1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: aijfact.c,v 1.100 1998/04/03 23:14:54 bsmith 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 A->qlist = 0; 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 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 343 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 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 ierr = VecGetArray(bb,&b); CHKERRQ(ierr); 398 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 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 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 444 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 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 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 491 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 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 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 551 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 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); 611 612 /* special case that simply copies fill pattern */ 613 ISIdentity(isrow,&row_identity); ISIdentity(iscol,&col_identity); 614 if (levels == 0 && row_identity && col_identity) { 615 ierr = MatConvertSameType_SeqAIJ(A,fact,DO_NOT_COPY_VALUES); CHKERRQ(ierr); 616 (*fact)->factor = FACTOR_LU; 617 b = (Mat_SeqAIJ *) (*fact)->data; 618 if (!b->diag) { 619 ierr = MatMarkDiag_SeqAIJ(*fact); CHKERRQ(ierr); 620 } 621 b->row = isrow; 622 b->col = iscol; 623 b->icol = isicol; 624 b->solve_work = (Scalar *) PetscMalloc((b->m+1)*sizeof(Scalar));CHKPTRQ(b->solve_work); 625 (*fact)->ops->solve = MatSolve_SeqAIJ_NaturalOrdering; 626 PetscFunctionReturn(0); 627 } 628 629 ierr = ISGetIndices(isrow,&r); CHKERRQ(ierr); 630 ierr = ISGetIndices(isicol,&ic); CHKERRQ(ierr); 631 632 /* get new row pointers */ 633 ainew = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(ainew); 634 ainew[0] = -shift; 635 /* don't know how many column pointers are needed so estimate */ 636 jmax = (int) (f*(ai[n]+!shift)); 637 ajnew = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajnew); 638 /* ajfill is level of fill for each fill entry */ 639 ajfill = (int *) PetscMalloc( (jmax)*sizeof(int) ); CHKPTRQ(ajfill); 640 /* fill is a linked list of nonzeros in active row */ 641 fill = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(fill); 642 /* im is level for each filled value */ 643 im = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(im); 644 /* dloc is location of diagonal in factor */ 645 dloc = (int *) PetscMalloc( (n+1)*sizeof(int)); CHKPTRQ(dloc); 646 dloc[0] = 0; 647 for ( prow=0; prow<n; prow++ ) { 648 /* first copy previous fill into linked list */ 649 nzf = nz = ai[r[prow]+1] - ai[r[prow]]; 650 if (!nz) SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,1,"Empty row in matrix"); 651 xi = aj + ai[r[prow]] + shift; 652 fill[n] = n; 653 while (nz--) { 654 fm = n; 655 idx = ic[*xi++ + shift]; 656 do { 657 m = fm; 658 fm = fill[m]; 659 } while (fm < idx); 660 fill[m] = idx; 661 fill[idx] = fm; 662 im[idx] = 0; 663 } 664 nzi = 0; 665 row = fill[n]; 666 while ( row < prow ) { 667 incrlev = im[row] + 1; 668 nz = dloc[row]; 669 xi = ajnew + ainew[row] + shift + nz; 670 flev = ajfill + ainew[row] + shift + nz + 1; 671 nnz = ainew[row+1] - ainew[row] - nz - 1; 672 if (*xi++ + shift != row) { 673 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,0,"Zero pivot: try running with -pc_ilu_nonzeros_along_diagonal"); 674 } 675 fm = row; 676 while (nnz-- > 0) { 677 idx = *xi++ + shift; 678 if (*flev + incrlev > levels) { 679 flev++; 680 continue; 681 } 682 do { 683 m = fm; 684 fm = fill[m]; 685 } while (fm < idx); 686 if (fm != idx) { 687 im[idx] = *flev + incrlev; 688 fill[m] = idx; 689 fill[idx] = fm; 690 fm = idx; 691 nzf++; 692 } else { 693 if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev; 694 } 695 flev++; 696 } 697 row = fill[row]; 698 nzi++; 699 } 700 /* copy new filled row into permanent storage */ 701 ainew[prow+1] = ainew[prow] + nzf; 702 if (ainew[prow+1] > jmax-shift) { 703 704 /* estimate how much additional space we will need */ 705 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 706 /* just double the memory each time */ 707 /* maxadd = (int) ((f*(ai[n]+!shift)*(n-prow+5))/n); */ 708 int maxadd = jmax; 709 if (maxadd < nzf) maxadd = (n-prow)*(nzf+1); 710 jmax += maxadd; 711 712 /* allocate a longer ajnew and ajfill */ 713 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 714 PetscMemcpy(xi,ajnew,(ainew[prow]+shift)*sizeof(int)); 715 PetscFree(ajnew); 716 ajnew = xi; 717 xi = (int *) PetscMalloc( jmax*sizeof(int) );CHKPTRQ(xi); 718 PetscMemcpy(xi,ajfill,(ainew[prow]+shift)*sizeof(int)); 719 PetscFree(ajfill); 720 ajfill = xi; 721 realloc++; /* count how many times we realloc */ 722 } 723 xi = ajnew + ainew[prow] + shift; 724 flev = ajfill + ainew[prow] + shift; 725 dloc[prow] = nzi; 726 fm = fill[n]; 727 while (nzf--) { 728 *xi++ = fm - shift; 729 *flev++ = im[fm]; 730 fm = fill[fm]; 731 } 732 } 733 PetscFree(ajfill); 734 ierr = ISRestoreIndices(isrow,&r); CHKERRQ(ierr); 735 ierr = ISRestoreIndices(isicol,&ic); CHKERRQ(ierr); 736 PetscFree(fill); PetscFree(im); 737 738 { 739 double af = ((double)ainew[n])/((double)ai[n]); 740 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Reallocs %d Fill ratio:given %g needed %g\n", 741 realloc,f,af); 742 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:Run with -pc_ilu_fill %g or use \n",af); 743 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:PCILUSetFill(pc,%g);\n",af); 744 PLogInfo(A,"MatILUFactorSymbolic_SeqAIJ:for best performance.\n"); 745 } 746 747 /* put together the new matrix */ 748 ierr = MatCreateSeqAIJ(A->comm,n,n,0,PETSC_NULL,fact); CHKERRQ(ierr); 749 PLogObjectParent(*fact,isicol); 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