1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: aijfact.c,v 1.97 1998/03/20 22:48:47 bsmith Exp balay $"; 3 #endif 4 5 #include "src/mat/impls/aij/seq/aij.h" 6 #include "src/vec/vecimpl.h" 7 #include "src/inline/dot.h" 8 9 #undef __FUNC__ 10 #define __FUNC__ "MatOrder_Flow_SeqAIJ" 11 int MatOrder_Flow_SeqAIJ(Mat mat,MatReorderingType type,IS *irow,IS *icol) 12 { 13 PetscFunctionBegin; 14 15 SETERRQ(PETSC_ERR_SUP,0,"Code not written"); 16 #if !defined(USE_PETSC_DEBUG) 17 PetscFunctionReturn(0); 18 #endif 19 } 20 21 /* 22 Factorization code for AIJ format. 23 */ 24 #undef __FUNC__ 25 #define __FUNC__ "MatLUFactorSymbolic_SeqAIJ" 26 int MatLUFactorSymbolic_SeqAIJ(Mat A,IS isrow,IS iscol,double f,Mat *B) 27 { 28 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data, *b; 29 IS isicol; 30 int *r,*ic, ierr, i, n = a->m, *ai = a->i, *aj = a->j; 31 int *ainew,*ajnew, jmax,*fill, *ajtmp, nz,shift = a->indexshift; 32 int *idnew, idx, row,m,fm, nnz, nzi, realloc = 0,nzbd,*im; 33 34 PetscFunctionBegin; 35 PetscValidHeaderSpecific(isrow,IS_COOKIE); 36 PetscValidHeaderSpecific(iscol,IS_COOKIE); 37 38 ierr = ISInvertPermutation(iscol,&isicol); CHKERRQ(ierr); 39 PLogObjectParent(*B,isicol); 40 ISGetIndices(isrow,&r); ISGetIndices(isicol,&ic); 41 42 /* get new row pointers */ 43 ainew = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(ainew); 44 ainew[0] = -shift; 45 /* don't know how many column pointers are needed so estimate */ 46 jmax = (int) (f*ai[n]+(!shift)); 47 ajnew = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajnew); 48 /* fill is a linked list of nonzeros in active row */ 49 fill = (int *) PetscMalloc( (2*n+1)*sizeof(int)); CHKPTRQ(fill); 50 im = fill + n + 1; 51 /* idnew is location of diagonal in factor */ 52 idnew = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(idnew); 53 idnew[0] = -shift; 54 55 for ( i=0; i<n; i++ ) { 56 /* first copy previous fill into linked list */ 57 nnz = nz = ai[r[i]+1] - ai[r[i]]; 58 if (!nz) SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,1,"Empty row in matrix"); 59 ajtmp = aj + ai[r[i]] + shift; 60 fill[n] = n; 61 while (nz--) { 62 fm = n; 63 idx = ic[*ajtmp++ + shift]; 64 do { 65 m = fm; 66 fm = fill[m]; 67 } while (fm < idx); 68 fill[m] = idx; 69 fill[idx] = fm; 70 } 71 row = fill[n]; 72 while ( row < i ) { 73 ajtmp = ajnew + idnew[row] + (!shift); 74 nzbd = 1 + idnew[row] - ainew[row]; 75 nz = im[row] - nzbd; 76 fm = row; 77 while (nz-- > 0) { 78 idx = *ajtmp++ + shift; 79 nzbd++; 80 if (idx == i) im[row] = nzbd; 81 do { 82 m = fm; 83 fm = fill[m]; 84 } while (fm < idx); 85 if (fm != idx) { 86 fill[m] = idx; 87 fill[idx] = fm; 88 fm = idx; 89 nnz++; 90 } 91 } 92 row = fill[row]; 93 } 94 /* copy new filled row into permanent storage */ 95 ainew[i+1] = ainew[i] + nnz; 96 if (ainew[i+1] > jmax) { 97 98 /* estimate how much additional space we will need */ 99 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 100 /* just double the memory each time */ 101 int maxadd = jmax; 102 /* maxadd = (int) ((f*(ai[n]+(!shift))*(n-i+5))/n); */ 103 if (maxadd < nnz) maxadd = (n-i)*(nnz+1); 104 jmax += maxadd; 105 106 /* allocate a longer ajnew */ 107 ajtmp = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(ajtmp); 108 PetscMemcpy(ajtmp,ajnew,(ainew[i]+shift)*sizeof(int)); 109 PetscFree(ajnew); 110 ajnew = ajtmp; 111 realloc++; /* count how many times we realloc */ 112 } 113 ajtmp = ajnew + ainew[i] + shift; 114 fm = fill[n]; 115 nzi = 0; 116 im[i] = nnz; 117 while (nnz--) { 118 if (fm < i) nzi++; 119 *ajtmp++ = fm - shift; 120 fm = fill[fm]; 121 } 122 idnew[i] = ainew[i] + nzi; 123 } 124 if (ai[n] != 0) { 125 double af = ((double)ainew[n])/((double)ai[n]); 126 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:Reallocs %d Fill ratio:given %g needed %g\n", 127 realloc,f,af); 128 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:Run with -pc_lu_fill %g or use \n",af); 129 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:PCLUSetFill(pc,%g);\n",af); 130 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:for best performance.\n"); 131 } else { 132 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ: Empty matrix\n"); 133 } 134 135 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 136 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 137 138 PetscFree(fill); 139 140 /* put together the new matrix */ 141 ierr = MatCreateSeqAIJ(A->comm,n,n,0,PETSC_NULL,B); CHKERRQ(ierr); 142 PLogObjectParent(*B,isicol); 143 b = (Mat_SeqAIJ *) (*B)->data; 144 PetscFree(b->imax); 145 b->singlemalloc = 0; 146 /* the next line frees the default space generated by the Create() */ 147 PetscFree(b->a); PetscFree(b->ilen); 148 b->a = (Scalar *) PetscMalloc((ainew[n]+shift+1)*sizeof(Scalar));CHKPTRQ(b->a); 149 b->j = ajnew; 150 b->i = ainew; 151 b->diag = idnew; 152 b->ilen = 0; 153 b->imax = 0; 154 b->row = isrow; 155 b->col = iscol; 156 b->icol = isicol; 157 b->solve_work = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar));CHKPTRQ(b->solve_work); 158 /* In b structure: Free imax, ilen, old a, old j. 159 Allocate idnew, solve_work, new a, new j */ 160 PLogObjectMemory(*B,(ainew[n]+shift-n)*(sizeof(int)+sizeof(Scalar))); 161 b->maxnz = b->nz = ainew[n] + shift; 162 163 (*B)->info.factor_mallocs = realloc; 164 (*B)->info.fill_ratio_given = f; 165 if (ai[i] != 0) { 166 (*B)->info.fill_ratio_needed = ((double)ainew[n])/((double)ai[i]); 167 } else { 168 (*B)->info.fill_ratio_needed = 0.0; 169 } 170 171 PetscFunctionReturn(0); 172 } 173 /* ----------------------------------------------------------- */ 174 int Mat_AIJ_CheckInode(Mat); 175 176 #undef __FUNC__ 177 #define __FUNC__ "MatLUFactorNumeric_SeqAIJ" 178 int MatLUFactorNumeric_SeqAIJ(Mat A,Mat *B) 179 { 180 Mat C = *B; 181 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data, *b = (Mat_SeqAIJ *)C->data; 182 IS isrow = b->row, isicol = b->icol; 183 int *r,*ic, ierr, i, j, n = a->m, *ai = b->i, *aj = b->j; 184 int *ajtmpold, *ajtmp, nz, row, *ics, shift = a->indexshift; 185 int *diag_offset = b->diag,diag,k; 186 int preserve_row_sums = (int) a->ilu_preserve_row_sums; 187 register int *pj; 188 Scalar *rtmp,*v, *pc, multiplier,sum,inner_sum,*rowsums = 0; 189 double ssum; 190 register Scalar *pv, *rtmps,*u_values; 191 192 PetscFunctionBegin; 193 194 ierr = ISGetIndices(isrow,&r); CHKERRQ(ierr); 195 ierr = ISGetIndices(isicol,&ic); CHKERRQ(ierr); 196 rtmp = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar) ); CHKPTRQ(rtmp); 197 PetscMemzero(rtmp,(n+1)*sizeof(Scalar)); 198 rtmps = rtmp + shift; ics = ic + shift; 199 200 /* precalcuate row sums */ 201 if (preserve_row_sums) { 202 rowsums = (Scalar *) PetscMalloc( n*sizeof(Scalar) ); CHKPTRQ(rowsums); 203 for ( i=0; i<n; i++ ) { 204 nz = a->i[r[i]+1] - a->i[r[i]]; 205 v = a->a + a->i[r[i]] + shift; 206 sum = 0.0; 207 for ( j=0; j<nz; j++ ) sum += v[j]; 208 rowsums[i] = sum; 209 } 210 } 211 212 for ( i=0; i<n; i++ ) { 213 nz = ai[i+1] - ai[i]; 214 ajtmp = aj + ai[i] + shift; 215 for ( j=0; j<nz; j++ ) rtmps[ajtmp[j]] = 0.0; 216 217 /* load in initial (unfactored row) */ 218 nz = a->i[r[i]+1] - a->i[r[i]]; 219 ajtmpold = a->j + a->i[r[i]] + shift; 220 v = a->a + a->i[r[i]] + shift; 221 for ( j=0; j<nz; j++ ) rtmp[ics[ajtmpold[j]]] = v[j]; 222 223 row = *ajtmp++ + shift; 224 while (row < i ) { 225 pc = rtmp + row; 226 if (*pc != 0.0) { 227 pv = b->a + diag_offset[row] + shift; 228 pj = b->j + diag_offset[row] + (!shift); 229 multiplier = *pc / *pv++; 230 *pc = multiplier; 231 nz = ai[row+1] - diag_offset[row] - 1; 232 for (j=0; j<nz; j++) rtmps[pj[j]] -= multiplier * pv[j]; 233 PLogFlops(2*nz); 234 } 235 row = *ajtmp++ + shift; 236 } 237 /* finished row so stick it into b->a */ 238 pv = b->a + ai[i] + shift; 239 pj = b->j + ai[i] + shift; 240 nz = ai[i+1] - ai[i]; 241 for ( j=0; j<nz; j++ ) {pv[j] = rtmps[pj[j]];} 242 diag = diag_offset[i] - ai[i]; 243 /* 244 Possibly adjust diagonal entry on current row to force 245 LU matrix to have same row sum as initial matrix. 246 */ 247 if (pv[diag] == 0.0) { 248 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,0,"Zero pivot"); 249 } 250 if (preserve_row_sums) { 251 pj = b->j + ai[i] + shift; 252 sum = rowsums[i]; 253 for ( j=0; j<diag; j++ ) { 254 u_values = b->a + diag_offset[pj[j]] + shift; 255 nz = ai[pj[j]+1] - diag_offset[pj[j]]; 256 inner_sum = 0.0; 257 for ( k=0; k<nz; k++ ) { 258 inner_sum += u_values[k]; 259 } 260 sum -= pv[j]*inner_sum; 261 262 } 263 nz = ai[i+1] - diag_offset[i] - 1; 264 u_values = b->a + diag_offset[i] + 1 + shift; 265 for ( k=0; k<nz; k++ ) { 266 sum -= u_values[k]; 267 } 268 ssum = PetscAbsScalar(sum/pv[diag]); 269 if (ssum < 1000. && ssum > .001) pv[diag] = sum; 270 } 271 /* check pivot entry for current row */ 272 } 273 274 /* invert diagonal entries for simplier triangular solves */ 275 for ( i=0; i<n; i++ ) { 276 b->a[diag_offset[i]+shift] = 1.0/b->a[diag_offset[i]+shift]; 277 } 278 279 if (preserve_row_sums) PetscFree(rowsums); 280 PetscFree(rtmp); 281 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 282 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 283 C->factor = FACTOR_LU; 284 ierr = Mat_AIJ_CheckInode(C); CHKERRQ(ierr); 285 C->assembled = PETSC_TRUE; 286 PLogFlops(b->n); 287 PetscFunctionReturn(0); 288 } 289 /* ----------------------------------------------------------- */ 290 #undef __FUNC__ 291 #define __FUNC__ "MatLUFactor_SeqAIJ" 292 int MatLUFactor_SeqAIJ(Mat A,IS row,IS col,double f) 293 { 294 Mat_SeqAIJ *mat = (Mat_SeqAIJ *) A->data; 295 int ierr; 296 Mat C; 297 PetscOps *Abops; 298 struct _MatOps *Aops; 299 300 PetscFunctionBegin; 301 ierr = MatLUFactorSymbolic(A,row,col,f,&C); CHKERRQ(ierr); 302 ierr = MatLUFactorNumeric(A,&C); CHKERRQ(ierr); 303 304 /* free all the data structures from mat */ 305 PetscFree(mat->a); 306 if (!mat->singlemalloc) {PetscFree(mat->i); PetscFree(mat->j);} 307 if (mat->diag) PetscFree(mat->diag); 308 if (mat->ilen) PetscFree(mat->ilen); 309 if (mat->imax) PetscFree(mat->imax); 310 if (mat->solve_work) PetscFree(mat->solve_work); 311 if (mat->inode.size) PetscFree(mat->inode.size); 312 PetscFree(mat); 313 314 /* 315 This is horrible, horrible code. We need to keep the 316 A pointers for the bops and ops but copy everything 317 else from C. 318 */ 319 Abops = A->bops; 320 Aops = A->ops; 321 PetscMemcpy(A,C,sizeof(struct _p_Mat)); 322 A->bops = Abops; 323 A->ops = Aops; 324 325 PetscHeaderDestroy(C); 326 PetscFunctionReturn(0); 327 } 328 /* ----------------------------------------------------------- */ 329 #undef __FUNC__ 330 #define __FUNC__ "MatSolve_SeqAIJ" 331 int MatSolve_SeqAIJ(Mat A,Vec bb, Vec xx) 332 { 333 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 334 IS iscol = a->col, isrow = a->row; 335 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 336 int nz,shift = a->indexshift,*rout,*cout; 337 Scalar *x,*b,*tmp, *tmps, *aa = a->a, sum, *v; 338 339 PetscFunctionBegin; 340 if (!n) PetscFunctionReturn(0); 341 342 VecGetArray_Fast(bb,b); 343 VecGetArray_Fast(xx,x); 344 tmp = a->solve_work; 345 346 ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout; 347 ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout + (n-1); 348 349 /* forward solve the lower triangular */ 350 tmp[0] = b[*r++]; 351 tmps = tmp + shift; 352 for ( i=1; i<n; i++ ) { 353 v = aa + ai[i] + shift; 354 vi = aj + ai[i] + shift; 355 nz = a->diag[i] - ai[i]; 356 sum = b[*r++]; 357 while (nz--) sum -= *v++ * tmps[*vi++]; 358 tmp[i] = sum; 359 } 360 361 /* backward solve the upper triangular */ 362 for ( i=n-1; i>=0; i-- ){ 363 v = aa + a->diag[i] + (!shift); 364 vi = aj + a->diag[i] + (!shift); 365 nz = ai[i+1] - a->diag[i] - 1; 366 sum = tmp[i]; 367 while (nz--) sum -= *v++ * tmps[*vi++]; 368 x[*c--] = tmp[i] = sum*aa[a->diag[i]+shift]; 369 } 370 371 ierr = ISRestoreIndices(isrow,&rout); CHKERRQ(ierr); 372 ierr = ISRestoreIndices(iscol,&cout); CHKERRQ(ierr); 373 PLogFlops(2*a->nz - a->n); 374 PetscFunctionReturn(0); 375 } 376 377 /* ----------------------------------------------------------- */ 378 #undef __FUNC__ 379 #define __FUNC__ "MatSolve_SeqAIJ_NaturalOrdering" 380 int MatSolve_SeqAIJ_NaturalOrdering(Mat A,Vec bb, Vec xx) 381 { 382 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 383 int n = a->m, *ai = a->i, *aj = a->j, *adiag = a->diag,ierr; 384 Scalar *x,*b, *aa = a->a, sum; 385 #if !defined(USE_FORTRAN_KERNELS) 386 int adiag_i,i,*vi,nz,ai_i; 387 Scalar *v; 388 #endif 389 390 PetscFunctionBegin; 391 if (!n) PetscFunctionReturn(0); 392 if (a->indexshift) { 393 ierr = MatSolve_SeqAIJ(A,bb,xx);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 VecGetArray_Fast(bb,b); 398 VecGetArray_Fast(xx,x); 399 400 #if defined(USE_FORTRAN_KERNELS) 401 fortransolveaij_(&n,x,ai,aj,adiag,aa,b); 402 #else 403 /* forward solve the lower triangular */ 404 x[0] = b[0]; 405 for ( i=1; i<n; i++ ) { 406 ai_i = ai[i]; 407 v = aa + ai_i; 408 vi = aj + ai_i; 409 nz = adiag[i] - ai_i; 410 sum = b[i]; 411 while (nz--) sum -= *v++ * x[*vi++]; 412 x[i] = sum; 413 } 414 415 /* backward solve the upper triangular */ 416 for ( i=n-1; i>=0; i-- ){ 417 adiag_i = adiag[i]; 418 v = aa + adiag_i + 1; 419 vi = aj + adiag_i + 1; 420 nz = ai[i+1] - adiag_i - 1; 421 sum = x[i]; 422 while (nz--) sum -= *v++ * x[*vi++]; 423 x[i] = sum*aa[adiag_i]; 424 } 425 #endif 426 PLogFlops(2*a->nz - a->n); 427 PetscFunctionReturn(0); 428 } 429 430 #undef __FUNC__ 431 #define __FUNC__ "MatSolveAdd_SeqAIJ" 432 int MatSolveAdd_SeqAIJ(Mat A,Vec bb, Vec yy, Vec xx) 433 { 434 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 435 IS iscol = a->col, isrow = a->row; 436 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 437 int nz, shift = a->indexshift,*rout,*cout; 438 Scalar *x,*b,*tmp, *aa = a->a, sum, *v; 439 440 PetscFunctionBegin; 441 if (yy != xx) {ierr = VecCopy(yy,xx); CHKERRQ(ierr);} 442 443 VecGetArray_Fast(bb,b); 444 VecGetArray_Fast(xx,x); 445 tmp = a->solve_work; 446 447 ierr = ISGetIndices(isrow,&rout); CHKERRQ(ierr); r = rout; 448 ierr = ISGetIndices(iscol,&cout); CHKERRQ(ierr); c = cout + (n-1); 449 450 /* forward solve the lower triangular */ 451 tmp[0] = b[*r++]; 452 for ( i=1; i<n; i++ ) { 453 v = aa + ai[i] + shift; 454 vi = aj + ai[i] + shift; 455 nz = a->diag[i] - ai[i]; 456 sum = b[*r++]; 457 while (nz--) sum -= *v++ * tmp[*vi++ + shift]; 458 tmp[i] = sum; 459 } 460 461 /* backward solve the upper triangular */ 462 for ( i=n-1; i>=0; i-- ){ 463 v = aa + a->diag[i] + (!shift); 464 vi = aj + a->diag[i] + (!shift); 465 nz = ai[i+1] - a->diag[i] - 1; 466 sum = tmp[i]; 467 while (nz--) sum -= *v++ * tmp[*vi++ + shift]; 468 tmp[i] = sum*aa[a->diag[i]+shift]; 469 x[*c--] += tmp[i]; 470 } 471 472 ierr = ISRestoreIndices(isrow,&rout); CHKERRQ(ierr); 473 ierr = ISRestoreIndices(iscol,&cout); CHKERRQ(ierr); 474 PLogFlops(2*a->nz); 475 476 PetscFunctionReturn(0); 477 } 478 /* -------------------------------------------------------------------*/ 479 #undef __FUNC__ 480 #define __FUNC__ "MatSolveTrans_SeqAIJ" 481 int MatSolveTrans_SeqAIJ(Mat A,Vec bb, Vec xx) 482 { 483 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 484 IS iscol = a->col, isrow = a->row, invisrow,inviscol; 485 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 486 int nz,shift = a->indexshift,*rout,*cout; 487 Scalar *x,*b,*tmp, *aa = a->a, *v; 488 489 PetscFunctionBegin; 490 VecGetArray_Fast(bb,b); 491 VecGetArray_Fast(xx,x); 492 tmp = a->solve_work; 493 494 /* invert the permutations */ 495 ierr = ISInvertPermutation(isrow,&invisrow); CHKERRQ(ierr); 496 ierr = ISInvertPermutation(iscol,&inviscol); CHKERRQ(ierr); 497 498 ierr = ISGetIndices(invisrow,&rout); CHKERRQ(ierr); r = rout; 499 ierr = ISGetIndices(inviscol,&cout); CHKERRQ(ierr); c = cout; 500 501 /* copy the b into temp work space according to permutation */ 502 for ( i=0; i<n; i++ ) tmp[c[i]] = b[i]; 503 504 /* forward solve the U^T */ 505 for ( i=0; i<n; i++ ) { 506 v = aa + a->diag[i] + shift; 507 vi = aj + a->diag[i] + (!shift); 508 nz = ai[i+1] - a->diag[i] - 1; 509 tmp[i] *= *v++; 510 while (nz--) { 511 tmp[*vi++ + shift] -= (*v++)*tmp[i]; 512 } 513 } 514 515 /* backward solve the L^T */ 516 for ( i=n-1; i>=0; i-- ){ 517 v = aa + a->diag[i] - 1 + shift; 518 vi = aj + a->diag[i] - 1 + shift; 519 nz = a->diag[i] - ai[i]; 520 while (nz--) { 521 tmp[*vi-- + shift] -= (*v--)*tmp[i]; 522 } 523 } 524 525 /* copy tmp into x according to permutation */ 526 for ( i=0; i<n; i++ ) x[r[i]] = tmp[i]; 527 528 ierr = ISRestoreIndices(invisrow,&rout); CHKERRQ(ierr); 529 ierr = ISRestoreIndices(inviscol,&cout); CHKERRQ(ierr); 530 ierr = ISDestroy(invisrow); CHKERRQ(ierr); 531 ierr = ISDestroy(inviscol); CHKERRQ(ierr); 532 533 PLogFlops(2*a->nz-a->n); 534 PetscFunctionReturn(0); 535 } 536 537 #undef __FUNC__ 538 #define __FUNC__ "MatSolveTransAdd_SeqAIJ" 539 int MatSolveTransAdd_SeqAIJ(Mat A,Vec bb, Vec zz,Vec xx) 540 { 541 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 542 IS iscol = a->col, isrow = a->row, invisrow,inviscol; 543 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 544 int nz,shift = a->indexshift, *rout, *cout; 545 Scalar *x,*b,*tmp, *aa = a->a, *v; 546 547 PetscFunctionBegin; 548 if (zz != xx) VecCopy(zz,xx); 549 550 VecGetArray_Fast(bb,b); 551 VecGetArray_Fast(xx,x); 552 tmp = a->solve_work; 553 554 /* invert the permutations */ 555 ierr = ISInvertPermutation(isrow,&invisrow); CHKERRQ(ierr); 556 ierr = ISInvertPermutation(iscol,&inviscol); CHKERRQ(ierr); 557 ierr = ISGetIndices(invisrow,&rout); CHKERRQ(ierr); r = rout; 558 ierr = ISGetIndices(inviscol,&cout); CHKERRQ(ierr); c = cout; 559 560 /* copy the b into temp work space according to permutation */ 561 for ( i=0; i<n; i++ ) tmp[c[i]] = b[i]; 562 563 /* forward solve the U^T */ 564 for ( i=0; i<n; i++ ) { 565 v = aa + a->diag[i] + shift; 566 vi = aj + a->diag[i] + (!shift); 567 nz = ai[i+1] - a->diag[i] - 1; 568 tmp[i] *= *v++; 569 while (nz--) { 570 tmp[*vi++ + shift] -= (*v++)*tmp[i]; 571 } 572 } 573 574 /* backward solve the L^T */ 575 for ( i=n-1; i>=0; i-- ){ 576 v = aa + a->diag[i] - 1 + shift; 577 vi = aj + a->diag[i] - 1 + shift; 578 nz = a->diag[i] - ai[i]; 579 while (nz--) { 580 tmp[*vi-- + shift] -= (*v--)*tmp[i]; 581 } 582 } 583 584 /* copy tmp into x according to permutation */ 585 for ( i=0; i<n; i++ ) x[r[i]] += tmp[i]; 586 587 ierr = ISRestoreIndices(invisrow,&rout); CHKERRQ(ierr); 588 ierr = ISRestoreIndices(inviscol,&cout); CHKERRQ(ierr); 589 ierr = ISDestroy(invisrow); CHKERRQ(ierr); 590 ierr = ISDestroy(inviscol); CHKERRQ(ierr); 591 592 PLogFlops(2*a->nz); 593 PetscFunctionReturn(0); 594 } 595 /* ----------------------------------------------------------------*/ 596 597 #undef __FUNC__ 598 #define __FUNC__ "MatILUFactorSymbolic_SeqAIJ" 599 int MatILUFactorSymbolic_SeqAIJ(Mat A,IS isrow,IS iscol,double f,int levels,Mat *fact) 600 { 601 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data, *b; 602 IS isicol; 603 int *r,*ic, ierr, prow, n = a->m, *ai = a->i, *aj = a->j; 604 int *ainew,*ajnew, jmax,*fill, *xi, nz, *im,*ajfill,*flev; 605 int *dloc, idx, row,m,fm, nzf, nzi,len, realloc = 0; 606 int incrlev,nnz,i,shift = a->indexshift; 607 PetscTruth col_identity, row_identity; 608 609 PetscFunctionBegin; 610 ierr = ISInvertPermutation(iscol,&isicol); CHKERRQ(ierr); 611 PLogObjectParent(*fact,isicol); 612 613 /* special case that simply copies fill pattern */ 614 ISIdentity(isrow,&row_identity); ISIdentity(iscol,&col_identity); 615 if (levels == 0 && row_identity && col_identity) { 616 ierr = MatConvertSameType_SeqAIJ(A,fact,DO_NOT_COPY_VALUES); CHKERRQ(ierr); 617 (*fact)->factor = FACTOR_LU; 618 b = (Mat_SeqAIJ *) (*fact)->data; 619 if (!b->diag) { 620 ierr = MatMarkDiag_SeqAIJ(*fact); CHKERRQ(ierr); 621 } 622 b->row = isrow; 623 b->col = iscol; 624 b->icol = isicol; 625 b->solve_work = (Scalar *) PetscMalloc((b->m+1)*sizeof(Scalar));CHKPTRQ(b->solve_work); 626 (*fact)->ops->solve = MatSolve_SeqAIJ_NaturalOrdering; 627 PetscFunctionReturn(0); 628 } 629 630 ierr = ISGetIndices(isrow,&r); CHKERRQ(ierr); 631 ierr = ISGetIndices(isicol,&ic); CHKERRQ(ierr); 632 633 /* get new row pointers */ 634 ainew = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(ainew); 635 ainew[0] = -shift; 636 /* don't know how many column pointers are needed so estimate */ 637 jmax = (int) (f*(ai[n]+!shift)); 638 ajnew = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajnew); 639 /* ajfill is level of fill for each fill entry */ 640 ajfill = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajfill); 641 /* fill is a linked list of nonzeros in active row */ 642 fill = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(fill); 643 /* im is level for each filled value */ 644 im = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(im); 645 /* dloc is location of diagonal in factor */ 646 dloc = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(dloc); 647 dloc[0] = 0; 648 for ( prow=0; prow<n; prow++ ) { 649 /* first copy previous fill into linked list */ 650 nzf = nz = ai[r[prow]+1] - ai[r[prow]]; 651 if (!nz) SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,1,"Empty row in matrix"); 652 xi = aj + ai[r[prow]] + shift; 653 fill[n] = n; 654 while (nz--) { 655 fm = n; 656 idx = ic[*xi++ + shift]; 657 do { 658 m = fm; 659 fm = fill[m]; 660 } while (fm < idx); 661 fill[m] = idx; 662 fill[idx] = fm; 663 im[idx] = 0; 664 } 665 nzi = 0; 666 row = fill[n]; 667 while ( row < prow ) { 668 incrlev = im[row] + 1; 669 nz = dloc[row]; 670 xi = ajnew + ainew[row] + shift + nz; 671 flev = ajfill + ainew[row] + shift + nz + 1; 672 nnz = ainew[row+1] - ainew[row] - nz - 1; 673 if (*xi++ + shift != row) { 674 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,0,"Zero pivot: try running with -pc_ilu_nonzeros_along_diagonal"); 675 } 676 fm = row; 677 while (nnz-- > 0) { 678 idx = *xi++ + shift; 679 if (*flev + incrlev > levels) { 680 flev++; 681 continue; 682 } 683 do { 684 m = fm; 685 fm = fill[m]; 686 } while (fm < idx); 687 if (fm != idx) { 688 im[idx] = *flev + incrlev; 689 fill[m] = idx; 690 fill[idx] = fm; 691 fm = idx; 692 nzf++; 693 } else { 694 if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev; 695 } 696 flev++; 697 } 698 row = fill[row]; 699 nzi++; 700 } 701 /* copy new filled row into permanent storage */ 702 ainew[prow+1] = ainew[prow] + nzf; 703 if (ainew[prow+1] > jmax-shift) { 704 705 /* estimate how much additional space we will need */ 706 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 707 /* just double the memory each time */ 708 /* maxadd = (int) ((f*(ai[n]+!shift)*(n-prow+5))/n); */ 709 int maxadd = jmax; 710 if (maxadd < nzf) maxadd = (n-prow)*(nzf+1); 711 jmax += maxadd; 712 713 /* allocate a longer ajnew and ajfill */ 714 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 715 PetscMemcpy(xi,ajnew,(ainew[prow]+shift)*sizeof(int)); 716 PetscFree(ajnew); 717 ajnew = xi; 718 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 719 PetscMemcpy(xi,ajfill,(ainew[prow]+shift)*sizeof(int)); 720 PetscFree(ajfill); 721 ajfill = xi; 722 realloc++; /* count how many times we realloc */ 723 } 724 xi = ajnew + ainew[prow] + shift; 725 flev = ajfill + ainew[prow] + shift; 726 dloc[prow] = nzi; 727 fm = fill[n]; 728 while (nzf--) { 729 *xi++ = fm - shift; 730 *flev++ = im[fm]; 731 fm = fill[fm]; 732 } 733 } 734 PetscFree(ajfill); 735 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 736 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 737 PetscFree(fill); PetscFree(im); 738 739 { 740 double af = ((double)ainew[n])/((double)ai[n]); 741 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Reallocs %d Fill ratio:given %g needed %g\n", 742 realloc,f,af); 743 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Run with -pc_ilu_fill %g or use \n",af); 744 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:PCILUSetFill(pc,%g);\n",af); 745 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:for best performance.\n"); 746 } 747 748 /* put together the new matrix */ 749 ierr = MatCreateSeqAIJ(A->comm,n,n,0,PETSC_NULL,fact); CHKERRQ(ierr); 750 b = (Mat_SeqAIJ *) (*fact)->data; 751 PetscFree(b->imax); 752 b->singlemalloc = 0; 753 len = (ainew[n] + shift)*sizeof(Scalar); 754 /* the next line frees the default space generated by the Create() */ 755 PetscFree(b->a); PetscFree(b->ilen); 756 b->a = (Scalar *) PetscMalloc( len+1 ); CHKPTRQ(b->a); 757 b->j = ajnew; 758 b->i = ainew; 759 for ( i=0; i<n; i++ ) dloc[i] += ainew[i]; 760 b->diag = dloc; 761 b->ilen = 0; 762 b->imax = 0; 763 b->row = isrow; 764 b->col = iscol; 765 b->icol = isicol; 766 b->solve_work = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar)); CHKPTRQ(b->solve_work); 767 /* In b structure: Free imax, ilen, old a, old j. 768 Allocate dloc, solve_work, new a, new j */ 769 PLogObjectMemory(*fact,(ainew[n]+shift-n) * (sizeof(int)+sizeof(Scalar))); 770 b->maxnz = b->nz = ainew[n] + shift; 771 (*fact)->factor = FACTOR_LU; 772 773 (*fact)->info.factor_mallocs = realloc; 774 (*fact)->info.fill_ratio_given = f; 775 (*fact)->info.fill_ratio_needed = ((double)ainew[n])/((double)ai[prow]); 776 777 PetscFunctionReturn(0); 778 } 779 780 781 782 783