1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: aijfact.c,v 1.96 1998/03/16 18:51:28 balay Exp bsmith $"; 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 ISGetIndices(isrow,&r); ISGetIndices(isicol,&ic); 40 41 /* get new row pointers */ 42 ainew = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(ainew); 43 ainew[0] = -shift; 44 /* don't know how many column pointers are needed so estimate */ 45 jmax = (int) (f*ai[n]+(!shift)); 46 ajnew = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajnew); 47 /* fill is a linked list of nonzeros in active row */ 48 fill = (int *) PetscMalloc( (2*n+1)*sizeof(int)); CHKPTRQ(fill); 49 im = fill + n + 1; 50 /* idnew is location of diagonal in factor */ 51 idnew = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(idnew); 52 idnew[0] = -shift; 53 54 for ( i=0; i<n; i++ ) { 55 /* first copy previous fill into linked list */ 56 nnz = nz = ai[r[i]+1] - ai[r[i]]; 57 if (!nz) SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,1,"Empty row in matrix"); 58 ajtmp = aj + ai[r[i]] + shift; 59 fill[n] = n; 60 while (nz--) { 61 fm = n; 62 idx = ic[*ajtmp++ + shift]; 63 do { 64 m = fm; 65 fm = fill[m]; 66 } while (fm < idx); 67 fill[m] = idx; 68 fill[idx] = fm; 69 } 70 row = fill[n]; 71 while ( row < i ) { 72 ajtmp = ajnew + idnew[row] + (!shift); 73 nzbd = 1 + idnew[row] - ainew[row]; 74 nz = im[row] - nzbd; 75 fm = row; 76 while (nz-- > 0) { 77 idx = *ajtmp++ + shift; 78 nzbd++; 79 if (idx == i) im[row] = nzbd; 80 do { 81 m = fm; 82 fm = fill[m]; 83 } while (fm < idx); 84 if (fm != idx) { 85 fill[m] = idx; 86 fill[idx] = fm; 87 fm = idx; 88 nnz++; 89 } 90 } 91 row = fill[row]; 92 } 93 /* copy new filled row into permanent storage */ 94 ainew[i+1] = ainew[i] + nnz; 95 if (ainew[i+1] > jmax) { 96 97 /* estimate how much additional space we will need */ 98 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 99 /* just double the memory each time */ 100 int maxadd = jmax; 101 /* maxadd = (int) ((f*(ai[n]+(!shift))*(n-i+5))/n); */ 102 if (maxadd < nnz) maxadd = (n-i)*(nnz+1); 103 jmax += maxadd; 104 105 /* allocate a longer ajnew */ 106 ajtmp = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(ajtmp); 107 PetscMemcpy(ajtmp,ajnew,(ainew[i]+shift)*sizeof(int)); 108 PetscFree(ajnew); 109 ajnew = ajtmp; 110 realloc++; /* count how many times we realloc */ 111 } 112 ajtmp = ajnew + ainew[i] + shift; 113 fm = fill[n]; 114 nzi = 0; 115 im[i] = nnz; 116 while (nnz--) { 117 if (fm < i) nzi++; 118 *ajtmp++ = fm - shift; 119 fm = fill[fm]; 120 } 121 idnew[i] = ainew[i] + nzi; 122 } 123 if (ai[n] != 0) { 124 double af = ((double)ainew[n])/((double)ai[n]); 125 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:Reallocs %d Fill ratio:given %g needed %g\n", 126 realloc,f,af); 127 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:Run with -pc_lu_fill %g or use \n",af); 128 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:PCLUSetFill(pc,%g);\n",af); 129 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ:for best performance.\n"); 130 } else { 131 PLogInfo(A,"MatLUFactorSymbolic_SeqAIJ: Empty matrix\n"); 132 } 133 134 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 135 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 136 137 PetscFree(fill); 138 139 /* put together the new matrix */ 140 ierr = MatCreateSeqAIJ(A->comm,n,n,0,PETSC_NULL,B); CHKERRQ(ierr); 141 PLogObjectParent(*B,isicol); 142 b = (Mat_SeqAIJ *) (*B)->data; 143 PetscFree(b->imax); 144 b->singlemalloc = 0; 145 /* the next line frees the default space generated by the Create() */ 146 PetscFree(b->a); PetscFree(b->ilen); 147 b->a = (Scalar *) PetscMalloc((ainew[n]+shift+1)*sizeof(Scalar));CHKPTRQ(b->a); 148 b->j = ajnew; 149 b->i = ainew; 150 b->diag = idnew; 151 b->ilen = 0; 152 b->imax = 0; 153 b->row = isrow; 154 b->col = iscol; 155 b->icol = isicol; 156 b->solve_work = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar));CHKPTRQ(b->solve_work); 157 /* In b structure: Free imax, ilen, old a, old j. 158 Allocate idnew, solve_work, new a, new j */ 159 PLogObjectMemory(*B,(ainew[n]+shift-n)*(sizeof(int)+sizeof(Scalar))); 160 b->maxnz = b->nz = ainew[n] + shift; 161 162 (*B)->info.factor_mallocs = realloc; 163 (*B)->info.fill_ratio_given = f; 164 if (ai[i] != 0) { 165 (*B)->info.fill_ratio_needed = ((double)ainew[n])/((double)ai[i]); 166 } else { 167 (*B)->info.fill_ratio_needed = 0.0; 168 } 169 170 PetscFunctionReturn(0); 171 } 172 /* ----------------------------------------------------------- */ 173 int Mat_AIJ_CheckInode(Mat); 174 175 #undef __FUNC__ 176 #define __FUNC__ "MatLUFactorNumeric_SeqAIJ" 177 int MatLUFactorNumeric_SeqAIJ(Mat A,Mat *B) 178 { 179 Mat C = *B; 180 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data, *b = (Mat_SeqAIJ *)C->data; 181 IS isrow = b->row, isicol = b->icol; 182 int *r,*ic, ierr, i, j, n = a->m, *ai = b->i, *aj = b->j; 183 int *ajtmpold, *ajtmp, nz, row, *ics, shift = a->indexshift; 184 int *diag_offset = b->diag,diag,k; 185 int preserve_row_sums = (int) a->ilu_preserve_row_sums; 186 register int *pj; 187 Scalar *rtmp,*v, *pc, multiplier,sum,inner_sum,*rowsums = 0; 188 double ssum; 189 register Scalar *pv, *rtmps,*u_values; 190 191 PetscFunctionBegin; 192 193 ierr = ISGetIndices(isrow,&r); CHKERRQ(ierr); 194 ierr = ISGetIndices(isicol,&ic); CHKERRQ(ierr); 195 rtmp = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar) ); CHKPTRQ(rtmp); 196 PetscMemzero(rtmp,(n+1)*sizeof(Scalar)); 197 rtmps = rtmp + shift; ics = ic + shift; 198 199 /* precalcuate row sums */ 200 if (preserve_row_sums) { 201 rowsums = (Scalar *) PetscMalloc( n*sizeof(Scalar) ); CHKPTRQ(rowsums); 202 for ( i=0; i<n; i++ ) { 203 nz = a->i[r[i]+1] - a->i[r[i]]; 204 v = a->a + a->i[r[i]] + shift; 205 sum = 0.0; 206 for ( j=0; j<nz; j++ ) sum += v[j]; 207 rowsums[i] = sum; 208 } 209 } 210 211 for ( i=0; i<n; i++ ) { 212 nz = ai[i+1] - ai[i]; 213 ajtmp = aj + ai[i] + shift; 214 for ( j=0; j<nz; j++ ) rtmps[ajtmp[j]] = 0.0; 215 216 /* load in initial (unfactored row) */ 217 nz = a->i[r[i]+1] - a->i[r[i]]; 218 ajtmpold = a->j + a->i[r[i]] + shift; 219 v = a->a + a->i[r[i]] + shift; 220 for ( j=0; j<nz; j++ ) rtmp[ics[ajtmpold[j]]] = v[j]; 221 222 row = *ajtmp++ + shift; 223 while (row < i ) { 224 pc = rtmp + row; 225 if (*pc != 0.0) { 226 pv = b->a + diag_offset[row] + shift; 227 pj = b->j + diag_offset[row] + (!shift); 228 multiplier = *pc / *pv++; 229 *pc = multiplier; 230 nz = ai[row+1] - diag_offset[row] - 1; 231 for (j=0; j<nz; j++) rtmps[pj[j]] -= multiplier * pv[j]; 232 PLogFlops(2*nz); 233 } 234 row = *ajtmp++ + shift; 235 } 236 /* finished row so stick it into b->a */ 237 pv = b->a + ai[i] + shift; 238 pj = b->j + ai[i] + shift; 239 nz = ai[i+1] - ai[i]; 240 for ( j=0; j<nz; j++ ) {pv[j] = rtmps[pj[j]];} 241 diag = diag_offset[i] - ai[i]; 242 /* 243 Possibly adjust diagonal entry on current row to force 244 LU matrix to have same row sum as initial matrix. 245 */ 246 if (pv[diag] == 0.0) { 247 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,0,"Zero pivot"); 248 } 249 if (preserve_row_sums) { 250 pj = b->j + ai[i] + shift; 251 sum = rowsums[i]; 252 for ( j=0; j<diag; j++ ) { 253 u_values = b->a + diag_offset[pj[j]] + shift; 254 nz = ai[pj[j]+1] - diag_offset[pj[j]]; 255 inner_sum = 0.0; 256 for ( k=0; k<nz; k++ ) { 257 inner_sum += u_values[k]; 258 } 259 sum -= pv[j]*inner_sum; 260 261 } 262 nz = ai[i+1] - diag_offset[i] - 1; 263 u_values = b->a + diag_offset[i] + 1 + shift; 264 for ( k=0; k<nz; k++ ) { 265 sum -= u_values[k]; 266 } 267 ssum = PetscAbsScalar(sum/pv[diag]); 268 if (ssum < 1000. && ssum > .001) pv[diag] = sum; 269 } 270 /* check pivot entry for current row */ 271 } 272 273 /* invert diagonal entries for simplier triangular solves */ 274 for ( i=0; i<n; i++ ) { 275 b->a[diag_offset[i]+shift] = 1.0/b->a[diag_offset[i]+shift]; 276 } 277 278 if (preserve_row_sums) PetscFree(rowsums); 279 PetscFree(rtmp); 280 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 281 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 282 C->factor = FACTOR_LU; 283 ierr = Mat_AIJ_CheckInode(C); CHKERRQ(ierr); 284 C->assembled = PETSC_TRUE; 285 PLogFlops(b->n); 286 PetscFunctionReturn(0); 287 } 288 /* ----------------------------------------------------------- */ 289 #undef __FUNC__ 290 #define __FUNC__ "MatLUFactor_SeqAIJ" 291 int MatLUFactor_SeqAIJ(Mat A,IS row,IS col,double f) 292 { 293 Mat_SeqAIJ *mat = (Mat_SeqAIJ *) A->data; 294 int ierr; 295 Mat C; 296 PetscOps *Abops; 297 struct _MatOps *Aops; 298 299 PetscFunctionBegin; 300 ierr = MatLUFactorSymbolic(A,row,col,f,&C); CHKERRQ(ierr); 301 ierr = MatLUFactorNumeric(A,&C); CHKERRQ(ierr); 302 303 /* free all the data structures from mat */ 304 PetscFree(mat->a); 305 if (!mat->singlemalloc) {PetscFree(mat->i); PetscFree(mat->j);} 306 if (mat->diag) PetscFree(mat->diag); 307 if (mat->ilen) PetscFree(mat->ilen); 308 if (mat->imax) PetscFree(mat->imax); 309 if (mat->solve_work) PetscFree(mat->solve_work); 310 if (mat->inode.size) PetscFree(mat->inode.size); 311 PetscFree(mat); 312 313 /* 314 This is horrible, horrible code. We need to keep the 315 A pointers for the bops and ops but copy everything 316 else from C. 317 */ 318 Abops = A->bops; 319 Aops = A->ops; 320 PetscMemcpy(A,C,sizeof(struct _p_Mat)); 321 A->bops = Abops; 322 A->ops = Aops; 323 324 PetscHeaderDestroy(C); 325 PetscFunctionReturn(0); 326 } 327 /* ----------------------------------------------------------- */ 328 #undef __FUNC__ 329 #define __FUNC__ "MatSolve_SeqAIJ" 330 int MatSolve_SeqAIJ(Mat A,Vec bb, Vec xx) 331 { 332 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 333 IS iscol = a->col, isrow = a->row; 334 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 335 int nz,shift = a->indexshift,*rout,*cout; 336 Scalar *x,*b,*tmp, *tmps, *aa = a->a, sum, *v; 337 338 PetscFunctionBegin; 339 if (!n) PetscFunctionReturn(0); 340 341 VecGetArray_Fast(bb,b); 342 VecGetArray_Fast(xx,x); 343 tmp = a->solve_work; 344 345 ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout; 346 ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout + (n-1); 347 348 /* forward solve the lower triangular */ 349 tmp[0] = b[*r++]; 350 tmps = tmp + shift; 351 for ( i=1; i<n; i++ ) { 352 v = aa + ai[i] + shift; 353 vi = aj + ai[i] + shift; 354 nz = a->diag[i] - ai[i]; 355 sum = b[*r++]; 356 while (nz--) sum -= *v++ * tmps[*vi++]; 357 tmp[i] = sum; 358 } 359 360 /* backward solve the upper triangular */ 361 for ( i=n-1; i>=0; i-- ){ 362 v = aa + a->diag[i] + (!shift); 363 vi = aj + a->diag[i] + (!shift); 364 nz = ai[i+1] - a->diag[i] - 1; 365 sum = tmp[i]; 366 while (nz--) sum -= *v++ * tmps[*vi++]; 367 x[*c--] = tmp[i] = sum*aa[a->diag[i]+shift]; 368 } 369 370 ierr = ISRestoreIndices(isrow,&rout); CHKERRQ(ierr); 371 ierr = ISRestoreIndices(iscol,&cout); CHKERRQ(ierr); 372 PLogFlops(2*a->nz - a->n); 373 PetscFunctionReturn(0); 374 } 375 376 /* ----------------------------------------------------------- */ 377 #undef __FUNC__ 378 #define __FUNC__ "MatSolve_SeqAIJ_NaturalOrdering" 379 int MatSolve_SeqAIJ_NaturalOrdering(Mat A,Vec bb, Vec xx) 380 { 381 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 382 int n = a->m, *ai = a->i, *aj = a->j, *adiag = a->diag,ierr; 383 Scalar *x,*b, *aa = a->a, sum; 384 #if !defined(USE_FORTRAN_KERNELS) 385 int adiag_i,i,*vi,nz,ai_i; 386 Scalar *v; 387 #endif 388 389 PetscFunctionBegin; 390 if (!n) PetscFunctionReturn(0); 391 if (a->indexshift) { 392 ierr = MatSolve_SeqAIJ(A,bb,xx);CHKERRQ(ierr); 393 PetscFunctionReturn(0); 394 } 395 396 VecGetArray_Fast(bb,b); 397 VecGetArray_Fast(xx,x); 398 399 #if defined(USE_FORTRAN_KERNELS) 400 fortransolveaij_(&n,x,ai,aj,adiag,aa,b); 401 #else 402 /* forward solve the lower triangular */ 403 x[0] = b[0]; 404 for ( i=1; i<n; i++ ) { 405 ai_i = ai[i]; 406 v = aa + ai_i; 407 vi = aj + ai_i; 408 nz = adiag[i] - ai_i; 409 sum = b[i]; 410 while (nz--) sum -= *v++ * x[*vi++]; 411 x[i] = sum; 412 } 413 414 /* backward solve the upper triangular */ 415 for ( i=n-1; i>=0; i-- ){ 416 adiag_i = adiag[i]; 417 v = aa + adiag_i + 1; 418 vi = aj + adiag_i + 1; 419 nz = ai[i+1] - adiag_i - 1; 420 sum = x[i]; 421 while (nz--) sum -= *v++ * x[*vi++]; 422 x[i] = sum*aa[adiag_i]; 423 } 424 #endif 425 PLogFlops(2*a->nz - a->n); 426 PetscFunctionReturn(0); 427 } 428 429 #undef __FUNC__ 430 #define __FUNC__ "MatSolveAdd_SeqAIJ" 431 int MatSolveAdd_SeqAIJ(Mat A,Vec bb, Vec yy, Vec xx) 432 { 433 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 434 IS iscol = a->col, isrow = a->row; 435 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 436 int nz, shift = a->indexshift,*rout,*cout; 437 Scalar *x,*b,*tmp, *aa = a->a, sum, *v; 438 439 PetscFunctionBegin; 440 if (yy != xx) {ierr = VecCopy(yy,xx); CHKERRQ(ierr);} 441 442 VecGetArray_Fast(bb,b); 443 VecGetArray_Fast(xx,x); 444 tmp = a->solve_work; 445 446 ierr = ISGetIndices(isrow,&rout); CHKERRQ(ierr); r = rout; 447 ierr = ISGetIndices(iscol,&cout); CHKERRQ(ierr); c = cout + (n-1); 448 449 /* forward solve the lower triangular */ 450 tmp[0] = b[*r++]; 451 for ( i=1; i<n; i++ ) { 452 v = aa + ai[i] + shift; 453 vi = aj + ai[i] + shift; 454 nz = a->diag[i] - ai[i]; 455 sum = b[*r++]; 456 while (nz--) sum -= *v++ * tmp[*vi++ + shift]; 457 tmp[i] = sum; 458 } 459 460 /* backward solve the upper triangular */ 461 for ( i=n-1; i>=0; i-- ){ 462 v = aa + a->diag[i] + (!shift); 463 vi = aj + a->diag[i] + (!shift); 464 nz = ai[i+1] - a->diag[i] - 1; 465 sum = tmp[i]; 466 while (nz--) sum -= *v++ * tmp[*vi++ + shift]; 467 tmp[i] = sum*aa[a->diag[i]+shift]; 468 x[*c--] += tmp[i]; 469 } 470 471 ierr = ISRestoreIndices(isrow,&rout); CHKERRQ(ierr); 472 ierr = ISRestoreIndices(iscol,&cout); CHKERRQ(ierr); 473 PLogFlops(2*a->nz); 474 475 PetscFunctionReturn(0); 476 } 477 /* -------------------------------------------------------------------*/ 478 #undef __FUNC__ 479 #define __FUNC__ "MatSolveTrans_SeqAIJ" 480 int MatSolveTrans_SeqAIJ(Mat A,Vec bb, Vec xx) 481 { 482 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 483 IS iscol = a->col, isrow = a->row, invisrow,inviscol; 484 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 485 int nz,shift = a->indexshift,*rout,*cout; 486 Scalar *x,*b,*tmp, *aa = a->a, *v; 487 488 PetscFunctionBegin; 489 VecGetArray_Fast(bb,b); 490 VecGetArray_Fast(xx,x); 491 tmp = a->solve_work; 492 493 /* invert the permutations */ 494 ierr = ISInvertPermutation(isrow,&invisrow); CHKERRQ(ierr); 495 ierr = ISInvertPermutation(iscol,&inviscol); CHKERRQ(ierr); 496 497 ierr = ISGetIndices(invisrow,&rout); CHKERRQ(ierr); r = rout; 498 ierr = ISGetIndices(inviscol,&cout); CHKERRQ(ierr); c = cout; 499 500 /* copy the b into temp work space according to permutation */ 501 for ( i=0; i<n; i++ ) tmp[c[i]] = b[i]; 502 503 /* forward solve the U^T */ 504 for ( i=0; i<n; i++ ) { 505 v = aa + a->diag[i] + shift; 506 vi = aj + a->diag[i] + (!shift); 507 nz = ai[i+1] - a->diag[i] - 1; 508 tmp[i] *= *v++; 509 while (nz--) { 510 tmp[*vi++ + shift] -= (*v++)*tmp[i]; 511 } 512 } 513 514 /* backward solve the L^T */ 515 for ( i=n-1; i>=0; i-- ){ 516 v = aa + a->diag[i] - 1 + shift; 517 vi = aj + a->diag[i] - 1 + shift; 518 nz = a->diag[i] - ai[i]; 519 while (nz--) { 520 tmp[*vi-- + shift] -= (*v--)*tmp[i]; 521 } 522 } 523 524 /* copy tmp into x according to permutation */ 525 for ( i=0; i<n; i++ ) x[r[i]] = tmp[i]; 526 527 ierr = ISRestoreIndices(invisrow,&rout); CHKERRQ(ierr); 528 ierr = ISRestoreIndices(inviscol,&cout); CHKERRQ(ierr); 529 ierr = ISDestroy(invisrow); CHKERRQ(ierr); 530 ierr = ISDestroy(inviscol); CHKERRQ(ierr); 531 532 PLogFlops(2*a->nz-a->n); 533 PetscFunctionReturn(0); 534 } 535 536 #undef __FUNC__ 537 #define __FUNC__ "MatSolveTransAdd_SeqAIJ" 538 int MatSolveTransAdd_SeqAIJ(Mat A,Vec bb, Vec zz,Vec xx) 539 { 540 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 541 IS iscol = a->col, isrow = a->row, invisrow,inviscol; 542 int *r,*c, ierr, i, n = a->m, *vi, *ai = a->i, *aj = a->j; 543 int nz,shift = a->indexshift, *rout, *cout; 544 Scalar *x,*b,*tmp, *aa = a->a, *v; 545 546 PetscFunctionBegin; 547 if (zz != xx) VecCopy(zz,xx); 548 549 VecGetArray_Fast(bb,b); 550 VecGetArray_Fast(xx,x); 551 tmp = a->solve_work; 552 553 /* invert the permutations */ 554 ierr = ISInvertPermutation(isrow,&invisrow); CHKERRQ(ierr); 555 ierr = ISInvertPermutation(iscol,&inviscol); CHKERRQ(ierr); 556 ierr = ISGetIndices(invisrow,&rout); CHKERRQ(ierr); r = rout; 557 ierr = ISGetIndices(inviscol,&cout); CHKERRQ(ierr); c = cout; 558 559 /* copy the b into temp work space according to permutation */ 560 for ( i=0; i<n; i++ ) tmp[c[i]] = b[i]; 561 562 /* forward solve the U^T */ 563 for ( i=0; i<n; i++ ) { 564 v = aa + a->diag[i] + shift; 565 vi = aj + a->diag[i] + (!shift); 566 nz = ai[i+1] - a->diag[i] - 1; 567 tmp[i] *= *v++; 568 while (nz--) { 569 tmp[*vi++ + shift] -= (*v++)*tmp[i]; 570 } 571 } 572 573 /* backward solve the L^T */ 574 for ( i=n-1; i>=0; i-- ){ 575 v = aa + a->diag[i] - 1 + shift; 576 vi = aj + a->diag[i] - 1 + shift; 577 nz = a->diag[i] - ai[i]; 578 while (nz--) { 579 tmp[*vi-- + shift] -= (*v--)*tmp[i]; 580 } 581 } 582 583 /* copy tmp into x according to permutation */ 584 for ( i=0; i<n; i++ ) x[r[i]] += tmp[i]; 585 586 ierr = ISRestoreIndices(invisrow,&rout); CHKERRQ(ierr); 587 ierr = ISRestoreIndices(inviscol,&cout); CHKERRQ(ierr); 588 ierr = ISDestroy(invisrow); CHKERRQ(ierr); 589 ierr = ISDestroy(inviscol); CHKERRQ(ierr); 590 591 PLogFlops(2*a->nz); 592 PetscFunctionReturn(0); 593 } 594 /* ----------------------------------------------------------------*/ 595 596 #undef __FUNC__ 597 #define __FUNC__ "MatILUFactorSymbolic_SeqAIJ" 598 int MatILUFactorSymbolic_SeqAIJ(Mat A,IS isrow,IS iscol,double f,int levels,Mat *fact) 599 { 600 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data, *b; 601 IS isicol; 602 int *r,*ic, ierr, prow, n = a->m, *ai = a->i, *aj = a->j; 603 int *ainew,*ajnew, jmax,*fill, *xi, nz, *im,*ajfill,*flev; 604 int *dloc, idx, row,m,fm, nzf, nzi,len, realloc = 0; 605 int incrlev,nnz,i,shift = a->indexshift; 606 PetscTruth col_identity, row_identity; 607 608 PetscFunctionBegin; 609 ierr = ISInvertPermutation(iscol,&isicol); CHKERRQ(ierr); 610 611 /* special case that simply copies fill pattern */ 612 ISIdentity(isrow,&row_identity); ISIdentity(iscol,&col_identity); 613 if (levels == 0 && row_identity && col_identity) { 614 ierr = MatConvertSameType_SeqAIJ(A,fact,DO_NOT_COPY_VALUES); CHKERRQ(ierr); 615 (*fact)->factor = FACTOR_LU; 616 b = (Mat_SeqAIJ *) (*fact)->data; 617 if (!b->diag) { 618 ierr = MatMarkDiag_SeqAIJ(*fact); CHKERRQ(ierr); 619 } 620 b->row = isrow; 621 b->col = iscol; 622 b->icol = isicol; 623 b->solve_work = (Scalar *) PetscMalloc((b->m+1)*sizeof(Scalar));CHKPTRQ(b->solve_work); 624 (*fact)->ops->solve = MatSolve_SeqAIJ_NaturalOrdering; 625 PetscFunctionReturn(0); 626 } 627 628 ierr = ISGetIndices(isrow,&r); CHKERRQ(ierr); 629 ierr = ISGetIndices(isicol,&ic); CHKERRQ(ierr); 630 631 /* get new row pointers */ 632 ainew = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(ainew); 633 ainew[0] = -shift; 634 /* don't know how many column pointers are needed so estimate */ 635 jmax = (int) (f*(ai[n]+!shift)); 636 ajnew = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajnew); 637 /* ajfill is level of fill for each fill entry */ 638 ajfill = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajfill); 639 /* fill is a linked list of nonzeros in active row */ 640 fill = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(fill); 641 /* im is level for each filled value */ 642 im = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(im); 643 /* dloc is location of diagonal in factor */ 644 dloc = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(dloc); 645 dloc[0] = 0; 646 for ( prow=0; prow<n; prow++ ) { 647 /* first copy previous fill into linked list */ 648 nzf = nz = ai[r[prow]+1] - ai[r[prow]]; 649 if (!nz) SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,1,"Empty row in matrix"); 650 xi = aj + ai[r[prow]] + shift; 651 fill[n] = n; 652 while (nz--) { 653 fm = n; 654 idx = ic[*xi++ + shift]; 655 do { 656 m = fm; 657 fm = fill[m]; 658 } while (fm < idx); 659 fill[m] = idx; 660 fill[idx] = fm; 661 im[idx] = 0; 662 } 663 nzi = 0; 664 row = fill[n]; 665 while ( row < prow ) { 666 incrlev = im[row] + 1; 667 nz = dloc[row]; 668 xi = ajnew + ainew[row] + shift + nz; 669 flev = ajfill + ainew[row] + shift + nz + 1; 670 nnz = ainew[row+1] - ainew[row] - nz - 1; 671 if (*xi++ + shift != row) { 672 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,0,"Zero pivot: try running with -pc_ilu_nonzeros_along_diagonal"); 673 } 674 fm = row; 675 while (nnz-- > 0) { 676 idx = *xi++ + shift; 677 if (*flev + incrlev > levels) { 678 flev++; 679 continue; 680 } 681 do { 682 m = fm; 683 fm = fill[m]; 684 } while (fm < idx); 685 if (fm != idx) { 686 im[idx] = *flev + incrlev; 687 fill[m] = idx; 688 fill[idx] = fm; 689 fm = idx; 690 nzf++; 691 } else { 692 if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev; 693 } 694 flev++; 695 } 696 row = fill[row]; 697 nzi++; 698 } 699 /* copy new filled row into permanent storage */ 700 ainew[prow+1] = ainew[prow] + nzf; 701 if (ainew[prow+1] > jmax-shift) { 702 703 /* estimate how much additional space we will need */ 704 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 705 /* just double the memory each time */ 706 /* maxadd = (int) ((f*(ai[n]+!shift)*(n-prow+5))/n); */ 707 int maxadd = jmax; 708 if (maxadd < nzf) maxadd = (n-prow)*(nzf+1); 709 jmax += maxadd; 710 711 /* allocate a longer ajnew and ajfill */ 712 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 713 PetscMemcpy(xi,ajnew,(ainew[prow]+shift)*sizeof(int)); 714 PetscFree(ajnew); 715 ajnew = xi; 716 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 717 PetscMemcpy(xi,ajfill,(ainew[prow]+shift)*sizeof(int)); 718 PetscFree(ajfill); 719 ajfill = xi; 720 realloc++; /* count how many times we realloc */ 721 } 722 xi = ajnew + ainew[prow] + shift; 723 flev = ajfill + ainew[prow] + shift; 724 dloc[prow] = nzi; 725 fm = fill[n]; 726 while (nzf--) { 727 *xi++ = fm - shift; 728 *flev++ = im[fm]; 729 fm = fill[fm]; 730 } 731 } 732 PetscFree(ajfill); 733 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 734 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 735 PetscFree(fill); PetscFree(im); 736 737 { 738 double af = ((double)ainew[n])/((double)ai[n]); 739 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Reallocs %d Fill ratio:given %g needed %g\n", 740 realloc,f,af); 741 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Run with -pc_ilu_fill %g or use \n",af); 742 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:PCILUSetFill(pc,%g);\n",af); 743 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:for best performance.\n"); 744 } 745 746 /* put together the new matrix */ 747 ierr = MatCreateSeqAIJ(A->comm,n,n,0,PETSC_NULL,fact); CHKERRQ(ierr); 748 b = (Mat_SeqAIJ *) (*fact)->data; 749 PetscFree(b->imax); 750 b->singlemalloc = 0; 751 len = (ainew[n] + shift)*sizeof(Scalar); 752 /* the next line frees the default space generated by the Create() */ 753 PetscFree(b->a); PetscFree(b->ilen); 754 b->a = (Scalar *) PetscMalloc( len+1 ); CHKPTRQ(b->a); 755 b->j = ajnew; 756 b->i = ainew; 757 for ( i=0; i<n; i++ ) dloc[i] += ainew[i]; 758 b->diag = dloc; 759 b->ilen = 0; 760 b->imax = 0; 761 b->row = isrow; 762 b->col = iscol; 763 b->icol = isicol; 764 b->solve_work = (Scalar *) PetscMalloc( (n+1)*sizeof(Scalar)); CHKPTRQ(b->solve_work); 765 /* In b structure: Free imax, ilen, old a, old j. 766 Allocate dloc, solve_work, new a, new j */ 767 PLogObjectMemory(*fact,(ainew[n]+shift-n) * (sizeof(int)+sizeof(Scalar))); 768 b->maxnz = b->nz = ainew[n] + shift; 769 (*fact)->factor = FACTOR_LU; 770 771 (*fact)->info.factor_mallocs = realloc; 772 (*fact)->info.fill_ratio_given = f; 773 (*fact)->info.fill_ratio_needed = ((double)ainew[n])/((double)ai[prow]); 774 775 PetscFunctionReturn(0); 776 } 777 778 779 780 781