1 2 /* 3 Factorization code for BAIJ format. 4 */ 5 #include <../src/mat/impls/baij/seq/baij.h> 6 #include <../src/mat/blockinvert.h> 7 8 #undef __FUNCT__ 9 #define __FUNCT__ "MatSeqBAIJSetNumericFactorization" 10 /* 11 This is used to set the numeric factorization for both LU and ILU symbolic factorization 12 */ 13 PetscErrorCode MatSeqBAIJSetNumericFactorization(Mat fact,PetscBool natural) 14 { 15 PetscFunctionBegin; 16 if (natural) { 17 switch (fact->rmap->bs) { 18 case 1: 19 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_1; 20 break; 21 case 2: 22 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering; 23 break; 24 case 3: 25 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_3_NaturalOrdering; 26 break; 27 case 4: 28 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering; 29 break; 30 case 5: 31 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_5_NaturalOrdering; 32 break; 33 case 6: 34 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_6_NaturalOrdering; 35 break; 36 case 7: 37 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_7_NaturalOrdering; 38 break; 39 case 15: 40 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_15_NaturalOrdering; 41 break; 42 default: 43 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_N; 44 break; 45 } 46 } else { 47 switch (fact->rmap->bs) { 48 case 1: 49 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_1; 50 break; 51 case 2: 52 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_2; 53 break; 54 case 3: 55 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_3; 56 break; 57 case 4: 58 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4; 59 break; 60 case 5: 61 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_5; 62 break; 63 case 6: 64 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_6; 65 break; 66 case 7: 67 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_7; 68 break; 69 default: 70 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_N; 71 break; 72 } 73 } 74 PetscFunctionReturn(0); 75 } 76 77 #undef __FUNCT__ 78 #define __FUNCT__ "MatSeqBAIJSetNumericFactorization_inplace" 79 PetscErrorCode MatSeqBAIJSetNumericFactorization_inplace(Mat inA,PetscBool natural) 80 { 81 PetscFunctionBegin; 82 if (natural) { 83 switch (inA->rmap->bs) { 84 case 1: 85 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_1_inplace; 86 break; 87 case 2: 88 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace; 89 break; 90 case 3: 91 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_3_NaturalOrdering_inplace; 92 break; 93 case 4: 94 #if defined(PETSC_USE_REAL_MAT_SINGLE) 95 { 96 PetscBool sse_enabled_local; 97 PetscErrorCode ierr; 98 ierr = PetscSSEIsEnabled(inA->comm,&sse_enabled_local,PETSC_NULL);CHKERRQ(ierr); 99 if (sse_enabled_local) { 100 # if defined(PETSC_HAVE_SSE) 101 int i,*AJ=a->j,nz=a->nz,n=a->mbs; 102 if (n==(unsigned short)n) { 103 unsigned short *aj=(unsigned short*)AJ; 104 for (i=0; i<nz; i++) aj[i] = (unsigned short)AJ[i]; 105 106 inA->ops->setunfactored = MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE_usj; 107 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering_SSE_usj; 108 109 ierr = PetscInfo(inA,"Using special SSE, in-place natural ordering, ushort j index factor BS=4\n");CHKERRQ(ierr); 110 } else { 111 /* Scale the column indices for easier indexing in MatSolve. */ 112 /* for (i=0;i<nz;i++) { */ 113 /* AJ[i] = AJ[i]*4; */ 114 /* } */ 115 inA->ops->setunfactored = MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE; 116 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering_SSE; 117 118 ierr = PetscInfo(inA,"Using special SSE, in-place natural ordering, int j index factor BS=4\n");CHKERRQ(ierr); 119 } 120 # else 121 /* This should never be reached. If so, problem in PetscSSEIsEnabled. */ 122 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSE Hardware unavailable"); 123 # endif 124 } else { 125 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering_inplace; 126 } 127 } 128 #else 129 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_NaturalOrdering_inplace; 130 #endif 131 break; 132 case 5: 133 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_5_NaturalOrdering_inplace; 134 break; 135 case 6: 136 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_6_NaturalOrdering_inplace; 137 break; 138 case 7: 139 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_7_NaturalOrdering_inplace; 140 break; 141 default: 142 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_N_inplace; 143 break; 144 } 145 } else { 146 switch (inA->rmap->bs) { 147 case 1: 148 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_1_inplace; 149 break; 150 case 2: 151 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_2_inplace; 152 break; 153 case 3: 154 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_3_inplace; 155 break; 156 case 4: 157 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_4_inplace; 158 break; 159 case 5: 160 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_5_inplace; 161 break; 162 case 6: 163 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_6_inplace; 164 break; 165 case 7: 166 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_7_inplace; 167 break; 168 default: 169 inA->ops->lufactornumeric = MatLUFactorNumeric_SeqBAIJ_N_inplace; 170 break; 171 } 172 } 173 PetscFunctionReturn(0); 174 } 175 176 /* 177 The symbolic factorization code is identical to that for AIJ format, 178 except for very small changes since this is now a SeqBAIJ datastructure. 179 NOT good code reuse. 180 */ 181 #include <petscbt.h> 182 #include <../src/mat/utils/freespace.h> 183 184 #undef __FUNCT__ 185 #define __FUNCT__ "MatLUFactorSymbolic_SeqBAIJ" 186 PetscErrorCode MatLUFactorSymbolic_SeqBAIJ(Mat B,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 187 { 188 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 189 PetscInt n =a->mbs,bs = A->rmap->bs,bs2=a->bs2; 190 PetscBool row_identity,col_identity,both_identity; 191 IS isicol; 192 PetscErrorCode ierr; 193 const PetscInt *r,*ic; 194 PetscInt i,*ai=a->i,*aj=a->j; 195 PetscInt *bi,*bj,*ajtmp; 196 PetscInt *bdiag,row,nnz,nzi,reallocs=0,nzbd,*im; 197 PetscReal f; 198 PetscInt nlnk,*lnk,k,**bi_ptr; 199 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 200 PetscBT lnkbt; 201 202 PetscFunctionBegin; 203 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"matrix must be square"); 204 if (bs>1) { /* check shifttype */ 205 if (info->shifttype == MAT_SHIFT_NONZERO || info->shifttype == MAT_SHIFT_POSITIVE_DEFINITE) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only MAT_SHIFT_NONE and MAT_SHIFT_INBLOCKS are supported for BAIJ matrix"); 206 } 207 208 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 209 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 210 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 211 212 /* get new row and diagonal pointers, must be allocated separately because they will be given to the Mat_SeqAIJ and freed separately */ 213 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 214 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr); 215 bi[0] = bdiag[0] = 0; 216 217 /* linked list for storing column indices of the active row */ 218 nlnk = n + 1; 219 ierr = PetscLLCreate(n,n,nlnk,lnk,lnkbt);CHKERRQ(ierr); 220 221 ierr = PetscMalloc2(n+1,PetscInt**,&bi_ptr,n+1,PetscInt,&im);CHKERRQ(ierr); 222 223 /* initial FreeSpace size is f*(ai[n]+1) */ 224 f = info->fill; 225 ierr = PetscFreeSpaceGet((PetscInt)(f*(ai[n]+1)),&free_space);CHKERRQ(ierr); 226 227 current_space = free_space; 228 229 for (i=0; i<n; i++) { 230 /* copy previous fill into linked list */ 231 nzi = 0; 232 nnz = ai[r[i]+1] - ai[r[i]]; 233 if (!nnz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i); 234 ajtmp = aj + ai[r[i]]; 235 ierr = PetscLLAddPerm(nnz,ajtmp,ic,n,nlnk,lnk,lnkbt);CHKERRQ(ierr); 236 nzi += nlnk; 237 238 /* add pivot rows into linked list */ 239 row = lnk[n]; 240 while (row < i) { 241 nzbd = bdiag[row] + 1; /* num of entries in the row with column index <= row */ 242 ajtmp = bi_ptr[row] + nzbd; /* points to the entry next to the diagonal */ 243 ierr = PetscLLAddSortedLU(ajtmp,row,nlnk,lnk,lnkbt,i,nzbd,im);CHKERRQ(ierr); 244 nzi += nlnk; 245 row = lnk[row]; 246 } 247 bi[i+1] = bi[i] + nzi; 248 im[i] = nzi; 249 250 /* mark bdiag */ 251 nzbd = 0; 252 nnz = nzi; 253 k = lnk[n]; 254 while (nnz-- && k < i) { 255 nzbd++; 256 k = lnk[k]; 257 } 258 bdiag[i] = nzbd; /* note : bdaig[i] = nnzL as input for PetscFreeSpaceContiguous_LU() */ 259 260 /* if free space is not available, make more free space */ 261 if (current_space->local_remaining<nzi) { 262 nnz = 2*(n - i)*nzi; /* estimated and max additional space needed */ 263 ierr = PetscFreeSpaceGet(nnz,¤t_space);CHKERRQ(ierr); 264 reallocs++; 265 } 266 267 /* copy data into free space, then initialize lnk */ 268 ierr = PetscLLClean(n,n,nzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 269 270 bi_ptr[i] = current_space->array; 271 current_space->array += nzi; 272 current_space->local_used += nzi; 273 current_space->local_remaining -= nzi; 274 } 275 276 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 277 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 278 279 /* copy free_space into bj and free free_space; set bi, bj, bdiag in new datastructure; */ 280 ierr = PetscMalloc((bi[n]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 281 ierr = PetscFreeSpaceContiguous_LU(&free_space,bj,n,bi,bdiag);CHKERRQ(ierr); 282 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 283 ierr = PetscFree2(bi_ptr,im);CHKERRQ(ierr); 284 285 /* put together the new matrix */ 286 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 287 ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr); 288 b = (Mat_SeqBAIJ*)(B)->data; 289 290 b->free_a = PETSC_TRUE; 291 b->free_ij = PETSC_TRUE; 292 b->singlemalloc = PETSC_FALSE; 293 294 ierr = PetscMalloc((bdiag[0]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 295 b->j = bj; 296 b->i = bi; 297 b->diag = bdiag; 298 b->free_diag = PETSC_TRUE; 299 b->ilen = 0; 300 b->imax = 0; 301 b->row = isrow; 302 b->col = iscol; 303 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 304 305 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 306 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 307 b->icol = isicol; 308 ierr = PetscMalloc((bs*n+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 309 ierr = PetscLogObjectMemory(B,(bdiag[0]+1)*(sizeof(PetscInt)+sizeof(PetscScalar)*bs2));CHKERRQ(ierr); 310 311 b->maxnz = b->nz = bdiag[0]+1; 312 313 B->factortype = MAT_FACTOR_LU; 314 B->info.factor_mallocs = reallocs; 315 B->info.fill_ratio_given = f; 316 317 if (ai[n] != 0) { 318 B->info.fill_ratio_needed = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]); 319 } else { 320 B->info.fill_ratio_needed = 0.0; 321 } 322 #if defined(PETSC_USE_INFO) 323 if (ai[n] != 0) { 324 PetscReal af = B->info.fill_ratio_needed; 325 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr); 326 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 327 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr); 328 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 329 } else { 330 ierr = PetscInfo(A,"Empty matrix\n");CHKERRQ(ierr); 331 } 332 #endif 333 334 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 335 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 336 337 both_identity = (PetscBool) (row_identity && col_identity); 338 339 ierr = MatSeqBAIJSetNumericFactorization(B,both_identity);CHKERRQ(ierr); 340 PetscFunctionReturn(0); 341 } 342 343 #undef __FUNCT__ 344 #define __FUNCT__ "MatLUFactorSymbolic_SeqBAIJ_inplace" 345 PetscErrorCode MatLUFactorSymbolic_SeqBAIJ_inplace(Mat B,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 346 { 347 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 348 PetscInt n =a->mbs,bs = A->rmap->bs,bs2=a->bs2; 349 PetscBool row_identity,col_identity,both_identity; 350 IS isicol; 351 PetscErrorCode ierr; 352 const PetscInt *r,*ic; 353 PetscInt i,*ai=a->i,*aj=a->j; 354 PetscInt *bi,*bj,*ajtmp; 355 PetscInt *bdiag,row,nnz,nzi,reallocs=0,nzbd,*im; 356 PetscReal f; 357 PetscInt nlnk,*lnk,k,**bi_ptr; 358 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 359 PetscBT lnkbt; 360 361 PetscFunctionBegin; 362 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"matrix must be square"); 363 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 364 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 365 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 366 367 /* get new row and diagonal pointers, must be allocated separately because they will be given to the Mat_SeqAIJ and freed separately */ 368 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 369 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr); 370 371 bi[0] = bdiag[0] = 0; 372 373 /* linked list for storing column indices of the active row */ 374 nlnk = n + 1; 375 ierr = PetscLLCreate(n,n,nlnk,lnk,lnkbt);CHKERRQ(ierr); 376 377 ierr = PetscMalloc2(n+1,PetscInt**,&bi_ptr,n+1,PetscInt,&im);CHKERRQ(ierr); 378 379 /* initial FreeSpace size is f*(ai[n]+1) */ 380 f = info->fill; 381 ierr = PetscFreeSpaceGet((PetscInt)(f*(ai[n]+1)),&free_space);CHKERRQ(ierr); 382 current_space = free_space; 383 384 for (i=0; i<n; i++) { 385 /* copy previous fill into linked list */ 386 nzi = 0; 387 nnz = ai[r[i]+1] - ai[r[i]]; 388 if (!nnz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i); 389 ajtmp = aj + ai[r[i]]; 390 ierr = PetscLLAddPerm(nnz,ajtmp,ic,n,nlnk,lnk,lnkbt);CHKERRQ(ierr); 391 nzi += nlnk; 392 393 /* add pivot rows into linked list */ 394 row = lnk[n]; 395 while (row < i) { 396 nzbd = bdiag[row] - bi[row] + 1; /* num of entries in the row with column index <= row */ 397 ajtmp = bi_ptr[row] + nzbd; /* points to the entry next to the diagonal */ 398 ierr = PetscLLAddSortedLU(ajtmp,row,nlnk,lnk,lnkbt,i,nzbd,im);CHKERRQ(ierr); 399 nzi += nlnk; 400 row = lnk[row]; 401 } 402 bi[i+1] = bi[i] + nzi; 403 im[i] = nzi; 404 405 /* mark bdiag */ 406 nzbd = 0; 407 nnz = nzi; 408 k = lnk[n]; 409 while (nnz-- && k < i) { 410 nzbd++; 411 k = lnk[k]; 412 } 413 bdiag[i] = bi[i] + nzbd; 414 415 /* if free space is not available, make more free space */ 416 if (current_space->local_remaining<nzi) { 417 nnz = (n - i)*nzi; /* estimated and max additional space needed */ 418 ierr = PetscFreeSpaceGet(nnz,¤t_space);CHKERRQ(ierr); 419 reallocs++; 420 } 421 422 /* copy data into free space, then initialize lnk */ 423 ierr = PetscLLClean(n,n,nzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 424 425 bi_ptr[i] = current_space->array; 426 current_space->array += nzi; 427 current_space->local_used += nzi; 428 current_space->local_remaining -= nzi; 429 } 430 #if defined(PETSC_USE_INFO) 431 if (ai[n] != 0) { 432 PetscReal af = ((PetscReal)bi[n])/((PetscReal)ai[n]); 433 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr); 434 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 435 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr); 436 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 437 } else { 438 ierr = PetscInfo(A,"Empty matrix\n");CHKERRQ(ierr); 439 } 440 #endif 441 442 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 443 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 444 445 /* destroy list of free space and other temporary array(s) */ 446 ierr = PetscMalloc((bi[n]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 447 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 448 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 449 ierr = PetscFree2(bi_ptr,im);CHKERRQ(ierr); 450 451 /* put together the new matrix */ 452 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 453 ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr); 454 b = (Mat_SeqBAIJ*)(B)->data; 455 456 b->free_a = PETSC_TRUE; 457 b->free_ij = PETSC_TRUE; 458 b->singlemalloc = PETSC_FALSE; 459 460 ierr = PetscMalloc((bi[n]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 461 b->j = bj; 462 b->i = bi; 463 b->diag = bdiag; 464 b->free_diag = PETSC_TRUE; 465 b->ilen = 0; 466 b->imax = 0; 467 b->row = isrow; 468 b->col = iscol; 469 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 470 471 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 472 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 473 b->icol = isicol; 474 475 ierr = PetscMalloc((bs*n+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 476 ierr = PetscLogObjectMemory(B,(bi[n]-n)*(sizeof(PetscInt)+sizeof(PetscScalar)*bs2));CHKERRQ(ierr); 477 478 b->maxnz = b->nz = bi[n]; 479 480 (B)->factortype = MAT_FACTOR_LU; 481 (B)->info.factor_mallocs = reallocs; 482 (B)->info.fill_ratio_given = f; 483 484 if (ai[n] != 0) { 485 (B)->info.fill_ratio_needed = ((PetscReal)bi[n])/((PetscReal)ai[n]); 486 } else { 487 (B)->info.fill_ratio_needed = 0.0; 488 } 489 490 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 491 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 492 493 both_identity = (PetscBool) (row_identity && col_identity); 494 495 ierr = MatSeqBAIJSetNumericFactorization_inplace(B,both_identity);CHKERRQ(ierr); 496 PetscFunctionReturn(0); 497 } 498 499