5137 5138 /* stuff for MatGetRow() */ 5139 b->rowindices = 0; 5140 b->rowvalues = 0; 5141 b->getrowactive = PETSC_FALSE; 5142 5143 /* flexible pointer used in CUSP/CUSPARSE classes */ 5144 b->spptr = NULL; 5145 5146 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5147 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5148 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5149 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5150 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5151 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5152 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5153 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5154 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5155 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5156 #if defined(PETSC_HAVE_ELEMENTAL) 5157 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5158 #endif 5159 #if defined(PETSC_HAVE_HYPRE) 5160 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5161 #endif 5162 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5163 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5164 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5165 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5166 #if defined(PETSC_HAVE_HYPRE) 5167 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5168 #endif 5169 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5170 PetscFunctionReturn(0); 5171 } 5172 5173 /*@C 5174 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5175 and "off-diagonal" part of the matrix in CSR format. 5176 5177 Collective on MPI_Comm 5178 5179 Input Parameters: 5180 + comm - MPI communicator 5181 . m - number of local rows (Cannot be PETSC_DECIDE) 5182 . n - This value should be the same as the local size used in creating the 5183 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5184 calculated if N is given) For square matrices n is almost always m. 5185 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5186 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5187 . i - row indices for "diagonal" portion of matrix 5188 . j - column indices 5189 . a - matrix values 5190 . oi - row indices for "off-diagonal" portion of matrix 5191 . oj - column indices 5192 - oa - matrix values 5193 5194 Output Parameter: 5195 . mat - the matrix 5196 5197 Level: advanced 5198 5199 Notes: 5200 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5201 must free the arrays once the matrix has been destroyed and not before. 5202 5203 The i and j indices are 0 based 5204 5205 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5206 5207 This sets local rows and cannot be used to set off-processor values. 5208 5209 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5210 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5211 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5212 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5213 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5214 communication if it is known that only local entries will be set. 5215 5216 .keywords: matrix, aij, compressed row, sparse, parallel 5217 5218 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5219 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5220 @*/ 5221 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) 5222 { 5223 PetscErrorCode ierr; 5224 Mat_MPIAIJ *maij; 5225 5226 PetscFunctionBegin; 5227 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5228 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5229 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5230 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5231 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5232 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5233 maij = (Mat_MPIAIJ*) (*mat)->data; 5234 5235 (*mat)->preallocated = PETSC_TRUE; 5236 5237 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5238 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5239 5240 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5241 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5242 5243 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5244 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5245 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5246 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5247 5248 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5249 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5250 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5251 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5252 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5253 PetscFunctionReturn(0); 5254 } 5255 5256 /* 5257 Special version for direct calls from Fortran 5258 */ 5259 #include <petsc/private/fortranimpl.h> 5260 5261 /* Change these macros so can be used in void function */ 5262 #undef CHKERRQ 5263 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5264 #undef SETERRQ2 5265 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5266 #undef SETERRQ3 5267 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5268 #undef SETERRQ 5269 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5270 5271 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5272 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5273 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5274 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5275 #else 5276 #endif 5277 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) 5278 { 5279 Mat mat = *mmat; 5280 PetscInt m = *mm, n = *mn; 5281 InsertMode addv = *maddv; 5282 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5283 PetscScalar value; 5284 PetscErrorCode ierr; 5285 5286 MatCheckPreallocated(mat,1); 5287 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5288 5289 #if defined(PETSC_USE_DEBUG) 5290 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5291 #endif 5292 { 5293 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5294 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5295 PetscBool roworiented = aij->roworiented; 5296 5297 /* Some Variables required in the macro */ 5298 Mat A = aij->A; 5299 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5300 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5301 MatScalar *aa = a->a; 5302 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5303 Mat B = aij->B; 5304 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5305 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5306 MatScalar *ba = b->a; 5307 5308 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5309 PetscInt nonew = a->nonew; 5310 MatScalar *ap1,*ap2; 5311 5312 PetscFunctionBegin; 5313 for (i=0; i<m; i++) { 5314 if (im[i] < 0) continue; 5315 #if defined(PETSC_USE_DEBUG) 5316 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); 5317 #endif 5318 if (im[i] >= rstart && im[i] < rend) { 5319 row = im[i] - rstart; 5320 lastcol1 = -1; 5321 rp1 = aj + ai[row]; 5322 ap1 = aa + ai[row]; 5323 rmax1 = aimax[row]; 5324 nrow1 = ailen[row]; 5325 low1 = 0; 5326 high1 = nrow1; 5327 lastcol2 = -1; 5328 rp2 = bj + bi[row]; 5329 ap2 = ba + bi[row]; 5330 rmax2 = bimax[row]; 5331 nrow2 = bilen[row]; 5332 low2 = 0; 5333 high2 = nrow2; 5334 5335 for (j=0; j<n; j++) { 5336 if (roworiented) value = v[i*n+j]; 5337 else value = v[i+j*m]; 5338 if (in[j] >= cstart && in[j] < cend) { 5339 col = in[j] - cstart; 5340 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5341 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5342 } else if (in[j] < 0) continue; 5343 #if defined(PETSC_USE_DEBUG) 5344 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); 5345 #endif 5346 else { 5347 if (mat->was_assembled) { 5348 if (!aij->colmap) { 5349 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5350 } 5351 #if defined(PETSC_USE_CTABLE) 5352 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5353 col--; 5354 #else 5355 col = aij->colmap[in[j]] - 1; 5356 #endif 5357 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5358 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5359 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5360 col = in[j]; 5361 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5362 B = aij->B; 5363 b = (Mat_SeqAIJ*)B->data; 5364 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5365 rp2 = bj + bi[row]; 5366 ap2 = ba + bi[row]; 5367 rmax2 = bimax[row]; 5368 nrow2 = bilen[row]; 5369 low2 = 0; 5370 high2 = nrow2; 5371 bm = aij->B->rmap->n; 5372 ba = b->a; 5373 } 5374 } else col = in[j]; 5375 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5376 } 5377 } 5378 } else if (!aij->donotstash) { 5379 if (roworiented) { 5380 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5381 } else { 5382 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5383 } 5384 } 5385 } 5386 } 5387 PetscFunctionReturnVoid(); 5388 } 5389 5390