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 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 135 { 136 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 137 PetscErrorCode ierr; 138 PetscInt i,rstart,nrows,*rows; 139 140 PetscFunctionBegin; 141 *zrows = NULL; 142 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 143 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 144 for (i=0; i<nrows; i++) rows[i] += rstart; 145 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 146 PetscFunctionReturn(0); 147 } 148 149 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 150 { 151 PetscErrorCode ierr; 152 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 153 PetscInt i,n,*garray = aij->garray; 154 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 155 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 156 PetscReal *work; 157 158 PetscFunctionBegin; 159 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 160 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 161 if (type == NORM_2) { 162 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 163 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 164 } 165 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 166 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 167 } 168 } else if (type == NORM_1) { 169 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 170 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 171 } 172 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 173 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 174 } 175 } else if (type == NORM_INFINITY) { 176 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 177 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 178 } 179 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 180 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 181 } 182 183 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 184 if (type == NORM_INFINITY) { 185 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 186 } else { 187 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 188 } 189 ierr = PetscFree(work);CHKERRQ(ierr); 190 if (type == NORM_2) { 191 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 192 } 193 PetscFunctionReturn(0); 194 } 195 196 PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is) 197 { 198 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 199 IS sis,gis; 200 PetscErrorCode ierr; 201 const PetscInt *isis,*igis; 202 PetscInt n,*iis,nsis,ngis,rstart,i; 203 204 PetscFunctionBegin; 205 ierr = MatFindOffBlockDiagonalEntries(a->A,&sis);CHKERRQ(ierr); 206 ierr = MatFindNonzeroRows(a->B,&gis);CHKERRQ(ierr); 207 ierr = ISGetSize(gis,&ngis);CHKERRQ(ierr); 208 ierr = ISGetSize(sis,&nsis);CHKERRQ(ierr); 209 ierr = ISGetIndices(sis,&isis);CHKERRQ(ierr); 210 ierr = ISGetIndices(gis,&igis);CHKERRQ(ierr); 211 212 ierr = PetscMalloc1(ngis+nsis,&iis);CHKERRQ(ierr); 213 ierr = PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));CHKERRQ(ierr); 214 ierr = PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));CHKERRQ(ierr); 215 n = ngis + nsis; 216 ierr = PetscSortRemoveDupsInt(&n,iis);CHKERRQ(ierr); 217 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 218 for (i=0; i<n; i++) iis[i] += rstart; 219 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 220 221 ierr = ISRestoreIndices(sis,&isis);CHKERRQ(ierr); 222 ierr = ISRestoreIndices(gis,&igis);CHKERRQ(ierr); 223 ierr = ISDestroy(&sis);CHKERRQ(ierr); 224 ierr = ISDestroy(&gis);CHKERRQ(ierr); 225 PetscFunctionReturn(0); 226 } 227 228 /* 229 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 230 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 231 232 Only for square matrices 233 234 Used by a preconditioner, hence PETSC_EXTERN 235 */ 236 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 237 { 238 PetscMPIInt rank,size; 239 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 240 PetscErrorCode ierr; 241 Mat mat; 242 Mat_SeqAIJ *gmata; 243 PetscMPIInt tag; 244 MPI_Status status; 245 PetscBool aij; 246 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 247 248 PetscFunctionBegin; 249 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 250 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 251 if (!rank) { 252 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 253 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 254 } 255 if (reuse == MAT_INITIAL_MATRIX) { 256 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 257 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 258 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 259 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 260 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 261 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 262 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 263 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 264 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 265 266 rowners[0] = 0; 267 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 268 rstart = rowners[rank]; 269 rend = rowners[rank+1]; 270 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 271 if (!rank) { 272 gmata = (Mat_SeqAIJ*) gmat->data; 273 /* send row lengths to all processors */ 274 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 275 for (i=1; i<size; i++) { 276 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 277 } 278 /* determine number diagonal and off-diagonal counts */ 279 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 280 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 281 jj = 0; 282 for (i=0; i<m; i++) { 283 for (j=0; j<dlens[i]; j++) { 284 if (gmata->j[jj] < rstart) ld[i]++; 285 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 286 jj++; 287 } 288 } 289 /* send column indices to other processes */ 290 for (i=1; i<size; i++) { 291 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 292 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 293 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 294 } 295 296 /* send numerical values to other processes */ 297 for (i=1; i<size; i++) { 298 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 299 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 300 } 301 gmataa = gmata->a; 302 gmataj = gmata->j; 303 304 } else { 305 /* receive row lengths */ 306 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 307 /* receive column indices */ 308 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 309 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 310 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 311 /* determine number diagonal and off-diagonal counts */ 312 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 313 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 314 jj = 0; 315 for (i=0; i<m; i++) { 316 for (j=0; j<dlens[i]; j++) { 317 if (gmataj[jj] < rstart) ld[i]++; 318 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 319 jj++; 320 } 321 } 322 /* receive numerical values */ 323 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 324 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 325 } 326 /* set preallocation */ 327 for (i=0; i<m; i++) { 328 dlens[i] -= olens[i]; 329 } 330 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 331 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 332 333 for (i=0; i<m; i++) { 334 dlens[i] += olens[i]; 335 } 336 cnt = 0; 337 for (i=0; i<m; i++) { 338 row = rstart + i; 339 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 340 cnt += dlens[i]; 341 } 342 if (rank) { 343 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 344 } 345 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 346 ierr = PetscFree(rowners);CHKERRQ(ierr); 347 348 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 349 350 *inmat = mat; 351 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 352 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 353 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 354 mat = *inmat; 355 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 356 if (!rank) { 357 /* send numerical values to other processes */ 358 gmata = (Mat_SeqAIJ*) gmat->data; 359 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 360 gmataa = gmata->a; 361 for (i=1; i<size; i++) { 362 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 363 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 364 } 365 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 366 } else { 367 /* receive numerical values from process 0*/ 368 nz = Ad->nz + Ao->nz; 369 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 370 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 371 } 372 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 373 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 374 ad = Ad->a; 375 ao = Ao->a; 376 if (mat->rmap->n) { 377 i = 0; 378 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 379 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 380 } 381 for (i=1; i<mat->rmap->n; i++) { 382 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; 383 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 384 } 385 i--; 386 if (mat->rmap->n) { 387 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 388 } 389 if (rank) { 390 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 391 } 392 } 393 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 394 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 395 PetscFunctionReturn(0); 396 } 397 398 /* 399 Local utility routine that creates a mapping from the global column 400 number to the local number in the off-diagonal part of the local 401 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 402 a slightly higher hash table cost; without it it is not scalable (each processor 403 has an order N integer array but is fast to acess. 404 */ 405 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 406 { 407 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 408 PetscErrorCode ierr; 409 PetscInt n = aij->B->cmap->n,i; 410 411 PetscFunctionBegin; 412 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 413 #if defined(PETSC_USE_CTABLE) 414 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 415 for (i=0; i<n; i++) { 416 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 417 } 418 #else 419 ierr = PetscCalloc1(mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 420 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 421 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 422 #endif 423 PetscFunctionReturn(0); 424 } 425 426 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \ 427 { \ 428 if (col <= lastcol1) low1 = 0; \ 429 else high1 = nrow1; \ 430 lastcol1 = col;\ 431 while (high1-low1 > 5) { \ 432 t = (low1+high1)/2; \ 433 if (rp1[t] > col) high1 = t; \ 434 else low1 = t; \ 435 } \ 436 for (_i=low1; _i<high1; _i++) { \ 437 if (rp1[_i] > col) break; \ 438 if (rp1[_i] == col) { \ 439 if (addv == ADD_VALUES) ap1[_i] += value; \ 440 else ap1[_i] = value; \ 441 goto a_noinsert; \ 442 } \ 443 } \ 444 if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 445 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 446 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); \ 447 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 448 N = nrow1++ - 1; a->nz++; high1++; \ 449 /* shift up all the later entries in this row */ \ 450 for (ii=N; ii>=_i; ii--) { \ 451 rp1[ii+1] = rp1[ii]; \ 452 ap1[ii+1] = ap1[ii]; \ 453 } \ 454 rp1[_i] = col; \ 455 ap1[_i] = value; \ 456 A->nonzerostate++;\ 457 a_noinsert: ; \ 458 ailen[row] = nrow1; \ 459 } 460 461 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \ 462 { \ 463 if (col <= lastcol2) low2 = 0; \ 464 else high2 = nrow2; \ 465 lastcol2 = col; \ 466 while (high2-low2 > 5) { \ 467 t = (low2+high2)/2; \ 468 if (rp2[t] > col) high2 = t; \ 469 else low2 = t; \ 470 } \ 471 for (_i=low2; _i<high2; _i++) { \ 472 if (rp2[_i] > col) break; \ 473 if (rp2[_i] == col) { \ 474 if (addv == ADD_VALUES) ap2[_i] += value; \ 475 else ap2[_i] = value; \ 476 goto b_noinsert; \ 477 } \ 478 } \ 479 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 480 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 481 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); \ 482 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 483 N = nrow2++ - 1; b->nz++; high2++; \ 484 /* shift up all the later entries in this row */ \ 485 for (ii=N; ii>=_i; ii--) { \ 486 rp2[ii+1] = rp2[ii]; \ 487 ap2[ii+1] = ap2[ii]; \ 488 } \ 489 rp2[_i] = col; \ 490 ap2[_i] = value; \ 491 B->nonzerostate++; \ 492 b_noinsert: ; \ 493 bilen[row] = nrow2; \ 494 } 495 496 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 497 { 498 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 499 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 500 PetscErrorCode ierr; 501 PetscInt l,*garray = mat->garray,diag; 502 503 PetscFunctionBegin; 504 /* code only works for square matrices A */ 505 506 /* find size of row to the left of the diagonal part */ 507 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 508 row = row - diag; 509 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 510 if (garray[b->j[b->i[row]+l]] > diag) break; 511 } 512 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 513 514 /* diagonal part */ 515 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 516 517 /* right of diagonal part */ 518 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); 519 PetscFunctionReturn(0); 520 } 521 522 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 523 { 524 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 525 PetscScalar value; 526 PetscErrorCode ierr; 527 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 528 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 529 PetscBool roworiented = aij->roworiented; 530 531 /* Some Variables required in the macro */ 532 Mat A = aij->A; 533 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 534 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 535 MatScalar *aa = a->a; 536 PetscBool ignorezeroentries = a->ignorezeroentries; 537 Mat B = aij->B; 538 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 539 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 540 MatScalar *ba = b->a; 541 542 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 543 PetscInt nonew; 544 MatScalar *ap1,*ap2; 545 546 PetscFunctionBegin; 547 for (i=0; i<m; i++) { 548 if (im[i] < 0) continue; 549 #if defined(PETSC_USE_DEBUG) 550 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); 551 #endif 552 if (im[i] >= rstart && im[i] < rend) { 553 row = im[i] - rstart; 554 lastcol1 = -1; 555 rp1 = aj + ai[row]; 556 ap1 = aa + ai[row]; 557 rmax1 = aimax[row]; 558 nrow1 = ailen[row]; 559 low1 = 0; 560 high1 = nrow1; 561 lastcol2 = -1; 562 rp2 = bj + bi[row]; 563 ap2 = ba + bi[row]; 564 rmax2 = bimax[row]; 565 nrow2 = bilen[row]; 566 low2 = 0; 567 high2 = nrow2; 568 569 for (j=0; j<n; j++) { 570 if (roworiented) value = v[i*n+j]; 571 else value = v[i+j*m]; 572 if (in[j] >= cstart && in[j] < cend) { 573 col = in[j] - cstart; 574 nonew = a->nonew; 575 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 576 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 577 } else if (in[j] < 0) continue; 578 #if defined(PETSC_USE_DEBUG) 579 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); 580 #endif 581 else { 582 if (mat->was_assembled) { 583 if (!aij->colmap) { 584 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 585 } 586 #if defined(PETSC_USE_CTABLE) 587 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 588 col--; 589 #else 590 col = aij->colmap[in[j]] - 1; 591 #endif 592 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 593 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 594 col = in[j]; 595 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 596 B = aij->B; 597 b = (Mat_SeqAIJ*)B->data; 598 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 599 rp2 = bj + bi[row]; 600 ap2 = ba + bi[row]; 601 rmax2 = bimax[row]; 602 nrow2 = bilen[row]; 603 low2 = 0; 604 high2 = nrow2; 605 bm = aij->B->rmap->n; 606 ba = b->a; 607 } 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]); 608 } else col = in[j]; 609 nonew = b->nonew; 610 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 611 } 612 } 613 } else { 614 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]); 615 if (!aij->donotstash) { 616 mat->assembled = PETSC_FALSE; 617 if (roworiented) { 618 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 619 } else { 620 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 621 } 622 } 623 } 624 } 625 PetscFunctionReturn(0); 626 } 627 628 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 629 { 630 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 631 PetscErrorCode ierr; 632 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 633 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 634 635 PetscFunctionBegin; 636 for (i=0; i<m; i++) { 637 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 638 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); 639 if (idxm[i] >= rstart && idxm[i] < rend) { 640 row = idxm[i] - rstart; 641 for (j=0; j<n; j++) { 642 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 643 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); 644 if (idxn[j] >= cstart && idxn[j] < cend) { 645 col = idxn[j] - cstart; 646 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 647 } else { 648 if (!aij->colmap) { 649 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 650 } 651 #if defined(PETSC_USE_CTABLE) 652 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 653 col--; 654 #else 655 col = aij->colmap[idxn[j]] - 1; 656 #endif 657 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 658 else { 659 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 660 } 661 } 662 } 663 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 664 } 665 PetscFunctionReturn(0); 666 } 667 668 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 669 670 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 671 { 672 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 673 PetscErrorCode ierr; 674 PetscInt nstash,reallocs; 675 676 PetscFunctionBegin; 677 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 678 679 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 680 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 681 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 682 PetscFunctionReturn(0); 683 } 684 685 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 686 { 687 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 688 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 689 PetscErrorCode ierr; 690 PetscMPIInt n; 691 PetscInt i,j,rstart,ncols,flg; 692 PetscInt *row,*col; 693 PetscBool other_disassembled; 694 PetscScalar *val; 695 696 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 697 698 PetscFunctionBegin; 699 if (!aij->donotstash && !mat->nooffprocentries) { 700 while (1) { 701 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 702 if (!flg) break; 703 704 for (i=0; i<n; ) { 705 /* Now identify the consecutive vals belonging to the same row */ 706 for (j=i,rstart=row[j]; j<n; j++) { 707 if (row[j] != rstart) break; 708 } 709 if (j < n) ncols = j-i; 710 else ncols = n-i; 711 /* Now assemble all these values with a single function call */ 712 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 713 714 i = j; 715 } 716 } 717 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 718 } 719 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 720 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 721 722 /* determine if any processor has disassembled, if so we must 723 also disassemble ourselfs, in order that we may reassemble. */ 724 /* 725 if nonzero structure of submatrix B cannot change then we know that 726 no processor disassembled thus we can skip this stuff 727 */ 728 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 729 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 730 if (mat->was_assembled && !other_disassembled) { 731 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 732 } 733 } 734 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 735 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 736 } 737 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 738 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 739 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 740 741 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 742 743 aij->rowvalues = 0; 744 745 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 746 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 747 748 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 749 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 750 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 751 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 752 } 753 PetscFunctionReturn(0); 754 } 755 756 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 757 { 758 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 759 PetscErrorCode ierr; 760 761 PetscFunctionBegin; 762 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 763 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 764 PetscFunctionReturn(0); 765 } 766 767 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 768 { 769 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 770 PetscInt *lrows; 771 PetscInt r, len; 772 PetscErrorCode ierr; 773 774 PetscFunctionBegin; 775 /* get locally owned rows */ 776 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 777 /* fix right hand side if needed */ 778 if (x && b) { 779 const PetscScalar *xx; 780 PetscScalar *bb; 781 782 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 783 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 784 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 785 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 786 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 787 } 788 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 789 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 790 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 791 PetscBool cong; 792 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 793 if (cong) A->congruentlayouts = 1; 794 else A->congruentlayouts = 0; 795 } 796 if ((diag != 0.0) && A->congruentlayouts) { 797 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 798 } else if (diag != 0.0) { 799 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 800 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"); 801 for (r = 0; r < len; ++r) { 802 const PetscInt row = lrows[r] + A->rmap->rstart; 803 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 804 } 805 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 806 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 807 } else { 808 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 809 } 810 ierr = PetscFree(lrows);CHKERRQ(ierr); 811 812 /* only change matrix nonzero state if pattern was allowed to be changed */ 813 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 814 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 815 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 816 } 817 PetscFunctionReturn(0); 818 } 819 820 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 821 { 822 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 823 PetscErrorCode ierr; 824 PetscMPIInt n = A->rmap->n; 825 PetscInt i,j,r,m,p = 0,len = 0; 826 PetscInt *lrows,*owners = A->rmap->range; 827 PetscSFNode *rrows; 828 PetscSF sf; 829 const PetscScalar *xx; 830 PetscScalar *bb,*mask; 831 Vec xmask,lmask; 832 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 833 const PetscInt *aj, *ii,*ridx; 834 PetscScalar *aa; 835 836 PetscFunctionBegin; 837 /* Create SF where leaves are input rows and roots are owned rows */ 838 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 839 for (r = 0; r < n; ++r) lrows[r] = -1; 840 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 841 for (r = 0; r < N; ++r) { 842 const PetscInt idx = rows[r]; 843 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); 844 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 845 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 846 } 847 rrows[r].rank = p; 848 rrows[r].index = rows[r] - owners[p]; 849 } 850 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 851 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 852 /* Collect flags for rows to be zeroed */ 853 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 854 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 855 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 856 /* Compress and put in row numbers */ 857 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 858 /* zero diagonal part of matrix */ 859 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 860 /* handle off diagonal part of matrix */ 861 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 862 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 863 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 864 for (i=0; i<len; i++) bb[lrows[i]] = 1; 865 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 866 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 867 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 868 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 869 if (x) { 870 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 871 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 872 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 873 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 874 } 875 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 876 /* remove zeroed rows of off diagonal matrix */ 877 ii = aij->i; 878 for (i=0; i<len; i++) { 879 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 880 } 881 /* loop over all elements of off process part of matrix zeroing removed columns*/ 882 if (aij->compressedrow.use) { 883 m = aij->compressedrow.nrows; 884 ii = aij->compressedrow.i; 885 ridx = aij->compressedrow.rindex; 886 for (i=0; i<m; i++) { 887 n = ii[i+1] - ii[i]; 888 aj = aij->j + ii[i]; 889 aa = aij->a + ii[i]; 890 891 for (j=0; j<n; j++) { 892 if (PetscAbsScalar(mask[*aj])) { 893 if (b) bb[*ridx] -= *aa*xx[*aj]; 894 *aa = 0.0; 895 } 896 aa++; 897 aj++; 898 } 899 ridx++; 900 } 901 } else { /* do not use compressed row format */ 902 m = l->B->rmap->n; 903 for (i=0; i<m; i++) { 904 n = ii[i+1] - ii[i]; 905 aj = aij->j + ii[i]; 906 aa = aij->a + ii[i]; 907 for (j=0; j<n; j++) { 908 if (PetscAbsScalar(mask[*aj])) { 909 if (b) bb[i] -= *aa*xx[*aj]; 910 *aa = 0.0; 911 } 912 aa++; 913 aj++; 914 } 915 } 916 } 917 if (x) { 918 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 919 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 920 } 921 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 922 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 923 ierr = PetscFree(lrows);CHKERRQ(ierr); 924 925 /* only change matrix nonzero state if pattern was allowed to be changed */ 926 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 927 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 928 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 929 } 930 PetscFunctionReturn(0); 931 } 932 933 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 934 { 935 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 936 PetscErrorCode ierr; 937 PetscInt nt; 938 939 PetscFunctionBegin; 940 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 941 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); 942 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 943 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 944 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 945 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 946 PetscFunctionReturn(0); 947 } 948 949 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 950 { 951 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 952 PetscErrorCode ierr; 953 954 PetscFunctionBegin; 955 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 956 PetscFunctionReturn(0); 957 } 958 959 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 960 { 961 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 962 PetscErrorCode ierr; 963 964 PetscFunctionBegin; 965 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 966 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 967 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 968 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 969 PetscFunctionReturn(0); 970 } 971 972 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 973 { 974 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 975 PetscErrorCode ierr; 976 PetscBool merged; 977 978 PetscFunctionBegin; 979 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 980 /* do nondiagonal part */ 981 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 982 if (!merged) { 983 /* send it on its way */ 984 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 985 /* do local part */ 986 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 987 /* receive remote parts: note this assumes the values are not actually */ 988 /* added in yy until the next line, */ 989 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 990 } else { 991 /* do local part */ 992 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 993 /* send it on its way */ 994 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 995 /* values actually were received in the Begin() but we need to call this nop */ 996 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 997 } 998 PetscFunctionReturn(0); 999 } 1000 1001 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1002 { 1003 MPI_Comm comm; 1004 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1005 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1006 IS Me,Notme; 1007 PetscErrorCode ierr; 1008 PetscInt M,N,first,last,*notme,i; 1009 PetscMPIInt size; 1010 1011 PetscFunctionBegin; 1012 /* Easy test: symmetric diagonal block */ 1013 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1014 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1015 if (!*f) PetscFunctionReturn(0); 1016 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1017 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1018 if (size == 1) PetscFunctionReturn(0); 1019 1020 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 1021 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1022 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1023 ierr = PetscMalloc1(N-last+first,¬me);CHKERRQ(ierr); 1024 for (i=0; i<first; i++) notme[i] = i; 1025 for (i=last; i<M; i++) notme[i-last+first] = i; 1026 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1027 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1028 ierr = MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1029 Aoff = Aoffs[0]; 1030 ierr = MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1031 Boff = Boffs[0]; 1032 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1033 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1034 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1035 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1036 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1037 ierr = PetscFree(notme);CHKERRQ(ierr); 1038 PetscFunctionReturn(0); 1039 } 1040 1041 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1042 { 1043 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1044 PetscErrorCode ierr; 1045 1046 PetscFunctionBegin; 1047 /* do nondiagonal part */ 1048 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1049 /* send it on its way */ 1050 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1051 /* do local part */ 1052 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1053 /* receive remote parts */ 1054 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 /* 1059 This only works correctly for square matrices where the subblock A->A is the 1060 diagonal block 1061 */ 1062 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1063 { 1064 PetscErrorCode ierr; 1065 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1066 1067 PetscFunctionBegin; 1068 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1069 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"); 1070 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1071 PetscFunctionReturn(0); 1072 } 1073 1074 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1075 { 1076 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1077 PetscErrorCode ierr; 1078 1079 PetscFunctionBegin; 1080 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1081 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1082 PetscFunctionReturn(0); 1083 } 1084 1085 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1086 { 1087 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 #if defined(PETSC_USE_LOG) 1092 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1093 #endif 1094 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1095 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1096 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1097 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1098 #if defined(PETSC_USE_CTABLE) 1099 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1100 #else 1101 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1102 #endif 1103 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1104 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1105 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1106 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1107 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1108 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1109 1110 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1118 #if defined(PETSC_HAVE_ELEMENTAL) 1119 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1120 #endif 1121 #if defined(PETSC_HAVE_HYPRE) 1122 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);CHKERRQ(ierr); 1123 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);CHKERRQ(ierr); 1124 #endif 1125 PetscFunctionReturn(0); 1126 } 1127 1128 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1129 { 1130 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1131 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1132 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1133 PetscErrorCode ierr; 1134 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1135 int fd; 1136 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1137 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1138 PetscScalar *column_values; 1139 PetscInt message_count,flowcontrolcount; 1140 FILE *file; 1141 1142 PetscFunctionBegin; 1143 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1144 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1145 nz = A->nz + B->nz; 1146 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1147 if (!rank) { 1148 header[0] = MAT_FILE_CLASSID; 1149 header[1] = mat->rmap->N; 1150 header[2] = mat->cmap->N; 1151 1152 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1153 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1154 /* get largest number of rows any processor has */ 1155 rlen = mat->rmap->n; 1156 range = mat->rmap->range; 1157 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1158 } else { 1159 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1160 rlen = mat->rmap->n; 1161 } 1162 1163 /* load up the local row counts */ 1164 ierr = PetscMalloc1(rlen+1,&row_lengths);CHKERRQ(ierr); 1165 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]; 1166 1167 /* store the row lengths to the file */ 1168 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1169 if (!rank) { 1170 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1171 for (i=1; i<size; i++) { 1172 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1173 rlen = range[i+1] - range[i]; 1174 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1175 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1176 } 1177 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1178 } else { 1179 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1180 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1181 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1182 } 1183 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1184 1185 /* load up the local column indices */ 1186 nzmax = nz; /* th processor needs space a largest processor needs */ 1187 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1188 ierr = PetscMalloc1(nzmax+1,&column_indices);CHKERRQ(ierr); 1189 cnt = 0; 1190 for (i=0; i<mat->rmap->n; i++) { 1191 for (j=B->i[i]; j<B->i[i+1]; j++) { 1192 if ((col = garray[B->j[j]]) > cstart) break; 1193 column_indices[cnt++] = col; 1194 } 1195 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1196 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1197 } 1198 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); 1199 1200 /* store the column indices to the file */ 1201 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1202 if (!rank) { 1203 MPI_Status status; 1204 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1205 for (i=1; i<size; i++) { 1206 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1207 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1208 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1209 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1210 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1211 } 1212 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1213 } else { 1214 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1215 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1216 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1217 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1218 } 1219 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1220 1221 /* load up the local column values */ 1222 ierr = PetscMalloc1(nzmax+1,&column_values);CHKERRQ(ierr); 1223 cnt = 0; 1224 for (i=0; i<mat->rmap->n; i++) { 1225 for (j=B->i[i]; j<B->i[i+1]; j++) { 1226 if (garray[B->j[j]] > cstart) break; 1227 column_values[cnt++] = B->a[j]; 1228 } 1229 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1230 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1231 } 1232 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); 1233 1234 /* store the column values to the file */ 1235 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1236 if (!rank) { 1237 MPI_Status status; 1238 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1239 for (i=1; i<size; i++) { 1240 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1241 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1242 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1243 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1244 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1245 } 1246 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1247 } else { 1248 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1249 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1250 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1251 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1252 } 1253 ierr = PetscFree(column_values);CHKERRQ(ierr); 1254 1255 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1256 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1257 PetscFunctionReturn(0); 1258 } 1259 1260 #include <petscdraw.h> 1261 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1262 { 1263 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1264 PetscErrorCode ierr; 1265 PetscMPIInt rank = aij->rank,size = aij->size; 1266 PetscBool isdraw,iascii,isbinary; 1267 PetscViewer sviewer; 1268 PetscViewerFormat format; 1269 1270 PetscFunctionBegin; 1271 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1272 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1273 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1274 if (iascii) { 1275 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1276 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1277 MatInfo info; 1278 PetscBool inodes; 1279 1280 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1281 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1282 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1283 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1284 if (!inodes) { 1285 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1286 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1287 } else { 1288 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1289 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1290 } 1291 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1292 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1293 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1294 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1295 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1296 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1297 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1298 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1299 PetscFunctionReturn(0); 1300 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1301 PetscInt inodecount,inodelimit,*inodes; 1302 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1303 if (inodes) { 1304 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1305 } else { 1306 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1307 } 1308 PetscFunctionReturn(0); 1309 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1310 PetscFunctionReturn(0); 1311 } 1312 } else if (isbinary) { 1313 if (size == 1) { 1314 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1315 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1316 } else { 1317 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1318 } 1319 PetscFunctionReturn(0); 1320 } else if (isdraw) { 1321 PetscDraw draw; 1322 PetscBool isnull; 1323 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1324 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1325 if (isnull) PetscFunctionReturn(0); 1326 } 1327 1328 { 1329 /* assemble the entire matrix onto first processor. */ 1330 Mat A; 1331 Mat_SeqAIJ *Aloc; 1332 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1333 MatScalar *a; 1334 1335 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1336 if (!rank) { 1337 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1338 } else { 1339 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1340 } 1341 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1342 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1343 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1344 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1345 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1346 1347 /* copy over the A part */ 1348 Aloc = (Mat_SeqAIJ*)aij->A->data; 1349 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1350 row = mat->rmap->rstart; 1351 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1352 for (i=0; i<m; i++) { 1353 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1354 row++; 1355 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1356 } 1357 aj = Aloc->j; 1358 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1359 1360 /* copy over the B part */ 1361 Aloc = (Mat_SeqAIJ*)aij->B->data; 1362 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1363 row = mat->rmap->rstart; 1364 ierr = PetscMalloc1(ai[m]+1,&cols);CHKERRQ(ierr); 1365 ct = cols; 1366 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1367 for (i=0; i<m; i++) { 1368 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1369 row++; 1370 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1371 } 1372 ierr = PetscFree(ct);CHKERRQ(ierr); 1373 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1374 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1375 /* 1376 Everyone has to call to draw the matrix since the graphics waits are 1377 synchronized across all processors that share the PetscDraw object 1378 */ 1379 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1380 if (!rank) { 1381 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1382 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1383 } 1384 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1385 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1386 ierr = MatDestroy(&A);CHKERRQ(ierr); 1387 } 1388 PetscFunctionReturn(0); 1389 } 1390 1391 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1392 { 1393 PetscErrorCode ierr; 1394 PetscBool iascii,isdraw,issocket,isbinary; 1395 1396 PetscFunctionBegin; 1397 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1398 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1399 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1400 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1401 if (iascii || isdraw || isbinary || issocket) { 1402 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1403 } 1404 PetscFunctionReturn(0); 1405 } 1406 1407 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1408 { 1409 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1410 PetscErrorCode ierr; 1411 Vec bb1 = 0; 1412 PetscBool hasop; 1413 1414 PetscFunctionBegin; 1415 if (flag == SOR_APPLY_UPPER) { 1416 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1417 PetscFunctionReturn(0); 1418 } 1419 1420 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1421 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1422 } 1423 1424 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1425 if (flag & SOR_ZERO_INITIAL_GUESS) { 1426 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1427 its--; 1428 } 1429 1430 while (its--) { 1431 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1432 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1433 1434 /* update rhs: bb1 = bb - B*x */ 1435 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1436 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1437 1438 /* local sweep */ 1439 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1440 } 1441 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1442 if (flag & SOR_ZERO_INITIAL_GUESS) { 1443 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1444 its--; 1445 } 1446 while (its--) { 1447 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1448 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1449 1450 /* update rhs: bb1 = bb - B*x */ 1451 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1452 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1453 1454 /* local sweep */ 1455 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1456 } 1457 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1458 if (flag & SOR_ZERO_INITIAL_GUESS) { 1459 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1460 its--; 1461 } 1462 while (its--) { 1463 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1464 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1465 1466 /* update rhs: bb1 = bb - B*x */ 1467 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1468 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1469 1470 /* local sweep */ 1471 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1472 } 1473 } else if (flag & SOR_EISENSTAT) { 1474 Vec xx1; 1475 1476 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1477 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1478 1479 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1480 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1481 if (!mat->diag) { 1482 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1483 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1484 } 1485 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1486 if (hasop) { 1487 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1488 } else { 1489 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1490 } 1491 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1492 1493 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1494 1495 /* local sweep */ 1496 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1497 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1498 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1499 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1500 1501 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1502 1503 matin->factorerrortype = mat->A->factorerrortype; 1504 PetscFunctionReturn(0); 1505 } 1506 1507 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1508 { 1509 Mat aA,aB,Aperm; 1510 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1511 PetscScalar *aa,*ba; 1512 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1513 PetscSF rowsf,sf; 1514 IS parcolp = NULL; 1515 PetscBool done; 1516 PetscErrorCode ierr; 1517 1518 PetscFunctionBegin; 1519 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1520 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1521 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1522 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1523 1524 /* Invert row permutation to find out where my rows should go */ 1525 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1526 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1527 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1528 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1529 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1530 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1531 1532 /* Invert column permutation to find out where my columns should go */ 1533 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1534 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1535 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1536 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1537 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1538 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1539 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1540 1541 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1542 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1543 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1544 1545 /* Find out where my gcols should go */ 1546 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1547 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1548 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1549 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1550 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1551 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1552 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1553 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1554 1555 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1556 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1557 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1558 for (i=0; i<m; i++) { 1559 PetscInt row = rdest[i],rowner; 1560 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1561 for (j=ai[i]; j<ai[i+1]; j++) { 1562 PetscInt cowner,col = cdest[aj[j]]; 1563 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1564 if (rowner == cowner) dnnz[i]++; 1565 else onnz[i]++; 1566 } 1567 for (j=bi[i]; j<bi[i+1]; j++) { 1568 PetscInt cowner,col = gcdest[bj[j]]; 1569 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1570 if (rowner == cowner) dnnz[i]++; 1571 else onnz[i]++; 1572 } 1573 } 1574 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1575 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1576 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1577 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1578 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1579 1580 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1581 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1582 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1583 for (i=0; i<m; i++) { 1584 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1585 PetscInt j0,rowlen; 1586 rowlen = ai[i+1] - ai[i]; 1587 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1588 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1589 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1590 } 1591 rowlen = bi[i+1] - bi[i]; 1592 for (j0=j=0; j<rowlen; j0=j) { 1593 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1594 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1595 } 1596 } 1597 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1598 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1599 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1600 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1601 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1602 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1603 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1604 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1605 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1606 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1607 *B = Aperm; 1608 PetscFunctionReturn(0); 1609 } 1610 1611 PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 1612 { 1613 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1614 PetscErrorCode ierr; 1615 1616 PetscFunctionBegin; 1617 ierr = MatGetSize(aij->B,NULL,nghosts);CHKERRQ(ierr); 1618 if (ghosts) *ghosts = aij->garray; 1619 PetscFunctionReturn(0); 1620 } 1621 1622 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1623 { 1624 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1625 Mat A = mat->A,B = mat->B; 1626 PetscErrorCode ierr; 1627 PetscReal isend[5],irecv[5]; 1628 1629 PetscFunctionBegin; 1630 info->block_size = 1.0; 1631 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1632 1633 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1634 isend[3] = info->memory; isend[4] = info->mallocs; 1635 1636 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1637 1638 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1639 isend[3] += info->memory; isend[4] += info->mallocs; 1640 if (flag == MAT_LOCAL) { 1641 info->nz_used = isend[0]; 1642 info->nz_allocated = isend[1]; 1643 info->nz_unneeded = isend[2]; 1644 info->memory = isend[3]; 1645 info->mallocs = isend[4]; 1646 } else if (flag == MAT_GLOBAL_MAX) { 1647 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1648 1649 info->nz_used = irecv[0]; 1650 info->nz_allocated = irecv[1]; 1651 info->nz_unneeded = irecv[2]; 1652 info->memory = irecv[3]; 1653 info->mallocs = irecv[4]; 1654 } else if (flag == MAT_GLOBAL_SUM) { 1655 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1656 1657 info->nz_used = irecv[0]; 1658 info->nz_allocated = irecv[1]; 1659 info->nz_unneeded = irecv[2]; 1660 info->memory = irecv[3]; 1661 info->mallocs = irecv[4]; 1662 } 1663 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1664 info->fill_ratio_needed = 0; 1665 info->factor_mallocs = 0; 1666 PetscFunctionReturn(0); 1667 } 1668 1669 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1670 { 1671 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1672 PetscErrorCode ierr; 1673 1674 PetscFunctionBegin; 1675 switch (op) { 1676 case MAT_NEW_NONZERO_LOCATIONS: 1677 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1678 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1679 case MAT_KEEP_NONZERO_PATTERN: 1680 case MAT_NEW_NONZERO_LOCATION_ERR: 1681 case MAT_USE_INODES: 1682 case MAT_IGNORE_ZERO_ENTRIES: 1683 MatCheckPreallocated(A,1); 1684 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1685 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1686 break; 1687 case MAT_ROW_ORIENTED: 1688 MatCheckPreallocated(A,1); 1689 a->roworiented = flg; 1690 1691 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1692 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1693 break; 1694 case MAT_NEW_DIAGONALS: 1695 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1696 break; 1697 case MAT_IGNORE_OFF_PROC_ENTRIES: 1698 a->donotstash = flg; 1699 break; 1700 case MAT_SPD: 1701 A->spd_set = PETSC_TRUE; 1702 A->spd = flg; 1703 if (flg) { 1704 A->symmetric = PETSC_TRUE; 1705 A->structurally_symmetric = PETSC_TRUE; 1706 A->symmetric_set = PETSC_TRUE; 1707 A->structurally_symmetric_set = PETSC_TRUE; 1708 } 1709 break; 1710 case MAT_SYMMETRIC: 1711 MatCheckPreallocated(A,1); 1712 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1713 break; 1714 case MAT_STRUCTURALLY_SYMMETRIC: 1715 MatCheckPreallocated(A,1); 1716 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1717 break; 1718 case MAT_HERMITIAN: 1719 MatCheckPreallocated(A,1); 1720 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1721 break; 1722 case MAT_SYMMETRY_ETERNAL: 1723 MatCheckPreallocated(A,1); 1724 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1725 break; 1726 case MAT_SUBMAT_SINGLEIS: 1727 A->submat_singleis = flg; 1728 break; 1729 default: 1730 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1731 } 1732 PetscFunctionReturn(0); 1733 } 1734 1735 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1736 { 1737 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1738 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1739 PetscErrorCode ierr; 1740 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1741 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1742 PetscInt *cmap,*idx_p; 1743 1744 PetscFunctionBegin; 1745 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1746 mat->getrowactive = PETSC_TRUE; 1747 1748 if (!mat->rowvalues && (idx || v)) { 1749 /* 1750 allocate enough space to hold information from the longest row. 1751 */ 1752 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1753 PetscInt max = 1,tmp; 1754 for (i=0; i<matin->rmap->n; i++) { 1755 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1756 if (max < tmp) max = tmp; 1757 } 1758 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1759 } 1760 1761 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1762 lrow = row - rstart; 1763 1764 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1765 if (!v) {pvA = 0; pvB = 0;} 1766 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1767 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1768 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1769 nztot = nzA + nzB; 1770 1771 cmap = mat->garray; 1772 if (v || idx) { 1773 if (nztot) { 1774 /* Sort by increasing column numbers, assuming A and B already sorted */ 1775 PetscInt imark = -1; 1776 if (v) { 1777 *v = v_p = mat->rowvalues; 1778 for (i=0; i<nzB; i++) { 1779 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1780 else break; 1781 } 1782 imark = i; 1783 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1784 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1785 } 1786 if (idx) { 1787 *idx = idx_p = mat->rowindices; 1788 if (imark > -1) { 1789 for (i=0; i<imark; i++) { 1790 idx_p[i] = cmap[cworkB[i]]; 1791 } 1792 } else { 1793 for (i=0; i<nzB; i++) { 1794 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1795 else break; 1796 } 1797 imark = i; 1798 } 1799 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1800 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1801 } 1802 } else { 1803 if (idx) *idx = 0; 1804 if (v) *v = 0; 1805 } 1806 } 1807 *nz = nztot; 1808 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1809 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1810 PetscFunctionReturn(0); 1811 } 1812 1813 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1814 { 1815 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1816 1817 PetscFunctionBegin; 1818 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1819 aij->getrowactive = PETSC_FALSE; 1820 PetscFunctionReturn(0); 1821 } 1822 1823 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1824 { 1825 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1826 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1827 PetscErrorCode ierr; 1828 PetscInt i,j,cstart = mat->cmap->rstart; 1829 PetscReal sum = 0.0; 1830 MatScalar *v; 1831 1832 PetscFunctionBegin; 1833 if (aij->size == 1) { 1834 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1835 } else { 1836 if (type == NORM_FROBENIUS) { 1837 v = amat->a; 1838 for (i=0; i<amat->nz; i++) { 1839 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1840 } 1841 v = bmat->a; 1842 for (i=0; i<bmat->nz; i++) { 1843 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1844 } 1845 ierr = MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1846 *norm = PetscSqrtReal(*norm); 1847 ierr = PetscLogFlops(2*amat->nz+2*bmat->nz);CHKERRQ(ierr); 1848 } else if (type == NORM_1) { /* max column norm */ 1849 PetscReal *tmp,*tmp2; 1850 PetscInt *jj,*garray = aij->garray; 1851 ierr = PetscCalloc1(mat->cmap->N+1,&tmp);CHKERRQ(ierr); 1852 ierr = PetscMalloc1(mat->cmap->N+1,&tmp2);CHKERRQ(ierr); 1853 *norm = 0.0; 1854 v = amat->a; jj = amat->j; 1855 for (j=0; j<amat->nz; j++) { 1856 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1857 } 1858 v = bmat->a; jj = bmat->j; 1859 for (j=0; j<bmat->nz; j++) { 1860 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1861 } 1862 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1863 for (j=0; j<mat->cmap->N; j++) { 1864 if (tmp2[j] > *norm) *norm = tmp2[j]; 1865 } 1866 ierr = PetscFree(tmp);CHKERRQ(ierr); 1867 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1868 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1869 } else if (type == NORM_INFINITY) { /* max row norm */ 1870 PetscReal ntemp = 0.0; 1871 for (j=0; j<aij->A->rmap->n; j++) { 1872 v = amat->a + amat->i[j]; 1873 sum = 0.0; 1874 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1875 sum += PetscAbsScalar(*v); v++; 1876 } 1877 v = bmat->a + bmat->i[j]; 1878 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1879 sum += PetscAbsScalar(*v); v++; 1880 } 1881 if (sum > ntemp) ntemp = sum; 1882 } 1883 ierr = MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1884 ierr = PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));CHKERRQ(ierr); 1885 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1886 } 1887 PetscFunctionReturn(0); 1888 } 1889 1890 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1891 { 1892 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1893 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1894 PetscErrorCode ierr; 1895 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1896 PetscInt cstart = A->cmap->rstart,ncol; 1897 Mat B; 1898 MatScalar *array; 1899 1900 PetscFunctionBegin; 1901 if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1902 1903 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1904 ai = Aloc->i; aj = Aloc->j; 1905 bi = Bloc->i; bj = Bloc->j; 1906 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1907 PetscInt *d_nnz,*g_nnz,*o_nnz; 1908 PetscSFNode *oloc; 1909 PETSC_UNUSED PetscSF sf; 1910 1911 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1912 /* compute d_nnz for preallocation */ 1913 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1914 for (i=0; i<ai[ma]; i++) { 1915 d_nnz[aj[i]]++; 1916 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1917 } 1918 /* compute local off-diagonal contributions */ 1919 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1920 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1921 /* map those to global */ 1922 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1923 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1924 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1925 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1926 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1927 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1928 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1929 1930 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1931 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1932 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1933 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1934 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1935 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 1936 } else { 1937 B = *matout; 1938 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 1939 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1940 } 1941 1942 /* copy over the A part */ 1943 array = Aloc->a; 1944 row = A->rmap->rstart; 1945 for (i=0; i<ma; i++) { 1946 ncol = ai[i+1]-ai[i]; 1947 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1948 row++; 1949 array += ncol; aj += ncol; 1950 } 1951 aj = Aloc->j; 1952 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1953 1954 /* copy over the B part */ 1955 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 1956 array = Bloc->a; 1957 row = A->rmap->rstart; 1958 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 1959 cols_tmp = cols; 1960 for (i=0; i<mb; i++) { 1961 ncol = bi[i+1]-bi[i]; 1962 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1963 row++; 1964 array += ncol; cols_tmp += ncol; 1965 } 1966 ierr = PetscFree(cols);CHKERRQ(ierr); 1967 1968 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1969 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1970 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 1971 *matout = B; 1972 } else { 1973 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1974 } 1975 PetscFunctionReturn(0); 1976 } 1977 1978 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1979 { 1980 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1981 Mat a = aij->A,b = aij->B; 1982 PetscErrorCode ierr; 1983 PetscInt s1,s2,s3; 1984 1985 PetscFunctionBegin; 1986 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1987 if (rr) { 1988 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1989 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1990 /* Overlap communication with computation. */ 1991 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1992 } 1993 if (ll) { 1994 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1995 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1996 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1997 } 1998 /* scale the diagonal block */ 1999 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2000 2001 if (rr) { 2002 /* Do a scatter end and then right scale the off-diagonal block */ 2003 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2004 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2005 } 2006 PetscFunctionReturn(0); 2007 } 2008 2009 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2010 { 2011 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2012 PetscErrorCode ierr; 2013 2014 PetscFunctionBegin; 2015 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2016 PetscFunctionReturn(0); 2017 } 2018 2019 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2020 { 2021 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2022 Mat a,b,c,d; 2023 PetscBool flg; 2024 PetscErrorCode ierr; 2025 2026 PetscFunctionBegin; 2027 a = matA->A; b = matA->B; 2028 c = matB->A; d = matB->B; 2029 2030 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2031 if (flg) { 2032 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2033 } 2034 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2035 PetscFunctionReturn(0); 2036 } 2037 2038 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2039 { 2040 PetscErrorCode ierr; 2041 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2042 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2043 2044 PetscFunctionBegin; 2045 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2046 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2047 /* because of the column compression in the off-processor part of the matrix a->B, 2048 the number of columns in a->B and b->B may be different, hence we cannot call 2049 the MatCopy() directly on the two parts. If need be, we can provide a more 2050 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2051 then copying the submatrices */ 2052 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2053 } else { 2054 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2055 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2056 } 2057 PetscFunctionReturn(0); 2058 } 2059 2060 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2061 { 2062 PetscErrorCode ierr; 2063 2064 PetscFunctionBegin; 2065 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2066 PetscFunctionReturn(0); 2067 } 2068 2069 /* 2070 Computes the number of nonzeros per row needed for preallocation when X and Y 2071 have different nonzero structure. 2072 */ 2073 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) 2074 { 2075 PetscInt i,j,k,nzx,nzy; 2076 2077 PetscFunctionBegin; 2078 /* Set the number of nonzeros in the new matrix */ 2079 for (i=0; i<m; i++) { 2080 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2081 nzx = xi[i+1] - xi[i]; 2082 nzy = yi[i+1] - yi[i]; 2083 nnz[i] = 0; 2084 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2085 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2086 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2087 nnz[i]++; 2088 } 2089 for (; k<nzy; k++) nnz[i]++; 2090 } 2091 PetscFunctionReturn(0); 2092 } 2093 2094 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2095 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2096 { 2097 PetscErrorCode ierr; 2098 PetscInt m = Y->rmap->N; 2099 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2100 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2101 2102 PetscFunctionBegin; 2103 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2104 PetscFunctionReturn(0); 2105 } 2106 2107 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2108 { 2109 PetscErrorCode ierr; 2110 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2111 PetscBLASInt bnz,one=1; 2112 Mat_SeqAIJ *x,*y; 2113 2114 PetscFunctionBegin; 2115 if (str == SAME_NONZERO_PATTERN) { 2116 PetscScalar alpha = a; 2117 x = (Mat_SeqAIJ*)xx->A->data; 2118 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2119 y = (Mat_SeqAIJ*)yy->A->data; 2120 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2121 x = (Mat_SeqAIJ*)xx->B->data; 2122 y = (Mat_SeqAIJ*)yy->B->data; 2123 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2124 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2125 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2126 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2127 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2128 } else { 2129 Mat B; 2130 PetscInt *nnz_d,*nnz_o; 2131 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2132 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2133 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2134 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2135 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2136 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2137 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2138 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2139 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2140 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2141 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2142 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2143 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2144 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2145 } 2146 PetscFunctionReturn(0); 2147 } 2148 2149 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2150 2151 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2152 { 2153 #if defined(PETSC_USE_COMPLEX) 2154 PetscErrorCode ierr; 2155 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2156 2157 PetscFunctionBegin; 2158 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2159 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2160 #else 2161 PetscFunctionBegin; 2162 #endif 2163 PetscFunctionReturn(0); 2164 } 2165 2166 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2167 { 2168 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2169 PetscErrorCode ierr; 2170 2171 PetscFunctionBegin; 2172 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2173 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2174 PetscFunctionReturn(0); 2175 } 2176 2177 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2178 { 2179 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2180 PetscErrorCode ierr; 2181 2182 PetscFunctionBegin; 2183 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2184 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2185 PetscFunctionReturn(0); 2186 } 2187 2188 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2189 { 2190 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2191 PetscErrorCode ierr; 2192 PetscInt i,*idxb = 0; 2193 PetscScalar *va,*vb; 2194 Vec vtmp; 2195 2196 PetscFunctionBegin; 2197 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2198 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2199 if (idx) { 2200 for (i=0; i<A->rmap->n; i++) { 2201 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2202 } 2203 } 2204 2205 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2206 if (idx) { 2207 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2208 } 2209 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2210 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2211 2212 for (i=0; i<A->rmap->n; i++) { 2213 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2214 va[i] = vb[i]; 2215 if (idx) idx[i] = a->garray[idxb[i]]; 2216 } 2217 } 2218 2219 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2220 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2221 ierr = PetscFree(idxb);CHKERRQ(ierr); 2222 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2223 PetscFunctionReturn(0); 2224 } 2225 2226 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2227 { 2228 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2229 PetscErrorCode ierr; 2230 PetscInt i,*idxb = 0; 2231 PetscScalar *va,*vb; 2232 Vec vtmp; 2233 2234 PetscFunctionBegin; 2235 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2236 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2237 if (idx) { 2238 for (i=0; i<A->cmap->n; i++) { 2239 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2240 } 2241 } 2242 2243 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2244 if (idx) { 2245 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2246 } 2247 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2248 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2249 2250 for (i=0; i<A->rmap->n; i++) { 2251 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2252 va[i] = vb[i]; 2253 if (idx) idx[i] = a->garray[idxb[i]]; 2254 } 2255 } 2256 2257 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2258 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2259 ierr = PetscFree(idxb);CHKERRQ(ierr); 2260 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2261 PetscFunctionReturn(0); 2262 } 2263 2264 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2265 { 2266 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2267 PetscInt n = A->rmap->n; 2268 PetscInt cstart = A->cmap->rstart; 2269 PetscInt *cmap = mat->garray; 2270 PetscInt *diagIdx, *offdiagIdx; 2271 Vec diagV, offdiagV; 2272 PetscScalar *a, *diagA, *offdiagA; 2273 PetscInt r; 2274 PetscErrorCode ierr; 2275 2276 PetscFunctionBegin; 2277 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2278 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2279 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2280 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2281 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2282 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2283 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2284 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2285 for (r = 0; r < n; ++r) { 2286 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2287 a[r] = diagA[r]; 2288 idx[r] = cstart + diagIdx[r]; 2289 } else { 2290 a[r] = offdiagA[r]; 2291 idx[r] = cmap[offdiagIdx[r]]; 2292 } 2293 } 2294 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2295 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2296 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2297 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2298 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2299 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2300 PetscFunctionReturn(0); 2301 } 2302 2303 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2304 { 2305 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2306 PetscInt n = A->rmap->n; 2307 PetscInt cstart = A->cmap->rstart; 2308 PetscInt *cmap = mat->garray; 2309 PetscInt *diagIdx, *offdiagIdx; 2310 Vec diagV, offdiagV; 2311 PetscScalar *a, *diagA, *offdiagA; 2312 PetscInt r; 2313 PetscErrorCode ierr; 2314 2315 PetscFunctionBegin; 2316 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2317 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2318 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2319 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2320 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2321 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2322 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2323 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2324 for (r = 0; r < n; ++r) { 2325 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2326 a[r] = diagA[r]; 2327 idx[r] = cstart + diagIdx[r]; 2328 } else { 2329 a[r] = offdiagA[r]; 2330 idx[r] = cmap[offdiagIdx[r]]; 2331 } 2332 } 2333 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2334 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2335 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2336 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2337 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2338 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2339 PetscFunctionReturn(0); 2340 } 2341 2342 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2343 { 2344 PetscErrorCode ierr; 2345 Mat *dummy; 2346 2347 PetscFunctionBegin; 2348 ierr = MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2349 *newmat = *dummy; 2350 ierr = PetscFree(dummy);CHKERRQ(ierr); 2351 PetscFunctionReturn(0); 2352 } 2353 2354 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2355 { 2356 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2357 PetscErrorCode ierr; 2358 2359 PetscFunctionBegin; 2360 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2361 A->factorerrortype = a->A->factorerrortype; 2362 PetscFunctionReturn(0); 2363 } 2364 2365 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2366 { 2367 PetscErrorCode ierr; 2368 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2369 2370 PetscFunctionBegin; 2371 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2372 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2373 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2374 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2375 PetscFunctionReturn(0); 2376 } 2377 2378 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc) 2379 { 2380 PetscFunctionBegin; 2381 if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable; 2382 else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ; 2383 PetscFunctionReturn(0); 2384 } 2385 2386 /*@ 2387 MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap 2388 2389 Collective on Mat 2390 2391 Input Parameters: 2392 + A - the matrix 2393 - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm) 2394 2395 Level: advanced 2396 2397 @*/ 2398 PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc) 2399 { 2400 PetscErrorCode ierr; 2401 2402 PetscFunctionBegin; 2403 ierr = PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));CHKERRQ(ierr); 2404 PetscFunctionReturn(0); 2405 } 2406 2407 PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A) 2408 { 2409 PetscErrorCode ierr; 2410 PetscBool sc = PETSC_FALSE,flg; 2411 2412 PetscFunctionBegin; 2413 ierr = PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");CHKERRQ(ierr); 2414 ierr = PetscObjectOptionsBegin((PetscObject)A); 2415 if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE; 2416 ierr = PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);CHKERRQ(ierr); 2417 if (flg) { 2418 ierr = MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);CHKERRQ(ierr); 2419 } 2420 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2421 PetscFunctionReturn(0); 2422 } 2423 2424 PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a) 2425 { 2426 PetscErrorCode ierr; 2427 Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data; 2428 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data; 2429 2430 PetscFunctionBegin; 2431 if (!Y->preallocated) { 2432 ierr = MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);CHKERRQ(ierr); 2433 } else if (!aij->nz) { 2434 PetscInt nonew = aij->nonew; 2435 ierr = MatSeqAIJSetPreallocation(maij->A,1,NULL);CHKERRQ(ierr); 2436 aij->nonew = nonew; 2437 } 2438 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2439 PetscFunctionReturn(0); 2440 } 2441 2442 PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d) 2443 { 2444 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2445 PetscErrorCode ierr; 2446 2447 PetscFunctionBegin; 2448 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2449 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2450 if (d) { 2451 PetscInt rstart; 2452 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2453 *d += rstart; 2454 2455 } 2456 PetscFunctionReturn(0); 2457 } 2458 2459 2460 /* -------------------------------------------------------------------*/ 2461 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2462 MatGetRow_MPIAIJ, 2463 MatRestoreRow_MPIAIJ, 2464 MatMult_MPIAIJ, 2465 /* 4*/ MatMultAdd_MPIAIJ, 2466 MatMultTranspose_MPIAIJ, 2467 MatMultTransposeAdd_MPIAIJ, 2468 0, 2469 0, 2470 0, 2471 /*10*/ 0, 2472 0, 2473 0, 2474 MatSOR_MPIAIJ, 2475 MatTranspose_MPIAIJ, 2476 /*15*/ MatGetInfo_MPIAIJ, 2477 MatEqual_MPIAIJ, 2478 MatGetDiagonal_MPIAIJ, 2479 MatDiagonalScale_MPIAIJ, 2480 MatNorm_MPIAIJ, 2481 /*20*/ MatAssemblyBegin_MPIAIJ, 2482 MatAssemblyEnd_MPIAIJ, 2483 MatSetOption_MPIAIJ, 2484 MatZeroEntries_MPIAIJ, 2485 /*24*/ MatZeroRows_MPIAIJ, 2486 0, 2487 0, 2488 0, 2489 0, 2490 /*29*/ MatSetUp_MPIAIJ, 2491 0, 2492 0, 2493 MatGetDiagonalBlock_MPIAIJ, 2494 0, 2495 /*34*/ MatDuplicate_MPIAIJ, 2496 0, 2497 0, 2498 0, 2499 0, 2500 /*39*/ MatAXPY_MPIAIJ, 2501 MatCreateSubMatrices_MPIAIJ, 2502 MatIncreaseOverlap_MPIAIJ, 2503 MatGetValues_MPIAIJ, 2504 MatCopy_MPIAIJ, 2505 /*44*/ MatGetRowMax_MPIAIJ, 2506 MatScale_MPIAIJ, 2507 MatShift_MPIAIJ, 2508 MatDiagonalSet_MPIAIJ, 2509 MatZeroRowsColumns_MPIAIJ, 2510 /*49*/ MatSetRandom_MPIAIJ, 2511 0, 2512 0, 2513 0, 2514 0, 2515 /*54*/ MatFDColoringCreate_MPIXAIJ, 2516 0, 2517 MatSetUnfactored_MPIAIJ, 2518 MatPermute_MPIAIJ, 2519 0, 2520 /*59*/ MatCreateSubMatrix_MPIAIJ, 2521 MatDestroy_MPIAIJ, 2522 MatView_MPIAIJ, 2523 0, 2524 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2525 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2526 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2527 0, 2528 0, 2529 0, 2530 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2531 MatGetRowMinAbs_MPIAIJ, 2532 0, 2533 0, 2534 0, 2535 0, 2536 /*75*/ MatFDColoringApply_AIJ, 2537 MatSetFromOptions_MPIAIJ, 2538 0, 2539 0, 2540 MatFindZeroDiagonals_MPIAIJ, 2541 /*80*/ 0, 2542 0, 2543 0, 2544 /*83*/ MatLoad_MPIAIJ, 2545 0, 2546 0, 2547 0, 2548 0, 2549 0, 2550 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2551 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2552 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2553 MatPtAP_MPIAIJ_MPIAIJ, 2554 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2555 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2556 0, 2557 0, 2558 0, 2559 0, 2560 /*99*/ 0, 2561 0, 2562 0, 2563 MatConjugate_MPIAIJ, 2564 0, 2565 /*104*/MatSetValuesRow_MPIAIJ, 2566 MatRealPart_MPIAIJ, 2567 MatImaginaryPart_MPIAIJ, 2568 0, 2569 0, 2570 /*109*/0, 2571 0, 2572 MatGetRowMin_MPIAIJ, 2573 0, 2574 MatMissingDiagonal_MPIAIJ, 2575 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2576 0, 2577 MatGetGhosts_MPIAIJ, 2578 0, 2579 0, 2580 /*119*/0, 2581 0, 2582 0, 2583 0, 2584 MatGetMultiProcBlock_MPIAIJ, 2585 /*124*/MatFindNonzeroRows_MPIAIJ, 2586 MatGetColumnNorms_MPIAIJ, 2587 MatInvertBlockDiagonal_MPIAIJ, 2588 0, 2589 MatCreateSubMatricesMPI_MPIAIJ, 2590 /*129*/0, 2591 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2592 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2593 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2594 0, 2595 /*134*/0, 2596 0, 2597 0, 2598 0, 2599 0, 2600 /*139*/MatSetBlockSizes_MPIAIJ, 2601 0, 2602 0, 2603 MatFDColoringSetUp_MPIXAIJ, 2604 MatFindOffBlockDiagonalEntries_MPIAIJ, 2605 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2606 }; 2607 2608 /* ----------------------------------------------------------------------------------------*/ 2609 2610 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2611 { 2612 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2613 PetscErrorCode ierr; 2614 2615 PetscFunctionBegin; 2616 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2617 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2618 PetscFunctionReturn(0); 2619 } 2620 2621 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2622 { 2623 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2624 PetscErrorCode ierr; 2625 2626 PetscFunctionBegin; 2627 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2628 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2629 PetscFunctionReturn(0); 2630 } 2631 2632 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2633 { 2634 Mat_MPIAIJ *b; 2635 PetscErrorCode ierr; 2636 2637 PetscFunctionBegin; 2638 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2639 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2640 b = (Mat_MPIAIJ*)B->data; 2641 2642 #if defined(PETSC_USE_CTABLE) 2643 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2644 #else 2645 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2646 #endif 2647 ierr = PetscFree(b->garray);CHKERRQ(ierr); 2648 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 2649 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 2650 2651 /* Because the B will have been resized we simply destroy it and create a new one each time */ 2652 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 2653 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2654 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2655 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2656 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2657 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2658 2659 if (!B->preallocated) { 2660 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2661 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2662 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2663 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2664 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2665 } 2666 2667 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2668 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2669 B->preallocated = PETSC_TRUE; 2670 B->was_assembled = PETSC_FALSE; 2671 B->assembled = PETSC_FALSE;; 2672 PetscFunctionReturn(0); 2673 } 2674 2675 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2676 { 2677 Mat mat; 2678 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2679 PetscErrorCode ierr; 2680 2681 PetscFunctionBegin; 2682 *newmat = 0; 2683 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2684 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2685 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2686 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2687 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2688 a = (Mat_MPIAIJ*)mat->data; 2689 2690 mat->factortype = matin->factortype; 2691 mat->assembled = PETSC_TRUE; 2692 mat->insertmode = NOT_SET_VALUES; 2693 mat->preallocated = PETSC_TRUE; 2694 2695 a->size = oldmat->size; 2696 a->rank = oldmat->rank; 2697 a->donotstash = oldmat->donotstash; 2698 a->roworiented = oldmat->roworiented; 2699 a->rowindices = 0; 2700 a->rowvalues = 0; 2701 a->getrowactive = PETSC_FALSE; 2702 2703 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2704 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2705 2706 if (oldmat->colmap) { 2707 #if defined(PETSC_USE_CTABLE) 2708 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2709 #else 2710 ierr = PetscMalloc1(mat->cmap->N,&a->colmap);CHKERRQ(ierr); 2711 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2712 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2713 #endif 2714 } else a->colmap = 0; 2715 if (oldmat->garray) { 2716 PetscInt len; 2717 len = oldmat->B->cmap->n; 2718 ierr = PetscMalloc1(len+1,&a->garray);CHKERRQ(ierr); 2719 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2720 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2721 } else a->garray = 0; 2722 2723 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2724 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2725 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2726 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2727 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2729 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2730 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2731 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2732 *newmat = mat; 2733 PetscFunctionReturn(0); 2734 } 2735 2736 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2737 { 2738 PetscScalar *vals,*svals; 2739 MPI_Comm comm; 2740 PetscErrorCode ierr; 2741 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2742 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2743 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2744 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2745 PetscInt cend,cstart,n,*rowners; 2746 int fd; 2747 PetscInt bs = newMat->rmap->bs; 2748 2749 PetscFunctionBegin; 2750 /* force binary viewer to load .info file if it has not yet done so */ 2751 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 2752 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2753 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2754 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2755 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2756 if (!rank) { 2757 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2758 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2759 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ"); 2760 } 2761 2762 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");CHKERRQ(ierr); 2763 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2764 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2765 if (bs < 0) bs = 1; 2766 2767 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2768 M = header[1]; N = header[2]; 2769 2770 /* If global sizes are set, check if they are consistent with that given in the file */ 2771 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); 2772 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); 2773 2774 /* determine ownership of all (block) rows */ 2775 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2776 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2777 else m = newMat->rmap->n; /* Set by user */ 2778 2779 ierr = PetscMalloc1(size+1,&rowners);CHKERRQ(ierr); 2780 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2781 2782 /* First process needs enough room for process with most rows */ 2783 if (!rank) { 2784 mmax = rowners[1]; 2785 for (i=2; i<=size; i++) { 2786 mmax = PetscMax(mmax, rowners[i]); 2787 } 2788 } else mmax = -1; /* unused, but compilers complain */ 2789 2790 rowners[0] = 0; 2791 for (i=2; i<=size; i++) { 2792 rowners[i] += rowners[i-1]; 2793 } 2794 rstart = rowners[rank]; 2795 rend = rowners[rank+1]; 2796 2797 /* distribute row lengths to all processors */ 2798 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2799 if (!rank) { 2800 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2801 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2802 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2803 for (j=0; j<m; j++) { 2804 procsnz[0] += ourlens[j]; 2805 } 2806 for (i=1; i<size; i++) { 2807 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2808 /* calculate the number of nonzeros on each processor */ 2809 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2810 procsnz[i] += rowlengths[j]; 2811 } 2812 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2813 } 2814 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2815 } else { 2816 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2817 } 2818 2819 if (!rank) { 2820 /* determine max buffer needed and allocate it */ 2821 maxnz = 0; 2822 for (i=0; i<size; i++) { 2823 maxnz = PetscMax(maxnz,procsnz[i]); 2824 } 2825 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2826 2827 /* read in my part of the matrix column indices */ 2828 nz = procsnz[0]; 2829 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2830 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2831 2832 /* read in every one elses and ship off */ 2833 for (i=1; i<size; i++) { 2834 nz = procsnz[i]; 2835 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2836 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2837 } 2838 ierr = PetscFree(cols);CHKERRQ(ierr); 2839 } else { 2840 /* determine buffer space needed for message */ 2841 nz = 0; 2842 for (i=0; i<m; i++) { 2843 nz += ourlens[i]; 2844 } 2845 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2846 2847 /* receive message of column indices*/ 2848 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2849 } 2850 2851 /* determine column ownership if matrix is not square */ 2852 if (N != M) { 2853 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 2854 else n = newMat->cmap->n; 2855 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2856 cstart = cend - n; 2857 } else { 2858 cstart = rstart; 2859 cend = rend; 2860 n = cend - cstart; 2861 } 2862 2863 /* loop over local rows, determining number of off diagonal entries */ 2864 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2865 jj = 0; 2866 for (i=0; i<m; i++) { 2867 for (j=0; j<ourlens[i]; j++) { 2868 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2869 jj++; 2870 } 2871 } 2872 2873 for (i=0; i<m; i++) { 2874 ourlens[i] -= offlens[i]; 2875 } 2876 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 2877 2878 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 2879 2880 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 2881 2882 for (i=0; i<m; i++) { 2883 ourlens[i] += offlens[i]; 2884 } 2885 2886 if (!rank) { 2887 ierr = PetscMalloc1(maxnz+1,&vals);CHKERRQ(ierr); 2888 2889 /* read in my part of the matrix numerical values */ 2890 nz = procsnz[0]; 2891 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2892 2893 /* insert into matrix */ 2894 jj = rstart; 2895 smycols = mycols; 2896 svals = vals; 2897 for (i=0; i<m; i++) { 2898 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2899 smycols += ourlens[i]; 2900 svals += ourlens[i]; 2901 jj++; 2902 } 2903 2904 /* read in other processors and ship out */ 2905 for (i=1; i<size; i++) { 2906 nz = procsnz[i]; 2907 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2908 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2909 } 2910 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2911 } else { 2912 /* receive numeric values */ 2913 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 2914 2915 /* receive message of values*/ 2916 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 2917 2918 /* insert into matrix */ 2919 jj = rstart; 2920 smycols = mycols; 2921 svals = vals; 2922 for (i=0; i<m; i++) { 2923 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2924 smycols += ourlens[i]; 2925 svals += ourlens[i]; 2926 jj++; 2927 } 2928 } 2929 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2930 ierr = PetscFree(vals);CHKERRQ(ierr); 2931 ierr = PetscFree(mycols);CHKERRQ(ierr); 2932 ierr = PetscFree(rowners);CHKERRQ(ierr); 2933 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2934 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2935 PetscFunctionReturn(0); 2936 } 2937 2938 /* Not scalable because of ISAllGather() unless getting all columns. */ 2939 PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq) 2940 { 2941 PetscErrorCode ierr; 2942 IS iscol_local; 2943 PetscBool isstride; 2944 PetscMPIInt lisstride=0,gisstride; 2945 2946 PetscFunctionBegin; 2947 /* check if we are grabbing all columns*/ 2948 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);CHKERRQ(ierr); 2949 2950 if (isstride) { 2951 PetscInt start,len,mstart,mlen; 2952 ierr = ISStrideGetInfo(iscol,&start,NULL);CHKERRQ(ierr); 2953 ierr = ISGetLocalSize(iscol,&len);CHKERRQ(ierr); 2954 ierr = MatGetOwnershipRangeColumn(mat,&mstart,&mlen);CHKERRQ(ierr); 2955 if (mstart == start && mlen-mstart == len) lisstride = 1; 2956 } 2957 2958 ierr = MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2959 if (gisstride) { 2960 PetscInt N; 2961 ierr = MatGetSize(mat,NULL,&N);CHKERRQ(ierr); 2962 ierr = ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);CHKERRQ(ierr); 2963 ierr = ISSetIdentity(iscol_local);CHKERRQ(ierr); 2964 ierr = PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");CHKERRQ(ierr); 2965 } else { 2966 PetscInt cbs; 2967 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2968 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2969 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 2970 } 2971 2972 *isseq = iscol_local; 2973 PetscFunctionReturn(0); 2974 } 2975 2976 /* 2977 Used for avoiding ISAllGather() and global size of iscol_local (see MatCreateSubMatrix_MPIAIJ_nonscalable) 2978 2979 Input Parameters: 2980 mat - matrix 2981 iscol - parallel column index set; its local indices are a subset of local columns of mat, 2982 i.e., mat->cstart <= iscol[i] < mat->cend 2983 Output Parameter: 2984 iscol_sub - sequential column index set, a subset of iscol 2985 iscmap - column map; iscmap[i] indicates global location of iscol_sub[i] in iscol 2986 */ 2987 PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,IS *isgarray) 2988 { 2989 PetscErrorCode ierr; 2990 Vec x,cmap; 2991 const PetscInt *is_idx; 2992 PetscScalar *xarray,*cmaparray; 2993 PetscInt ncols,isstart,*idx,*camp,count,m,rstart; 2994 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 2995 Mat B=a->B; 2996 Vec lvec=a->lvec,lcmap; 2997 PetscInt i,cstart,cend,Bn=B->cmap->N; 2998 MPI_Comm comm; 2999 3000 PetscFunctionBegin; 3001 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3002 PetscMPIInt rank; 3003 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3004 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 3005 3006 /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */ 3007 ierr = MatCreateVecs(mat,&x,NULL);CHKERRQ(ierr); 3008 ierr = VecDuplicate(x,&cmap);CHKERRQ(ierr); 3009 ierr = VecSet(x,-1.0);CHKERRQ(ierr); 3010 3011 /* get start indices */ 3012 ierr = MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3013 isstart -= ncols; 3014 ierr = MatGetOwnershipRangeColumn(mat,&cstart,&cend);CHKERRQ(ierr); 3015 3016 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3017 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 3018 ierr = VecGetArray(cmap,&cmaparray);CHKERRQ(ierr); 3019 ierr = PetscMalloc1(ncols,&idx);CHKERRQ(ierr); 3020 for (i=0; i<ncols; i++) { 3021 xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i]; 3022 cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */ 3023 3024 idx[i] = is_idx[i]-cstart; 3025 } 3026 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 3027 ierr = VecRestoreArray(cmap,&cmaparray);CHKERRQ(ierr); 3028 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3029 3030 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_COPY_VALUES,iscol_d);CHKERRQ(ierr); 3031 ierr = ISGetBlockSize(iscol,&i);CHKERRQ(ierr); 3032 ierr = ISSetBlockSize(*iscol_d,i);CHKERRQ(ierr); 3033 ierr = PetscFree(idx);CHKERRQ(ierr); 3034 3035 ierr = ISGetLocalSize(isrow,&m);CHKERRQ(ierr); 3036 rstart = mat->rmap->rstart; 3037 ierr = PetscMalloc1(m,&idx);CHKERRQ(ierr); 3038 ierr = ISGetIndices(isrow,&is_idx);CHKERRQ(ierr); 3039 for (i=0; i<m; i++) { 3040 idx[i] = is_idx[i]-rstart; 3041 } 3042 ierr = ISRestoreIndices(isrow,&is_idx);CHKERRQ(ierr); 3043 3044 ierr = ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_COPY_VALUES,isrow_d);CHKERRQ(ierr); 3045 ierr = ISGetBlockSize(isrow,&i);CHKERRQ(ierr); 3046 ierr = ISSetBlockSize(*isrow_d,i);CHKERRQ(ierr); 3047 ierr = PetscFree(idx);CHKERRQ(ierr); 3048 3049 /* (2) scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */ 3050 ierr = VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3051 3052 ierr = VecDuplicate(lvec,&lcmap);CHKERRQ(ierr); 3053 3054 ierr = VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3055 ierr = VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3056 3057 count = ncols + Bn; 3058 ierr = PetscMalloc2(count,&idx,count,&camp);CHKERRQ(ierr); 3059 3060 ierr = VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 3061 3062 /* (3) create scalable iscol_sub (a subset of iscol) and iscmap */ 3063 /* local column indices */ 3064 ierr = ISGetIndices(iscol,&is_idx);CHKERRQ(ierr); 3065 for (i=0; i<ncols; i++) { 3066 idx[i] = is_idx[i]; 3067 camp[i] = i + isstart; /* global index of iscol = column index in submat */ 3068 } 3069 ierr = ISRestoreIndices(iscol,&is_idx);CHKERRQ(ierr); 3070 count = ncols; 3071 3072 /* off-process column indices */ 3073 PetscInt *idx1,*cmap1,count1=0; 3074 ierr = PetscMalloc2(Bn,&idx1,Bn,&cmap1);CHKERRQ(ierr); 3075 3076 ierr = VecGetArray(lvec,&xarray);CHKERRQ(ierr); 3077 ierr = VecGetArray(lcmap,&cmaparray);CHKERRQ(ierr); 3078 for (i=0; i<Bn; i++) { 3079 if (PetscRealPart(xarray[i]) > -1.0) { 3080 idx1[count1] = i; /* local column index in off-diagonal part B */ 3081 cmap1[count1++] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */ 3082 3083 idx[count] = (PetscInt)PetscRealPart(xarray[i]); 3084 camp[count++] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */ 3085 } 3086 } 3087 ierr = VecRestoreArray(lvec,&xarray);CHKERRQ(ierr); 3088 ierr = VecRestoreArray(lcmap,&cmaparray);CHKERRQ(ierr); 3089 3090 ierr = PetscSortIntWithArray(count,camp,idx);CHKERRQ(ierr); 3091 3092 ierr = ISCreateGeneral(PETSC_COMM_SELF,count1,idx1,PETSC_COPY_VALUES,iscol_o);CHKERRQ(ierr); 3093 ierr = ISCreateGeneral(PETSC_COMM_SELF,count1,cmap1,PETSC_COPY_VALUES,isgarray);CHKERRQ(ierr); 3094 ierr = ISGetBlockSize(iscol,&i);CHKERRQ(ierr); 3095 ierr = ISSetBlockSize(*iscol_o,i);CHKERRQ(ierr); 3096 ierr = PetscFree2(idx1,cmap1);CHKERRQ(ierr); 3097 3098 ierr = PetscFree2(idx,camp);CHKERRQ(ierr); 3099 ierr = VecDestroy(&x);CHKERRQ(ierr); 3100 ierr = VecDestroy(&cmap);CHKERRQ(ierr); 3101 ierr = VecDestroy(&lcmap);CHKERRQ(ierr); 3102 PetscFunctionReturn(0); 3103 } 3104 3105 /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */ 3106 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat) 3107 { 3108 PetscErrorCode ierr; 3109 Mat_MPIAIJ *a = (Mat_MPIAIJ*)mat->data,*asub; 3110 Mat M = NULL; 3111 MPI_Comm comm; 3112 IS iscol_d,isrow_d,iscol_o; 3113 Mat Asub = NULL,Bsub = NULL; 3114 PetscInt n; 3115 3116 PetscFunctionBegin; 3117 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3118 PetscMPIInt rank; 3119 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3120 3121 if (call == MAT_REUSE_MATRIX) { 3122 if (!rank) printf(" _SameRowColDist reuse ...\n"); 3123 3124 /* Retrieve isrow_d, iscol_d and iscol_o from submat */ 3125 ierr = PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);CHKERRQ(ierr); 3126 if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse"); 3127 3128 ierr = PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);CHKERRQ(ierr); 3129 if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse"); 3130 3131 ierr = PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);CHKERRQ(ierr); 3132 if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse"); 3133 3134 /* Update diagonal and off-diagonal portions of submat */ 3135 asub = (Mat_MPIAIJ*)(*submat)->data; 3136 ierr = MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);CHKERRQ(ierr); 3137 ierr = ISGetLocalSize(iscol_o,&n);CHKERRQ(ierr); 3138 if (n) { 3139 ierr = MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);CHKERRQ(ierr); 3140 } 3141 ierr = MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3142 ierr = MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3143 3144 } else { /* call == MAT_INITIAL_MATRIX) */ 3145 IS isgarray; 3146 const PetscInt *garray1; 3147 PetscInt BsubN; 3148 3149 /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */ 3150 ierr = ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&isgarray);CHKERRQ(ierr); 3151 3152 /* Create local submatrices Asub and Bsub */ 3153 ierr = MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);CHKERRQ(ierr); 3154 ierr = MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);CHKERRQ(ierr); 3155 3156 ierr = ISGetIndices(isgarray,&garray1);CHKERRQ(ierr); 3157 ierr = MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray1,&M);CHKERRQ(ierr); 3158 ierr = ISRestoreIndices(isgarray,&garray1);CHKERRQ(ierr); 3159 3160 /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */ 3161 asub = (Mat_MPIAIJ*)M->data; 3162 3163 ierr = ISGetLocalSize(isgarray,&BsubN);CHKERRQ(ierr); 3164 n = asub->B->cmap->N; 3165 if (BsubN > n) { 3166 /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */ 3167 const PetscInt *idx; 3168 PetscInt i,j,*idx_new,*garray = asub->garray; //idx_new[n], 3169 printf("[%d] BsubN %d != Bn %d, update iscol_o \n",rank,BsubN,n); 3170 3171 ierr = PetscMalloc1(n,&idx_new);CHKERRQ(ierr); 3172 j = 0; 3173 ierr = ISGetIndices(iscol_o,&idx);CHKERRQ(ierr); 3174 for (i=0; i<n; i++) { 3175 if (j >= BsubN) break; 3176 while (garray[i] > garray1[j]) j++; 3177 3178 if (garray[i] == garray1[j]) { 3179 idx_new[i] = idx[j++]; 3180 } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"garray[%D]=%D cannot < garray1[%D]=%D",i,garray[i],j,garray1[j]); 3181 } 3182 ierr = ISRestoreIndices(iscol_o,&idx);CHKERRQ(ierr); 3183 3184 ierr = ISDestroy(&iscol_o);CHKERRQ(ierr); 3185 ierr = ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);CHKERRQ(ierr); 3186 3187 } else if (BsubN < n) { 3188 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N); 3189 } 3190 3191 ierr = ISDestroy(&isgarray);CHKERRQ(ierr); 3192 *submat = M; 3193 3194 /* Save isrow_d, iscol_d and iscol_o used in processor for next request */ 3195 ierr = PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);CHKERRQ(ierr); 3196 ierr = ISDestroy(&isrow_d);CHKERRQ(ierr); 3197 3198 ierr = PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);CHKERRQ(ierr); 3199 ierr = ISDestroy(&iscol_d);CHKERRQ(ierr); 3200 3201 ierr = PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);CHKERRQ(ierr); 3202 ierr = ISDestroy(&iscol_o);CHKERRQ(ierr); 3203 } 3204 PetscFunctionReturn(0); 3205 } 3206 3207 PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3208 { 3209 PetscErrorCode ierr; 3210 IS iscol_local,isrow_d; 3211 PetscInt csize; 3212 PetscInt n,i,j,start,end; 3213 PetscBool sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2]; 3214 MPI_Comm comm; 3215 3216 PetscFunctionBegin; 3217 /* If isrow has same processor distribution as mat, 3218 call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */ 3219 if (call == MAT_REUSE_MATRIX) { 3220 ierr = PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);CHKERRQ(ierr); 3221 if (isrow_d) { 3222 sameRowDist = PETSC_TRUE; 3223 tsameDist[1] = PETSC_TRUE; /* sameColDist */ 3224 } else { 3225 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3226 if (iscol_local) { 3227 sameRowDist = PETSC_TRUE; 3228 tsameDist[1] = PETSC_FALSE; /* !sameColDist */ 3229 } 3230 } 3231 } else { 3232 /* Check if isrow has same processor distribution as mat */ 3233 sameDist[0] = PETSC_FALSE; 3234 ierr = ISGetLocalSize(isrow,&n);CHKERRQ(ierr); 3235 if (!n) { 3236 sameDist[0] = PETSC_TRUE; 3237 } else { 3238 ierr = ISGetMinMax(isrow,&i,&j);CHKERRQ(ierr); 3239 ierr = MatGetOwnershipRange(mat,&start,&end);CHKERRQ(ierr); 3240 if (i >= start && j < end) { 3241 sameDist[0] = PETSC_TRUE; 3242 } 3243 } 3244 3245 /* Check if iscol has same processor distribution as mat */ 3246 sameDist[1] = PETSC_FALSE; 3247 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3248 if (!n) { 3249 sameDist[1] = PETSC_TRUE; 3250 } else { 3251 ierr = ISGetMinMax(iscol,&i,&j);CHKERRQ(ierr); 3252 ierr = MatGetOwnershipRangeColumn(mat,&start,&end);CHKERRQ(ierr); 3253 if (i >= start && j < end) sameDist[1] = PETSC_TRUE; 3254 } 3255 3256 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3257 ierr = MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);CHKERRQ(ierr); 3258 sameRowDist = tsameDist[0]; 3259 } 3260 3261 if (sameRowDist) { 3262 if (tsameDist[1]) { /* sameRowDist & sameColDist */ 3263 /* isrow and iscol have same processor distribution as mat */ 3264 ierr = MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3265 } else { /* sameRowDist */ 3266 /* isrow has same processor distribution as mat */ 3267 ierr = MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,call,newmat);CHKERRQ(ierr); 3268 } 3269 PetscFunctionReturn(0); 3270 } 3271 3272 /* General case: iscol -> iscol_local which has global size of iscol */ 3273 if (call == MAT_REUSE_MATRIX) { 3274 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3275 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3276 } else { 3277 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3278 } 3279 3280 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3281 ierr = MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3282 3283 if (call == MAT_INITIAL_MATRIX) { 3284 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3285 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3286 } 3287 PetscFunctionReturn(0); 3288 } 3289 3290 /*@C 3291 MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal" 3292 and "off-diagonal" part of the matrix in CSR format. 3293 3294 Collective on MPI_Comm 3295 3296 Input Parameters: 3297 + comm - MPI communicator 3298 . A - "diagonal" portion of matrix 3299 . B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine 3300 - garray - global index of B columns 3301 3302 Output Parameter: 3303 . mat - the matrix, with input A as its local diagonal matrix 3304 Level: advanced 3305 3306 Notes: 3307 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix. 3308 A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore. 3309 3310 .seealso: MatCreateMPIAIJWithSplitArrays() 3311 @*/ 3312 PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat) 3313 { 3314 PetscErrorCode ierr; 3315 Mat_MPIAIJ *maij; 3316 Mat_SeqAIJ *b=(Mat_SeqAIJ*)B->data,*bnew; 3317 PetscInt *oi=b->i,*oj=b->j,i,nz,col; 3318 PetscScalar *oa=b->a; 3319 Mat Bnew; 3320 PetscInt m,n,N; 3321 3322 PetscFunctionBegin; 3323 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3324 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 3325 if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N); 3326 if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs); 3327 if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); 3328 3329 /* Get global columns of mat */ 3330 ierr = MPIU_Allreduce(&n,&N,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 3331 3332 ierr = MatSetSizes(*mat,m,n,PETSC_DECIDE,N);CHKERRQ(ierr); 3333 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3334 ierr = MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 3335 maij = (Mat_MPIAIJ*)(*mat)->data; 3336 3337 (*mat)->preallocated = PETSC_TRUE; 3338 3339 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 3340 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 3341 3342 /* Set A as diagonal portion of *mat */ 3343 maij->A = A; 3344 3345 nz = oi[m]; 3346 for (i=0; i<nz; i++) { 3347 col = oj[i]; 3348 oj[i] = garray[col]; 3349 } 3350 3351 /* Set Bnew as off-diagonal portion of *mat */ 3352 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);CHKERRQ(ierr); 3353 bnew = (Mat_SeqAIJ*)Bnew->data; 3354 bnew->maxnz = b->maxnz; /* allocated nonzeros of B */ 3355 maij->B = Bnew; 3356 3357 if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N); 3358 3359 b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */ 3360 b->free_a = PETSC_FALSE; 3361 b->free_ij = PETSC_FALSE; 3362 ierr = MatDestroy(&B);CHKERRQ(ierr); 3363 3364 bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */ 3365 bnew->free_a = PETSC_TRUE; 3366 bnew->free_ij = PETSC_TRUE; 3367 3368 /* condense columns of maij->B */ 3369 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 3370 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3371 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3372 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 3373 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3374 PetscFunctionReturn(0); 3375 } 3376 3377 extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*); 3378 3379 PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3380 { 3381 PetscErrorCode ierr; 3382 PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs; 3383 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3384 Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data; 3385 Mat M,Msub,B=a->B; 3386 MatScalar *aa; 3387 Mat_SeqAIJ *aij; 3388 PetscInt *garray = a->garray,*colsub,Ncols; 3389 PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend; 3390 IS iscol_sub,iscmap; 3391 const PetscInt *is_idx,*cmap; 3392 PetscBool allcolumns=PETSC_FALSE; 3393 IS iscol_local=NULL; 3394 MPI_Comm comm; 3395 3396 PetscFunctionBegin; 3397 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3398 3399 if (call == MAT_REUSE_MATRIX) { 3400 ierr = PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);CHKERRQ(ierr); 3401 if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse"); 3402 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3403 3404 ierr = PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);CHKERRQ(ierr); 3405 if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse"); 3406 3407 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);CHKERRQ(ierr); 3408 if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3409 3410 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);CHKERRQ(ierr); 3411 3412 } else { /* call == MAT_INITIAL_MATRIX) */ 3413 PetscBool flg; 3414 3415 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3416 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); 3417 3418 /* (1) iscol -> nonscalable iscol_local */ 3419 ierr = ISGetSeqIS_Private(mat,iscol,&iscol_local);CHKERRQ(ierr); 3420 ierr = ISGetLocalSize(iscol_local,&n);CHKERRQ(ierr); /* local size of iscol_local = global columns of newmat */ 3421 if (n != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != Ncols %d",n,Ncols); 3422 3423 /* Check for special case: each processor gets entire matrix columns */ 3424 ierr = ISIdentity(iscol_local,&flg);CHKERRQ(ierr); 3425 if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3426 if (allcolumns) { 3427 iscol_sub = iscol_local; 3428 ierr = PetscObjectReference((PetscObject)iscol_local);CHKERRQ(ierr); 3429 ierr = ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);CHKERRQ(ierr); 3430 3431 } else { 3432 /* (2) iscol_local -> iscol_sub and iscmap */ 3433 PetscInt *idx,*cmap1,k,cbs; 3434 3435 /* implementation below requires iscol_local be sorted, it can have duplicate indices */ 3436 ierr = ISSorted(iscol_local,&flg);CHKERRQ(ierr); 3437 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unsorted iscol_local is not implemented yet"); 3438 3439 ierr = PetscMalloc1(Ncols,&idx);CHKERRQ(ierr); 3440 ierr = PetscMalloc1(Ncols,&cmap1);CHKERRQ(ierr); 3441 ierr = ISGetIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3442 count = 0; 3443 k = 0; 3444 for (i=0; i<Ncols; i++) { 3445 j = is_idx[i]; 3446 if (j >= cstart && j < cend) { 3447 /* diagonal part of mat */ 3448 idx[count] = j; 3449 cmap1[count++] = i; /* column index in submat */ 3450 } else if (Bn) { 3451 /* off-diagonal part of mat */ 3452 if (j == garray[k]) { 3453 idx[count] = j; 3454 cmap1[count++] = i; /* column index in submat */ 3455 } else if (j > garray[k]) { 3456 while (j > garray[k] && k < Bn-1) k++; 3457 if (j == garray[k]) { 3458 idx[count] = j; 3459 cmap1[count++] = i; /* column index in submat */ 3460 } 3461 } 3462 } 3463 } 3464 ierr = ISRestoreIndices(iscol_local,&is_idx);CHKERRQ(ierr); 3465 3466 ierr = ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);CHKERRQ(ierr); 3467 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3468 ierr = ISSetBlockSize(iscol_sub,cbs);CHKERRQ(ierr); 3469 3470 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);CHKERRQ(ierr); 3471 } 3472 3473 /* (3) Create sequential Msub */ 3474 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);CHKERRQ(ierr); 3475 } 3476 3477 ierr = ISGetLocalSize(iscol_sub,&count);CHKERRQ(ierr); 3478 aij = (Mat_SeqAIJ*)(Msub)->data; 3479 ii = aij->i; 3480 ierr = ISGetIndices(iscmap,&cmap);CHKERRQ(ierr); 3481 3482 /* 3483 m - number of local rows 3484 Ncols - number of columns (same on all processors) 3485 rstart - first row in new global matrix generated 3486 */ 3487 ierr = MatGetSize(Msub,&m,NULL);CHKERRQ(ierr); 3488 3489 if (call == MAT_INITIAL_MATRIX) { 3490 /* (4) Create parallel newmat */ 3491 PetscMPIInt rank,size; 3492 PetscInt csize; 3493 3494 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3495 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3496 3497 /* 3498 Determine the number of non-zeros in the diagonal and off-diagonal 3499 portions of the matrix in order to do correct preallocation 3500 */ 3501 3502 /* first get start and end of "diagonal" columns */ 3503 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3504 if (csize == PETSC_DECIDE) { 3505 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3506 if (mglobal == Ncols) { /* square matrix */ 3507 nlocal = m; 3508 } else { 3509 nlocal = Ncols/size + ((Ncols % size) > rank); 3510 } 3511 } else { 3512 nlocal = csize; 3513 } 3514 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3515 rstart = rend - nlocal; 3516 if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols); 3517 3518 /* next, compute all the lengths */ 3519 jj = aij->j; 3520 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3521 olens = dlens + m; 3522 for (i=0; i<m; i++) { 3523 jend = ii[i+1] - ii[i]; 3524 olen = 0; 3525 dlen = 0; 3526 for (j=0; j<jend; j++) { 3527 if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++; 3528 else dlen++; 3529 jj++; 3530 } 3531 olens[i] = olen; 3532 dlens[i] = dlen; 3533 } 3534 ierr = MatGetBlockSizes(Msub,&bs,&cbs);CHKERRQ(ierr); 3535 3536 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3537 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 3538 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3539 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3540 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3541 ierr = PetscFree(dlens);CHKERRQ(ierr); 3542 3543 } else { /* call == MAT_REUSE_MATRIX */ 3544 M = *newmat; 3545 ierr = MatGetLocalSize(M,&i,NULL);CHKERRQ(ierr); 3546 if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3547 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3548 /* 3549 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3550 rather than the slower MatSetValues(). 3551 */ 3552 M->was_assembled = PETSC_TRUE; 3553 M->assembled = PETSC_FALSE; 3554 } 3555 3556 /* (5) Set values of Msub to *newmat */ 3557 ierr = PetscMalloc1(count,&colsub);CHKERRQ(ierr); 3558 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 3559 3560 jj = aij->j; 3561 aa = aij->a; 3562 for (i=0; i<m; i++) { 3563 row = rstart + i; 3564 nz = ii[i+1] - ii[i]; 3565 for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]]; 3566 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);CHKERRQ(ierr); 3567 jj += nz; aa += nz; 3568 } 3569 ierr = ISRestoreIndices(iscmap,&cmap);CHKERRQ(ierr); 3570 3571 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3572 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3573 3574 ierr = PetscFree(colsub);CHKERRQ(ierr); 3575 3576 /* save Msub, iscol_sub and iscmap used in processor for next request */ 3577 if (call == MAT_INITIAL_MATRIX) { 3578 *newmat = M; 3579 ierr = PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);CHKERRQ(ierr); 3580 ierr = MatDestroy(&Msub);CHKERRQ(ierr); 3581 3582 ierr = PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);CHKERRQ(ierr); 3583 ierr = ISDestroy(&iscol_sub);CHKERRQ(ierr); 3584 3585 ierr = PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);CHKERRQ(ierr); 3586 ierr = ISDestroy(&iscmap);CHKERRQ(ierr); 3587 3588 if (iscol_local) { 3589 ierr = PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3590 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3591 } 3592 } 3593 PetscFunctionReturn(0); 3594 } 3595 3596 /* 3597 Not great since it makes two copies of the submatrix, first an SeqAIJ 3598 in local and then by concatenating the local matrices the end result. 3599 Writing it directly would be much like MatCreateSubMatrices_MPIAIJ() 3600 3601 Note: This requires a sequential iscol with all indices. 3602 */ 3603 PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3604 { 3605 PetscErrorCode ierr; 3606 PetscMPIInt rank,size; 3607 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3608 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3609 Mat M,Mreuse; 3610 MatScalar *aa,*vwork; 3611 MPI_Comm comm; 3612 Mat_SeqAIJ *aij; 3613 PetscBool colflag,allcolumns=PETSC_FALSE; 3614 3615 PetscFunctionBegin; 3616 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3617 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3618 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3619 3620 /* Check for special case: each processor gets entire matrix columns */ 3621 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3622 ierr = ISGetLocalSize(iscol,&n);CHKERRQ(ierr); 3623 if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE; 3624 3625 if (call == MAT_REUSE_MATRIX) { 3626 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3627 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3628 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3629 } else { 3630 ierr = MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);CHKERRQ(ierr); 3631 } 3632 3633 /* 3634 m - number of local rows 3635 n - number of columns (same on all processors) 3636 rstart - first row in new global matrix generated 3637 */ 3638 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3639 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3640 if (call == MAT_INITIAL_MATRIX) { 3641 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3642 ii = aij->i; 3643 jj = aij->j; 3644 3645 /* 3646 Determine the number of non-zeros in the diagonal and off-diagonal 3647 portions of the matrix in order to do correct preallocation 3648 */ 3649 3650 /* first get start and end of "diagonal" columns */ 3651 if (csize == PETSC_DECIDE) { 3652 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3653 if (mglobal == n) { /* square matrix */ 3654 nlocal = m; 3655 } else { 3656 nlocal = n/size + ((n % size) > rank); 3657 } 3658 } else { 3659 nlocal = csize; 3660 } 3661 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3662 rstart = rend - nlocal; 3663 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); 3664 3665 /* next, compute all the lengths */ 3666 ierr = PetscMalloc1(2*m+1,&dlens);CHKERRQ(ierr); 3667 olens = dlens + m; 3668 for (i=0; i<m; i++) { 3669 jend = ii[i+1] - ii[i]; 3670 olen = 0; 3671 dlen = 0; 3672 for (j=0; j<jend; j++) { 3673 if (*jj < rstart || *jj >= rend) olen++; 3674 else dlen++; 3675 jj++; 3676 } 3677 olens[i] = olen; 3678 dlens[i] = dlen; 3679 } 3680 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3681 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3682 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3683 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3684 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3685 ierr = PetscFree(dlens);CHKERRQ(ierr); 3686 } else { 3687 PetscInt ml,nl; 3688 3689 M = *newmat; 3690 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3691 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3692 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3693 /* 3694 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3695 rather than the slower MatSetValues(). 3696 */ 3697 M->was_assembled = PETSC_TRUE; 3698 M->assembled = PETSC_FALSE; 3699 } 3700 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3701 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3702 ii = aij->i; 3703 jj = aij->j; 3704 aa = aij->a; 3705 for (i=0; i<m; i++) { 3706 row = rstart + i; 3707 nz = ii[i+1] - ii[i]; 3708 cwork = jj; jj += nz; 3709 vwork = aa; aa += nz; 3710 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3711 } 3712 3713 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3714 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3715 *newmat = M; 3716 3717 /* save submatrix used in processor for next request */ 3718 if (call == MAT_INITIAL_MATRIX) { 3719 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3720 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3721 } 3722 PetscFunctionReturn(0); 3723 } 3724 3725 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3726 { 3727 PetscInt m,cstart, cend,j,nnz,i,d; 3728 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3729 const PetscInt *JJ; 3730 PetscScalar *values; 3731 PetscErrorCode ierr; 3732 PetscBool nooffprocentries; 3733 3734 PetscFunctionBegin; 3735 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3736 3737 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3738 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3739 m = B->rmap->n; 3740 cstart = B->cmap->rstart; 3741 cend = B->cmap->rend; 3742 rstart = B->rmap->rstart; 3743 3744 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3745 3746 #if defined(PETSC_USE_DEBUGGING) 3747 for (i=0; i<m; i++) { 3748 nnz = Ii[i+1]- Ii[i]; 3749 JJ = J + Ii[i]; 3750 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3751 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3752 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); 3753 } 3754 #endif 3755 3756 for (i=0; i<m; i++) { 3757 nnz = Ii[i+1]- Ii[i]; 3758 JJ = J + Ii[i]; 3759 nnz_max = PetscMax(nnz_max,nnz); 3760 d = 0; 3761 for (j=0; j<nnz; j++) { 3762 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3763 } 3764 d_nnz[i] = d; 3765 o_nnz[i] = nnz - d; 3766 } 3767 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3768 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3769 3770 if (v) values = (PetscScalar*)v; 3771 else { 3772 ierr = PetscCalloc1(nnz_max+1,&values);CHKERRQ(ierr); 3773 } 3774 3775 for (i=0; i<m; i++) { 3776 ii = i + rstart; 3777 nnz = Ii[i+1]- Ii[i]; 3778 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3779 } 3780 nooffprocentries = B->nooffprocentries; 3781 B->nooffprocentries = PETSC_TRUE; 3782 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3783 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3784 B->nooffprocentries = nooffprocentries; 3785 3786 if (!v) { 3787 ierr = PetscFree(values);CHKERRQ(ierr); 3788 } 3789 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3790 PetscFunctionReturn(0); 3791 } 3792 3793 /*@ 3794 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3795 (the default parallel PETSc format). 3796 3797 Collective on MPI_Comm 3798 3799 Input Parameters: 3800 + B - the matrix 3801 . i - the indices into j for the start of each local row (starts with zero) 3802 . j - the column indices for each local row (starts with zero) 3803 - v - optional values in the matrix 3804 3805 Level: developer 3806 3807 Notes: 3808 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3809 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3810 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3811 3812 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3813 3814 The format which is used for the sparse matrix input, is equivalent to a 3815 row-major ordering.. i.e for the following matrix, the input data expected is 3816 as shown 3817 3818 $ 1 0 0 3819 $ 2 0 3 P0 3820 $ ------- 3821 $ 4 5 6 P1 3822 $ 3823 $ Process0 [P0]: rows_owned=[0,1] 3824 $ i = {0,1,3} [size = nrow+1 = 2+1] 3825 $ j = {0,0,2} [size = 3] 3826 $ v = {1,2,3} [size = 3] 3827 $ 3828 $ Process1 [P1]: rows_owned=[2] 3829 $ i = {0,3} [size = nrow+1 = 1+1] 3830 $ j = {0,1,2} [size = 3] 3831 $ v = {4,5,6} [size = 3] 3832 3833 .keywords: matrix, aij, compressed row, sparse, parallel 3834 3835 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ, 3836 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3837 @*/ 3838 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3839 { 3840 PetscErrorCode ierr; 3841 3842 PetscFunctionBegin; 3843 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3844 PetscFunctionReturn(0); 3845 } 3846 3847 /*@C 3848 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3849 (the default parallel PETSc format). For good matrix assembly performance 3850 the user should preallocate the matrix storage by setting the parameters 3851 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3852 performance can be increased by more than a factor of 50. 3853 3854 Collective on MPI_Comm 3855 3856 Input Parameters: 3857 + B - the matrix 3858 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3859 (same value is used for all local rows) 3860 . d_nnz - array containing the number of nonzeros in the various rows of the 3861 DIAGONAL portion of the local submatrix (possibly different for each row) 3862 or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure. 3863 The size of this array is equal to the number of local rows, i.e 'm'. 3864 For matrices that will be factored, you must leave room for (and set) 3865 the diagonal entry even if it is zero. 3866 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3867 submatrix (same value is used for all local rows). 3868 - o_nnz - array containing the number of nonzeros in the various rows of the 3869 OFF-DIAGONAL portion of the local submatrix (possibly different for 3870 each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero 3871 structure. The size of this array is equal to the number 3872 of local rows, i.e 'm'. 3873 3874 If the *_nnz parameter is given then the *_nz parameter is ignored 3875 3876 The AIJ format (also called the Yale sparse matrix format or 3877 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3878 storage. The stored row and column indices begin with zero. 3879 See Users-Manual: ch_mat for details. 3880 3881 The parallel matrix is partitioned such that the first m0 rows belong to 3882 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3883 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3884 3885 The DIAGONAL portion of the local submatrix of a processor can be defined 3886 as the submatrix which is obtained by extraction the part corresponding to 3887 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3888 first row that belongs to the processor, r2 is the last row belonging to 3889 the this processor, and c1-c2 is range of indices of the local part of a 3890 vector suitable for applying the matrix to. This is an mxn matrix. In the 3891 common case of a square matrix, the row and column ranges are the same and 3892 the DIAGONAL part is also square. The remaining portion of the local 3893 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3894 3895 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3896 3897 You can call MatGetInfo() to get information on how effective the preallocation was; 3898 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3899 You can also run with the option -info and look for messages with the string 3900 malloc in them to see if additional memory allocation was needed. 3901 3902 Example usage: 3903 3904 Consider the following 8x8 matrix with 34 non-zero values, that is 3905 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3906 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3907 as follows: 3908 3909 .vb 3910 1 2 0 | 0 3 0 | 0 4 3911 Proc0 0 5 6 | 7 0 0 | 8 0 3912 9 0 10 | 11 0 0 | 12 0 3913 ------------------------------------- 3914 13 0 14 | 15 16 17 | 0 0 3915 Proc1 0 18 0 | 19 20 21 | 0 0 3916 0 0 0 | 22 23 0 | 24 0 3917 ------------------------------------- 3918 Proc2 25 26 27 | 0 0 28 | 29 0 3919 30 0 0 | 31 32 33 | 0 34 3920 .ve 3921 3922 This can be represented as a collection of submatrices as: 3923 3924 .vb 3925 A B C 3926 D E F 3927 G H I 3928 .ve 3929 3930 Where the submatrices A,B,C are owned by proc0, D,E,F are 3931 owned by proc1, G,H,I are owned by proc2. 3932 3933 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3934 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3935 The 'M','N' parameters are 8,8, and have the same values on all procs. 3936 3937 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3938 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3939 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3940 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3941 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3942 matrix, ans [DF] as another SeqAIJ matrix. 3943 3944 When d_nz, o_nz parameters are specified, d_nz storage elements are 3945 allocated for every row of the local diagonal submatrix, and o_nz 3946 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3947 One way to choose d_nz and o_nz is to use the max nonzerors per local 3948 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3949 In this case, the values of d_nz,o_nz are: 3950 .vb 3951 proc0 : dnz = 2, o_nz = 2 3952 proc1 : dnz = 3, o_nz = 2 3953 proc2 : dnz = 1, o_nz = 4 3954 .ve 3955 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3956 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3957 for proc3. i.e we are using 12+15+10=37 storage locations to store 3958 34 values. 3959 3960 When d_nnz, o_nnz parameters are specified, the storage is specified 3961 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3962 In the above case the values for d_nnz,o_nnz are: 3963 .vb 3964 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3965 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3966 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3967 .ve 3968 Here the space allocated is sum of all the above values i.e 34, and 3969 hence pre-allocation is perfect. 3970 3971 Level: intermediate 3972 3973 .keywords: matrix, aij, compressed row, sparse, parallel 3974 3975 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3976 MATMPIAIJ, MatGetInfo(), PetscSplitOwnership() 3977 @*/ 3978 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3979 { 3980 PetscErrorCode ierr; 3981 3982 PetscFunctionBegin; 3983 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3984 PetscValidType(B,1); 3985 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3986 PetscFunctionReturn(0); 3987 } 3988 3989 /*@ 3990 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3991 CSR format the local rows. 3992 3993 Collective on MPI_Comm 3994 3995 Input Parameters: 3996 + comm - MPI communicator 3997 . m - number of local rows (Cannot be PETSC_DECIDE) 3998 . n - This value should be the same as the local size used in creating the 3999 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4000 calculated if N is given) For square matrices n is almost always m. 4001 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4002 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4003 . i - row indices 4004 . j - column indices 4005 - a - matrix values 4006 4007 Output Parameter: 4008 . mat - the matrix 4009 4010 Level: intermediate 4011 4012 Notes: 4013 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4014 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4015 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4016 4017 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4018 4019 The format which is used for the sparse matrix input, is equivalent to a 4020 row-major ordering.. i.e for the following matrix, the input data expected is 4021 as shown 4022 4023 $ 1 0 0 4024 $ 2 0 3 P0 4025 $ ------- 4026 $ 4 5 6 P1 4027 $ 4028 $ Process0 [P0]: rows_owned=[0,1] 4029 $ i = {0,1,3} [size = nrow+1 = 2+1] 4030 $ j = {0,0,2} [size = 3] 4031 $ v = {1,2,3} [size = 3] 4032 $ 4033 $ Process1 [P1]: rows_owned=[2] 4034 $ i = {0,3} [size = nrow+1 = 1+1] 4035 $ j = {0,1,2} [size = 3] 4036 $ v = {4,5,6} [size = 3] 4037 4038 .keywords: matrix, aij, compressed row, sparse, parallel 4039 4040 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4041 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4042 @*/ 4043 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4044 { 4045 PetscErrorCode ierr; 4046 4047 PetscFunctionBegin; 4048 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4049 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4050 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4051 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4052 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4053 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4054 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4055 PetscFunctionReturn(0); 4056 } 4057 4058 /*@C 4059 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4060 (the default parallel PETSc format). For good matrix assembly performance 4061 the user should preallocate the matrix storage by setting the parameters 4062 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4063 performance can be increased by more than a factor of 50. 4064 4065 Collective on MPI_Comm 4066 4067 Input Parameters: 4068 + comm - MPI communicator 4069 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4070 This value should be the same as the local size used in creating the 4071 y vector for the matrix-vector product y = Ax. 4072 . n - This value should be the same as the local size used in creating the 4073 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4074 calculated if N is given) For square matrices n is almost always m. 4075 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4076 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4077 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4078 (same value is used for all local rows) 4079 . d_nnz - array containing the number of nonzeros in the various rows of the 4080 DIAGONAL portion of the local submatrix (possibly different for each row) 4081 or NULL, if d_nz is used to specify the nonzero structure. 4082 The size of this array is equal to the number of local rows, i.e 'm'. 4083 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4084 submatrix (same value is used for all local rows). 4085 - o_nnz - array containing the number of nonzeros in the various rows of the 4086 OFF-DIAGONAL portion of the local submatrix (possibly different for 4087 each row) or NULL, if o_nz is used to specify the nonzero 4088 structure. The size of this array is equal to the number 4089 of local rows, i.e 'm'. 4090 4091 Output Parameter: 4092 . A - the matrix 4093 4094 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4095 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4096 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4097 4098 Notes: 4099 If the *_nnz parameter is given then the *_nz parameter is ignored 4100 4101 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4102 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4103 storage requirements for this matrix. 4104 4105 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4106 processor than it must be used on all processors that share the object for 4107 that argument. 4108 4109 The user MUST specify either the local or global matrix dimensions 4110 (possibly both). 4111 4112 The parallel matrix is partitioned across processors such that the 4113 first m0 rows belong to process 0, the next m1 rows belong to 4114 process 1, the next m2 rows belong to process 2 etc.. where 4115 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4116 values corresponding to [m x N] submatrix. 4117 4118 The columns are logically partitioned with the n0 columns belonging 4119 to 0th partition, the next n1 columns belonging to the next 4120 partition etc.. where n0,n1,n2... are the input parameter 'n'. 4121 4122 The DIAGONAL portion of the local submatrix on any given processor 4123 is the submatrix corresponding to the rows and columns m,n 4124 corresponding to the given processor. i.e diagonal matrix on 4125 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4126 etc. The remaining portion of the local submatrix [m x (N-n)] 4127 constitute the OFF-DIAGONAL portion. The example below better 4128 illustrates this concept. 4129 4130 For a square global matrix we define each processor's diagonal portion 4131 to be its local rows and the corresponding columns (a square submatrix); 4132 each processor's off-diagonal portion encompasses the remainder of the 4133 local matrix (a rectangular submatrix). 4134 4135 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4136 4137 When calling this routine with a single process communicator, a matrix of 4138 type SEQAIJ is returned. If a matrix of type MATMPIAIJ is desired for this 4139 type of communicator, use the construction mechanism: 4140 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4141 4142 By default, this format uses inodes (identical nodes) when possible. 4143 We search for consecutive rows with the same nonzero structure, thereby 4144 reusing matrix information to achieve increased efficiency. 4145 4146 Options Database Keys: 4147 + -mat_no_inode - Do not use inodes 4148 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4149 - -mat_aij_oneindex - Internally use indexing starting at 1 4150 rather than 0. Note that when calling MatSetValues(), 4151 the user still MUST index entries starting at 0! 4152 4153 4154 Example usage: 4155 4156 Consider the following 8x8 matrix with 34 non-zero values, that is 4157 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4158 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4159 as follows: 4160 4161 .vb 4162 1 2 0 | 0 3 0 | 0 4 4163 Proc0 0 5 6 | 7 0 0 | 8 0 4164 9 0 10 | 11 0 0 | 12 0 4165 ------------------------------------- 4166 13 0 14 | 15 16 17 | 0 0 4167 Proc1 0 18 0 | 19 20 21 | 0 0 4168 0 0 0 | 22 23 0 | 24 0 4169 ------------------------------------- 4170 Proc2 25 26 27 | 0 0 28 | 29 0 4171 30 0 0 | 31 32 33 | 0 34 4172 .ve 4173 4174 This can be represented as a collection of submatrices as: 4175 4176 .vb 4177 A B C 4178 D E F 4179 G H I 4180 .ve 4181 4182 Where the submatrices A,B,C are owned by proc0, D,E,F are 4183 owned by proc1, G,H,I are owned by proc2. 4184 4185 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4186 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4187 The 'M','N' parameters are 8,8, and have the same values on all procs. 4188 4189 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4190 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4191 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4192 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4193 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4194 matrix, ans [DF] as another SeqAIJ matrix. 4195 4196 When d_nz, o_nz parameters are specified, d_nz storage elements are 4197 allocated for every row of the local diagonal submatrix, and o_nz 4198 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4199 One way to choose d_nz and o_nz is to use the max nonzerors per local 4200 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4201 In this case, the values of d_nz,o_nz are: 4202 .vb 4203 proc0 : dnz = 2, o_nz = 2 4204 proc1 : dnz = 3, o_nz = 2 4205 proc2 : dnz = 1, o_nz = 4 4206 .ve 4207 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4208 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4209 for proc3. i.e we are using 12+15+10=37 storage locations to store 4210 34 values. 4211 4212 When d_nnz, o_nnz parameters are specified, the storage is specified 4213 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4214 In the above case the values for d_nnz,o_nnz are: 4215 .vb 4216 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4217 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4218 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4219 .ve 4220 Here the space allocated is sum of all the above values i.e 34, and 4221 hence pre-allocation is perfect. 4222 4223 Level: intermediate 4224 4225 .keywords: matrix, aij, compressed row, sparse, parallel 4226 4227 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4228 MATMPIAIJ, MatCreateMPIAIJWithArrays() 4229 @*/ 4230 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) 4231 { 4232 PetscErrorCode ierr; 4233 PetscMPIInt size; 4234 4235 PetscFunctionBegin; 4236 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4237 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4238 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4239 if (size > 1) { 4240 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4241 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4242 } else { 4243 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4244 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4245 } 4246 PetscFunctionReturn(0); 4247 } 4248 4249 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4250 { 4251 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4252 PetscBool flg; 4253 PetscErrorCode ierr; 4254 4255 PetscFunctionBegin; 4256 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); 4257 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input"); 4258 if (Ad) *Ad = a->A; 4259 if (Ao) *Ao = a->B; 4260 if (colmap) *colmap = a->garray; 4261 PetscFunctionReturn(0); 4262 } 4263 4264 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4265 { 4266 PetscErrorCode ierr; 4267 PetscInt m,N,i,rstart,nnz,Ii; 4268 PetscInt *indx; 4269 PetscScalar *values; 4270 4271 PetscFunctionBegin; 4272 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4273 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4274 PetscInt *dnz,*onz,sum,bs,cbs; 4275 4276 if (n == PETSC_DECIDE) { 4277 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4278 } 4279 /* Check sum(n) = N */ 4280 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4281 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4282 4283 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4284 rstart -= m; 4285 4286 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4287 for (i=0; i<m; i++) { 4288 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4289 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4290 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4291 } 4292 4293 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4294 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4295 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4296 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4297 ierr = MatSetType(*outmat,MATAIJ);CHKERRQ(ierr); 4298 ierr = MatSeqAIJSetPreallocation(*outmat,0,dnz);CHKERRQ(ierr); 4299 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4300 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4301 } 4302 4303 /* numeric phase */ 4304 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4305 for (i=0; i<m; i++) { 4306 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4307 Ii = i + rstart; 4308 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4309 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4310 } 4311 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4312 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4313 PetscFunctionReturn(0); 4314 } 4315 4316 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4317 { 4318 PetscErrorCode ierr; 4319 PetscMPIInt rank; 4320 PetscInt m,N,i,rstart,nnz; 4321 size_t len; 4322 const PetscInt *indx; 4323 PetscViewer out; 4324 char *name; 4325 Mat B; 4326 const PetscScalar *values; 4327 4328 PetscFunctionBegin; 4329 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4330 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4331 /* Should this be the type of the diagonal block of A? */ 4332 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4333 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4334 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4335 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4336 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4337 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4338 for (i=0; i<m; i++) { 4339 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4340 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4341 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4342 } 4343 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4344 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4345 4346 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4347 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4348 ierr = PetscMalloc1(len+5,&name);CHKERRQ(ierr); 4349 sprintf(name,"%s.%d",outfile,rank); 4350 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4351 ierr = PetscFree(name);CHKERRQ(ierr); 4352 ierr = MatView(B,out);CHKERRQ(ierr); 4353 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4354 ierr = MatDestroy(&B);CHKERRQ(ierr); 4355 PetscFunctionReturn(0); 4356 } 4357 4358 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4359 { 4360 PetscErrorCode ierr; 4361 Mat_Merge_SeqsToMPI *merge; 4362 PetscContainer container; 4363 4364 PetscFunctionBegin; 4365 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4366 if (container) { 4367 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4368 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4369 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4370 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4371 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4372 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4373 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4374 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4375 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4376 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4377 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4378 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4379 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4380 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4381 ierr = PetscFree(merge);CHKERRQ(ierr); 4382 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4383 } 4384 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4385 PetscFunctionReturn(0); 4386 } 4387 4388 #include <../src/mat/utils/freespace.h> 4389 #include <petscbt.h> 4390 4391 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4392 { 4393 PetscErrorCode ierr; 4394 MPI_Comm comm; 4395 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4396 PetscMPIInt size,rank,taga,*len_s; 4397 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4398 PetscInt proc,m; 4399 PetscInt **buf_ri,**buf_rj; 4400 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4401 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4402 MPI_Request *s_waits,*r_waits; 4403 MPI_Status *status; 4404 MatScalar *aa=a->a; 4405 MatScalar **abuf_r,*ba_i; 4406 Mat_Merge_SeqsToMPI *merge; 4407 PetscContainer container; 4408 4409 PetscFunctionBegin; 4410 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4411 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4412 4413 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4414 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4415 4416 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4417 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4418 4419 bi = merge->bi; 4420 bj = merge->bj; 4421 buf_ri = merge->buf_ri; 4422 buf_rj = merge->buf_rj; 4423 4424 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4425 owners = merge->rowmap->range; 4426 len_s = merge->len_s; 4427 4428 /* send and recv matrix values */ 4429 /*-----------------------------*/ 4430 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4431 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4432 4433 ierr = PetscMalloc1(merge->nsend+1,&s_waits);CHKERRQ(ierr); 4434 for (proc=0,k=0; proc<size; proc++) { 4435 if (!len_s[proc]) continue; 4436 i = owners[proc]; 4437 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4438 k++; 4439 } 4440 4441 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4442 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4443 ierr = PetscFree(status);CHKERRQ(ierr); 4444 4445 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4446 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4447 4448 /* insert mat values of mpimat */ 4449 /*----------------------------*/ 4450 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4451 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4452 4453 for (k=0; k<merge->nrecv; k++) { 4454 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4455 nrows = *(buf_ri_k[k]); 4456 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4457 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4458 } 4459 4460 /* set values of ba */ 4461 m = merge->rowmap->n; 4462 for (i=0; i<m; i++) { 4463 arow = owners[rank] + i; 4464 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4465 bnzi = bi[i+1] - bi[i]; 4466 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4467 4468 /* add local non-zero vals of this proc's seqmat into ba */ 4469 anzi = ai[arow+1] - ai[arow]; 4470 aj = a->j + ai[arow]; 4471 aa = a->a + ai[arow]; 4472 nextaj = 0; 4473 for (j=0; nextaj<anzi; j++) { 4474 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4475 ba_i[j] += aa[nextaj++]; 4476 } 4477 } 4478 4479 /* add received vals into ba */ 4480 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4481 /* i-th row */ 4482 if (i == *nextrow[k]) { 4483 anzi = *(nextai[k]+1) - *nextai[k]; 4484 aj = buf_rj[k] + *(nextai[k]); 4485 aa = abuf_r[k] + *(nextai[k]); 4486 nextaj = 0; 4487 for (j=0; nextaj<anzi; j++) { 4488 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4489 ba_i[j] += aa[nextaj++]; 4490 } 4491 } 4492 nextrow[k]++; nextai[k]++; 4493 } 4494 } 4495 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4496 } 4497 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4498 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4499 4500 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4501 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4502 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4503 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4504 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4505 PetscFunctionReturn(0); 4506 } 4507 4508 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4509 { 4510 PetscErrorCode ierr; 4511 Mat B_mpi; 4512 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4513 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4514 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4515 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4516 PetscInt len,proc,*dnz,*onz,bs,cbs; 4517 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4518 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4519 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4520 MPI_Status *status; 4521 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4522 PetscBT lnkbt; 4523 Mat_Merge_SeqsToMPI *merge; 4524 PetscContainer container; 4525 4526 PetscFunctionBegin; 4527 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4528 4529 /* make sure it is a PETSc comm */ 4530 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4531 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4532 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4533 4534 ierr = PetscNew(&merge);CHKERRQ(ierr); 4535 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4536 4537 /* determine row ownership */ 4538 /*---------------------------------------------------------*/ 4539 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4540 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4541 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4542 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4543 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4544 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4545 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4546 4547 m = merge->rowmap->n; 4548 owners = merge->rowmap->range; 4549 4550 /* determine the number of messages to send, their lengths */ 4551 /*---------------------------------------------------------*/ 4552 len_s = merge->len_s; 4553 4554 len = 0; /* length of buf_si[] */ 4555 merge->nsend = 0; 4556 for (proc=0; proc<size; proc++) { 4557 len_si[proc] = 0; 4558 if (proc == rank) { 4559 len_s[proc] = 0; 4560 } else { 4561 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4562 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4563 } 4564 if (len_s[proc]) { 4565 merge->nsend++; 4566 nrows = 0; 4567 for (i=owners[proc]; i<owners[proc+1]; i++) { 4568 if (ai[i+1] > ai[i]) nrows++; 4569 } 4570 len_si[proc] = 2*(nrows+1); 4571 len += len_si[proc]; 4572 } 4573 } 4574 4575 /* determine the number and length of messages to receive for ij-structure */ 4576 /*-------------------------------------------------------------------------*/ 4577 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4578 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4579 4580 /* post the Irecv of j-structure */ 4581 /*-------------------------------*/ 4582 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4583 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4584 4585 /* post the Isend of j-structure */ 4586 /*--------------------------------*/ 4587 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4588 4589 for (proc=0, k=0; proc<size; proc++) { 4590 if (!len_s[proc]) continue; 4591 i = owners[proc]; 4592 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4593 k++; 4594 } 4595 4596 /* receives and sends of j-structure are complete */ 4597 /*------------------------------------------------*/ 4598 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4599 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4600 4601 /* send and recv i-structure */ 4602 /*---------------------------*/ 4603 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4604 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4605 4606 ierr = PetscMalloc1(len+1,&buf_s);CHKERRQ(ierr); 4607 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4608 for (proc=0,k=0; proc<size; proc++) { 4609 if (!len_s[proc]) continue; 4610 /* form outgoing message for i-structure: 4611 buf_si[0]: nrows to be sent 4612 [1:nrows]: row index (global) 4613 [nrows+1:2*nrows+1]: i-structure index 4614 */ 4615 /*-------------------------------------------*/ 4616 nrows = len_si[proc]/2 - 1; 4617 buf_si_i = buf_si + nrows+1; 4618 buf_si[0] = nrows; 4619 buf_si_i[0] = 0; 4620 nrows = 0; 4621 for (i=owners[proc]; i<owners[proc+1]; i++) { 4622 anzi = ai[i+1] - ai[i]; 4623 if (anzi) { 4624 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4625 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4626 nrows++; 4627 } 4628 } 4629 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4630 k++; 4631 buf_si += len_si[proc]; 4632 } 4633 4634 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4635 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4636 4637 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4638 for (i=0; i<merge->nrecv; i++) { 4639 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); 4640 } 4641 4642 ierr = PetscFree(len_si);CHKERRQ(ierr); 4643 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4644 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4645 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4646 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4647 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4648 ierr = PetscFree(status);CHKERRQ(ierr); 4649 4650 /* compute a local seq matrix in each processor */ 4651 /*----------------------------------------------*/ 4652 /* allocate bi array and free space for accumulating nonzero column info */ 4653 ierr = PetscMalloc1(m+1,&bi);CHKERRQ(ierr); 4654 bi[0] = 0; 4655 4656 /* create and initialize a linked list */ 4657 nlnk = N+1; 4658 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4659 4660 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4661 len = ai[owners[rank+1]] - ai[owners[rank]]; 4662 ierr = PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);CHKERRQ(ierr); 4663 4664 current_space = free_space; 4665 4666 /* determine symbolic info for each local row */ 4667 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4668 4669 for (k=0; k<merge->nrecv; k++) { 4670 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4671 nrows = *buf_ri_k[k]; 4672 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4673 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4674 } 4675 4676 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4677 len = 0; 4678 for (i=0; i<m; i++) { 4679 bnzi = 0; 4680 /* add local non-zero cols of this proc's seqmat into lnk */ 4681 arow = owners[rank] + i; 4682 anzi = ai[arow+1] - ai[arow]; 4683 aj = a->j + ai[arow]; 4684 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4685 bnzi += nlnk; 4686 /* add received col data into lnk */ 4687 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4688 if (i == *nextrow[k]) { /* i-th row */ 4689 anzi = *(nextai[k]+1) - *nextai[k]; 4690 aj = buf_rj[k] + *nextai[k]; 4691 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4692 bnzi += nlnk; 4693 nextrow[k]++; nextai[k]++; 4694 } 4695 } 4696 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4697 4698 /* if free space is not available, make more free space */ 4699 if (current_space->local_remaining<bnzi) { 4700 ierr = PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);CHKERRQ(ierr); 4701 nspacedouble++; 4702 } 4703 /* copy data into free space, then initialize lnk */ 4704 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4705 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4706 4707 current_space->array += bnzi; 4708 current_space->local_used += bnzi; 4709 current_space->local_remaining -= bnzi; 4710 4711 bi[i+1] = bi[i] + bnzi; 4712 } 4713 4714 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4715 4716 ierr = PetscMalloc1(bi[m]+1,&bj);CHKERRQ(ierr); 4717 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4718 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4719 4720 /* create symbolic parallel matrix B_mpi */ 4721 /*---------------------------------------*/ 4722 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4723 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4724 if (n==PETSC_DECIDE) { 4725 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4726 } else { 4727 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4728 } 4729 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4730 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4731 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4732 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4733 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4734 4735 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4736 B_mpi->assembled = PETSC_FALSE; 4737 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4738 merge->bi = bi; 4739 merge->bj = bj; 4740 merge->buf_ri = buf_ri; 4741 merge->buf_rj = buf_rj; 4742 merge->coi = NULL; 4743 merge->coj = NULL; 4744 merge->owners_co = NULL; 4745 4746 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4747 4748 /* attach the supporting struct to B_mpi for reuse */ 4749 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4750 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4751 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4752 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4753 *mpimat = B_mpi; 4754 4755 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4756 PetscFunctionReturn(0); 4757 } 4758 4759 /*@C 4760 MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential 4761 matrices from each processor 4762 4763 Collective on MPI_Comm 4764 4765 Input Parameters: 4766 + comm - the communicators the parallel matrix will live on 4767 . seqmat - the input sequential matrices 4768 . m - number of local rows (or PETSC_DECIDE) 4769 . n - number of local columns (or PETSC_DECIDE) 4770 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4771 4772 Output Parameter: 4773 . mpimat - the parallel matrix generated 4774 4775 Level: advanced 4776 4777 Notes: 4778 The dimensions of the sequential matrix in each processor MUST be the same. 4779 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4780 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4781 @*/ 4782 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4783 { 4784 PetscErrorCode ierr; 4785 PetscMPIInt size; 4786 4787 PetscFunctionBegin; 4788 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4789 if (size == 1) { 4790 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4791 if (scall == MAT_INITIAL_MATRIX) { 4792 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4793 } else { 4794 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4795 } 4796 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4797 PetscFunctionReturn(0); 4798 } 4799 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4800 if (scall == MAT_INITIAL_MATRIX) { 4801 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4802 } 4803 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4804 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4805 PetscFunctionReturn(0); 4806 } 4807 4808 /*@ 4809 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4810 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4811 with MatGetSize() 4812 4813 Not Collective 4814 4815 Input Parameters: 4816 + A - the matrix 4817 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4818 4819 Output Parameter: 4820 . A_loc - the local sequential matrix generated 4821 4822 Level: developer 4823 4824 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4825 4826 @*/ 4827 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4828 { 4829 PetscErrorCode ierr; 4830 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4831 Mat_SeqAIJ *mat,*a,*b; 4832 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4833 MatScalar *aa,*ba,*cam; 4834 PetscScalar *ca; 4835 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4836 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4837 PetscBool match; 4838 MPI_Comm comm; 4839 PetscMPIInt size; 4840 4841 PetscFunctionBegin; 4842 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4843 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4844 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4845 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4846 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4847 4848 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4849 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4850 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4851 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4852 aa = a->a; ba = b->a; 4853 if (scall == MAT_INITIAL_MATRIX) { 4854 if (size == 1) { 4855 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4856 PetscFunctionReturn(0); 4857 } 4858 4859 ierr = PetscMalloc1(1+am,&ci);CHKERRQ(ierr); 4860 ci[0] = 0; 4861 for (i=0; i<am; i++) { 4862 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4863 } 4864 ierr = PetscMalloc1(1+ci[am],&cj);CHKERRQ(ierr); 4865 ierr = PetscMalloc1(1+ci[am],&ca);CHKERRQ(ierr); 4866 k = 0; 4867 for (i=0; i<am; i++) { 4868 ncols_o = bi[i+1] - bi[i]; 4869 ncols_d = ai[i+1] - ai[i]; 4870 /* off-diagonal portion of A */ 4871 for (jo=0; jo<ncols_o; jo++) { 4872 col = cmap[*bj]; 4873 if (col >= cstart) break; 4874 cj[k] = col; bj++; 4875 ca[k++] = *ba++; 4876 } 4877 /* diagonal portion of A */ 4878 for (j=0; j<ncols_d; j++) { 4879 cj[k] = cstart + *aj++; 4880 ca[k++] = *aa++; 4881 } 4882 /* off-diagonal portion of A */ 4883 for (j=jo; j<ncols_o; j++) { 4884 cj[k] = cmap[*bj++]; 4885 ca[k++] = *ba++; 4886 } 4887 } 4888 /* put together the new matrix */ 4889 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4890 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4891 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4892 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4893 mat->free_a = PETSC_TRUE; 4894 mat->free_ij = PETSC_TRUE; 4895 mat->nonew = 0; 4896 } else if (scall == MAT_REUSE_MATRIX) { 4897 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4898 ci = mat->i; cj = mat->j; cam = mat->a; 4899 for (i=0; i<am; i++) { 4900 /* off-diagonal portion of A */ 4901 ncols_o = bi[i+1] - bi[i]; 4902 for (jo=0; jo<ncols_o; jo++) { 4903 col = cmap[*bj]; 4904 if (col >= cstart) break; 4905 *cam++ = *ba++; bj++; 4906 } 4907 /* diagonal portion of A */ 4908 ncols_d = ai[i+1] - ai[i]; 4909 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4910 /* off-diagonal portion of A */ 4911 for (j=jo; j<ncols_o; j++) { 4912 *cam++ = *ba++; bj++; 4913 } 4914 } 4915 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4916 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4917 PetscFunctionReturn(0); 4918 } 4919 4920 /*@C 4921 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns 4922 4923 Not Collective 4924 4925 Input Parameters: 4926 + A - the matrix 4927 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4928 - row, col - index sets of rows and columns to extract (or NULL) 4929 4930 Output Parameter: 4931 . A_loc - the local sequential matrix generated 4932 4933 Level: developer 4934 4935 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4936 4937 @*/ 4938 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4939 { 4940 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4941 PetscErrorCode ierr; 4942 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4943 IS isrowa,iscola; 4944 Mat *aloc; 4945 PetscBool match; 4946 4947 PetscFunctionBegin; 4948 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4949 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input"); 4950 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4951 if (!row) { 4952 start = A->rmap->rstart; end = A->rmap->rend; 4953 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4954 } else { 4955 isrowa = *row; 4956 } 4957 if (!col) { 4958 start = A->cmap->rstart; 4959 cmap = a->garray; 4960 nzA = a->A->cmap->n; 4961 nzB = a->B->cmap->n; 4962 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 4963 ncols = 0; 4964 for (i=0; i<nzB; i++) { 4965 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4966 else break; 4967 } 4968 imark = i; 4969 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4970 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4971 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4972 } else { 4973 iscola = *col; 4974 } 4975 if (scall != MAT_INITIAL_MATRIX) { 4976 ierr = PetscMalloc1(1,&aloc);CHKERRQ(ierr); 4977 aloc[0] = *A_loc; 4978 } 4979 ierr = MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4980 *A_loc = aloc[0]; 4981 ierr = PetscFree(aloc);CHKERRQ(ierr); 4982 if (!row) { 4983 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4984 } 4985 if (!col) { 4986 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4987 } 4988 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4989 PetscFunctionReturn(0); 4990 } 4991 4992 /*@C 4993 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4994 4995 Collective on Mat 4996 4997 Input Parameters: 4998 + A,B - the matrices in mpiaij format 4999 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5000 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5001 5002 Output Parameter: 5003 + rowb, colb - index sets of rows and columns of B to extract 5004 - B_seq - the sequential matrix generated 5005 5006 Level: developer 5007 5008 @*/ 5009 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5010 { 5011 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5012 PetscErrorCode ierr; 5013 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5014 IS isrowb,iscolb; 5015 Mat *bseq=NULL; 5016 5017 PetscFunctionBegin; 5018 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5019 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); 5020 } 5021 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5022 5023 if (scall == MAT_INITIAL_MATRIX) { 5024 start = A->cmap->rstart; 5025 cmap = a->garray; 5026 nzA = a->A->cmap->n; 5027 nzB = a->B->cmap->n; 5028 ierr = PetscMalloc1(nzA+nzB, &idx);CHKERRQ(ierr); 5029 ncols = 0; 5030 for (i=0; i<nzB; i++) { /* row < local row index */ 5031 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5032 else break; 5033 } 5034 imark = i; 5035 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5036 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5037 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5038 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5039 } else { 5040 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5041 isrowb = *rowb; iscolb = *colb; 5042 ierr = PetscMalloc1(1,&bseq);CHKERRQ(ierr); 5043 bseq[0] = *B_seq; 5044 } 5045 ierr = MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5046 *B_seq = bseq[0]; 5047 ierr = PetscFree(bseq);CHKERRQ(ierr); 5048 if (!rowb) { 5049 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5050 } else { 5051 *rowb = isrowb; 5052 } 5053 if (!colb) { 5054 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5055 } else { 5056 *colb = iscolb; 5057 } 5058 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5059 PetscFunctionReturn(0); 5060 } 5061 5062 /* 5063 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5064 of the OFF-DIAGONAL portion of local A 5065 5066 Collective on Mat 5067 5068 Input Parameters: 5069 + A,B - the matrices in mpiaij format 5070 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5071 5072 Output Parameter: 5073 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5074 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5075 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5076 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5077 5078 Level: developer 5079 5080 */ 5081 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5082 { 5083 VecScatter_MPI_General *gen_to,*gen_from; 5084 PetscErrorCode ierr; 5085 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5086 Mat_SeqAIJ *b_oth; 5087 VecScatter ctx =a->Mvctx; 5088 MPI_Comm comm; 5089 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5090 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5091 PetscInt *rvalues,*svalues; 5092 MatScalar *b_otha,*bufa,*bufA; 5093 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5094 MPI_Request *rwaits = NULL,*swaits = NULL; 5095 MPI_Status *sstatus,rstatus; 5096 PetscMPIInt jj,size; 5097 PetscInt *cols,sbs,rbs; 5098 PetscScalar *vals; 5099 5100 PetscFunctionBegin; 5101 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5102 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5103 5104 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5105 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); 5106 } 5107 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5108 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5109 5110 if (size == 1) { 5111 startsj_s = NULL; 5112 bufa_ptr = NULL; 5113 *B_oth = NULL; 5114 PetscFunctionReturn(0); 5115 } 5116 5117 gen_to = (VecScatter_MPI_General*)ctx->todata; 5118 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5119 nrecvs = gen_from->n; 5120 nsends = gen_to->n; 5121 5122 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 5123 srow = gen_to->indices; /* local row index to be sent */ 5124 sstarts = gen_to->starts; 5125 sprocs = gen_to->procs; 5126 sstatus = gen_to->sstatus; 5127 sbs = gen_to->bs; 5128 rstarts = gen_from->starts; 5129 rprocs = gen_from->procs; 5130 rbs = gen_from->bs; 5131 5132 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5133 if (scall == MAT_INITIAL_MATRIX) { 5134 /* i-array */ 5135 /*---------*/ 5136 /* post receives */ 5137 ierr = PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);CHKERRQ(ierr); 5138 for (i=0; i<nrecvs; i++) { 5139 rowlen = rvalues + rstarts[i]*rbs; 5140 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5141 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5142 } 5143 5144 /* pack the outgoing message */ 5145 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 5146 5147 sstartsj[0] = 0; 5148 rstartsj[0] = 0; 5149 len = 0; /* total length of j or a array to be sent */ 5150 k = 0; 5151 ierr = PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);CHKERRQ(ierr); 5152 for (i=0; i<nsends; i++) { 5153 rowlen = svalues + sstarts[i]*sbs; 5154 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5155 for (j=0; j<nrows; j++) { 5156 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5157 for (l=0; l<sbs; l++) { 5158 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5159 5160 rowlen[j*sbs+l] = ncols; 5161 5162 len += ncols; 5163 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5164 } 5165 k++; 5166 } 5167 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5168 5169 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5170 } 5171 /* recvs and sends of i-array are completed */ 5172 i = nrecvs; 5173 while (i--) { 5174 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5175 } 5176 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5177 ierr = PetscFree(svalues);CHKERRQ(ierr); 5178 5179 /* allocate buffers for sending j and a arrays */ 5180 ierr = PetscMalloc1(len+1,&bufj);CHKERRQ(ierr); 5181 ierr = PetscMalloc1(len+1,&bufa);CHKERRQ(ierr); 5182 5183 /* create i-array of B_oth */ 5184 ierr = PetscMalloc1(aBn+2,&b_othi);CHKERRQ(ierr); 5185 5186 b_othi[0] = 0; 5187 len = 0; /* total length of j or a array to be received */ 5188 k = 0; 5189 for (i=0; i<nrecvs; i++) { 5190 rowlen = rvalues + rstarts[i]*rbs; 5191 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */ 5192 for (j=0; j<nrows; j++) { 5193 b_othi[k+1] = b_othi[k] + rowlen[j]; 5194 ierr = PetscIntSumError(rowlen[j],len,&len);CHKERRQ(ierr); 5195 k++; 5196 } 5197 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5198 } 5199 ierr = PetscFree(rvalues);CHKERRQ(ierr); 5200 5201 /* allocate space for j and a arrrays of B_oth */ 5202 ierr = PetscMalloc1(b_othi[aBn]+1,&b_othj);CHKERRQ(ierr); 5203 ierr = PetscMalloc1(b_othi[aBn]+1,&b_otha);CHKERRQ(ierr); 5204 5205 /* j-array */ 5206 /*---------*/ 5207 /* post receives of j-array */ 5208 for (i=0; i<nrecvs; i++) { 5209 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5210 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5211 } 5212 5213 /* pack the outgoing message j-array */ 5214 k = 0; 5215 for (i=0; i<nsends; i++) { 5216 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5217 bufJ = bufj+sstartsj[i]; 5218 for (j=0; j<nrows; j++) { 5219 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5220 for (ll=0; ll<sbs; ll++) { 5221 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5222 for (l=0; l<ncols; l++) { 5223 *bufJ++ = cols[l]; 5224 } 5225 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5226 } 5227 } 5228 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5229 } 5230 5231 /* recvs and sends of j-array are completed */ 5232 i = nrecvs; 5233 while (i--) { 5234 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5235 } 5236 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5237 } else if (scall == MAT_REUSE_MATRIX) { 5238 sstartsj = *startsj_s; 5239 rstartsj = *startsj_r; 5240 bufa = *bufa_ptr; 5241 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5242 b_otha = b_oth->a; 5243 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5244 5245 /* a-array */ 5246 /*---------*/ 5247 /* post receives of a-array */ 5248 for (i=0; i<nrecvs; i++) { 5249 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5250 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5251 } 5252 5253 /* pack the outgoing message a-array */ 5254 k = 0; 5255 for (i=0; i<nsends; i++) { 5256 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5257 bufA = bufa+sstartsj[i]; 5258 for (j=0; j<nrows; j++) { 5259 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5260 for (ll=0; ll<sbs; ll++) { 5261 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5262 for (l=0; l<ncols; l++) { 5263 *bufA++ = vals[l]; 5264 } 5265 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5266 } 5267 } 5268 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5269 } 5270 /* recvs and sends of a-array are completed */ 5271 i = nrecvs; 5272 while (i--) { 5273 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5274 } 5275 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5276 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5277 5278 if (scall == MAT_INITIAL_MATRIX) { 5279 /* put together the new matrix */ 5280 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5281 5282 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5283 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5284 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5285 b_oth->free_a = PETSC_TRUE; 5286 b_oth->free_ij = PETSC_TRUE; 5287 b_oth->nonew = 0; 5288 5289 ierr = PetscFree(bufj);CHKERRQ(ierr); 5290 if (!startsj_s || !bufa_ptr) { 5291 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5292 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5293 } else { 5294 *startsj_s = sstartsj; 5295 *startsj_r = rstartsj; 5296 *bufa_ptr = bufa; 5297 } 5298 } 5299 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5300 PetscFunctionReturn(0); 5301 } 5302 5303 /*@C 5304 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5305 5306 Not Collective 5307 5308 Input Parameters: 5309 . A - The matrix in mpiaij format 5310 5311 Output Parameter: 5312 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5313 . colmap - A map from global column index to local index into lvec 5314 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5315 5316 Level: developer 5317 5318 @*/ 5319 #if defined(PETSC_USE_CTABLE) 5320 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5321 #else 5322 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5323 #endif 5324 { 5325 Mat_MPIAIJ *a; 5326 5327 PetscFunctionBegin; 5328 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5329 PetscValidPointer(lvec, 2); 5330 PetscValidPointer(colmap, 3); 5331 PetscValidPointer(multScatter, 4); 5332 a = (Mat_MPIAIJ*) A->data; 5333 if (lvec) *lvec = a->lvec; 5334 if (colmap) *colmap = a->colmap; 5335 if (multScatter) *multScatter = a->Mvctx; 5336 PetscFunctionReturn(0); 5337 } 5338 5339 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5340 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5341 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5342 #if defined(PETSC_HAVE_ELEMENTAL) 5343 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5344 #endif 5345 #if defined(PETSC_HAVE_HYPRE) 5346 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*); 5347 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 5348 #endif 5349 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*); 5350 5351 /* 5352 Computes (B'*A')' since computing B*A directly is untenable 5353 5354 n p p 5355 ( ) ( ) ( ) 5356 m ( A ) * n ( B ) = m ( C ) 5357 ( ) ( ) ( ) 5358 5359 */ 5360 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5361 { 5362 PetscErrorCode ierr; 5363 Mat At,Bt,Ct; 5364 5365 PetscFunctionBegin; 5366 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5367 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5368 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5369 ierr = MatDestroy(&At);CHKERRQ(ierr); 5370 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5371 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5372 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5373 PetscFunctionReturn(0); 5374 } 5375 5376 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5377 { 5378 PetscErrorCode ierr; 5379 PetscInt m=A->rmap->n,n=B->cmap->n; 5380 Mat Cmat; 5381 5382 PetscFunctionBegin; 5383 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); 5384 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5385 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5386 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5387 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5388 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5389 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5390 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5391 5392 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5393 5394 *C = Cmat; 5395 PetscFunctionReturn(0); 5396 } 5397 5398 /* ----------------------------------------------------------------*/ 5399 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5400 { 5401 PetscErrorCode ierr; 5402 5403 PetscFunctionBegin; 5404 if (scall == MAT_INITIAL_MATRIX) { 5405 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5406 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5407 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5408 } 5409 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5410 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5411 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5412 PetscFunctionReturn(0); 5413 } 5414 5415 /*MC 5416 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5417 5418 Options Database Keys: 5419 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5420 5421 Level: beginner 5422 5423 .seealso: MatCreateAIJ() 5424 M*/ 5425 5426 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5427 { 5428 Mat_MPIAIJ *b; 5429 PetscErrorCode ierr; 5430 PetscMPIInt size; 5431 5432 PetscFunctionBegin; 5433 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5434 5435 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5436 B->data = (void*)b; 5437 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5438 B->assembled = PETSC_FALSE; 5439 B->insertmode = NOT_SET_VALUES; 5440 b->size = size; 5441 5442 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5443 5444 /* build cache for off array entries formed */ 5445 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5446 5447 b->donotstash = PETSC_FALSE; 5448 b->colmap = 0; 5449 b->garray = 0; 5450 b->roworiented = PETSC_TRUE; 5451 5452 /* stuff used for matrix vector multiply */ 5453 b->lvec = NULL; 5454 b->Mvctx = NULL; 5455 5456 /* stuff for MatGetRow() */ 5457 b->rowindices = 0; 5458 b->rowvalues = 0; 5459 b->getrowactive = PETSC_FALSE; 5460 5461 /* flexible pointer used in CUSP/CUSPARSE classes */ 5462 b->spptr = NULL; 5463 5464 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);CHKERRQ(ierr); 5465 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5466 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5467 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5468 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5469 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5470 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5471 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5472 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5473 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5474 #if defined(PETSC_HAVE_ELEMENTAL) 5475 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5476 #endif 5477 #if defined(PETSC_HAVE_HYPRE) 5478 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 5479 #endif 5480 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);CHKERRQ(ierr); 5481 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5482 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5483 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5484 #if defined(PETSC_HAVE_HYPRE) 5485 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 5486 #endif 5487 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5488 PetscFunctionReturn(0); 5489 } 5490 5491 /*@C 5492 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5493 and "off-diagonal" part of the matrix in CSR format. 5494 5495 Collective on MPI_Comm 5496 5497 Input Parameters: 5498 + comm - MPI communicator 5499 . m - number of local rows (Cannot be PETSC_DECIDE) 5500 . n - This value should be the same as the local size used in creating the 5501 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5502 calculated if N is given) For square matrices n is almost always m. 5503 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5504 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5505 . i - row indices for "diagonal" portion of matrix 5506 . j - column indices 5507 . a - matrix values 5508 . oi - row indices for "off-diagonal" portion of matrix 5509 . oj - column indices 5510 - oa - matrix values 5511 5512 Output Parameter: 5513 . mat - the matrix 5514 5515 Level: advanced 5516 5517 Notes: 5518 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5519 must free the arrays once the matrix has been destroyed and not before. 5520 5521 The i and j indices are 0 based 5522 5523 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5524 5525 This sets local rows and cannot be used to set off-processor values. 5526 5527 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5528 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5529 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5530 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5531 keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5532 communication if it is known that only local entries will be set. 5533 5534 .keywords: matrix, aij, compressed row, sparse, parallel 5535 5536 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5537 MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5538 @*/ 5539 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) 5540 { 5541 PetscErrorCode ierr; 5542 Mat_MPIAIJ *maij; 5543 5544 PetscFunctionBegin; 5545 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5546 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5547 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5548 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5549 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5550 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5551 maij = (Mat_MPIAIJ*) (*mat)->data; 5552 5553 (*mat)->preallocated = PETSC_TRUE; 5554 5555 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5556 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5557 5558 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5559 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5560 5561 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5562 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5563 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5564 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5565 5566 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);CHKERRQ(ierr); 5567 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5568 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5569 ierr = MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);CHKERRQ(ierr); 5570 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5571 PetscFunctionReturn(0); 5572 } 5573 5574 /* 5575 Special version for direct calls from Fortran 5576 */ 5577 #include <petsc/private/fortranimpl.h> 5578 5579 /* Change these macros so can be used in void function */ 5580 #undef CHKERRQ 5581 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5582 #undef SETERRQ2 5583 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5584 #undef SETERRQ3 5585 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5586 #undef SETERRQ 5587 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5588 5589 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5590 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5591 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5592 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5593 #else 5594 #endif 5595 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) 5596 { 5597 Mat mat = *mmat; 5598 PetscInt m = *mm, n = *mn; 5599 InsertMode addv = *maddv; 5600 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5601 PetscScalar value; 5602 PetscErrorCode ierr; 5603 5604 MatCheckPreallocated(mat,1); 5605 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5606 5607 #if defined(PETSC_USE_DEBUG) 5608 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5609 #endif 5610 { 5611 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5612 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5613 PetscBool roworiented = aij->roworiented; 5614 5615 /* Some Variables required in the macro */ 5616 Mat A = aij->A; 5617 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5618 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5619 MatScalar *aa = a->a; 5620 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5621 Mat B = aij->B; 5622 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5623 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5624 MatScalar *ba = b->a; 5625 5626 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5627 PetscInt nonew = a->nonew; 5628 MatScalar *ap1,*ap2; 5629 5630 PetscFunctionBegin; 5631 for (i=0; i<m; i++) { 5632 if (im[i] < 0) continue; 5633 #if defined(PETSC_USE_DEBUG) 5634 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); 5635 #endif 5636 if (im[i] >= rstart && im[i] < rend) { 5637 row = im[i] - rstart; 5638 lastcol1 = -1; 5639 rp1 = aj + ai[row]; 5640 ap1 = aa + ai[row]; 5641 rmax1 = aimax[row]; 5642 nrow1 = ailen[row]; 5643 low1 = 0; 5644 high1 = nrow1; 5645 lastcol2 = -1; 5646 rp2 = bj + bi[row]; 5647 ap2 = ba + bi[row]; 5648 rmax2 = bimax[row]; 5649 nrow2 = bilen[row]; 5650 low2 = 0; 5651 high2 = nrow2; 5652 5653 for (j=0; j<n; j++) { 5654 if (roworiented) value = v[i*n+j]; 5655 else value = v[i+j*m]; 5656 if (in[j] >= cstart && in[j] < cend) { 5657 col = in[j] - cstart; 5658 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5659 MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]); 5660 } else if (in[j] < 0) continue; 5661 #if defined(PETSC_USE_DEBUG) 5662 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); 5663 #endif 5664 else { 5665 if (mat->was_assembled) { 5666 if (!aij->colmap) { 5667 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5668 } 5669 #if defined(PETSC_USE_CTABLE) 5670 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5671 col--; 5672 #else 5673 col = aij->colmap[in[j]] - 1; 5674 #endif 5675 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue; 5676 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5677 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5678 col = in[j]; 5679 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5680 B = aij->B; 5681 b = (Mat_SeqAIJ*)B->data; 5682 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5683 rp2 = bj + bi[row]; 5684 ap2 = ba + bi[row]; 5685 rmax2 = bimax[row]; 5686 nrow2 = bilen[row]; 5687 low2 = 0; 5688 high2 = nrow2; 5689 bm = aij->B->rmap->n; 5690 ba = b->a; 5691 } 5692 } else col = in[j]; 5693 MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]); 5694 } 5695 } 5696 } else if (!aij->donotstash) { 5697 if (roworiented) { 5698 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5699 } else { 5700 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5701 } 5702 } 5703 } 5704 } 5705 PetscFunctionReturnVoid(); 5706 } 5707 5708