1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPIU_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc1((M->rmap->n-cnt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 109 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 110 { 111 PetscErrorCode ierr; 112 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 113 114 PetscFunctionBegin; 115 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 116 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 117 } else { 118 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 119 } 120 PetscFunctionReturn(0); 121 } 122 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 126 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 127 { 128 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 129 PetscErrorCode ierr; 130 PetscInt i,rstart,nrows,*rows; 131 132 PetscFunctionBegin; 133 *zrows = NULL; 134 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 135 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 136 for (i=0; i<nrows; i++) rows[i] += rstart; 137 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 138 PetscFunctionReturn(0); 139 } 140 141 #undef __FUNCT__ 142 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 143 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 144 { 145 PetscErrorCode ierr; 146 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 147 PetscInt i,n,*garray = aij->garray; 148 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 149 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 150 PetscReal *work; 151 152 PetscFunctionBegin; 153 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 154 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 155 if (type == NORM_2) { 156 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 157 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 158 } 159 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 160 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 161 } 162 } else if (type == NORM_1) { 163 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 164 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 165 } 166 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 167 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 168 } 169 } else if (type == NORM_INFINITY) { 170 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 171 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 172 } 173 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 174 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 175 } 176 177 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 178 if (type == NORM_INFINITY) { 179 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 180 } else { 181 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 182 } 183 ierr = PetscFree(work);CHKERRQ(ierr); 184 if (type == NORM_2) { 185 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 186 } 187 PetscFunctionReturn(0); 188 } 189 190 #undef __FUNCT__ 191 #define __FUNCT__ "MatDistribute_MPIAIJ" 192 /* 193 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 194 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 195 196 Only for square matrices 197 198 Used by a preconditioner, hence PETSC_EXTERN 199 */ 200 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 201 { 202 PetscMPIInt rank,size; 203 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 204 PetscErrorCode ierr; 205 Mat mat; 206 Mat_SeqAIJ *gmata; 207 PetscMPIInt tag; 208 MPI_Status status; 209 PetscBool aij; 210 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 211 212 PetscFunctionBegin; 213 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 214 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 215 if (!rank) { 216 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 217 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 218 } 219 if (reuse == MAT_INITIAL_MATRIX) { 220 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 221 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 222 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 223 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 224 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 225 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 226 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 227 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 228 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 229 230 rowners[0] = 0; 231 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 232 rstart = rowners[rank]; 233 rend = rowners[rank+1]; 234 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 235 if (!rank) { 236 gmata = (Mat_SeqAIJ*) gmat->data; 237 /* send row lengths to all processors */ 238 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 239 for (i=1; i<size; i++) { 240 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 241 } 242 /* determine number diagonal and off-diagonal counts */ 243 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 244 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 245 jj = 0; 246 for (i=0; i<m; i++) { 247 for (j=0; j<dlens[i]; j++) { 248 if (gmata->j[jj] < rstart) ld[i]++; 249 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 250 jj++; 251 } 252 } 253 /* send column indices to other processes */ 254 for (i=1; i<size; i++) { 255 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 256 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 257 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 258 } 259 260 /* send numerical values to other processes */ 261 for (i=1; i<size; i++) { 262 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 263 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 264 } 265 gmataa = gmata->a; 266 gmataj = gmata->j; 267 268 } else { 269 /* receive row lengths */ 270 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 271 /* receive column indices */ 272 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 273 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 274 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 275 /* determine number diagonal and off-diagonal counts */ 276 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 277 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 278 jj = 0; 279 for (i=0; i<m; i++) { 280 for (j=0; j<dlens[i]; j++) { 281 if (gmataj[jj] < rstart) ld[i]++; 282 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 283 jj++; 284 } 285 } 286 /* receive numerical values */ 287 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 288 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 289 } 290 /* set preallocation */ 291 for (i=0; i<m; i++) { 292 dlens[i] -= olens[i]; 293 } 294 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 295 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 296 297 for (i=0; i<m; i++) { 298 dlens[i] += olens[i]; 299 } 300 cnt = 0; 301 for (i=0; i<m; i++) { 302 row = rstart + i; 303 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 304 cnt += dlens[i]; 305 } 306 if (rank) { 307 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 308 } 309 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 310 ierr = PetscFree(rowners);CHKERRQ(ierr); 311 312 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 313 314 *inmat = mat; 315 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 316 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 317 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 318 mat = *inmat; 319 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 320 if (!rank) { 321 /* send numerical values to other processes */ 322 gmata = (Mat_SeqAIJ*) gmat->data; 323 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 324 gmataa = gmata->a; 325 for (i=1; i<size; i++) { 326 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 327 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 328 } 329 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 330 } else { 331 /* receive numerical values from process 0*/ 332 nz = Ad->nz + Ao->nz; 333 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 334 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 335 } 336 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 337 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 338 ad = Ad->a; 339 ao = Ao->a; 340 if (mat->rmap->n) { 341 i = 0; 342 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 343 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 344 } 345 for (i=1; i<mat->rmap->n; i++) { 346 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; 347 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 348 } 349 i--; 350 if (mat->rmap->n) { 351 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 352 } 353 if (rank) { 354 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 355 } 356 } 357 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 358 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 359 PetscFunctionReturn(0); 360 } 361 362 /* 363 Local utility routine that creates a mapping from the global column 364 number to the local number in the off-diagonal part of the local 365 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 366 a slightly higher hash table cost; without it it is not scalable (each processor 367 has an order N integer array but is fast to acess. 368 */ 369 #undef __FUNCT__ 370 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 371 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 372 { 373 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 374 PetscErrorCode ierr; 375 PetscInt n = aij->B->cmap->n,i; 376 377 PetscFunctionBegin; 378 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 379 #if defined(PETSC_USE_CTABLE) 380 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 381 for (i=0; i<n; i++) { 382 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 383 } 384 #else 385 ierr = PetscCalloc1((mat->cmap->N+1),&aij->colmap);CHKERRQ(ierr); 386 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 387 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 388 #endif 389 PetscFunctionReturn(0); 390 } 391 392 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 393 { \ 394 if (col <= lastcol1) low1 = 0; \ 395 else high1 = nrow1; \ 396 lastcol1 = col;\ 397 while (high1-low1 > 5) { \ 398 t = (low1+high1)/2; \ 399 if (rp1[t] > col) high1 = t; \ 400 else low1 = t; \ 401 } \ 402 for (_i=low1; _i<high1; _i++) { \ 403 if (rp1[_i] > col) break; \ 404 if (rp1[_i] == col) { \ 405 if (addv == ADD_VALUES) ap1[_i] += value; \ 406 else ap1[_i] = value; \ 407 goto a_noinsert; \ 408 } \ 409 } \ 410 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 411 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 412 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 413 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 414 N = nrow1++ - 1; a->nz++; high1++; \ 415 /* shift up all the later entries in this row */ \ 416 for (ii=N; ii>=_i; ii--) { \ 417 rp1[ii+1] = rp1[ii]; \ 418 ap1[ii+1] = ap1[ii]; \ 419 } \ 420 rp1[_i] = col; \ 421 ap1[_i] = value; \ 422 A->nonzerostate++;\ 423 a_noinsert: ; \ 424 ailen[row] = nrow1; \ 425 } 426 427 428 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 429 { \ 430 if (col <= lastcol2) low2 = 0; \ 431 else high2 = nrow2; \ 432 lastcol2 = col; \ 433 while (high2-low2 > 5) { \ 434 t = (low2+high2)/2; \ 435 if (rp2[t] > col) high2 = t; \ 436 else low2 = t; \ 437 } \ 438 for (_i=low2; _i<high2; _i++) { \ 439 if (rp2[_i] > col) break; \ 440 if (rp2[_i] == col) { \ 441 if (addv == ADD_VALUES) ap2[_i] += value; \ 442 else ap2[_i] = value; \ 443 goto b_noinsert; \ 444 } \ 445 } \ 446 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 447 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 448 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 449 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 450 N = nrow2++ - 1; b->nz++; high2++; \ 451 /* shift up all the later entries in this row */ \ 452 for (ii=N; ii>=_i; ii--) { \ 453 rp2[ii+1] = rp2[ii]; \ 454 ap2[ii+1] = ap2[ii]; \ 455 } \ 456 rp2[_i] = col; \ 457 ap2[_i] = value; \ 458 B->nonzerostate++; \ 459 b_noinsert: ; \ 460 bilen[row] = nrow2; \ 461 } 462 463 #undef __FUNCT__ 464 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 465 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 466 { 467 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 468 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 469 PetscErrorCode ierr; 470 PetscInt l,*garray = mat->garray,diag; 471 472 PetscFunctionBegin; 473 /* code only works for square matrices A */ 474 475 /* find size of row to the left of the diagonal part */ 476 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 477 row = row - diag; 478 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 479 if (garray[b->j[b->i[row]+l]] > diag) break; 480 } 481 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 482 483 /* diagonal part */ 484 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 485 486 /* right of diagonal part */ 487 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); 488 PetscFunctionReturn(0); 489 } 490 491 #undef __FUNCT__ 492 #define __FUNCT__ "MatSetValues_MPIAIJ" 493 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 494 { 495 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 496 PetscScalar value; 497 PetscErrorCode ierr; 498 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 499 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 500 PetscBool roworiented = aij->roworiented; 501 502 /* Some Variables required in the macro */ 503 Mat A = aij->A; 504 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 505 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 506 MatScalar *aa = a->a; 507 PetscBool ignorezeroentries = a->ignorezeroentries; 508 Mat B = aij->B; 509 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 510 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 511 MatScalar *ba = b->a; 512 513 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 514 PetscInt nonew; 515 MatScalar *ap1,*ap2; 516 517 PetscFunctionBegin; 518 for (i=0; i<m; i++) { 519 if (im[i] < 0) continue; 520 #if defined(PETSC_USE_DEBUG) 521 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); 522 #endif 523 if (im[i] >= rstart && im[i] < rend) { 524 row = im[i] - rstart; 525 lastcol1 = -1; 526 rp1 = aj + ai[row]; 527 ap1 = aa + ai[row]; 528 rmax1 = aimax[row]; 529 nrow1 = ailen[row]; 530 low1 = 0; 531 high1 = nrow1; 532 lastcol2 = -1; 533 rp2 = bj + bi[row]; 534 ap2 = ba + bi[row]; 535 rmax2 = bimax[row]; 536 nrow2 = bilen[row]; 537 low2 = 0; 538 high2 = nrow2; 539 540 for (j=0; j<n; j++) { 541 if (roworiented) value = v[i*n+j]; 542 else value = v[i+j*m]; 543 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 544 if (in[j] >= cstart && in[j] < cend) { 545 col = in[j] - cstart; 546 nonew = a->nonew; 547 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 548 } else if (in[j] < 0) continue; 549 #if defined(PETSC_USE_DEBUG) 550 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); 551 #endif 552 else { 553 if (mat->was_assembled) { 554 if (!aij->colmap) { 555 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 556 } 557 #if defined(PETSC_USE_CTABLE) 558 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 559 col--; 560 #else 561 col = aij->colmap[in[j]] - 1; 562 #endif 563 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 564 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 565 col = in[j]; 566 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 567 B = aij->B; 568 b = (Mat_SeqAIJ*)B->data; 569 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 570 rp2 = bj + bi[row]; 571 ap2 = ba + bi[row]; 572 rmax2 = bimax[row]; 573 nrow2 = bilen[row]; 574 low2 = 0; 575 high2 = nrow2; 576 bm = aij->B->rmap->n; 577 ba = b->a; 578 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 579 } else col = in[j]; 580 nonew = b->nonew; 581 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 582 } 583 } 584 } else { 585 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]); 586 if (!aij->donotstash) { 587 mat->assembled = PETSC_FALSE; 588 if (roworiented) { 589 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 590 } else { 591 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 592 } 593 } 594 } 595 } 596 PetscFunctionReturn(0); 597 } 598 599 #undef __FUNCT__ 600 #define __FUNCT__ "MatGetValues_MPIAIJ" 601 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 602 { 603 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 604 PetscErrorCode ierr; 605 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 606 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 607 608 PetscFunctionBegin; 609 for (i=0; i<m; i++) { 610 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 611 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); 612 if (idxm[i] >= rstart && idxm[i] < rend) { 613 row = idxm[i] - rstart; 614 for (j=0; j<n; j++) { 615 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 616 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); 617 if (idxn[j] >= cstart && idxn[j] < cend) { 618 col = idxn[j] - cstart; 619 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 620 } else { 621 if (!aij->colmap) { 622 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 623 } 624 #if defined(PETSC_USE_CTABLE) 625 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 626 col--; 627 #else 628 col = aij->colmap[idxn[j]] - 1; 629 #endif 630 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 631 else { 632 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 633 } 634 } 635 } 636 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 637 } 638 PetscFunctionReturn(0); 639 } 640 641 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 642 643 #undef __FUNCT__ 644 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 645 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 646 { 647 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 648 PetscErrorCode ierr; 649 PetscInt nstash,reallocs; 650 InsertMode addv; 651 652 PetscFunctionBegin; 653 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 654 655 /* make sure all processors are either in INSERTMODE or ADDMODE */ 656 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 657 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 658 mat->insertmode = addv; /* in case this processor had no cache */ 659 660 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 661 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 662 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 663 PetscFunctionReturn(0); 664 } 665 666 #undef __FUNCT__ 667 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 668 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 669 { 670 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 671 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 672 PetscErrorCode ierr; 673 PetscMPIInt n; 674 PetscInt i,j,rstart,ncols,flg; 675 PetscInt *row,*col; 676 PetscBool other_disassembled; 677 PetscScalar *val; 678 InsertMode addv = mat->insertmode; 679 680 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 681 682 PetscFunctionBegin; 683 if (!aij->donotstash && !mat->nooffprocentries) { 684 while (1) { 685 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 686 if (!flg) break; 687 688 for (i=0; i<n; ) { 689 /* Now identify the consecutive vals belonging to the same row */ 690 for (j=i,rstart=row[j]; j<n; j++) { 691 if (row[j] != rstart) break; 692 } 693 if (j < n) ncols = j-i; 694 else ncols = n-i; 695 /* Now assemble all these values with a single function call */ 696 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 697 698 i = j; 699 } 700 } 701 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 702 } 703 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 704 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 705 706 /* determine if any processor has disassembled, if so we must 707 also disassemble ourselfs, in order that we may reassemble. */ 708 /* 709 if nonzero structure of submatrix B cannot change then we know that 710 no processor disassembled thus we can skip this stuff 711 */ 712 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 713 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 714 if (mat->was_assembled && !other_disassembled) { 715 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 716 } 717 } 718 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 719 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 720 } 721 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 722 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 723 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 724 725 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 726 727 aij->rowvalues = 0; 728 729 /* used by MatAXPY() */ 730 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 731 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 732 733 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 734 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 735 736 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 737 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 738 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 739 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 740 } 741 PetscFunctionReturn(0); 742 } 743 744 #undef __FUNCT__ 745 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 746 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 747 { 748 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 749 PetscErrorCode ierr; 750 751 PetscFunctionBegin; 752 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 753 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 754 PetscFunctionReturn(0); 755 } 756 757 #undef __FUNCT__ 758 #define __FUNCT__ "MatZeroRows_MPIAIJ" 759 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 760 { 761 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 762 PetscInt *owners = A->rmap->range; 763 PetscInt n = A->rmap->n; 764 PetscSF sf; 765 PetscInt *lrows; 766 PetscSFNode *rrows; 767 PetscInt r, p = 0, len = 0; 768 PetscErrorCode ierr; 769 770 PetscFunctionBegin; 771 /* Create SF where leaves are input rows and roots are owned rows */ 772 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 773 for (r = 0; r < n; ++r) lrows[r] = -1; 774 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 775 for (r = 0; r < N; ++r) { 776 const PetscInt idx = rows[r]; 777 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); 778 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 779 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 780 } 781 if (A->nooffproczerorows) { 782 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 783 lrows[len++] = idx - owners[p]; 784 } else { 785 rrows[r].rank = p; 786 rrows[r].index = rows[r] - owners[p]; 787 } 788 } 789 if (!A->nooffproczerorows) { 790 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 791 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 792 /* Collect flags for rows to be zeroed */ 793 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 794 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 795 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 796 /* Compress and put in row numbers */ 797 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 798 } 799 /* fix right hand side if needed */ 800 if (x && b) { 801 const PetscScalar *xx; 802 PetscScalar *bb; 803 804 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 805 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 806 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 807 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 808 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 809 } 810 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 811 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 812 if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) { 813 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 814 } else if (diag != 0.0) { 815 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 816 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"); 817 for (r = 0; r < len; ++r) { 818 const PetscInt row = lrows[r] + A->rmap->rstart; 819 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 820 } 821 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 822 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 823 } else { 824 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 825 } 826 ierr = PetscFree(lrows);CHKERRQ(ierr); 827 828 /* only change matrix nonzero state if pattern was allowed to be changed */ 829 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 830 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 831 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 832 } 833 PetscFunctionReturn(0); 834 } 835 836 #undef __FUNCT__ 837 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 838 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 839 { 840 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 841 PetscErrorCode ierr; 842 PetscMPIInt n = A->rmap->n; 843 PetscInt i,j,r,m,p = 0,len = 0; 844 PetscInt *lrows,*owners = A->rmap->range; 845 PetscSFNode *rrows; 846 PetscSF sf; 847 const PetscScalar *xx; 848 PetscScalar *bb,*mask; 849 Vec xmask,lmask; 850 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 851 const PetscInt *aj, *ii,*ridx; 852 PetscScalar *aa; 853 854 PetscFunctionBegin; 855 /* Create SF where leaves are input rows and roots are owned rows */ 856 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 857 for (r = 0; r < n; ++r) lrows[r] = -1; 858 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 859 for (r = 0; r < N; ++r) { 860 const PetscInt idx = rows[r]; 861 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); 862 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 863 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 864 } 865 rrows[r].rank = p; 866 rrows[r].index = rows[r] - owners[p]; 867 } 868 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 869 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 870 /* Collect flags for rows to be zeroed */ 871 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 872 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 873 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 874 /* Compress and put in row numbers */ 875 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 876 /* zero diagonal part of matrix */ 877 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 878 /* handle off diagonal part of matrix */ 879 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 880 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 881 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 882 for (i=0; i<len; i++) bb[lrows[i]] = 1; 883 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 884 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 885 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 886 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 887 if (x) { 888 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 889 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 890 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 891 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 892 } 893 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 894 /* remove zeroed rows of off diagonal matrix */ 895 ii = aij->i; 896 for (i=0; i<len; i++) { 897 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 898 } 899 /* loop over all elements of off process part of matrix zeroing removed columns*/ 900 if (aij->compressedrow.use) { 901 m = aij->compressedrow.nrows; 902 ii = aij->compressedrow.i; 903 ridx = aij->compressedrow.rindex; 904 for (i=0; i<m; i++) { 905 n = ii[i+1] - ii[i]; 906 aj = aij->j + ii[i]; 907 aa = aij->a + ii[i]; 908 909 for (j=0; j<n; j++) { 910 if (PetscAbsScalar(mask[*aj])) { 911 if (b) bb[*ridx] -= *aa*xx[*aj]; 912 *aa = 0.0; 913 } 914 aa++; 915 aj++; 916 } 917 ridx++; 918 } 919 } else { /* do not use compressed row format */ 920 m = l->B->rmap->n; 921 for (i=0; i<m; i++) { 922 n = ii[i+1] - ii[i]; 923 aj = aij->j + ii[i]; 924 aa = aij->a + ii[i]; 925 for (j=0; j<n; j++) { 926 if (PetscAbsScalar(mask[*aj])) { 927 if (b) bb[i] -= *aa*xx[*aj]; 928 *aa = 0.0; 929 } 930 aa++; 931 aj++; 932 } 933 } 934 } 935 if (x) { 936 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 937 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 938 } 939 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 940 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 941 ierr = PetscFree(lrows);CHKERRQ(ierr); 942 943 /* only change matrix nonzero state if pattern was allowed to be changed */ 944 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 945 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 946 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 947 } 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatMult_MPIAIJ" 953 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 954 { 955 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 956 PetscErrorCode ierr; 957 PetscInt nt; 958 959 PetscFunctionBegin; 960 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 961 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); 962 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 963 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 964 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 965 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 966 PetscFunctionReturn(0); 967 } 968 969 #undef __FUNCT__ 970 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 971 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 972 { 973 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 974 PetscErrorCode ierr; 975 976 PetscFunctionBegin; 977 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 978 PetscFunctionReturn(0); 979 } 980 981 #undef __FUNCT__ 982 #define __FUNCT__ "MatMultAdd_MPIAIJ" 983 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 984 { 985 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 986 PetscErrorCode ierr; 987 988 PetscFunctionBegin; 989 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 990 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 991 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 992 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 993 PetscFunctionReturn(0); 994 } 995 996 #undef __FUNCT__ 997 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 998 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 999 { 1000 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1001 PetscErrorCode ierr; 1002 PetscBool merged; 1003 1004 PetscFunctionBegin; 1005 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1006 /* do nondiagonal part */ 1007 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1008 if (!merged) { 1009 /* send it on its way */ 1010 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1011 /* do local part */ 1012 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1013 /* receive remote parts: note this assumes the values are not actually */ 1014 /* added in yy until the next line, */ 1015 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1016 } else { 1017 /* do local part */ 1018 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1019 /* send it on its way */ 1020 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1021 /* values actually were received in the Begin() but we need to call this nop */ 1022 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1023 } 1024 PetscFunctionReturn(0); 1025 } 1026 1027 #undef __FUNCT__ 1028 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1029 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1030 { 1031 MPI_Comm comm; 1032 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1033 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1034 IS Me,Notme; 1035 PetscErrorCode ierr; 1036 PetscInt M,N,first,last,*notme,i; 1037 PetscMPIInt size; 1038 1039 PetscFunctionBegin; 1040 /* Easy test: symmetric diagonal block */ 1041 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1042 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1043 if (!*f) PetscFunctionReturn(0); 1044 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1045 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1046 if (size == 1) PetscFunctionReturn(0); 1047 1048 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1049 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1050 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1051 ierr = PetscMalloc1((N-last+first),¬me);CHKERRQ(ierr); 1052 for (i=0; i<first; i++) notme[i] = i; 1053 for (i=last; i<M; i++) notme[i-last+first] = i; 1054 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1055 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1056 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1057 Aoff = Aoffs[0]; 1058 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1059 Boff = Boffs[0]; 1060 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1061 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1062 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1063 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1064 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1065 ierr = PetscFree(notme);CHKERRQ(ierr); 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1071 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1072 { 1073 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 /* do nondiagonal part */ 1078 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1079 /* send it on its way */ 1080 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1081 /* do local part */ 1082 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1083 /* receive remote parts */ 1084 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1085 PetscFunctionReturn(0); 1086 } 1087 1088 /* 1089 This only works correctly for square matrices where the subblock A->A is the 1090 diagonal block 1091 */ 1092 #undef __FUNCT__ 1093 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1094 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1095 { 1096 PetscErrorCode ierr; 1097 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1098 1099 PetscFunctionBegin; 1100 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1101 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"); 1102 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1103 PetscFunctionReturn(0); 1104 } 1105 1106 #undef __FUNCT__ 1107 #define __FUNCT__ "MatScale_MPIAIJ" 1108 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1109 { 1110 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1111 PetscErrorCode ierr; 1112 1113 PetscFunctionBegin; 1114 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1115 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 #undef __FUNCT__ 1120 #define __FUNCT__ "MatDestroy_Redundant" 1121 PetscErrorCode MatDestroy_Redundant(Mat_Redundant **redundant) 1122 { 1123 PetscErrorCode ierr; 1124 Mat_Redundant *redund = *redundant; 1125 PetscInt i; 1126 1127 PetscFunctionBegin; 1128 *redundant = NULL; 1129 if (redund){ 1130 if (redund->matseq) { /* via MatGetSubMatrices() */ 1131 ierr = ISDestroy(&redund->isrow);CHKERRQ(ierr); 1132 ierr = ISDestroy(&redund->iscol);CHKERRQ(ierr); 1133 ierr = MatDestroy(&redund->matseq[0]);CHKERRQ(ierr); 1134 ierr = PetscFree(redund->matseq);CHKERRQ(ierr); 1135 } else { 1136 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 1137 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1138 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1139 for (i=0; i<redund->nrecvs; i++) { 1140 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1141 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1142 } 1143 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1144 } 1145 1146 if (redund->subcomm) { 1147 ierr = PetscCommDestroy(&redund->subcomm);CHKERRQ(ierr); 1148 } 1149 ierr = PetscFree(redund);CHKERRQ(ierr); 1150 } 1151 PetscFunctionReturn(0); 1152 } 1153 1154 #undef __FUNCT__ 1155 #define __FUNCT__ "MatDestroy_MPIAIJ" 1156 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1157 { 1158 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1159 PetscErrorCode ierr; 1160 1161 PetscFunctionBegin; 1162 #if defined(PETSC_USE_LOG) 1163 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1164 #endif 1165 ierr = MatDestroy_Redundant(&mat->redundant);CHKERRQ(ierr); 1166 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1167 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1168 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1169 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1170 #if defined(PETSC_USE_CTABLE) 1171 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1172 #else 1173 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1174 #endif 1175 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1176 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1177 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1178 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1179 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1180 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1181 1182 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1184 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1185 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1186 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1187 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1188 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1189 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1190 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1191 #if defined(PETSC_HAVE_ELEMENTAL) 1192 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1193 #endif 1194 PetscFunctionReturn(0); 1195 } 1196 1197 #undef __FUNCT__ 1198 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1199 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1200 { 1201 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1202 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1203 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1204 PetscErrorCode ierr; 1205 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1206 int fd; 1207 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1208 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1209 PetscScalar *column_values; 1210 PetscInt message_count,flowcontrolcount; 1211 FILE *file; 1212 1213 PetscFunctionBegin; 1214 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1215 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1216 nz = A->nz + B->nz; 1217 if (!rank) { 1218 header[0] = MAT_FILE_CLASSID; 1219 header[1] = mat->rmap->N; 1220 header[2] = mat->cmap->N; 1221 1222 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1223 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1224 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1225 /* get largest number of rows any processor has */ 1226 rlen = mat->rmap->n; 1227 range = mat->rmap->range; 1228 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1229 } else { 1230 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1231 rlen = mat->rmap->n; 1232 } 1233 1234 /* load up the local row counts */ 1235 ierr = PetscMalloc1((rlen+1),&row_lengths);CHKERRQ(ierr); 1236 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]; 1237 1238 /* store the row lengths to the file */ 1239 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1240 if (!rank) { 1241 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1242 for (i=1; i<size; i++) { 1243 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1244 rlen = range[i+1] - range[i]; 1245 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1247 } 1248 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1249 } else { 1250 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1251 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1252 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1253 } 1254 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1255 1256 /* load up the local column indices */ 1257 nzmax = nz; /* th processor needs space a largest processor needs */ 1258 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1259 ierr = PetscMalloc1((nzmax+1),&column_indices);CHKERRQ(ierr); 1260 cnt = 0; 1261 for (i=0; i<mat->rmap->n; i++) { 1262 for (j=B->i[i]; j<B->i[i+1]; j++) { 1263 if ((col = garray[B->j[j]]) > cstart) break; 1264 column_indices[cnt++] = col; 1265 } 1266 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1267 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1268 } 1269 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); 1270 1271 /* store the column indices to the file */ 1272 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1273 if (!rank) { 1274 MPI_Status status; 1275 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1276 for (i=1; i<size; i++) { 1277 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1278 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1279 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1280 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1281 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1282 } 1283 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1284 } else { 1285 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1286 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1287 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1288 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1289 } 1290 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1291 1292 /* load up the local column values */ 1293 ierr = PetscMalloc1((nzmax+1),&column_values);CHKERRQ(ierr); 1294 cnt = 0; 1295 for (i=0; i<mat->rmap->n; i++) { 1296 for (j=B->i[i]; j<B->i[i+1]; j++) { 1297 if (garray[B->j[j]] > cstart) break; 1298 column_values[cnt++] = B->a[j]; 1299 } 1300 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1301 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1302 } 1303 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); 1304 1305 /* store the column values to the file */ 1306 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1307 if (!rank) { 1308 MPI_Status status; 1309 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1310 for (i=1; i<size; i++) { 1311 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1312 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1313 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1314 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1315 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1316 } 1317 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1318 } else { 1319 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1320 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1321 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1322 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1323 } 1324 ierr = PetscFree(column_values);CHKERRQ(ierr); 1325 1326 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1327 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1328 PetscFunctionReturn(0); 1329 } 1330 1331 #include <petscdraw.h> 1332 #undef __FUNCT__ 1333 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1334 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1335 { 1336 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1337 PetscErrorCode ierr; 1338 PetscMPIInt rank = aij->rank,size = aij->size; 1339 PetscBool isdraw,iascii,isbinary; 1340 PetscViewer sviewer; 1341 PetscViewerFormat format; 1342 1343 PetscFunctionBegin; 1344 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1345 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1346 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1347 if (iascii) { 1348 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1349 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1350 MatInfo info; 1351 PetscBool inodes; 1352 1353 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1354 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1355 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1356 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1357 if (!inodes) { 1358 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1359 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1360 } else { 1361 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1362 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1363 } 1364 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1365 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1366 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1367 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1368 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1369 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1370 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1371 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1372 PetscFunctionReturn(0); 1373 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1374 PetscInt inodecount,inodelimit,*inodes; 1375 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1376 if (inodes) { 1377 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1378 } else { 1379 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1380 } 1381 PetscFunctionReturn(0); 1382 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1383 PetscFunctionReturn(0); 1384 } 1385 } else if (isbinary) { 1386 if (size == 1) { 1387 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1388 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1389 } else { 1390 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1391 } 1392 PetscFunctionReturn(0); 1393 } else if (isdraw) { 1394 PetscDraw draw; 1395 PetscBool isnull; 1396 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1397 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1398 } 1399 1400 { 1401 /* assemble the entire matrix onto first processor. */ 1402 Mat A; 1403 Mat_SeqAIJ *Aloc; 1404 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1405 MatScalar *a; 1406 1407 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1408 if (!rank) { 1409 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1410 } else { 1411 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1412 } 1413 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1414 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1415 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1416 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1417 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1418 1419 /* copy over the A part */ 1420 Aloc = (Mat_SeqAIJ*)aij->A->data; 1421 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1422 row = mat->rmap->rstart; 1423 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1424 for (i=0; i<m; i++) { 1425 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1426 row++; 1427 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1428 } 1429 aj = Aloc->j; 1430 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1431 1432 /* copy over the B part */ 1433 Aloc = (Mat_SeqAIJ*)aij->B->data; 1434 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1435 row = mat->rmap->rstart; 1436 ierr = PetscMalloc1((ai[m]+1),&cols);CHKERRQ(ierr); 1437 ct = cols; 1438 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1439 for (i=0; i<m; i++) { 1440 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1441 row++; 1442 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1443 } 1444 ierr = PetscFree(ct);CHKERRQ(ierr); 1445 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1446 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1447 /* 1448 Everyone has to call to draw the matrix since the graphics waits are 1449 synchronized across all processors that share the PetscDraw object 1450 */ 1451 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1452 if (!rank) { 1453 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1454 } 1455 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1456 ierr = MatDestroy(&A);CHKERRQ(ierr); 1457 } 1458 PetscFunctionReturn(0); 1459 } 1460 1461 #undef __FUNCT__ 1462 #define __FUNCT__ "MatView_MPIAIJ" 1463 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1464 { 1465 PetscErrorCode ierr; 1466 PetscBool iascii,isdraw,issocket,isbinary; 1467 1468 PetscFunctionBegin; 1469 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1470 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1471 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1472 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1473 if (iascii || isdraw || isbinary || issocket) { 1474 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1475 } 1476 PetscFunctionReturn(0); 1477 } 1478 1479 #undef __FUNCT__ 1480 #define __FUNCT__ "MatSOR_MPIAIJ" 1481 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1482 { 1483 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1484 PetscErrorCode ierr; 1485 Vec bb1 = 0; 1486 PetscBool hasop; 1487 1488 PetscFunctionBegin; 1489 if (flag == SOR_APPLY_UPPER) { 1490 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1491 PetscFunctionReturn(0); 1492 } 1493 1494 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1495 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1496 } 1497 1498 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1499 if (flag & SOR_ZERO_INITIAL_GUESS) { 1500 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1501 its--; 1502 } 1503 1504 while (its--) { 1505 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1506 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1507 1508 /* update rhs: bb1 = bb - B*x */ 1509 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1510 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1511 1512 /* local sweep */ 1513 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1514 } 1515 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1516 if (flag & SOR_ZERO_INITIAL_GUESS) { 1517 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1518 its--; 1519 } 1520 while (its--) { 1521 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1522 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1523 1524 /* update rhs: bb1 = bb - B*x */ 1525 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1526 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1527 1528 /* local sweep */ 1529 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1530 } 1531 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1532 if (flag & SOR_ZERO_INITIAL_GUESS) { 1533 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1534 its--; 1535 } 1536 while (its--) { 1537 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1538 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1539 1540 /* update rhs: bb1 = bb - B*x */ 1541 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1542 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1543 1544 /* local sweep */ 1545 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1546 } 1547 } else if (flag & SOR_EISENSTAT) { 1548 Vec xx1; 1549 1550 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1551 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1552 1553 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1554 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1555 if (!mat->diag) { 1556 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1557 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1558 } 1559 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1560 if (hasop) { 1561 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1562 } else { 1563 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1564 } 1565 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1566 1567 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1568 1569 /* local sweep */ 1570 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1571 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1572 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1573 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1574 1575 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1576 PetscFunctionReturn(0); 1577 } 1578 1579 #undef __FUNCT__ 1580 #define __FUNCT__ "MatPermute_MPIAIJ" 1581 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1582 { 1583 Mat aA,aB,Aperm; 1584 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1585 PetscScalar *aa,*ba; 1586 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1587 PetscSF rowsf,sf; 1588 IS parcolp = NULL; 1589 PetscBool done; 1590 PetscErrorCode ierr; 1591 1592 PetscFunctionBegin; 1593 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1594 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1595 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1596 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1597 1598 /* Invert row permutation to find out where my rows should go */ 1599 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1600 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1601 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1602 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1603 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1604 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1605 1606 /* Invert column permutation to find out where my columns should go */ 1607 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1608 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1609 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1610 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1611 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1612 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1613 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1614 1615 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1616 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1617 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1618 1619 /* Find out where my gcols should go */ 1620 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1621 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1622 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1623 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1624 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1625 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1626 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1627 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1628 1629 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1630 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1631 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1632 for (i=0; i<m; i++) { 1633 PetscInt row = rdest[i],rowner; 1634 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1635 for (j=ai[i]; j<ai[i+1]; j++) { 1636 PetscInt cowner,col = cdest[aj[j]]; 1637 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1638 if (rowner == cowner) dnnz[i]++; 1639 else onnz[i]++; 1640 } 1641 for (j=bi[i]; j<bi[i+1]; j++) { 1642 PetscInt cowner,col = gcdest[bj[j]]; 1643 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1644 if (rowner == cowner) dnnz[i]++; 1645 else onnz[i]++; 1646 } 1647 } 1648 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1649 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1650 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1651 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1652 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1653 1654 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1655 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1656 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1657 for (i=0; i<m; i++) { 1658 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1659 PetscInt j0,rowlen; 1660 rowlen = ai[i+1] - ai[i]; 1661 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1662 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1663 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1664 } 1665 rowlen = bi[i+1] - bi[i]; 1666 for (j0=j=0; j<rowlen; j0=j) { 1667 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1668 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1669 } 1670 } 1671 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1672 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1673 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1674 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1675 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1676 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1677 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1678 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1679 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1680 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1681 *B = Aperm; 1682 PetscFunctionReturn(0); 1683 } 1684 1685 #undef __FUNCT__ 1686 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1687 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1688 { 1689 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1690 Mat A = mat->A,B = mat->B; 1691 PetscErrorCode ierr; 1692 PetscReal isend[5],irecv[5]; 1693 1694 PetscFunctionBegin; 1695 info->block_size = 1.0; 1696 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1697 1698 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1699 isend[3] = info->memory; isend[4] = info->mallocs; 1700 1701 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1702 1703 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1704 isend[3] += info->memory; isend[4] += info->mallocs; 1705 if (flag == MAT_LOCAL) { 1706 info->nz_used = isend[0]; 1707 info->nz_allocated = isend[1]; 1708 info->nz_unneeded = isend[2]; 1709 info->memory = isend[3]; 1710 info->mallocs = isend[4]; 1711 } else if (flag == MAT_GLOBAL_MAX) { 1712 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1713 1714 info->nz_used = irecv[0]; 1715 info->nz_allocated = irecv[1]; 1716 info->nz_unneeded = irecv[2]; 1717 info->memory = irecv[3]; 1718 info->mallocs = irecv[4]; 1719 } else if (flag == MAT_GLOBAL_SUM) { 1720 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1721 1722 info->nz_used = irecv[0]; 1723 info->nz_allocated = irecv[1]; 1724 info->nz_unneeded = irecv[2]; 1725 info->memory = irecv[3]; 1726 info->mallocs = irecv[4]; 1727 } 1728 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1729 info->fill_ratio_needed = 0; 1730 info->factor_mallocs = 0; 1731 PetscFunctionReturn(0); 1732 } 1733 1734 #undef __FUNCT__ 1735 #define __FUNCT__ "MatSetOption_MPIAIJ" 1736 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1737 { 1738 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1739 PetscErrorCode ierr; 1740 1741 PetscFunctionBegin; 1742 switch (op) { 1743 case MAT_NEW_NONZERO_LOCATIONS: 1744 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1745 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1746 case MAT_KEEP_NONZERO_PATTERN: 1747 case MAT_NEW_NONZERO_LOCATION_ERR: 1748 case MAT_USE_INODES: 1749 case MAT_IGNORE_ZERO_ENTRIES: 1750 MatCheckPreallocated(A,1); 1751 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1752 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1753 break; 1754 case MAT_ROW_ORIENTED: 1755 a->roworiented = flg; 1756 1757 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1758 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1759 break; 1760 case MAT_NEW_DIAGONALS: 1761 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1762 break; 1763 case MAT_IGNORE_OFF_PROC_ENTRIES: 1764 a->donotstash = flg; 1765 break; 1766 case MAT_SPD: 1767 A->spd_set = PETSC_TRUE; 1768 A->spd = flg; 1769 if (flg) { 1770 A->symmetric = PETSC_TRUE; 1771 A->structurally_symmetric = PETSC_TRUE; 1772 A->symmetric_set = PETSC_TRUE; 1773 A->structurally_symmetric_set = PETSC_TRUE; 1774 } 1775 break; 1776 case MAT_SYMMETRIC: 1777 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1778 break; 1779 case MAT_STRUCTURALLY_SYMMETRIC: 1780 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1781 break; 1782 case MAT_HERMITIAN: 1783 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1784 break; 1785 case MAT_SYMMETRY_ETERNAL: 1786 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1787 break; 1788 default: 1789 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1790 } 1791 PetscFunctionReturn(0); 1792 } 1793 1794 #undef __FUNCT__ 1795 #define __FUNCT__ "MatGetRow_MPIAIJ" 1796 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1797 { 1798 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1799 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1800 PetscErrorCode ierr; 1801 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1802 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1803 PetscInt *cmap,*idx_p; 1804 1805 PetscFunctionBegin; 1806 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1807 mat->getrowactive = PETSC_TRUE; 1808 1809 if (!mat->rowvalues && (idx || v)) { 1810 /* 1811 allocate enough space to hold information from the longest row. 1812 */ 1813 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1814 PetscInt max = 1,tmp; 1815 for (i=0; i<matin->rmap->n; i++) { 1816 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1817 if (max < tmp) max = tmp; 1818 } 1819 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1820 } 1821 1822 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1823 lrow = row - rstart; 1824 1825 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1826 if (!v) {pvA = 0; pvB = 0;} 1827 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1828 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1829 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1830 nztot = nzA + nzB; 1831 1832 cmap = mat->garray; 1833 if (v || idx) { 1834 if (nztot) { 1835 /* Sort by increasing column numbers, assuming A and B already sorted */ 1836 PetscInt imark = -1; 1837 if (v) { 1838 *v = v_p = mat->rowvalues; 1839 for (i=0; i<nzB; i++) { 1840 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1841 else break; 1842 } 1843 imark = i; 1844 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1845 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1846 } 1847 if (idx) { 1848 *idx = idx_p = mat->rowindices; 1849 if (imark > -1) { 1850 for (i=0; i<imark; i++) { 1851 idx_p[i] = cmap[cworkB[i]]; 1852 } 1853 } else { 1854 for (i=0; i<nzB; i++) { 1855 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1856 else break; 1857 } 1858 imark = i; 1859 } 1860 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1861 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1862 } 1863 } else { 1864 if (idx) *idx = 0; 1865 if (v) *v = 0; 1866 } 1867 } 1868 *nz = nztot; 1869 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1870 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1871 PetscFunctionReturn(0); 1872 } 1873 1874 #undef __FUNCT__ 1875 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1876 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1877 { 1878 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1879 1880 PetscFunctionBegin; 1881 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1882 aij->getrowactive = PETSC_FALSE; 1883 PetscFunctionReturn(0); 1884 } 1885 1886 #undef __FUNCT__ 1887 #define __FUNCT__ "MatNorm_MPIAIJ" 1888 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1889 { 1890 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1891 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1892 PetscErrorCode ierr; 1893 PetscInt i,j,cstart = mat->cmap->rstart; 1894 PetscReal sum = 0.0; 1895 MatScalar *v; 1896 1897 PetscFunctionBegin; 1898 if (aij->size == 1) { 1899 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1900 } else { 1901 if (type == NORM_FROBENIUS) { 1902 v = amat->a; 1903 for (i=0; i<amat->nz; i++) { 1904 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1905 } 1906 v = bmat->a; 1907 for (i=0; i<bmat->nz; i++) { 1908 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1909 } 1910 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1911 *norm = PetscSqrtReal(*norm); 1912 } else if (type == NORM_1) { /* max column norm */ 1913 PetscReal *tmp,*tmp2; 1914 PetscInt *jj,*garray = aij->garray; 1915 ierr = PetscCalloc1((mat->cmap->N+1),&tmp);CHKERRQ(ierr); 1916 ierr = PetscMalloc1((mat->cmap->N+1),&tmp2);CHKERRQ(ierr); 1917 *norm = 0.0; 1918 v = amat->a; jj = amat->j; 1919 for (j=0; j<amat->nz; j++) { 1920 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1921 } 1922 v = bmat->a; jj = bmat->j; 1923 for (j=0; j<bmat->nz; j++) { 1924 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1925 } 1926 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1927 for (j=0; j<mat->cmap->N; j++) { 1928 if (tmp2[j] > *norm) *norm = tmp2[j]; 1929 } 1930 ierr = PetscFree(tmp);CHKERRQ(ierr); 1931 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1932 } else if (type == NORM_INFINITY) { /* max row norm */ 1933 PetscReal ntemp = 0.0; 1934 for (j=0; j<aij->A->rmap->n; j++) { 1935 v = amat->a + amat->i[j]; 1936 sum = 0.0; 1937 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1938 sum += PetscAbsScalar(*v); v++; 1939 } 1940 v = bmat->a + bmat->i[j]; 1941 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1942 sum += PetscAbsScalar(*v); v++; 1943 } 1944 if (sum > ntemp) ntemp = sum; 1945 } 1946 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1947 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1948 } 1949 PetscFunctionReturn(0); 1950 } 1951 1952 #undef __FUNCT__ 1953 #define __FUNCT__ "MatTranspose_MPIAIJ" 1954 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1955 { 1956 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1957 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1958 PetscErrorCode ierr; 1959 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1960 PetscInt cstart = A->cmap->rstart,ncol; 1961 Mat B; 1962 MatScalar *array; 1963 1964 PetscFunctionBegin; 1965 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1966 1967 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1968 ai = Aloc->i; aj = Aloc->j; 1969 bi = Bloc->i; bj = Bloc->j; 1970 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1971 PetscInt *d_nnz,*g_nnz,*o_nnz; 1972 PetscSFNode *oloc; 1973 PETSC_UNUSED PetscSF sf; 1974 1975 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1976 /* compute d_nnz for preallocation */ 1977 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1978 for (i=0; i<ai[ma]; i++) { 1979 d_nnz[aj[i]]++; 1980 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1981 } 1982 /* compute local off-diagonal contributions */ 1983 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1984 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1985 /* map those to global */ 1986 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1987 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1988 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1989 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1990 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1991 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1992 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1993 1994 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1995 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1996 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1997 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1998 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1999 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2000 } else { 2001 B = *matout; 2002 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2003 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2004 } 2005 2006 /* copy over the A part */ 2007 array = Aloc->a; 2008 row = A->rmap->rstart; 2009 for (i=0; i<ma; i++) { 2010 ncol = ai[i+1]-ai[i]; 2011 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2012 row++; 2013 array += ncol; aj += ncol; 2014 } 2015 aj = Aloc->j; 2016 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2017 2018 /* copy over the B part */ 2019 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2020 array = Bloc->a; 2021 row = A->rmap->rstart; 2022 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2023 cols_tmp = cols; 2024 for (i=0; i<mb; i++) { 2025 ncol = bi[i+1]-bi[i]; 2026 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2027 row++; 2028 array += ncol; cols_tmp += ncol; 2029 } 2030 ierr = PetscFree(cols);CHKERRQ(ierr); 2031 2032 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2033 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2034 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2035 *matout = B; 2036 } else { 2037 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2038 } 2039 PetscFunctionReturn(0); 2040 } 2041 2042 #undef __FUNCT__ 2043 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2044 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2045 { 2046 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2047 Mat a = aij->A,b = aij->B; 2048 PetscErrorCode ierr; 2049 PetscInt s1,s2,s3; 2050 2051 PetscFunctionBegin; 2052 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2053 if (rr) { 2054 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2055 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2056 /* Overlap communication with computation. */ 2057 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2058 } 2059 if (ll) { 2060 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2061 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2062 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2063 } 2064 /* scale the diagonal block */ 2065 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2066 2067 if (rr) { 2068 /* Do a scatter end and then right scale the off-diagonal block */ 2069 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2070 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2071 } 2072 PetscFunctionReturn(0); 2073 } 2074 2075 #undef __FUNCT__ 2076 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2077 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2078 { 2079 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2080 PetscErrorCode ierr; 2081 2082 PetscFunctionBegin; 2083 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2084 PetscFunctionReturn(0); 2085 } 2086 2087 #undef __FUNCT__ 2088 #define __FUNCT__ "MatEqual_MPIAIJ" 2089 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2090 { 2091 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2092 Mat a,b,c,d; 2093 PetscBool flg; 2094 PetscErrorCode ierr; 2095 2096 PetscFunctionBegin; 2097 a = matA->A; b = matA->B; 2098 c = matB->A; d = matB->B; 2099 2100 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2101 if (flg) { 2102 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2103 } 2104 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2105 PetscFunctionReturn(0); 2106 } 2107 2108 #undef __FUNCT__ 2109 #define __FUNCT__ "MatCopy_MPIAIJ" 2110 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2111 { 2112 PetscErrorCode ierr; 2113 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2114 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2115 2116 PetscFunctionBegin; 2117 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2118 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2119 /* because of the column compression in the off-processor part of the matrix a->B, 2120 the number of columns in a->B and b->B may be different, hence we cannot call 2121 the MatCopy() directly on the two parts. If need be, we can provide a more 2122 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2123 then copying the submatrices */ 2124 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2125 } else { 2126 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2127 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2128 } 2129 PetscFunctionReturn(0); 2130 } 2131 2132 #undef __FUNCT__ 2133 #define __FUNCT__ "MatSetUp_MPIAIJ" 2134 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2135 { 2136 PetscErrorCode ierr; 2137 2138 PetscFunctionBegin; 2139 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2140 PetscFunctionReturn(0); 2141 } 2142 2143 /* 2144 Computes the number of nonzeros per row needed for preallocation when X and Y 2145 have different nonzero structure. 2146 */ 2147 #undef __FUNCT__ 2148 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2149 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) 2150 { 2151 PetscInt i,j,k,nzx,nzy; 2152 2153 PetscFunctionBegin; 2154 /* Set the number of nonzeros in the new matrix */ 2155 for (i=0; i<m; i++) { 2156 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2157 nzx = xi[i+1] - xi[i]; 2158 nzy = yi[i+1] - yi[i]; 2159 nnz[i] = 0; 2160 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2161 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2162 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2163 nnz[i]++; 2164 } 2165 for (; k<nzy; k++) nnz[i]++; 2166 } 2167 PetscFunctionReturn(0); 2168 } 2169 2170 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2171 #undef __FUNCT__ 2172 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2173 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2174 { 2175 PetscErrorCode ierr; 2176 PetscInt m = Y->rmap->N; 2177 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2178 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2179 2180 PetscFunctionBegin; 2181 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2182 PetscFunctionReturn(0); 2183 } 2184 2185 #undef __FUNCT__ 2186 #define __FUNCT__ "MatAXPY_MPIAIJ" 2187 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2188 { 2189 PetscErrorCode ierr; 2190 PetscInt i; 2191 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2192 PetscBLASInt bnz,one=1; 2193 Mat_SeqAIJ *x,*y; 2194 2195 PetscFunctionBegin; 2196 if (str == SAME_NONZERO_PATTERN) { 2197 PetscScalar alpha = a; 2198 x = (Mat_SeqAIJ*)xx->A->data; 2199 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2200 y = (Mat_SeqAIJ*)yy->A->data; 2201 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2202 x = (Mat_SeqAIJ*)xx->B->data; 2203 y = (Mat_SeqAIJ*)yy->B->data; 2204 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2205 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2206 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2207 } else if (str == SUBSET_NONZERO_PATTERN) { 2208 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2209 2210 x = (Mat_SeqAIJ*)xx->B->data; 2211 y = (Mat_SeqAIJ*)yy->B->data; 2212 if (y->xtoy && y->XtoY != xx->B) { 2213 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2214 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2215 } 2216 if (!y->xtoy) { /* get xtoy */ 2217 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2218 y->XtoY = xx->B; 2219 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2220 } 2221 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2222 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2223 } else { 2224 Mat B; 2225 PetscInt *nnz_d,*nnz_o; 2226 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2227 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2228 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2229 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2230 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2231 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2232 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2233 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2234 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2235 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2236 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2237 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2238 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2239 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2240 } 2241 PetscFunctionReturn(0); 2242 } 2243 2244 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2245 2246 #undef __FUNCT__ 2247 #define __FUNCT__ "MatConjugate_MPIAIJ" 2248 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2249 { 2250 #if defined(PETSC_USE_COMPLEX) 2251 PetscErrorCode ierr; 2252 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2253 2254 PetscFunctionBegin; 2255 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2256 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2257 #else 2258 PetscFunctionBegin; 2259 #endif 2260 PetscFunctionReturn(0); 2261 } 2262 2263 #undef __FUNCT__ 2264 #define __FUNCT__ "MatRealPart_MPIAIJ" 2265 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2266 { 2267 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2268 PetscErrorCode ierr; 2269 2270 PetscFunctionBegin; 2271 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2272 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2273 PetscFunctionReturn(0); 2274 } 2275 2276 #undef __FUNCT__ 2277 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2278 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2279 { 2280 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2281 PetscErrorCode ierr; 2282 2283 PetscFunctionBegin; 2284 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2285 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2286 PetscFunctionReturn(0); 2287 } 2288 2289 #if defined(PETSC_HAVE_PBGL) 2290 2291 #include <boost/parallel/mpi/bsp_process_group.hpp> 2292 #include <boost/graph/distributed/ilu_default_graph.hpp> 2293 #include <boost/graph/distributed/ilu_0_block.hpp> 2294 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2295 #include <boost/graph/distributed/petsc/interface.hpp> 2296 #include <boost/multi_array.hpp> 2297 #include <boost/parallel/distributed_property_map->hpp> 2298 2299 #undef __FUNCT__ 2300 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2301 /* 2302 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2303 */ 2304 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2305 { 2306 namespace petsc = boost::distributed::petsc; 2307 2308 namespace graph_dist = boost::graph::distributed; 2309 using boost::graph::distributed::ilu_default::process_group_type; 2310 using boost::graph::ilu_permuted; 2311 2312 PetscBool row_identity, col_identity; 2313 PetscContainer c; 2314 PetscInt m, n, M, N; 2315 PetscErrorCode ierr; 2316 2317 PetscFunctionBegin; 2318 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2319 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2320 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2321 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2322 2323 process_group_type pg; 2324 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2325 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2326 lgraph_type& level_graph = *lgraph_p; 2327 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2328 2329 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2330 ilu_permuted(level_graph); 2331 2332 /* put together the new matrix */ 2333 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2334 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2335 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2336 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2337 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2338 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2339 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2340 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2341 2342 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2343 ierr = PetscContainerSetPointer(c, lgraph_p); 2344 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2345 ierr = PetscContainerDestroy(&c); 2346 PetscFunctionReturn(0); 2347 } 2348 2349 #undef __FUNCT__ 2350 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2351 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2352 { 2353 PetscFunctionBegin; 2354 PetscFunctionReturn(0); 2355 } 2356 2357 #undef __FUNCT__ 2358 #define __FUNCT__ "MatSolve_MPIAIJ" 2359 /* 2360 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2361 */ 2362 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2363 { 2364 namespace graph_dist = boost::graph::distributed; 2365 2366 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2367 lgraph_type *lgraph_p; 2368 PetscContainer c; 2369 PetscErrorCode ierr; 2370 2371 PetscFunctionBegin; 2372 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2373 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2374 ierr = VecCopy(b, x);CHKERRQ(ierr); 2375 2376 PetscScalar *array_x; 2377 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2378 PetscInt sx; 2379 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2380 2381 PetscScalar *array_b; 2382 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2383 PetscInt sb; 2384 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2385 2386 lgraph_type& level_graph = *lgraph_p; 2387 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2388 2389 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2390 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2391 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2392 2393 typedef boost::iterator_property_map<array_ref_type::iterator, 2394 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2395 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2396 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2397 2398 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2399 PetscFunctionReturn(0); 2400 } 2401 #endif 2402 2403 #undef __FUNCT__ 2404 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2405 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2406 { 2407 PetscErrorCode ierr; 2408 MPI_Comm comm; 2409 PetscMPIInt size; 2410 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N,bs=mat->rmap->bs; 2411 Mat_Redundant *redund=NULL; 2412 PetscSubcomm psubcomm=NULL; 2413 MPI_Comm subcomm_in=subcomm; 2414 Mat *matseq; 2415 IS isrow,iscol; 2416 PetscBool newsubcomm=PETSC_FALSE; 2417 2418 PetscFunctionBegin; 2419 if (subcomm_in == MPI_COMM_NULL && reuse == MAT_INITIAL_MATRIX) { /* get subcomm if user does not provide subcomm */ 2420 /* create psubcomm, then get subcomm */ 2421 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2422 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2423 if (nsubcomm < 1 || nsubcomm > size) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"nsubcomm must between 1 and %D",size); 2424 2425 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2426 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2427 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2428 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2429 ierr = PetscCommDuplicate(psubcomm->comm,&subcomm,NULL);CHKERRQ(ierr); 2430 newsubcomm = PETSC_TRUE; 2431 ierr = PetscSubcommDestroy(&psubcomm);CHKERRQ(ierr); 2432 } 2433 2434 /* get isrow, iscol and a local sequential matrix matseq[0] */ 2435 if (reuse == MAT_INITIAL_MATRIX) { 2436 mloc_sub = PETSC_DECIDE; 2437 ierr = PetscSplitOwnershipBlock(subcomm,bs,&mloc_sub,&M);CHKERRQ(ierr); 2438 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2439 rstart = rend - mloc_sub; 2440 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2441 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2442 } else { /* reuse == MAT_REUSE_MATRIX */ 2443 /* retrieve subcomm */ 2444 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2445 redund = (*matredundant)->redundant; 2446 isrow = redund->isrow; 2447 iscol = redund->iscol; 2448 matseq = redund->matseq; 2449 } 2450 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2451 2452 /* get matredundant over subcomm */ 2453 ierr = MatCreateMPIMatConcatenateSeqMat(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2454 2455 if (reuse == MAT_INITIAL_MATRIX) { 2456 /* create a supporting struct and attach it to C for reuse */ 2457 ierr = PetscNewLog(*matredundant,&redund);CHKERRQ(ierr); 2458 (*matredundant)->redundant = redund; 2459 redund->isrow = isrow; 2460 redund->iscol = iscol; 2461 redund->matseq = matseq; 2462 if (newsubcomm) { 2463 redund->subcomm = subcomm; 2464 } else { 2465 redund->subcomm = MPI_COMM_NULL; 2466 } 2467 } 2468 PetscFunctionReturn(0); 2469 } 2470 2471 #undef __FUNCT__ 2472 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2473 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2474 { 2475 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2476 PetscErrorCode ierr; 2477 PetscInt i,*idxb = 0; 2478 PetscScalar *va,*vb; 2479 Vec vtmp; 2480 2481 PetscFunctionBegin; 2482 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2483 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2484 if (idx) { 2485 for (i=0; i<A->rmap->n; i++) { 2486 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2487 } 2488 } 2489 2490 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2491 if (idx) { 2492 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2493 } 2494 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2495 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2496 2497 for (i=0; i<A->rmap->n; i++) { 2498 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2499 va[i] = vb[i]; 2500 if (idx) idx[i] = a->garray[idxb[i]]; 2501 } 2502 } 2503 2504 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2505 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2506 ierr = PetscFree(idxb);CHKERRQ(ierr); 2507 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2508 PetscFunctionReturn(0); 2509 } 2510 2511 #undef __FUNCT__ 2512 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2513 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2514 { 2515 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2516 PetscErrorCode ierr; 2517 PetscInt i,*idxb = 0; 2518 PetscScalar *va,*vb; 2519 Vec vtmp; 2520 2521 PetscFunctionBegin; 2522 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2523 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2524 if (idx) { 2525 for (i=0; i<A->cmap->n; i++) { 2526 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2527 } 2528 } 2529 2530 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2531 if (idx) { 2532 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2533 } 2534 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2535 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2536 2537 for (i=0; i<A->rmap->n; i++) { 2538 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2539 va[i] = vb[i]; 2540 if (idx) idx[i] = a->garray[idxb[i]]; 2541 } 2542 } 2543 2544 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2545 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2546 ierr = PetscFree(idxb);CHKERRQ(ierr); 2547 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2548 PetscFunctionReturn(0); 2549 } 2550 2551 #undef __FUNCT__ 2552 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2553 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2554 { 2555 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2556 PetscInt n = A->rmap->n; 2557 PetscInt cstart = A->cmap->rstart; 2558 PetscInt *cmap = mat->garray; 2559 PetscInt *diagIdx, *offdiagIdx; 2560 Vec diagV, offdiagV; 2561 PetscScalar *a, *diagA, *offdiagA; 2562 PetscInt r; 2563 PetscErrorCode ierr; 2564 2565 PetscFunctionBegin; 2566 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2567 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2568 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2569 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2570 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2571 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2572 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2573 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2574 for (r = 0; r < n; ++r) { 2575 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2576 a[r] = diagA[r]; 2577 idx[r] = cstart + diagIdx[r]; 2578 } else { 2579 a[r] = offdiagA[r]; 2580 idx[r] = cmap[offdiagIdx[r]]; 2581 } 2582 } 2583 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2584 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2585 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2586 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2587 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2588 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2589 PetscFunctionReturn(0); 2590 } 2591 2592 #undef __FUNCT__ 2593 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2594 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2595 { 2596 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2597 PetscInt n = A->rmap->n; 2598 PetscInt cstart = A->cmap->rstart; 2599 PetscInt *cmap = mat->garray; 2600 PetscInt *diagIdx, *offdiagIdx; 2601 Vec diagV, offdiagV; 2602 PetscScalar *a, *diagA, *offdiagA; 2603 PetscInt r; 2604 PetscErrorCode ierr; 2605 2606 PetscFunctionBegin; 2607 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2608 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2609 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2610 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2611 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2612 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2613 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2614 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2615 for (r = 0; r < n; ++r) { 2616 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2617 a[r] = diagA[r]; 2618 idx[r] = cstart + diagIdx[r]; 2619 } else { 2620 a[r] = offdiagA[r]; 2621 idx[r] = cmap[offdiagIdx[r]]; 2622 } 2623 } 2624 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2625 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2626 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2627 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2628 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2629 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2630 PetscFunctionReturn(0); 2631 } 2632 2633 #undef __FUNCT__ 2634 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2635 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2636 { 2637 PetscErrorCode ierr; 2638 Mat *dummy; 2639 2640 PetscFunctionBegin; 2641 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2642 *newmat = *dummy; 2643 ierr = PetscFree(dummy);CHKERRQ(ierr); 2644 PetscFunctionReturn(0); 2645 } 2646 2647 #undef __FUNCT__ 2648 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2649 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2650 { 2651 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2652 PetscErrorCode ierr; 2653 2654 PetscFunctionBegin; 2655 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2656 PetscFunctionReturn(0); 2657 } 2658 2659 #undef __FUNCT__ 2660 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2661 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2662 { 2663 PetscErrorCode ierr; 2664 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2665 2666 PetscFunctionBegin; 2667 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2668 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2669 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2670 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2671 PetscFunctionReturn(0); 2672 } 2673 2674 /* -------------------------------------------------------------------*/ 2675 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2676 MatGetRow_MPIAIJ, 2677 MatRestoreRow_MPIAIJ, 2678 MatMult_MPIAIJ, 2679 /* 4*/ MatMultAdd_MPIAIJ, 2680 MatMultTranspose_MPIAIJ, 2681 MatMultTransposeAdd_MPIAIJ, 2682 #if defined(PETSC_HAVE_PBGL) 2683 MatSolve_MPIAIJ, 2684 #else 2685 0, 2686 #endif 2687 0, 2688 0, 2689 /*10*/ 0, 2690 0, 2691 0, 2692 MatSOR_MPIAIJ, 2693 MatTranspose_MPIAIJ, 2694 /*15*/ MatGetInfo_MPIAIJ, 2695 MatEqual_MPIAIJ, 2696 MatGetDiagonal_MPIAIJ, 2697 MatDiagonalScale_MPIAIJ, 2698 MatNorm_MPIAIJ, 2699 /*20*/ MatAssemblyBegin_MPIAIJ, 2700 MatAssemblyEnd_MPIAIJ, 2701 MatSetOption_MPIAIJ, 2702 MatZeroEntries_MPIAIJ, 2703 /*24*/ MatZeroRows_MPIAIJ, 2704 0, 2705 #if defined(PETSC_HAVE_PBGL) 2706 0, 2707 #else 2708 0, 2709 #endif 2710 0, 2711 0, 2712 /*29*/ MatSetUp_MPIAIJ, 2713 #if defined(PETSC_HAVE_PBGL) 2714 0, 2715 #else 2716 0, 2717 #endif 2718 0, 2719 0, 2720 0, 2721 /*34*/ MatDuplicate_MPIAIJ, 2722 0, 2723 0, 2724 0, 2725 0, 2726 /*39*/ MatAXPY_MPIAIJ, 2727 MatGetSubMatrices_MPIAIJ, 2728 MatIncreaseOverlap_MPIAIJ, 2729 MatGetValues_MPIAIJ, 2730 MatCopy_MPIAIJ, 2731 /*44*/ MatGetRowMax_MPIAIJ, 2732 MatScale_MPIAIJ, 2733 0, 2734 MatDiagonalSet_MPIAIJ, 2735 MatZeroRowsColumns_MPIAIJ, 2736 /*49*/ MatSetRandom_MPIAIJ, 2737 0, 2738 0, 2739 0, 2740 0, 2741 /*54*/ MatFDColoringCreate_MPIXAIJ, 2742 0, 2743 MatSetUnfactored_MPIAIJ, 2744 MatPermute_MPIAIJ, 2745 0, 2746 /*59*/ MatGetSubMatrix_MPIAIJ, 2747 MatDestroy_MPIAIJ, 2748 MatView_MPIAIJ, 2749 0, 2750 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2751 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2752 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2753 0, 2754 0, 2755 0, 2756 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2757 MatGetRowMinAbs_MPIAIJ, 2758 0, 2759 MatSetColoring_MPIAIJ, 2760 0, 2761 MatSetValuesAdifor_MPIAIJ, 2762 /*75*/ MatFDColoringApply_AIJ, 2763 0, 2764 0, 2765 0, 2766 MatFindZeroDiagonals_MPIAIJ, 2767 /*80*/ 0, 2768 0, 2769 0, 2770 /*83*/ MatLoad_MPIAIJ, 2771 0, 2772 0, 2773 0, 2774 0, 2775 0, 2776 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2777 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2778 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2779 MatPtAP_MPIAIJ_MPIAIJ, 2780 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2781 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2782 0, 2783 0, 2784 0, 2785 0, 2786 /*99*/ 0, 2787 0, 2788 0, 2789 MatConjugate_MPIAIJ, 2790 0, 2791 /*104*/MatSetValuesRow_MPIAIJ, 2792 MatRealPart_MPIAIJ, 2793 MatImaginaryPart_MPIAIJ, 2794 0, 2795 0, 2796 /*109*/0, 2797 MatGetRedundantMatrix_MPIAIJ, 2798 MatGetRowMin_MPIAIJ, 2799 0, 2800 0, 2801 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2802 0, 2803 0, 2804 0, 2805 0, 2806 /*119*/0, 2807 0, 2808 0, 2809 0, 2810 MatGetMultiProcBlock_MPIAIJ, 2811 /*124*/MatFindNonzeroRows_MPIAIJ, 2812 MatGetColumnNorms_MPIAIJ, 2813 MatInvertBlockDiagonal_MPIAIJ, 2814 0, 2815 MatGetSubMatricesParallel_MPIAIJ, 2816 /*129*/0, 2817 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2818 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2819 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2820 0, 2821 /*134*/0, 2822 0, 2823 0, 2824 0, 2825 0, 2826 /*139*/0, 2827 0, 2828 0, 2829 MatFDColoringSetUp_MPIXAIJ, 2830 0, 2831 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2832 }; 2833 2834 /* ----------------------------------------------------------------------------------------*/ 2835 2836 #undef __FUNCT__ 2837 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2838 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2839 { 2840 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2841 PetscErrorCode ierr; 2842 2843 PetscFunctionBegin; 2844 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2845 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2846 PetscFunctionReturn(0); 2847 } 2848 2849 #undef __FUNCT__ 2850 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2851 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2852 { 2853 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2854 PetscErrorCode ierr; 2855 2856 PetscFunctionBegin; 2857 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2858 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2859 PetscFunctionReturn(0); 2860 } 2861 2862 #undef __FUNCT__ 2863 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2864 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2865 { 2866 Mat_MPIAIJ *b; 2867 PetscErrorCode ierr; 2868 2869 PetscFunctionBegin; 2870 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2871 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2872 b = (Mat_MPIAIJ*)B->data; 2873 2874 if (!B->preallocated) { 2875 /* Explicitly create 2 MATSEQAIJ matrices. */ 2876 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2877 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2878 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2879 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2880 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2881 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2882 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2883 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2884 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2885 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2886 } 2887 2888 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2889 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2890 B->preallocated = PETSC_TRUE; 2891 PetscFunctionReturn(0); 2892 } 2893 2894 #undef __FUNCT__ 2895 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2896 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2897 { 2898 Mat mat; 2899 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2900 PetscErrorCode ierr; 2901 2902 PetscFunctionBegin; 2903 *newmat = 0; 2904 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2905 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2906 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2907 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2908 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2909 a = (Mat_MPIAIJ*)mat->data; 2910 2911 mat->factortype = matin->factortype; 2912 mat->assembled = PETSC_TRUE; 2913 mat->insertmode = NOT_SET_VALUES; 2914 mat->preallocated = PETSC_TRUE; 2915 2916 a->size = oldmat->size; 2917 a->rank = oldmat->rank; 2918 a->donotstash = oldmat->donotstash; 2919 a->roworiented = oldmat->roworiented; 2920 a->rowindices = 0; 2921 a->rowvalues = 0; 2922 a->getrowactive = PETSC_FALSE; 2923 2924 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2925 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2926 2927 if (oldmat->colmap) { 2928 #if defined(PETSC_USE_CTABLE) 2929 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2930 #else 2931 ierr = PetscMalloc1((mat->cmap->N),&a->colmap);CHKERRQ(ierr); 2932 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2933 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2934 #endif 2935 } else a->colmap = 0; 2936 if (oldmat->garray) { 2937 PetscInt len; 2938 len = oldmat->B->cmap->n; 2939 ierr = PetscMalloc1((len+1),&a->garray);CHKERRQ(ierr); 2940 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2941 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2942 } else a->garray = 0; 2943 2944 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2945 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2946 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2947 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2948 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2949 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2950 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2951 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2952 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2953 *newmat = mat; 2954 PetscFunctionReturn(0); 2955 } 2956 2957 2958 2959 #undef __FUNCT__ 2960 #define __FUNCT__ "MatLoad_MPIAIJ" 2961 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2962 { 2963 PetscScalar *vals,*svals; 2964 MPI_Comm comm; 2965 PetscErrorCode ierr; 2966 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2967 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 2968 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2969 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2970 PetscInt cend,cstart,n,*rowners,sizesset=1; 2971 int fd; 2972 PetscInt bs = 1; 2973 2974 PetscFunctionBegin; 2975 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2976 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2977 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2978 if (!rank) { 2979 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2980 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2981 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2982 } 2983 2984 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 2985 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2986 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2987 2988 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 2989 2990 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2991 M = header[1]; N = header[2]; 2992 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2993 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 2994 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 2995 2996 /* If global sizes are set, check if they are consistent with that given in the file */ 2997 if (sizesset) { 2998 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 2999 } 3000 if (sizesset && newMat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 3001 if (sizesset && newMat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 3002 3003 /* determine ownership of all (block) rows */ 3004 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3005 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3006 else m = newMat->rmap->n; /* Set by user */ 3007 3008 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 3009 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3010 3011 /* First process needs enough room for process with most rows */ 3012 if (!rank) { 3013 mmax = rowners[1]; 3014 for (i=2; i<=size; i++) { 3015 mmax = PetscMax(mmax, rowners[i]); 3016 } 3017 } else mmax = -1; /* unused, but compilers complain */ 3018 3019 rowners[0] = 0; 3020 for (i=2; i<=size; i++) { 3021 rowners[i] += rowners[i-1]; 3022 } 3023 rstart = rowners[rank]; 3024 rend = rowners[rank+1]; 3025 3026 /* distribute row lengths to all processors */ 3027 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 3028 if (!rank) { 3029 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3030 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3031 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3032 for (j=0; j<m; j++) { 3033 procsnz[0] += ourlens[j]; 3034 } 3035 for (i=1; i<size; i++) { 3036 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3037 /* calculate the number of nonzeros on each processor */ 3038 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3039 procsnz[i] += rowlengths[j]; 3040 } 3041 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3042 } 3043 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3044 } else { 3045 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3046 } 3047 3048 if (!rank) { 3049 /* determine max buffer needed and allocate it */ 3050 maxnz = 0; 3051 for (i=0; i<size; i++) { 3052 maxnz = PetscMax(maxnz,procsnz[i]); 3053 } 3054 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3055 3056 /* read in my part of the matrix column indices */ 3057 nz = procsnz[0]; 3058 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3059 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3060 3061 /* read in every one elses and ship off */ 3062 for (i=1; i<size; i++) { 3063 nz = procsnz[i]; 3064 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3065 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3066 } 3067 ierr = PetscFree(cols);CHKERRQ(ierr); 3068 } else { 3069 /* determine buffer space needed for message */ 3070 nz = 0; 3071 for (i=0; i<m; i++) { 3072 nz += ourlens[i]; 3073 } 3074 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3075 3076 /* receive message of column indices*/ 3077 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3078 } 3079 3080 /* determine column ownership if matrix is not square */ 3081 if (N != M) { 3082 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3083 else n = newMat->cmap->n; 3084 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3085 cstart = cend - n; 3086 } else { 3087 cstart = rstart; 3088 cend = rend; 3089 n = cend - cstart; 3090 } 3091 3092 /* loop over local rows, determining number of off diagonal entries */ 3093 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3094 jj = 0; 3095 for (i=0; i<m; i++) { 3096 for (j=0; j<ourlens[i]; j++) { 3097 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3098 jj++; 3099 } 3100 } 3101 3102 for (i=0; i<m; i++) { 3103 ourlens[i] -= offlens[i]; 3104 } 3105 if (!sizesset) { 3106 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3107 } 3108 3109 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3110 3111 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3112 3113 for (i=0; i<m; i++) { 3114 ourlens[i] += offlens[i]; 3115 } 3116 3117 if (!rank) { 3118 ierr = PetscMalloc1((maxnz+1),&vals);CHKERRQ(ierr); 3119 3120 /* read in my part of the matrix numerical values */ 3121 nz = procsnz[0]; 3122 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3123 3124 /* insert into matrix */ 3125 jj = rstart; 3126 smycols = mycols; 3127 svals = vals; 3128 for (i=0; i<m; i++) { 3129 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3130 smycols += ourlens[i]; 3131 svals += ourlens[i]; 3132 jj++; 3133 } 3134 3135 /* read in other processors and ship out */ 3136 for (i=1; i<size; i++) { 3137 nz = procsnz[i]; 3138 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3139 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3140 } 3141 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3142 } else { 3143 /* receive numeric values */ 3144 ierr = PetscMalloc1((nz+1),&vals);CHKERRQ(ierr); 3145 3146 /* receive message of values*/ 3147 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3148 3149 /* insert into matrix */ 3150 jj = rstart; 3151 smycols = mycols; 3152 svals = vals; 3153 for (i=0; i<m; i++) { 3154 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3155 smycols += ourlens[i]; 3156 svals += ourlens[i]; 3157 jj++; 3158 } 3159 } 3160 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3161 ierr = PetscFree(vals);CHKERRQ(ierr); 3162 ierr = PetscFree(mycols);CHKERRQ(ierr); 3163 ierr = PetscFree(rowners);CHKERRQ(ierr); 3164 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3165 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3166 PetscFunctionReturn(0); 3167 } 3168 3169 #undef __FUNCT__ 3170 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3171 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3172 { 3173 PetscErrorCode ierr; 3174 IS iscol_local; 3175 PetscInt csize; 3176 3177 PetscFunctionBegin; 3178 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3179 if (call == MAT_REUSE_MATRIX) { 3180 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3181 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3182 } else { 3183 PetscInt cbs; 3184 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3185 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3186 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3187 } 3188 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3189 if (call == MAT_INITIAL_MATRIX) { 3190 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3191 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3192 } 3193 PetscFunctionReturn(0); 3194 } 3195 3196 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3197 #undef __FUNCT__ 3198 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3199 /* 3200 Not great since it makes two copies of the submatrix, first an SeqAIJ 3201 in local and then by concatenating the local matrices the end result. 3202 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3203 3204 Note: This requires a sequential iscol with all indices. 3205 */ 3206 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3207 { 3208 PetscErrorCode ierr; 3209 PetscMPIInt rank,size; 3210 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3211 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3212 PetscBool allcolumns, colflag; 3213 Mat M,Mreuse; 3214 MatScalar *vwork,*aa; 3215 MPI_Comm comm; 3216 Mat_SeqAIJ *aij; 3217 3218 PetscFunctionBegin; 3219 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3220 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3221 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3222 3223 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3224 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3225 if (colflag && ncol == mat->cmap->N) { 3226 allcolumns = PETSC_TRUE; 3227 } else { 3228 allcolumns = PETSC_FALSE; 3229 } 3230 if (call == MAT_REUSE_MATRIX) { 3231 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3232 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3233 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3234 } else { 3235 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3236 } 3237 3238 /* 3239 m - number of local rows 3240 n - number of columns (same on all processors) 3241 rstart - first row in new global matrix generated 3242 */ 3243 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3244 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3245 if (call == MAT_INITIAL_MATRIX) { 3246 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3247 ii = aij->i; 3248 jj = aij->j; 3249 3250 /* 3251 Determine the number of non-zeros in the diagonal and off-diagonal 3252 portions of the matrix in order to do correct preallocation 3253 */ 3254 3255 /* first get start and end of "diagonal" columns */ 3256 if (csize == PETSC_DECIDE) { 3257 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3258 if (mglobal == n) { /* square matrix */ 3259 nlocal = m; 3260 } else { 3261 nlocal = n/size + ((n % size) > rank); 3262 } 3263 } else { 3264 nlocal = csize; 3265 } 3266 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3267 rstart = rend - nlocal; 3268 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); 3269 3270 /* next, compute all the lengths */ 3271 ierr = PetscMalloc1((2*m+1),&dlens);CHKERRQ(ierr); 3272 olens = dlens + m; 3273 for (i=0; i<m; i++) { 3274 jend = ii[i+1] - ii[i]; 3275 olen = 0; 3276 dlen = 0; 3277 for (j=0; j<jend; j++) { 3278 if (*jj < rstart || *jj >= rend) olen++; 3279 else dlen++; 3280 jj++; 3281 } 3282 olens[i] = olen; 3283 dlens[i] = dlen; 3284 } 3285 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3286 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3287 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3288 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3289 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3290 ierr = PetscFree(dlens);CHKERRQ(ierr); 3291 } else { 3292 PetscInt ml,nl; 3293 3294 M = *newmat; 3295 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3296 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3297 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3298 /* 3299 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3300 rather than the slower MatSetValues(). 3301 */ 3302 M->was_assembled = PETSC_TRUE; 3303 M->assembled = PETSC_FALSE; 3304 } 3305 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3306 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3307 ii = aij->i; 3308 jj = aij->j; 3309 aa = aij->a; 3310 for (i=0; i<m; i++) { 3311 row = rstart + i; 3312 nz = ii[i+1] - ii[i]; 3313 cwork = jj; jj += nz; 3314 vwork = aa; aa += nz; 3315 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3316 } 3317 3318 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3319 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3320 *newmat = M; 3321 3322 /* save submatrix used in processor for next request */ 3323 if (call == MAT_INITIAL_MATRIX) { 3324 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3325 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3326 } 3327 PetscFunctionReturn(0); 3328 } 3329 3330 #undef __FUNCT__ 3331 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3332 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3333 { 3334 PetscInt m,cstart, cend,j,nnz,i,d; 3335 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3336 const PetscInt *JJ; 3337 PetscScalar *values; 3338 PetscErrorCode ierr; 3339 3340 PetscFunctionBegin; 3341 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3342 3343 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3344 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3345 m = B->rmap->n; 3346 cstart = B->cmap->rstart; 3347 cend = B->cmap->rend; 3348 rstart = B->rmap->rstart; 3349 3350 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3351 3352 #if defined(PETSC_USE_DEBUGGING) 3353 for (i=0; i<m; i++) { 3354 nnz = Ii[i+1]- Ii[i]; 3355 JJ = J + Ii[i]; 3356 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3357 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3358 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); 3359 } 3360 #endif 3361 3362 for (i=0; i<m; i++) { 3363 nnz = Ii[i+1]- Ii[i]; 3364 JJ = J + Ii[i]; 3365 nnz_max = PetscMax(nnz_max,nnz); 3366 d = 0; 3367 for (j=0; j<nnz; j++) { 3368 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3369 } 3370 d_nnz[i] = d; 3371 o_nnz[i] = nnz - d; 3372 } 3373 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3374 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3375 3376 if (v) values = (PetscScalar*)v; 3377 else { 3378 ierr = PetscCalloc1((nnz_max+1),&values);CHKERRQ(ierr); 3379 } 3380 3381 for (i=0; i<m; i++) { 3382 ii = i + rstart; 3383 nnz = Ii[i+1]- Ii[i]; 3384 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3385 } 3386 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3387 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3388 3389 if (!v) { 3390 ierr = PetscFree(values);CHKERRQ(ierr); 3391 } 3392 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3393 PetscFunctionReturn(0); 3394 } 3395 3396 #undef __FUNCT__ 3397 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3398 /*@ 3399 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3400 (the default parallel PETSc format). 3401 3402 Collective on MPI_Comm 3403 3404 Input Parameters: 3405 + B - the matrix 3406 . i - the indices into j for the start of each local row (starts with zero) 3407 . j - the column indices for each local row (starts with zero) 3408 - v - optional values in the matrix 3409 3410 Level: developer 3411 3412 Notes: 3413 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3414 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3415 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3416 3417 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3418 3419 The format which is used for the sparse matrix input, is equivalent to a 3420 row-major ordering.. i.e for the following matrix, the input data expected is 3421 as shown: 3422 3423 1 0 0 3424 2 0 3 P0 3425 ------- 3426 4 5 6 P1 3427 3428 Process0 [P0]: rows_owned=[0,1] 3429 i = {0,1,3} [size = nrow+1 = 2+1] 3430 j = {0,0,2} [size = nz = 6] 3431 v = {1,2,3} [size = nz = 6] 3432 3433 Process1 [P1]: rows_owned=[2] 3434 i = {0,3} [size = nrow+1 = 1+1] 3435 j = {0,1,2} [size = nz = 6] 3436 v = {4,5,6} [size = nz = 6] 3437 3438 .keywords: matrix, aij, compressed row, sparse, parallel 3439 3440 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3441 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3442 @*/ 3443 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3444 { 3445 PetscErrorCode ierr; 3446 3447 PetscFunctionBegin; 3448 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3449 PetscFunctionReturn(0); 3450 } 3451 3452 #undef __FUNCT__ 3453 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3454 /*@C 3455 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3456 (the default parallel PETSc format). For good matrix assembly performance 3457 the user should preallocate the matrix storage by setting the parameters 3458 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3459 performance can be increased by more than a factor of 50. 3460 3461 Collective on MPI_Comm 3462 3463 Input Parameters: 3464 + B - the matrix 3465 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3466 (same value is used for all local rows) 3467 . d_nnz - array containing the number of nonzeros in the various rows of the 3468 DIAGONAL portion of the local submatrix (possibly different for each row) 3469 or NULL, if d_nz is used to specify the nonzero structure. 3470 The size of this array is equal to the number of local rows, i.e 'm'. 3471 For matrices that will be factored, you must leave room for (and set) 3472 the diagonal entry even if it is zero. 3473 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3474 submatrix (same value is used for all local rows). 3475 - o_nnz - array containing the number of nonzeros in the various rows of the 3476 OFF-DIAGONAL portion of the local submatrix (possibly different for 3477 each row) or NULL, if o_nz is used to specify the nonzero 3478 structure. The size of this array is equal to the number 3479 of local rows, i.e 'm'. 3480 3481 If the *_nnz parameter is given then the *_nz parameter is ignored 3482 3483 The AIJ format (also called the Yale sparse matrix format or 3484 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3485 storage. The stored row and column indices begin with zero. 3486 See Users-Manual: ch_mat for details. 3487 3488 The parallel matrix is partitioned such that the first m0 rows belong to 3489 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3490 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3491 3492 The DIAGONAL portion of the local submatrix of a processor can be defined 3493 as the submatrix which is obtained by extraction the part corresponding to 3494 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3495 first row that belongs to the processor, r2 is the last row belonging to 3496 the this processor, and c1-c2 is range of indices of the local part of a 3497 vector suitable for applying the matrix to. This is an mxn matrix. In the 3498 common case of a square matrix, the row and column ranges are the same and 3499 the DIAGONAL part is also square. The remaining portion of the local 3500 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3501 3502 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3503 3504 You can call MatGetInfo() to get information on how effective the preallocation was; 3505 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3506 You can also run with the option -info and look for messages with the string 3507 malloc in them to see if additional memory allocation was needed. 3508 3509 Example usage: 3510 3511 Consider the following 8x8 matrix with 34 non-zero values, that is 3512 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3513 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3514 as follows: 3515 3516 .vb 3517 1 2 0 | 0 3 0 | 0 4 3518 Proc0 0 5 6 | 7 0 0 | 8 0 3519 9 0 10 | 11 0 0 | 12 0 3520 ------------------------------------- 3521 13 0 14 | 15 16 17 | 0 0 3522 Proc1 0 18 0 | 19 20 21 | 0 0 3523 0 0 0 | 22 23 0 | 24 0 3524 ------------------------------------- 3525 Proc2 25 26 27 | 0 0 28 | 29 0 3526 30 0 0 | 31 32 33 | 0 34 3527 .ve 3528 3529 This can be represented as a collection of submatrices as: 3530 3531 .vb 3532 A B C 3533 D E F 3534 G H I 3535 .ve 3536 3537 Where the submatrices A,B,C are owned by proc0, D,E,F are 3538 owned by proc1, G,H,I are owned by proc2. 3539 3540 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3541 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3542 The 'M','N' parameters are 8,8, and have the same values on all procs. 3543 3544 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3545 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3546 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3547 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3548 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3549 matrix, ans [DF] as another SeqAIJ matrix. 3550 3551 When d_nz, o_nz parameters are specified, d_nz storage elements are 3552 allocated for every row of the local diagonal submatrix, and o_nz 3553 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3554 One way to choose d_nz and o_nz is to use the max nonzerors per local 3555 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3556 In this case, the values of d_nz,o_nz are: 3557 .vb 3558 proc0 : dnz = 2, o_nz = 2 3559 proc1 : dnz = 3, o_nz = 2 3560 proc2 : dnz = 1, o_nz = 4 3561 .ve 3562 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3563 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3564 for proc3. i.e we are using 12+15+10=37 storage locations to store 3565 34 values. 3566 3567 When d_nnz, o_nnz parameters are specified, the storage is specified 3568 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3569 In the above case the values for d_nnz,o_nnz are: 3570 .vb 3571 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3572 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3573 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3574 .ve 3575 Here the space allocated is sum of all the above values i.e 34, and 3576 hence pre-allocation is perfect. 3577 3578 Level: intermediate 3579 3580 .keywords: matrix, aij, compressed row, sparse, parallel 3581 3582 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3583 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3584 @*/ 3585 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3586 { 3587 PetscErrorCode ierr; 3588 3589 PetscFunctionBegin; 3590 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3591 PetscValidType(B,1); 3592 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3593 PetscFunctionReturn(0); 3594 } 3595 3596 #undef __FUNCT__ 3597 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3598 /*@ 3599 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3600 CSR format the local rows. 3601 3602 Collective on MPI_Comm 3603 3604 Input Parameters: 3605 + comm - MPI communicator 3606 . m - number of local rows (Cannot be PETSC_DECIDE) 3607 . n - This value should be the same as the local size used in creating the 3608 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3609 calculated if N is given) For square matrices n is almost always m. 3610 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3611 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3612 . i - row indices 3613 . j - column indices 3614 - a - matrix values 3615 3616 Output Parameter: 3617 . mat - the matrix 3618 3619 Level: intermediate 3620 3621 Notes: 3622 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3623 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3624 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3625 3626 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3627 3628 The format which is used for the sparse matrix input, is equivalent to a 3629 row-major ordering.. i.e for the following matrix, the input data expected is 3630 as shown: 3631 3632 1 0 0 3633 2 0 3 P0 3634 ------- 3635 4 5 6 P1 3636 3637 Process0 [P0]: rows_owned=[0,1] 3638 i = {0,1,3} [size = nrow+1 = 2+1] 3639 j = {0,0,2} [size = nz = 6] 3640 v = {1,2,3} [size = nz = 6] 3641 3642 Process1 [P1]: rows_owned=[2] 3643 i = {0,3} [size = nrow+1 = 1+1] 3644 j = {0,1,2} [size = nz = 6] 3645 v = {4,5,6} [size = nz = 6] 3646 3647 .keywords: matrix, aij, compressed row, sparse, parallel 3648 3649 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3650 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3651 @*/ 3652 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3653 { 3654 PetscErrorCode ierr; 3655 3656 PetscFunctionBegin; 3657 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3658 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3659 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3660 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3661 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3662 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3663 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3664 PetscFunctionReturn(0); 3665 } 3666 3667 #undef __FUNCT__ 3668 #define __FUNCT__ "MatCreateAIJ" 3669 /*@C 3670 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3671 (the default parallel PETSc format). For good matrix assembly performance 3672 the user should preallocate the matrix storage by setting the parameters 3673 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3674 performance can be increased by more than a factor of 50. 3675 3676 Collective on MPI_Comm 3677 3678 Input Parameters: 3679 + comm - MPI communicator 3680 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3681 This value should be the same as the local size used in creating the 3682 y vector for the matrix-vector product y = Ax. 3683 . n - This value should be the same as the local size used in creating the 3684 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3685 calculated if N is given) For square matrices n is almost always m. 3686 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3687 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3688 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3689 (same value is used for all local rows) 3690 . d_nnz - array containing the number of nonzeros in the various rows of the 3691 DIAGONAL portion of the local submatrix (possibly different for each row) 3692 or NULL, if d_nz is used to specify the nonzero structure. 3693 The size of this array is equal to the number of local rows, i.e 'm'. 3694 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3695 submatrix (same value is used for all local rows). 3696 - o_nnz - array containing the number of nonzeros in the various rows of the 3697 OFF-DIAGONAL portion of the local submatrix (possibly different for 3698 each row) or NULL, if o_nz is used to specify the nonzero 3699 structure. The size of this array is equal to the number 3700 of local rows, i.e 'm'. 3701 3702 Output Parameter: 3703 . A - the matrix 3704 3705 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3706 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3707 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3708 3709 Notes: 3710 If the *_nnz parameter is given then the *_nz parameter is ignored 3711 3712 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3713 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3714 storage requirements for this matrix. 3715 3716 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3717 processor than it must be used on all processors that share the object for 3718 that argument. 3719 3720 The user MUST specify either the local or global matrix dimensions 3721 (possibly both). 3722 3723 The parallel matrix is partitioned across processors such that the 3724 first m0 rows belong to process 0, the next m1 rows belong to 3725 process 1, the next m2 rows belong to process 2 etc.. where 3726 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3727 values corresponding to [m x N] submatrix. 3728 3729 The columns are logically partitioned with the n0 columns belonging 3730 to 0th partition, the next n1 columns belonging to the next 3731 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3732 3733 The DIAGONAL portion of the local submatrix on any given processor 3734 is the submatrix corresponding to the rows and columns m,n 3735 corresponding to the given processor. i.e diagonal matrix on 3736 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3737 etc. The remaining portion of the local submatrix [m x (N-n)] 3738 constitute the OFF-DIAGONAL portion. The example below better 3739 illustrates this concept. 3740 3741 For a square global matrix we define each processor's diagonal portion 3742 to be its local rows and the corresponding columns (a square submatrix); 3743 each processor's off-diagonal portion encompasses the remainder of the 3744 local matrix (a rectangular submatrix). 3745 3746 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3747 3748 When calling this routine with a single process communicator, a matrix of 3749 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3750 type of communicator, use the construction mechanism: 3751 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3752 3753 By default, this format uses inodes (identical nodes) when possible. 3754 We search for consecutive rows with the same nonzero structure, thereby 3755 reusing matrix information to achieve increased efficiency. 3756 3757 Options Database Keys: 3758 + -mat_no_inode - Do not use inodes 3759 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3760 - -mat_aij_oneindex - Internally use indexing starting at 1 3761 rather than 0. Note that when calling MatSetValues(), 3762 the user still MUST index entries starting at 0! 3763 3764 3765 Example usage: 3766 3767 Consider the following 8x8 matrix with 34 non-zero values, that is 3768 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3769 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3770 as follows: 3771 3772 .vb 3773 1 2 0 | 0 3 0 | 0 4 3774 Proc0 0 5 6 | 7 0 0 | 8 0 3775 9 0 10 | 11 0 0 | 12 0 3776 ------------------------------------- 3777 13 0 14 | 15 16 17 | 0 0 3778 Proc1 0 18 0 | 19 20 21 | 0 0 3779 0 0 0 | 22 23 0 | 24 0 3780 ------------------------------------- 3781 Proc2 25 26 27 | 0 0 28 | 29 0 3782 30 0 0 | 31 32 33 | 0 34 3783 .ve 3784 3785 This can be represented as a collection of submatrices as: 3786 3787 .vb 3788 A B C 3789 D E F 3790 G H I 3791 .ve 3792 3793 Where the submatrices A,B,C are owned by proc0, D,E,F are 3794 owned by proc1, G,H,I are owned by proc2. 3795 3796 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3797 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3798 The 'M','N' parameters are 8,8, and have the same values on all procs. 3799 3800 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3801 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3802 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3803 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3804 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3805 matrix, ans [DF] as another SeqAIJ matrix. 3806 3807 When d_nz, o_nz parameters are specified, d_nz storage elements are 3808 allocated for every row of the local diagonal submatrix, and o_nz 3809 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3810 One way to choose d_nz and o_nz is to use the max nonzerors per local 3811 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3812 In this case, the values of d_nz,o_nz are: 3813 .vb 3814 proc0 : dnz = 2, o_nz = 2 3815 proc1 : dnz = 3, o_nz = 2 3816 proc2 : dnz = 1, o_nz = 4 3817 .ve 3818 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3819 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3820 for proc3. i.e we are using 12+15+10=37 storage locations to store 3821 34 values. 3822 3823 When d_nnz, o_nnz parameters are specified, the storage is specified 3824 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3825 In the above case the values for d_nnz,o_nnz are: 3826 .vb 3827 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3828 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3829 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3830 .ve 3831 Here the space allocated is sum of all the above values i.e 34, and 3832 hence pre-allocation is perfect. 3833 3834 Level: intermediate 3835 3836 .keywords: matrix, aij, compressed row, sparse, parallel 3837 3838 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3839 MPIAIJ, MatCreateMPIAIJWithArrays() 3840 @*/ 3841 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) 3842 { 3843 PetscErrorCode ierr; 3844 PetscMPIInt size; 3845 3846 PetscFunctionBegin; 3847 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3848 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3849 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3850 if (size > 1) { 3851 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3852 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3853 } else { 3854 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3855 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3856 } 3857 PetscFunctionReturn(0); 3858 } 3859 3860 #undef __FUNCT__ 3861 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3862 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3863 { 3864 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3865 3866 PetscFunctionBegin; 3867 if (Ad) *Ad = a->A; 3868 if (Ao) *Ao = a->B; 3869 if (colmap) *colmap = a->garray; 3870 PetscFunctionReturn(0); 3871 } 3872 3873 #undef __FUNCT__ 3874 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3875 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3876 { 3877 PetscErrorCode ierr; 3878 PetscInt i; 3879 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3880 3881 PetscFunctionBegin; 3882 if (coloring->ctype == IS_COLORING_GLOBAL) { 3883 ISColoringValue *allcolors,*colors; 3884 ISColoring ocoloring; 3885 3886 /* set coloring for diagonal portion */ 3887 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3888 3889 /* set coloring for off-diagonal portion */ 3890 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3891 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 3892 for (i=0; i<a->B->cmap->n; i++) { 3893 colors[i] = allcolors[a->garray[i]]; 3894 } 3895 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3896 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3897 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3898 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3899 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3900 ISColoringValue *colors; 3901 PetscInt *larray; 3902 ISColoring ocoloring; 3903 3904 /* set coloring for diagonal portion */ 3905 ierr = PetscMalloc1((a->A->cmap->n+1),&larray);CHKERRQ(ierr); 3906 for (i=0; i<a->A->cmap->n; i++) { 3907 larray[i] = i + A->cmap->rstart; 3908 } 3909 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3910 ierr = PetscMalloc1((a->A->cmap->n+1),&colors);CHKERRQ(ierr); 3911 for (i=0; i<a->A->cmap->n; i++) { 3912 colors[i] = coloring->colors[larray[i]]; 3913 } 3914 ierr = PetscFree(larray);CHKERRQ(ierr); 3915 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3916 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3917 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3918 3919 /* set coloring for off-diagonal portion */ 3920 ierr = PetscMalloc1((a->B->cmap->n+1),&larray);CHKERRQ(ierr); 3921 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3922 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 3923 for (i=0; i<a->B->cmap->n; i++) { 3924 colors[i] = coloring->colors[larray[i]]; 3925 } 3926 ierr = PetscFree(larray);CHKERRQ(ierr); 3927 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3928 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3929 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3930 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3931 PetscFunctionReturn(0); 3932 } 3933 3934 #undef __FUNCT__ 3935 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3936 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3937 { 3938 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3939 PetscErrorCode ierr; 3940 3941 PetscFunctionBegin; 3942 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3943 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3944 PetscFunctionReturn(0); 3945 } 3946 3947 #undef __FUNCT__ 3948 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 3949 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 3950 { 3951 PetscErrorCode ierr; 3952 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 3953 PetscInt *indx; 3954 3955 PetscFunctionBegin; 3956 /* This routine will ONLY return MPIAIJ type matrix */ 3957 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3958 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3959 if (n == PETSC_DECIDE) { 3960 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3961 } 3962 /* Check sum(n) = N */ 3963 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3964 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3965 3966 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3967 rstart -= m; 3968 3969 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3970 for (i=0; i<m; i++) { 3971 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3972 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3973 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3974 } 3975 3976 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3977 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3978 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3979 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3980 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3981 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3982 PetscFunctionReturn(0); 3983 } 3984 3985 #undef __FUNCT__ 3986 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 3987 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 3988 { 3989 PetscErrorCode ierr; 3990 PetscInt m,N,i,rstart,nnz,Ii; 3991 PetscInt *indx; 3992 PetscScalar *values; 3993 3994 PetscFunctionBegin; 3995 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3996 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 3997 for (i=0; i<m; i++) { 3998 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3999 Ii = i + rstart; 4000 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4001 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4002 } 4003 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4004 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4005 PetscFunctionReturn(0); 4006 } 4007 4008 #undef __FUNCT__ 4009 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 4010 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4011 { 4012 PetscErrorCode ierr; 4013 PetscMPIInt size; 4014 4015 PetscFunctionBegin; 4016 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4017 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4018 if (size == 1) { 4019 if (scall == MAT_INITIAL_MATRIX) { 4020 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4021 } else { 4022 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4023 } 4024 } else { 4025 if (scall == MAT_INITIAL_MATRIX) { 4026 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4027 } 4028 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4029 } 4030 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4031 PetscFunctionReturn(0); 4032 } 4033 4034 #undef __FUNCT__ 4035 #define __FUNCT__ "MatFileSplit" 4036 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4037 { 4038 PetscErrorCode ierr; 4039 PetscMPIInt rank; 4040 PetscInt m,N,i,rstart,nnz; 4041 size_t len; 4042 const PetscInt *indx; 4043 PetscViewer out; 4044 char *name; 4045 Mat B; 4046 const PetscScalar *values; 4047 4048 PetscFunctionBegin; 4049 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4050 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4051 /* Should this be the type of the diagonal block of A? */ 4052 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4053 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4054 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4055 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4056 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4057 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4058 for (i=0; i<m; i++) { 4059 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4060 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4061 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4062 } 4063 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4064 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4065 4066 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4067 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4068 ierr = PetscMalloc1((len+5),&name);CHKERRQ(ierr); 4069 sprintf(name,"%s.%d",outfile,rank); 4070 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4071 ierr = PetscFree(name);CHKERRQ(ierr); 4072 ierr = MatView(B,out);CHKERRQ(ierr); 4073 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4074 ierr = MatDestroy(&B);CHKERRQ(ierr); 4075 PetscFunctionReturn(0); 4076 } 4077 4078 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4079 #undef __FUNCT__ 4080 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4081 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4082 { 4083 PetscErrorCode ierr; 4084 Mat_Merge_SeqsToMPI *merge; 4085 PetscContainer container; 4086 4087 PetscFunctionBegin; 4088 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4089 if (container) { 4090 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4091 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4092 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4093 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4094 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4095 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4096 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4097 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4098 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4099 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4100 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4101 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4102 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4103 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4104 ierr = PetscFree(merge);CHKERRQ(ierr); 4105 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4106 } 4107 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4108 PetscFunctionReturn(0); 4109 } 4110 4111 #include <../src/mat/utils/freespace.h> 4112 #include <petscbt.h> 4113 4114 #undef __FUNCT__ 4115 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4116 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4117 { 4118 PetscErrorCode ierr; 4119 MPI_Comm comm; 4120 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4121 PetscMPIInt size,rank,taga,*len_s; 4122 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4123 PetscInt proc,m; 4124 PetscInt **buf_ri,**buf_rj; 4125 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4126 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4127 MPI_Request *s_waits,*r_waits; 4128 MPI_Status *status; 4129 MatScalar *aa=a->a; 4130 MatScalar **abuf_r,*ba_i; 4131 Mat_Merge_SeqsToMPI *merge; 4132 PetscContainer container; 4133 4134 PetscFunctionBegin; 4135 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4136 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4137 4138 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4139 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4140 4141 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4142 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4143 4144 bi = merge->bi; 4145 bj = merge->bj; 4146 buf_ri = merge->buf_ri; 4147 buf_rj = merge->buf_rj; 4148 4149 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4150 owners = merge->rowmap->range; 4151 len_s = merge->len_s; 4152 4153 /* send and recv matrix values */ 4154 /*-----------------------------*/ 4155 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4156 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4157 4158 ierr = PetscMalloc1((merge->nsend+1),&s_waits);CHKERRQ(ierr); 4159 for (proc=0,k=0; proc<size; proc++) { 4160 if (!len_s[proc]) continue; 4161 i = owners[proc]; 4162 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4163 k++; 4164 } 4165 4166 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4167 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4168 ierr = PetscFree(status);CHKERRQ(ierr); 4169 4170 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4171 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4172 4173 /* insert mat values of mpimat */ 4174 /*----------------------------*/ 4175 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4176 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4177 4178 for (k=0; k<merge->nrecv; k++) { 4179 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4180 nrows = *(buf_ri_k[k]); 4181 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4182 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4183 } 4184 4185 /* set values of ba */ 4186 m = merge->rowmap->n; 4187 for (i=0; i<m; i++) { 4188 arow = owners[rank] + i; 4189 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4190 bnzi = bi[i+1] - bi[i]; 4191 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4192 4193 /* add local non-zero vals of this proc's seqmat into ba */ 4194 anzi = ai[arow+1] - ai[arow]; 4195 aj = a->j + ai[arow]; 4196 aa = a->a + ai[arow]; 4197 nextaj = 0; 4198 for (j=0; nextaj<anzi; j++) { 4199 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4200 ba_i[j] += aa[nextaj++]; 4201 } 4202 } 4203 4204 /* add received vals into ba */ 4205 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4206 /* i-th row */ 4207 if (i == *nextrow[k]) { 4208 anzi = *(nextai[k]+1) - *nextai[k]; 4209 aj = buf_rj[k] + *(nextai[k]); 4210 aa = abuf_r[k] + *(nextai[k]); 4211 nextaj = 0; 4212 for (j=0; nextaj<anzi; j++) { 4213 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4214 ba_i[j] += aa[nextaj++]; 4215 } 4216 } 4217 nextrow[k]++; nextai[k]++; 4218 } 4219 } 4220 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4221 } 4222 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4223 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4224 4225 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4226 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4227 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4228 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4229 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4230 PetscFunctionReturn(0); 4231 } 4232 4233 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4234 4235 #undef __FUNCT__ 4236 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4237 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4238 { 4239 PetscErrorCode ierr; 4240 Mat B_mpi; 4241 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4242 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4243 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4244 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4245 PetscInt len,proc,*dnz,*onz,bs,cbs; 4246 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4247 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4248 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4249 MPI_Status *status; 4250 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4251 PetscBT lnkbt; 4252 Mat_Merge_SeqsToMPI *merge; 4253 PetscContainer container; 4254 4255 PetscFunctionBegin; 4256 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4257 4258 /* make sure it is a PETSc comm */ 4259 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4260 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4261 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4262 4263 ierr = PetscNew(&merge);CHKERRQ(ierr); 4264 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4265 4266 /* determine row ownership */ 4267 /*---------------------------------------------------------*/ 4268 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4269 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4270 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4271 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4272 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4273 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4274 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4275 4276 m = merge->rowmap->n; 4277 owners = merge->rowmap->range; 4278 4279 /* determine the number of messages to send, their lengths */ 4280 /*---------------------------------------------------------*/ 4281 len_s = merge->len_s; 4282 4283 len = 0; /* length of buf_si[] */ 4284 merge->nsend = 0; 4285 for (proc=0; proc<size; proc++) { 4286 len_si[proc] = 0; 4287 if (proc == rank) { 4288 len_s[proc] = 0; 4289 } else { 4290 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4291 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4292 } 4293 if (len_s[proc]) { 4294 merge->nsend++; 4295 nrows = 0; 4296 for (i=owners[proc]; i<owners[proc+1]; i++) { 4297 if (ai[i+1] > ai[i]) nrows++; 4298 } 4299 len_si[proc] = 2*(nrows+1); 4300 len += len_si[proc]; 4301 } 4302 } 4303 4304 /* determine the number and length of messages to receive for ij-structure */ 4305 /*-------------------------------------------------------------------------*/ 4306 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4307 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4308 4309 /* post the Irecv of j-structure */ 4310 /*-------------------------------*/ 4311 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4312 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4313 4314 /* post the Isend of j-structure */ 4315 /*--------------------------------*/ 4316 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4317 4318 for (proc=0, k=0; proc<size; proc++) { 4319 if (!len_s[proc]) continue; 4320 i = owners[proc]; 4321 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4322 k++; 4323 } 4324 4325 /* receives and sends of j-structure are complete */ 4326 /*------------------------------------------------*/ 4327 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4328 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4329 4330 /* send and recv i-structure */ 4331 /*---------------------------*/ 4332 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4333 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4334 4335 ierr = PetscMalloc1((len+1),&buf_s);CHKERRQ(ierr); 4336 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4337 for (proc=0,k=0; proc<size; proc++) { 4338 if (!len_s[proc]) continue; 4339 /* form outgoing message for i-structure: 4340 buf_si[0]: nrows to be sent 4341 [1:nrows]: row index (global) 4342 [nrows+1:2*nrows+1]: i-structure index 4343 */ 4344 /*-------------------------------------------*/ 4345 nrows = len_si[proc]/2 - 1; 4346 buf_si_i = buf_si + nrows+1; 4347 buf_si[0] = nrows; 4348 buf_si_i[0] = 0; 4349 nrows = 0; 4350 for (i=owners[proc]; i<owners[proc+1]; i++) { 4351 anzi = ai[i+1] - ai[i]; 4352 if (anzi) { 4353 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4354 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4355 nrows++; 4356 } 4357 } 4358 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4359 k++; 4360 buf_si += len_si[proc]; 4361 } 4362 4363 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4364 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4365 4366 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4367 for (i=0; i<merge->nrecv; i++) { 4368 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); 4369 } 4370 4371 ierr = PetscFree(len_si);CHKERRQ(ierr); 4372 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4373 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4374 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4375 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4376 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4377 ierr = PetscFree(status);CHKERRQ(ierr); 4378 4379 /* compute a local seq matrix in each processor */ 4380 /*----------------------------------------------*/ 4381 /* allocate bi array and free space for accumulating nonzero column info */ 4382 ierr = PetscMalloc1((m+1),&bi);CHKERRQ(ierr); 4383 bi[0] = 0; 4384 4385 /* create and initialize a linked list */ 4386 nlnk = N+1; 4387 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4388 4389 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4390 len = ai[owners[rank+1]] - ai[owners[rank]]; 4391 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4392 4393 current_space = free_space; 4394 4395 /* determine symbolic info for each local row */ 4396 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4397 4398 for (k=0; k<merge->nrecv; k++) { 4399 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4400 nrows = *buf_ri_k[k]; 4401 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4402 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4403 } 4404 4405 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4406 len = 0; 4407 for (i=0; i<m; i++) { 4408 bnzi = 0; 4409 /* add local non-zero cols of this proc's seqmat into lnk */ 4410 arow = owners[rank] + i; 4411 anzi = ai[arow+1] - ai[arow]; 4412 aj = a->j + ai[arow]; 4413 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4414 bnzi += nlnk; 4415 /* add received col data into lnk */ 4416 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4417 if (i == *nextrow[k]) { /* i-th row */ 4418 anzi = *(nextai[k]+1) - *nextai[k]; 4419 aj = buf_rj[k] + *nextai[k]; 4420 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4421 bnzi += nlnk; 4422 nextrow[k]++; nextai[k]++; 4423 } 4424 } 4425 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4426 4427 /* if free space is not available, make more free space */ 4428 if (current_space->local_remaining<bnzi) { 4429 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4430 nspacedouble++; 4431 } 4432 /* copy data into free space, then initialize lnk */ 4433 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4434 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4435 4436 current_space->array += bnzi; 4437 current_space->local_used += bnzi; 4438 current_space->local_remaining -= bnzi; 4439 4440 bi[i+1] = bi[i] + bnzi; 4441 } 4442 4443 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4444 4445 ierr = PetscMalloc1((bi[m]+1),&bj);CHKERRQ(ierr); 4446 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4447 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4448 4449 /* create symbolic parallel matrix B_mpi */ 4450 /*---------------------------------------*/ 4451 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4452 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4453 if (n==PETSC_DECIDE) { 4454 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4455 } else { 4456 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4457 } 4458 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4459 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4460 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4461 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4462 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4463 4464 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4465 B_mpi->assembled = PETSC_FALSE; 4466 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4467 merge->bi = bi; 4468 merge->bj = bj; 4469 merge->buf_ri = buf_ri; 4470 merge->buf_rj = buf_rj; 4471 merge->coi = NULL; 4472 merge->coj = NULL; 4473 merge->owners_co = NULL; 4474 4475 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4476 4477 /* attach the supporting struct to B_mpi for reuse */ 4478 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4479 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4480 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4481 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4482 *mpimat = B_mpi; 4483 4484 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4485 PetscFunctionReturn(0); 4486 } 4487 4488 #undef __FUNCT__ 4489 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4490 /*@C 4491 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4492 matrices from each processor 4493 4494 Collective on MPI_Comm 4495 4496 Input Parameters: 4497 + comm - the communicators the parallel matrix will live on 4498 . seqmat - the input sequential matrices 4499 . m - number of local rows (or PETSC_DECIDE) 4500 . n - number of local columns (or PETSC_DECIDE) 4501 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4502 4503 Output Parameter: 4504 . mpimat - the parallel matrix generated 4505 4506 Level: advanced 4507 4508 Notes: 4509 The dimensions of the sequential matrix in each processor MUST be the same. 4510 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4511 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4512 @*/ 4513 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4514 { 4515 PetscErrorCode ierr; 4516 PetscMPIInt size; 4517 4518 PetscFunctionBegin; 4519 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4520 if (size == 1) { 4521 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4522 if (scall == MAT_INITIAL_MATRIX) { 4523 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4524 } else { 4525 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4526 } 4527 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4528 PetscFunctionReturn(0); 4529 } 4530 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4531 if (scall == MAT_INITIAL_MATRIX) { 4532 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4533 } 4534 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4535 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4536 PetscFunctionReturn(0); 4537 } 4538 4539 #undef __FUNCT__ 4540 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4541 /*@ 4542 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4543 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4544 with MatGetSize() 4545 4546 Not Collective 4547 4548 Input Parameters: 4549 + A - the matrix 4550 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4551 4552 Output Parameter: 4553 . A_loc - the local sequential matrix generated 4554 4555 Level: developer 4556 4557 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4558 4559 @*/ 4560 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4561 { 4562 PetscErrorCode ierr; 4563 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4564 Mat_SeqAIJ *mat,*a,*b; 4565 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4566 MatScalar *aa,*ba,*cam; 4567 PetscScalar *ca; 4568 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4569 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4570 PetscBool match; 4571 MPI_Comm comm; 4572 PetscMPIInt size; 4573 4574 PetscFunctionBegin; 4575 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4576 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4577 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4578 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4579 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4580 4581 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4582 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4583 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4584 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4585 aa = a->a; ba = b->a; 4586 if (scall == MAT_INITIAL_MATRIX) { 4587 if (size == 1) { 4588 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4589 PetscFunctionReturn(0); 4590 } 4591 4592 ierr = PetscMalloc1((1+am),&ci);CHKERRQ(ierr); 4593 ci[0] = 0; 4594 for (i=0; i<am; i++) { 4595 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4596 } 4597 ierr = PetscMalloc1((1+ci[am]),&cj);CHKERRQ(ierr); 4598 ierr = PetscMalloc1((1+ci[am]),&ca);CHKERRQ(ierr); 4599 k = 0; 4600 for (i=0; i<am; i++) { 4601 ncols_o = bi[i+1] - bi[i]; 4602 ncols_d = ai[i+1] - ai[i]; 4603 /* off-diagonal portion of A */ 4604 for (jo=0; jo<ncols_o; jo++) { 4605 col = cmap[*bj]; 4606 if (col >= cstart) break; 4607 cj[k] = col; bj++; 4608 ca[k++] = *ba++; 4609 } 4610 /* diagonal portion of A */ 4611 for (j=0; j<ncols_d; j++) { 4612 cj[k] = cstart + *aj++; 4613 ca[k++] = *aa++; 4614 } 4615 /* off-diagonal portion of A */ 4616 for (j=jo; j<ncols_o; j++) { 4617 cj[k] = cmap[*bj++]; 4618 ca[k++] = *ba++; 4619 } 4620 } 4621 /* put together the new matrix */ 4622 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4623 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4624 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4625 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4626 mat->free_a = PETSC_TRUE; 4627 mat->free_ij = PETSC_TRUE; 4628 mat->nonew = 0; 4629 } else if (scall == MAT_REUSE_MATRIX) { 4630 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4631 ci = mat->i; cj = mat->j; cam = mat->a; 4632 for (i=0; i<am; i++) { 4633 /* off-diagonal portion of A */ 4634 ncols_o = bi[i+1] - bi[i]; 4635 for (jo=0; jo<ncols_o; jo++) { 4636 col = cmap[*bj]; 4637 if (col >= cstart) break; 4638 *cam++ = *ba++; bj++; 4639 } 4640 /* diagonal portion of A */ 4641 ncols_d = ai[i+1] - ai[i]; 4642 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4643 /* off-diagonal portion of A */ 4644 for (j=jo; j<ncols_o; j++) { 4645 *cam++ = *ba++; bj++; 4646 } 4647 } 4648 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4649 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4650 PetscFunctionReturn(0); 4651 } 4652 4653 #undef __FUNCT__ 4654 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4655 /*@C 4656 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4657 4658 Not Collective 4659 4660 Input Parameters: 4661 + A - the matrix 4662 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4663 - row, col - index sets of rows and columns to extract (or NULL) 4664 4665 Output Parameter: 4666 . A_loc - the local sequential matrix generated 4667 4668 Level: developer 4669 4670 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4671 4672 @*/ 4673 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4674 { 4675 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4676 PetscErrorCode ierr; 4677 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4678 IS isrowa,iscola; 4679 Mat *aloc; 4680 PetscBool match; 4681 4682 PetscFunctionBegin; 4683 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4684 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4685 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4686 if (!row) { 4687 start = A->rmap->rstart; end = A->rmap->rend; 4688 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4689 } else { 4690 isrowa = *row; 4691 } 4692 if (!col) { 4693 start = A->cmap->rstart; 4694 cmap = a->garray; 4695 nzA = a->A->cmap->n; 4696 nzB = a->B->cmap->n; 4697 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 4698 ncols = 0; 4699 for (i=0; i<nzB; i++) { 4700 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4701 else break; 4702 } 4703 imark = i; 4704 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4705 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4706 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4707 } else { 4708 iscola = *col; 4709 } 4710 if (scall != MAT_INITIAL_MATRIX) { 4711 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4712 aloc[0] = *A_loc; 4713 } 4714 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4715 *A_loc = aloc[0]; 4716 ierr = PetscFree(aloc);CHKERRQ(ierr); 4717 if (!row) { 4718 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4719 } 4720 if (!col) { 4721 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4722 } 4723 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4724 PetscFunctionReturn(0); 4725 } 4726 4727 #undef __FUNCT__ 4728 #define __FUNCT__ "MatGetBrowsOfAcols" 4729 /*@C 4730 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4731 4732 Collective on Mat 4733 4734 Input Parameters: 4735 + A,B - the matrices in mpiaij format 4736 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4737 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4738 4739 Output Parameter: 4740 + rowb, colb - index sets of rows and columns of B to extract 4741 - B_seq - the sequential matrix generated 4742 4743 Level: developer 4744 4745 @*/ 4746 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4747 { 4748 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4749 PetscErrorCode ierr; 4750 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4751 IS isrowb,iscolb; 4752 Mat *bseq=NULL; 4753 4754 PetscFunctionBegin; 4755 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4756 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); 4757 } 4758 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4759 4760 if (scall == MAT_INITIAL_MATRIX) { 4761 start = A->cmap->rstart; 4762 cmap = a->garray; 4763 nzA = a->A->cmap->n; 4764 nzB = a->B->cmap->n; 4765 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 4766 ncols = 0; 4767 for (i=0; i<nzB; i++) { /* row < local row index */ 4768 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4769 else break; 4770 } 4771 imark = i; 4772 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4773 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4774 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4775 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4776 } else { 4777 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4778 isrowb = *rowb; iscolb = *colb; 4779 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4780 bseq[0] = *B_seq; 4781 } 4782 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4783 *B_seq = bseq[0]; 4784 ierr = PetscFree(bseq);CHKERRQ(ierr); 4785 if (!rowb) { 4786 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4787 } else { 4788 *rowb = isrowb; 4789 } 4790 if (!colb) { 4791 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4792 } else { 4793 *colb = iscolb; 4794 } 4795 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4796 PetscFunctionReturn(0); 4797 } 4798 4799 #undef __FUNCT__ 4800 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4801 /* 4802 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4803 of the OFF-DIAGONAL portion of local A 4804 4805 Collective on Mat 4806 4807 Input Parameters: 4808 + A,B - the matrices in mpiaij format 4809 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4810 4811 Output Parameter: 4812 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4813 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4814 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4815 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4816 4817 Level: developer 4818 4819 */ 4820 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4821 { 4822 VecScatter_MPI_General *gen_to,*gen_from; 4823 PetscErrorCode ierr; 4824 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4825 Mat_SeqAIJ *b_oth; 4826 VecScatter ctx =a->Mvctx; 4827 MPI_Comm comm; 4828 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4829 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4830 PetscScalar *rvalues,*svalues; 4831 MatScalar *b_otha,*bufa,*bufA; 4832 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4833 MPI_Request *rwaits = NULL,*swaits = NULL; 4834 MPI_Status *sstatus,rstatus; 4835 PetscMPIInt jj,size; 4836 PetscInt *cols,sbs,rbs; 4837 PetscScalar *vals; 4838 4839 PetscFunctionBegin; 4840 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4841 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4842 if (size == 1) PetscFunctionReturn(0); 4843 4844 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4845 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); 4846 } 4847 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4848 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4849 4850 gen_to = (VecScatter_MPI_General*)ctx->todata; 4851 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4852 rvalues = gen_from->values; /* holds the length of receiving row */ 4853 svalues = gen_to->values; /* holds the length of sending row */ 4854 nrecvs = gen_from->n; 4855 nsends = gen_to->n; 4856 4857 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4858 srow = gen_to->indices; /* local row index to be sent */ 4859 sstarts = gen_to->starts; 4860 sprocs = gen_to->procs; 4861 sstatus = gen_to->sstatus; 4862 sbs = gen_to->bs; 4863 rstarts = gen_from->starts; 4864 rprocs = gen_from->procs; 4865 rbs = gen_from->bs; 4866 4867 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4868 if (scall == MAT_INITIAL_MATRIX) { 4869 /* i-array */ 4870 /*---------*/ 4871 /* post receives */ 4872 for (i=0; i<nrecvs; i++) { 4873 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4874 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4875 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4876 } 4877 4878 /* pack the outgoing message */ 4879 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4880 4881 sstartsj[0] = 0; 4882 rstartsj[0] = 0; 4883 len = 0; /* total length of j or a array to be sent */ 4884 k = 0; 4885 for (i=0; i<nsends; i++) { 4886 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4887 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4888 for (j=0; j<nrows; j++) { 4889 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4890 for (l=0; l<sbs; l++) { 4891 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4892 4893 rowlen[j*sbs+l] = ncols; 4894 4895 len += ncols; 4896 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4897 } 4898 k++; 4899 } 4900 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4901 4902 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4903 } 4904 /* recvs and sends of i-array are completed */ 4905 i = nrecvs; 4906 while (i--) { 4907 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4908 } 4909 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4910 4911 /* allocate buffers for sending j and a arrays */ 4912 ierr = PetscMalloc1((len+1),&bufj);CHKERRQ(ierr); 4913 ierr = PetscMalloc1((len+1),&bufa);CHKERRQ(ierr); 4914 4915 /* create i-array of B_oth */ 4916 ierr = PetscMalloc1((aBn+2),&b_othi);CHKERRQ(ierr); 4917 4918 b_othi[0] = 0; 4919 len = 0; /* total length of j or a array to be received */ 4920 k = 0; 4921 for (i=0; i<nrecvs; i++) { 4922 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4923 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4924 for (j=0; j<nrows; j++) { 4925 b_othi[k+1] = b_othi[k] + rowlen[j]; 4926 len += rowlen[j]; k++; 4927 } 4928 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4929 } 4930 4931 /* allocate space for j and a arrrays of B_oth */ 4932 ierr = PetscMalloc1((b_othi[aBn]+1),&b_othj);CHKERRQ(ierr); 4933 ierr = PetscMalloc1((b_othi[aBn]+1),&b_otha);CHKERRQ(ierr); 4934 4935 /* j-array */ 4936 /*---------*/ 4937 /* post receives of j-array */ 4938 for (i=0; i<nrecvs; i++) { 4939 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4940 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4941 } 4942 4943 /* pack the outgoing message j-array */ 4944 k = 0; 4945 for (i=0; i<nsends; i++) { 4946 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4947 bufJ = bufj+sstartsj[i]; 4948 for (j=0; j<nrows; j++) { 4949 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4950 for (ll=0; ll<sbs; ll++) { 4951 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4952 for (l=0; l<ncols; l++) { 4953 *bufJ++ = cols[l]; 4954 } 4955 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4956 } 4957 } 4958 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4959 } 4960 4961 /* recvs and sends of j-array are completed */ 4962 i = nrecvs; 4963 while (i--) { 4964 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4965 } 4966 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4967 } else if (scall == MAT_REUSE_MATRIX) { 4968 sstartsj = *startsj_s; 4969 rstartsj = *startsj_r; 4970 bufa = *bufa_ptr; 4971 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4972 b_otha = b_oth->a; 4973 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4974 4975 /* a-array */ 4976 /*---------*/ 4977 /* post receives of a-array */ 4978 for (i=0; i<nrecvs; i++) { 4979 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4980 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4981 } 4982 4983 /* pack the outgoing message a-array */ 4984 k = 0; 4985 for (i=0; i<nsends; i++) { 4986 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4987 bufA = bufa+sstartsj[i]; 4988 for (j=0; j<nrows; j++) { 4989 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4990 for (ll=0; ll<sbs; ll++) { 4991 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4992 for (l=0; l<ncols; l++) { 4993 *bufA++ = vals[l]; 4994 } 4995 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4996 } 4997 } 4998 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4999 } 5000 /* recvs and sends of a-array are completed */ 5001 i = nrecvs; 5002 while (i--) { 5003 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5004 } 5005 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5006 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5007 5008 if (scall == MAT_INITIAL_MATRIX) { 5009 /* put together the new matrix */ 5010 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5011 5012 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5013 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5014 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5015 b_oth->free_a = PETSC_TRUE; 5016 b_oth->free_ij = PETSC_TRUE; 5017 b_oth->nonew = 0; 5018 5019 ierr = PetscFree(bufj);CHKERRQ(ierr); 5020 if (!startsj_s || !bufa_ptr) { 5021 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5022 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5023 } else { 5024 *startsj_s = sstartsj; 5025 *startsj_r = rstartsj; 5026 *bufa_ptr = bufa; 5027 } 5028 } 5029 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5030 PetscFunctionReturn(0); 5031 } 5032 5033 #undef __FUNCT__ 5034 #define __FUNCT__ "MatGetCommunicationStructs" 5035 /*@C 5036 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5037 5038 Not Collective 5039 5040 Input Parameters: 5041 . A - The matrix in mpiaij format 5042 5043 Output Parameter: 5044 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5045 . colmap - A map from global column index to local index into lvec 5046 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5047 5048 Level: developer 5049 5050 @*/ 5051 #if defined(PETSC_USE_CTABLE) 5052 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5053 #else 5054 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5055 #endif 5056 { 5057 Mat_MPIAIJ *a; 5058 5059 PetscFunctionBegin; 5060 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5061 PetscValidPointer(lvec, 2); 5062 PetscValidPointer(colmap, 3); 5063 PetscValidPointer(multScatter, 4); 5064 a = (Mat_MPIAIJ*) A->data; 5065 if (lvec) *lvec = a->lvec; 5066 if (colmap) *colmap = a->colmap; 5067 if (multScatter) *multScatter = a->Mvctx; 5068 PetscFunctionReturn(0); 5069 } 5070 5071 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5072 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5073 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5074 #if defined(PETSC_HAVE_ELEMENTAL) 5075 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5076 #endif 5077 5078 #undef __FUNCT__ 5079 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5080 /* 5081 Computes (B'*A')' since computing B*A directly is untenable 5082 5083 n p p 5084 ( ) ( ) ( ) 5085 m ( A ) * n ( B ) = m ( C ) 5086 ( ) ( ) ( ) 5087 5088 */ 5089 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5090 { 5091 PetscErrorCode ierr; 5092 Mat At,Bt,Ct; 5093 5094 PetscFunctionBegin; 5095 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5096 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5097 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5098 ierr = MatDestroy(&At);CHKERRQ(ierr); 5099 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5100 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5101 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5102 PetscFunctionReturn(0); 5103 } 5104 5105 #undef __FUNCT__ 5106 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5107 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5108 { 5109 PetscErrorCode ierr; 5110 PetscInt m=A->rmap->n,n=B->cmap->n; 5111 Mat Cmat; 5112 5113 PetscFunctionBegin; 5114 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); 5115 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5116 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5117 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5118 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5119 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5120 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5121 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5122 5123 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5124 5125 *C = Cmat; 5126 PetscFunctionReturn(0); 5127 } 5128 5129 /* ----------------------------------------------------------------*/ 5130 #undef __FUNCT__ 5131 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5132 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5133 { 5134 PetscErrorCode ierr; 5135 5136 PetscFunctionBegin; 5137 if (scall == MAT_INITIAL_MATRIX) { 5138 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5139 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5140 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5141 } 5142 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5143 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5144 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5145 PetscFunctionReturn(0); 5146 } 5147 5148 #if defined(PETSC_HAVE_MUMPS) 5149 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5150 #endif 5151 #if defined(PETSC_HAVE_PASTIX) 5152 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5153 #endif 5154 #if defined(PETSC_HAVE_SUPERLU_DIST) 5155 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5156 #endif 5157 #if defined(PETSC_HAVE_CLIQUE) 5158 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5159 #endif 5160 5161 /*MC 5162 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5163 5164 Options Database Keys: 5165 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5166 5167 Level: beginner 5168 5169 .seealso: MatCreateAIJ() 5170 M*/ 5171 5172 #undef __FUNCT__ 5173 #define __FUNCT__ "MatCreate_MPIAIJ" 5174 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5175 { 5176 Mat_MPIAIJ *b; 5177 PetscErrorCode ierr; 5178 PetscMPIInt size; 5179 5180 PetscFunctionBegin; 5181 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5182 5183 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5184 B->data = (void*)b; 5185 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5186 B->assembled = PETSC_FALSE; 5187 B->insertmode = NOT_SET_VALUES; 5188 b->size = size; 5189 5190 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5191 5192 /* build cache for off array entries formed */ 5193 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5194 5195 b->donotstash = PETSC_FALSE; 5196 b->colmap = 0; 5197 b->garray = 0; 5198 b->roworiented = PETSC_TRUE; 5199 5200 /* stuff used for matrix vector multiply */ 5201 b->lvec = NULL; 5202 b->Mvctx = NULL; 5203 5204 /* stuff for MatGetRow() */ 5205 b->rowindices = 0; 5206 b->rowvalues = 0; 5207 b->getrowactive = PETSC_FALSE; 5208 5209 /* flexible pointer used in CUSP/CUSPARSE classes */ 5210 b->spptr = NULL; 5211 5212 #if defined(PETSC_HAVE_MUMPS) 5213 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5214 #endif 5215 #if defined(PETSC_HAVE_PASTIX) 5216 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5217 #endif 5218 #if defined(PETSC_HAVE_SUPERLU_DIST) 5219 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5220 #endif 5221 #if defined(PETSC_HAVE_CLIQUE) 5222 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5223 #endif 5224 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5225 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5226 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5227 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5228 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5229 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5230 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5231 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5232 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5233 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5234 #if defined(PETSC_HAVE_ELEMENTAL) 5235 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5236 #endif 5237 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5238 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5239 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5240 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5241 PetscFunctionReturn(0); 5242 } 5243 5244 #undef __FUNCT__ 5245 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5246 /*@ 5247 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5248 and "off-diagonal" part of the matrix in CSR format. 5249 5250 Collective on MPI_Comm 5251 5252 Input Parameters: 5253 + comm - MPI communicator 5254 . m - number of local rows (Cannot be PETSC_DECIDE) 5255 . n - This value should be the same as the local size used in creating the 5256 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5257 calculated if N is given) For square matrices n is almost always m. 5258 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5259 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5260 . i - row indices for "diagonal" portion of matrix 5261 . j - column indices 5262 . a - matrix values 5263 . oi - row indices for "off-diagonal" portion of matrix 5264 . oj - column indices 5265 - oa - matrix values 5266 5267 Output Parameter: 5268 . mat - the matrix 5269 5270 Level: advanced 5271 5272 Notes: 5273 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5274 must free the arrays once the matrix has been destroyed and not before. 5275 5276 The i and j indices are 0 based 5277 5278 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5279 5280 This sets local rows and cannot be used to set off-processor values. 5281 5282 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5283 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5284 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5285 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5286 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5287 communication if it is known that only local entries will be set. 5288 5289 .keywords: matrix, aij, compressed row, sparse, parallel 5290 5291 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5292 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5293 @*/ 5294 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) 5295 { 5296 PetscErrorCode ierr; 5297 Mat_MPIAIJ *maij; 5298 5299 PetscFunctionBegin; 5300 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5301 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5302 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5303 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5304 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5305 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5306 maij = (Mat_MPIAIJ*) (*mat)->data; 5307 5308 (*mat)->preallocated = PETSC_TRUE; 5309 5310 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5311 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5312 5313 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5314 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5315 5316 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5317 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5318 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5319 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5320 5321 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5322 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5323 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5324 PetscFunctionReturn(0); 5325 } 5326 5327 /* 5328 Special version for direct calls from Fortran 5329 */ 5330 #include <petsc-private/fortranimpl.h> 5331 5332 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5333 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5334 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5335 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5336 #endif 5337 5338 /* Change these macros so can be used in void function */ 5339 #undef CHKERRQ 5340 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5341 #undef SETERRQ2 5342 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5343 #undef SETERRQ3 5344 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5345 #undef SETERRQ 5346 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5347 5348 #undef __FUNCT__ 5349 #define __FUNCT__ "matsetvaluesmpiaij_" 5350 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) 5351 { 5352 Mat mat = *mmat; 5353 PetscInt m = *mm, n = *mn; 5354 InsertMode addv = *maddv; 5355 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5356 PetscScalar value; 5357 PetscErrorCode ierr; 5358 5359 MatCheckPreallocated(mat,1); 5360 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5361 5362 #if defined(PETSC_USE_DEBUG) 5363 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5364 #endif 5365 { 5366 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5367 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5368 PetscBool roworiented = aij->roworiented; 5369 5370 /* Some Variables required in the macro */ 5371 Mat A = aij->A; 5372 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5373 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5374 MatScalar *aa = a->a; 5375 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5376 Mat B = aij->B; 5377 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5378 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5379 MatScalar *ba = b->a; 5380 5381 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5382 PetscInt nonew = a->nonew; 5383 MatScalar *ap1,*ap2; 5384 5385 PetscFunctionBegin; 5386 for (i=0; i<m; i++) { 5387 if (im[i] < 0) continue; 5388 #if defined(PETSC_USE_DEBUG) 5389 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); 5390 #endif 5391 if (im[i] >= rstart && im[i] < rend) { 5392 row = im[i] - rstart; 5393 lastcol1 = -1; 5394 rp1 = aj + ai[row]; 5395 ap1 = aa + ai[row]; 5396 rmax1 = aimax[row]; 5397 nrow1 = ailen[row]; 5398 low1 = 0; 5399 high1 = nrow1; 5400 lastcol2 = -1; 5401 rp2 = bj + bi[row]; 5402 ap2 = ba + bi[row]; 5403 rmax2 = bimax[row]; 5404 nrow2 = bilen[row]; 5405 low2 = 0; 5406 high2 = nrow2; 5407 5408 for (j=0; j<n; j++) { 5409 if (roworiented) value = v[i*n+j]; 5410 else value = v[i+j*m]; 5411 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5412 if (in[j] >= cstart && in[j] < cend) { 5413 col = in[j] - cstart; 5414 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5415 } else if (in[j] < 0) continue; 5416 #if defined(PETSC_USE_DEBUG) 5417 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); 5418 #endif 5419 else { 5420 if (mat->was_assembled) { 5421 if (!aij->colmap) { 5422 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5423 } 5424 #if defined(PETSC_USE_CTABLE) 5425 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5426 col--; 5427 #else 5428 col = aij->colmap[in[j]] - 1; 5429 #endif 5430 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5431 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5432 col = in[j]; 5433 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5434 B = aij->B; 5435 b = (Mat_SeqAIJ*)B->data; 5436 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5437 rp2 = bj + bi[row]; 5438 ap2 = ba + bi[row]; 5439 rmax2 = bimax[row]; 5440 nrow2 = bilen[row]; 5441 low2 = 0; 5442 high2 = nrow2; 5443 bm = aij->B->rmap->n; 5444 ba = b->a; 5445 } 5446 } else col = in[j]; 5447 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5448 } 5449 } 5450 } else if (!aij->donotstash) { 5451 if (roworiented) { 5452 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5453 } else { 5454 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5455 } 5456 } 5457 } 5458 } 5459 PetscFunctionReturnVoid(); 5460 } 5461 5462