1 2 #include "src/mat/impls/baij/seq/baij.h" 3 #include "src/mat/impls/sbaij/seq/sbaij.h" 4 #include "src/inline/ilu.h" 5 #include "include/petscis.h" 6 7 #if !defined(PETSC_USE_COMPLEX) 8 /* 9 input: 10 F -- numeric factor 11 output: 12 nneg, nzero, npos: matrix inertia 13 */ 14 15 #undef __FUNCT__ 16 #define __FUNCT__ "MatGetInertia_SeqSBAIJ" 17 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,int *nneig,int *nzero,int *npos) 18 { 19 Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data; 20 PetscScalar *dd = fact_ptr->a; 21 int mbs=fact_ptr->mbs,bs=fact_ptr->bs,i,nneig_tmp,npos_tmp, 22 *fi = fact_ptr->i; 23 24 PetscFunctionBegin; 25 if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"No support for bs: %d >1 yet",bs); 26 nneig_tmp = 0; npos_tmp = 0; 27 for (i=0; i<mbs; i++){ 28 if (PetscRealPart(dd[*fi]) > 0.0){ 29 npos_tmp++; 30 } else if (PetscRealPart(dd[*fi]) < 0.0){ 31 nneig_tmp++; 32 } 33 fi++; 34 } 35 if (nneig) *nneig = nneig_tmp; 36 if (npos) *npos = npos_tmp; 37 if (nzero) *nzero = mbs - nneig_tmp - npos_tmp; 38 39 PetscFunctionReturn(0); 40 } 41 #endif /* !defined(PETSC_USE_COMPLEX) */ 42 43 /* Using Modified Sparse Row (MSR) storage. 44 See page 85, "Iterative Methods ..." by Saad. */ 45 /* 46 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 47 */ 48 /* Use Modified Sparse Row storage for u and ju, see Saad pp.85 */ 49 #undef __FUNCT__ 50 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 51 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *B) 52 { 53 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 54 PetscErrorCode ierr; 55 int *rip,i,mbs = a->mbs,*ai,*aj; 56 int *jutmp,bs = a->bs,bs2=a->bs2; 57 int m,realloc = 0,prow; 58 int *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 59 int *il,ili,nextprow; 60 PetscReal f = info->fill; 61 PetscTruth perm_identity; 62 63 PetscFunctionBegin; 64 /* check whether perm is the identity mapping */ 65 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 66 67 /* -- inplace factorization, i.e., use sbaij for *B -- */ 68 if (perm_identity && bs==1 ){ 69 if (!perm_identity) a->permute = PETSC_TRUE; 70 71 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 72 73 if (perm_identity){ /* without permutation */ 74 ai = a->i; aj = a->j; 75 } else { /* non-trivial permutation */ 76 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 77 ai = a->inew; aj = a->jnew; 78 } 79 80 /* initialization */ 81 ierr = PetscMalloc((mbs+1)*sizeof(int),&iu);CHKERRQ(ierr); 82 umax = (int)(f*ai[mbs] + 1); 83 ierr = PetscMalloc(umax*sizeof(int),&ju);CHKERRQ(ierr); 84 iu[0] = 0; 85 juidx = 0; /* index for ju */ 86 ierr = PetscMalloc((3*mbs+1)*sizeof(int),&jl);CHKERRQ(ierr); /* linked list for getting pivot row */ 87 q = jl + mbs; /* linked list for col index of active row */ 88 il = q + mbs; 89 for (i=0; i<mbs; i++){ 90 jl[i] = mbs; 91 q[i] = 0; 92 il[i] = 0; 93 } 94 95 /* for each row k */ 96 for (k=0; k<mbs; k++){ 97 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 98 q[k] = mbs; 99 /* initialize nonzero structure of k-th row to row rip[k] of A */ 100 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 101 jmax = ai[rip[k]+1]; 102 for (j=jmin; j<jmax; j++){ 103 vj = rip[aj[j]]; /* col. value */ 104 if(vj > k){ 105 qm = k; 106 do { 107 m = qm; qm = q[m]; 108 } while(qm < vj); 109 if (qm == vj) { 110 SETERRQ(PETSC_ERR_PLIB,"Duplicate entry in A\n"); 111 } 112 nzk++; 113 q[m] = vj; 114 q[vj] = qm; 115 } /* if(vj > k) */ 116 } /* for (j=jmin; j<jmax; j++) */ 117 118 /* modify nonzero structure of k-th row by computing fill-in 119 for each row i to be merged in */ 120 prow = k; 121 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 122 123 while (prow < k){ 124 nextprow = jl[prow]; 125 126 /* merge row prow into k-th row */ 127 ili = il[prow]; 128 jmin = ili + 1; /* points to 2nd nzero entry in U(prow,k:mbs-1) */ 129 jmax = iu[prow+1]; 130 qm = k; 131 for (j=jmin; j<jmax; j++){ 132 vj = ju[j]; 133 do { 134 m = qm; qm = q[m]; 135 } while (qm < vj); 136 if (qm != vj){ /* a fill */ 137 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 138 } 139 } /* end of for (j=jmin; j<jmax; j++) */ 140 if (jmin < jmax){ 141 il[prow] = jmin; 142 j = ju[jmin]; 143 jl[prow] = jl[j]; jl[j] = prow; /* update jl */ 144 } 145 prow = nextprow; 146 } 147 148 /* update il and jl */ 149 if (nzk > 0){ 150 i = q[k]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 151 jl[k] = jl[i]; jl[i] = k; 152 il[k] = iu[k] + 1; 153 } 154 iu[k+1] = iu[k] + nzk + 1; /* include diag[k] */ 155 156 /* allocate more space to ju if needed */ 157 if (iu[k+1] > umax) { 158 /* estimate how much additional space we will need */ 159 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 160 /* just double the memory each time */ 161 maxadd = umax; 162 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 163 umax += maxadd; 164 165 /* allocate a longer ju */ 166 ierr = PetscMalloc(umax*sizeof(int),&jutmp);CHKERRQ(ierr); 167 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(int));CHKERRQ(ierr); 168 ierr = PetscFree(ju);CHKERRQ(ierr); 169 ju = jutmp; 170 realloc++; /* count how many times we realloc */ 171 } 172 173 /* save nonzero structure of k-th row in ju */ 174 ju[juidx++] = k; /* diag[k] */ 175 i = k; 176 while (nzk --) { 177 i = q[i]; 178 ju[juidx++] = i; 179 } 180 } 181 182 if (ai[mbs] != 0) { 183 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 184 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Reallocs %d Fill ratio:given %g needed %g\n",realloc,f,af); 185 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Run with -pc_cholesky_fill %g or use \n",af); 186 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:PCCholeskySetFill(pc,%g);\n",af); 187 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:for best performance.\n"); 188 } else { 189 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Empty matrix.\n"); 190 } 191 192 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 193 /* ierr = PetscFree(q);CHKERRQ(ierr); */ 194 ierr = PetscFree(jl);CHKERRQ(ierr); 195 196 /* put together the new matrix */ 197 ierr = MatCreate(A->comm,bs*mbs,bs*mbs,bs*mbs,bs*mbs,B);CHKERRQ(ierr); 198 ierr = MatSetType(*B,A->type_name);CHKERRQ(ierr); 199 ierr = MatSeqSBAIJSetPreallocation(*B,bs,0,PETSC_NULL);CHKERRQ(ierr); 200 201 /* PetscLogObjectParent(*B,iperm); */ 202 b = (Mat_SeqSBAIJ*)(*B)->data; 203 ierr = PetscFree(b->imax);CHKERRQ(ierr); 204 b->singlemalloc = PETSC_FALSE; 205 /* the next line frees the default space generated by the Create() */ 206 ierr = PetscFree(b->a);CHKERRQ(ierr); 207 ierr = PetscFree(b->ilen);CHKERRQ(ierr); 208 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 209 b->j = ju; 210 b->i = iu; 211 b->diag = 0; 212 b->ilen = 0; 213 b->imax = 0; 214 b->row = perm; 215 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 216 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 217 b->icol = perm; 218 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 219 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 220 /* In b structure: Free imax, ilen, old a, old j. 221 Allocate idnew, solve_work, new a, new j */ 222 PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(int)+sizeof(MatScalar))); 223 b->maxnz = b->nz = iu[mbs]; 224 225 (*B)->factor = FACTOR_CHOLESKY; 226 (*B)->info.factor_mallocs = realloc; 227 (*B)->info.fill_ratio_given = f; 228 if (ai[mbs] != 0) { 229 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 230 } else { 231 (*B)->info.fill_ratio_needed = 0.0; 232 } 233 234 235 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 236 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 237 (*B)->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 238 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=1\n"); 239 240 PetscFunctionReturn(0); 241 } 242 /* ----------- end of new code --------------------*/ 243 244 245 if (!perm_identity) a->permute = PETSC_TRUE; 246 247 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 248 249 if (perm_identity){ /* without permutation */ 250 ai = a->i; aj = a->j; 251 } else { /* non-trivial permutation */ 252 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 253 ai = a->inew; aj = a->jnew; 254 } 255 256 /* initialization */ 257 ierr = PetscMalloc((mbs+1)*sizeof(int),&iu);CHKERRQ(ierr); 258 umax = (int)(f*ai[mbs] + 1); umax += mbs + 1; 259 ierr = PetscMalloc(umax*sizeof(int),&ju);CHKERRQ(ierr); 260 iu[0] = mbs+1; 261 juidx = mbs + 1; /* index for ju */ 262 ierr = PetscMalloc(2*mbs*sizeof(int),&jl);CHKERRQ(ierr); /* linked list for pivot row */ 263 q = jl + mbs; /* linked list for col index */ 264 for (i=0; i<mbs; i++){ 265 jl[i] = mbs; 266 q[i] = 0; 267 } 268 269 /* for each row k */ 270 for (k=0; k<mbs; k++){ 271 for (i=0; i<mbs; i++) q[i] = 0; /* to be removed! */ 272 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 273 q[k] = mbs; 274 /* initialize nonzero structure of k-th row to row rip[k] of A */ 275 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 276 jmax = ai[rip[k]+1]; 277 for (j=jmin; j<jmax; j++){ 278 vj = rip[aj[j]]; /* col. value */ 279 if(vj > k){ 280 qm = k; 281 do { 282 m = qm; qm = q[m]; 283 } while(qm < vj); 284 if (qm == vj) { 285 SETERRQ(PETSC_ERR_PLIB,"Duplicate entry in A\n"); 286 } 287 nzk++; 288 q[m] = vj; 289 q[vj] = qm; 290 } /* if(vj > k) */ 291 } /* for (j=jmin; j<jmax; j++) */ 292 293 /* modify nonzero structure of k-th row by computing fill-in 294 for each row i to be merged in */ 295 prow = k; 296 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 297 298 while (prow < k){ 299 /* merge row prow into k-th row */ 300 jmin = iu[prow] + 1; jmax = iu[prow+1]; 301 qm = k; 302 for (j=jmin; j<jmax; j++){ 303 vj = ju[j]; 304 do { 305 m = qm; qm = q[m]; 306 } while (qm < vj); 307 if (qm != vj){ 308 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 309 } 310 } 311 prow = jl[prow]; /* next pivot row */ 312 } 313 314 /* add k to row list for first nonzero element in k-th row */ 315 if (nzk > 0){ 316 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 317 jl[k] = jl[i]; jl[i] = k; 318 } 319 iu[k+1] = iu[k] + nzk; 320 321 /* allocate more space to ju if needed */ 322 if (iu[k+1] > umax) { 323 /* estimate how much additional space we will need */ 324 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 325 /* just double the memory each time */ 326 maxadd = umax; 327 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 328 umax += maxadd; 329 330 /* allocate a longer ju */ 331 ierr = PetscMalloc(umax*sizeof(int),&jutmp);CHKERRQ(ierr); 332 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(int));CHKERRQ(ierr); 333 ierr = PetscFree(ju);CHKERRQ(ierr); 334 ju = jutmp; 335 realloc++; /* count how many times we realloc */ 336 } 337 338 /* save nonzero structure of k-th row in ju */ 339 i=k; 340 while (nzk --) { 341 i = q[i]; 342 ju[juidx++] = i; 343 } 344 } 345 346 if (ai[mbs] != 0) { 347 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 348 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Reallocs %d Fill ratio:given %g needed %g\n",realloc,f,af); 349 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Run with -pc_cholesky_fill %g or use \n",af); 350 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:PCCholeskySetFill(pc,%g);\n",af); 351 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:for best performance.\n"); 352 } else { 353 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Empty matrix.\n"); 354 } 355 356 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 357 /* ierr = PetscFree(q);CHKERRQ(ierr); */ 358 ierr = PetscFree(jl);CHKERRQ(ierr); 359 360 /* put together the new matrix */ 361 ierr = MatCreate(A->comm,bs*mbs,bs*mbs,bs*mbs,bs*mbs,B);CHKERRQ(ierr); 362 ierr = MatSetType(*B,A->type_name);CHKERRQ(ierr); 363 ierr = MatSeqSBAIJSetPreallocation(*B,bs,0,PETSC_NULL);CHKERRQ(ierr); 364 365 /* PetscLogObjectParent(*B,iperm); */ 366 b = (Mat_SeqSBAIJ*)(*B)->data; 367 ierr = PetscFree(b->imax);CHKERRQ(ierr); 368 b->singlemalloc = PETSC_FALSE; 369 /* the next line frees the default space generated by the Create() */ 370 ierr = PetscFree(b->a);CHKERRQ(ierr); 371 ierr = PetscFree(b->ilen);CHKERRQ(ierr); 372 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 373 b->j = ju; 374 b->i = iu; 375 b->diag = 0; 376 b->ilen = 0; 377 b->imax = 0; 378 b->row = perm; 379 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 380 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 381 b->icol = perm; 382 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 383 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 384 /* In b structure: Free imax, ilen, old a, old j. 385 Allocate idnew, solve_work, new a, new j */ 386 PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(int)+sizeof(MatScalar))); 387 b->maxnz = b->nz = iu[mbs]; 388 389 (*B)->factor = FACTOR_CHOLESKY; 390 (*B)->info.factor_mallocs = realloc; 391 (*B)->info.fill_ratio_given = f; 392 if (ai[mbs] != 0) { 393 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 394 } else { 395 (*B)->info.fill_ratio_needed = 0.0; 396 } 397 398 if (perm_identity){ 399 switch (bs) { 400 case 1: 401 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 402 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 403 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=1\n"); 404 break; 405 case 2: 406 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 407 (*B)->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 408 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=2\n"); 409 break; 410 case 3: 411 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 412 (*B)->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 413 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:sing special in-place natural ordering factor and solve BS=3\n"); 414 break; 415 case 4: 416 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 417 (*B)->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 418 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=4\n"); 419 break; 420 case 5: 421 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 422 (*B)->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 423 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=5\n"); 424 break; 425 case 6: 426 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 427 (*B)->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 428 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=6\n"); 429 break; 430 case 7: 431 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 432 (*B)->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 433 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=7\n"); 434 break; 435 default: 436 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 437 (*B)->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 438 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS>7\n"); 439 break; 440 } 441 } 442 443 PetscFunctionReturn(0); 444 } 445 446 447 #undef __FUNCT__ 448 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 449 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,Mat *B) 450 { 451 Mat C = *B; 452 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 453 IS perm = b->row; 454 PetscErrorCode ierr; 455 int *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 456 int *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 457 int bs=a->bs,bs2 = a->bs2; 458 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 459 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 460 MatScalar *work; 461 int *pivots; 462 463 PetscFunctionBegin; 464 465 /* initialization */ 466 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 467 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 468 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 469 jl = il + mbs; 470 for (i=0; i<mbs; i++) { 471 jl[i] = mbs; il[0] = 0; 472 } 473 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 474 uik = dk + bs2; 475 work = uik + bs2; 476 ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr); 477 478 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 479 480 /* check permutation */ 481 if (!a->permute){ 482 ai = a->i; aj = a->j; aa = a->a; 483 } else { 484 ai = a->inew; aj = a->jnew; 485 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 486 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 487 ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr); 488 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 489 490 for (i=0; i<mbs; i++){ 491 jmin = ai[i]; jmax = ai[i+1]; 492 for (j=jmin; j<jmax; j++){ 493 while (a2anew[j] != j){ 494 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 495 for (k1=0; k1<bs2; k1++){ 496 dk[k1] = aa[k*bs2+k1]; 497 aa[k*bs2+k1] = aa[j*bs2+k1]; 498 aa[j*bs2+k1] = dk[k1]; 499 } 500 } 501 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 502 if (i > aj[j]){ 503 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 504 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 505 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 506 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 507 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 508 } 509 } 510 } 511 } 512 ierr = PetscFree(a2anew);CHKERRQ(ierr); 513 } 514 515 /* for each row k */ 516 for (k = 0; k<mbs; k++){ 517 518 /*initialize k-th row with elements nonzero in row perm(k) of A */ 519 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 520 521 ap = aa + jmin*bs2; 522 for (j = jmin; j < jmax; j++){ 523 vj = perm_ptr[aj[j]]; /* block col. index */ 524 rtmp_ptr = rtmp + vj*bs2; 525 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 526 } 527 528 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 529 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 530 i = jl[k]; /* first row to be added to k_th row */ 531 532 while (i < k){ 533 nexti = jl[i]; /* next row to be added to k_th row */ 534 535 /* compute multiplier */ 536 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 537 538 /* uik = -inv(Di)*U_bar(i,k) */ 539 diag = ba + i*bs2; 540 u = ba + ili*bs2; 541 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 542 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 543 544 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 545 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 546 547 /* update -U(i,k) */ 548 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 549 550 /* add multiple of row i to k-th row ... */ 551 jmin = ili + 1; jmax = bi[i+1]; 552 if (jmin < jmax){ 553 for (j=jmin; j<jmax; j++) { 554 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 555 rtmp_ptr = rtmp + bj[j]*bs2; 556 u = ba + j*bs2; 557 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 558 } 559 560 /* ... add i to row list for next nonzero entry */ 561 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 562 j = bj[jmin]; 563 jl[i] = jl[j]; jl[j] = i; /* update jl */ 564 } 565 i = nexti; 566 } 567 568 /* save nonzero entries in k-th row of U ... */ 569 570 /* invert diagonal block */ 571 diag = ba+k*bs2; 572 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 573 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 574 575 jmin = bi[k]; jmax = bi[k+1]; 576 if (jmin < jmax) { 577 for (j=jmin; j<jmax; j++){ 578 vj = bj[j]; /* block col. index of U */ 579 u = ba + j*bs2; 580 rtmp_ptr = rtmp + vj*bs2; 581 for (k1=0; k1<bs2; k1++){ 582 *u++ = *rtmp_ptr; 583 *rtmp_ptr++ = 0.0; 584 } 585 } 586 587 /* ... add k to row list for first nonzero entry in k-th row */ 588 il[k] = jmin; 589 i = bj[jmin]; 590 jl[k] = jl[i]; jl[i] = k; 591 } 592 } 593 594 ierr = PetscFree(rtmp);CHKERRQ(ierr); 595 ierr = PetscFree(il);CHKERRQ(ierr); 596 ierr = PetscFree(dk);CHKERRQ(ierr); 597 ierr = PetscFree(pivots);CHKERRQ(ierr); 598 if (a->permute){ 599 ierr = PetscFree(aa);CHKERRQ(ierr); 600 } 601 602 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 603 C->factor = FACTOR_CHOLESKY; 604 C->assembled = PETSC_TRUE; 605 C->preallocated = PETSC_TRUE; 606 PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */ 607 PetscFunctionReturn(0); 608 } 609 610 #undef __FUNCT__ 611 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 612 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,Mat *B) 613 { 614 Mat C = *B; 615 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 616 PetscErrorCode ierr; 617 int i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 618 int *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 619 int bs=a->bs,bs2 = a->bs2; 620 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 621 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 622 MatScalar *work; 623 int *pivots; 624 625 PetscFunctionBegin; 626 627 /* initialization */ 628 629 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 630 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 631 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 632 jl = il + mbs; 633 for (i=0; i<mbs; i++) { 634 jl[i] = mbs; il[0] = 0; 635 } 636 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 637 uik = dk + bs2; 638 work = uik + bs2; 639 ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr); 640 641 ai = a->i; aj = a->j; aa = a->a; 642 643 /* for each row k */ 644 for (k = 0; k<mbs; k++){ 645 646 /*initialize k-th row with elements nonzero in row k of A */ 647 jmin = ai[k]; jmax = ai[k+1]; 648 ap = aa + jmin*bs2; 649 for (j = jmin; j < jmax; j++){ 650 vj = aj[j]; /* block col. index */ 651 rtmp_ptr = rtmp + vj*bs2; 652 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 653 } 654 655 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 656 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 657 i = jl[k]; /* first row to be added to k_th row */ 658 659 while (i < k){ 660 nexti = jl[i]; /* next row to be added to k_th row */ 661 662 /* compute multiplier */ 663 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 664 665 /* uik = -inv(Di)*U_bar(i,k) */ 666 diag = ba + i*bs2; 667 u = ba + ili*bs2; 668 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 669 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 670 671 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 672 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 673 674 /* update -U(i,k) */ 675 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 676 677 /* add multiple of row i to k-th row ... */ 678 jmin = ili + 1; jmax = bi[i+1]; 679 if (jmin < jmax){ 680 for (j=jmin; j<jmax; j++) { 681 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 682 rtmp_ptr = rtmp + bj[j]*bs2; 683 u = ba + j*bs2; 684 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 685 } 686 687 /* ... add i to row list for next nonzero entry */ 688 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 689 j = bj[jmin]; 690 jl[i] = jl[j]; jl[j] = i; /* update jl */ 691 } 692 i = nexti; 693 } 694 695 /* save nonzero entries in k-th row of U ... */ 696 697 /* invert diagonal block */ 698 diag = ba+k*bs2; 699 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 700 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 701 702 jmin = bi[k]; jmax = bi[k+1]; 703 if (jmin < jmax) { 704 for (j=jmin; j<jmax; j++){ 705 vj = bj[j]; /* block col. index of U */ 706 u = ba + j*bs2; 707 rtmp_ptr = rtmp + vj*bs2; 708 for (k1=0; k1<bs2; k1++){ 709 *u++ = *rtmp_ptr; 710 *rtmp_ptr++ = 0.0; 711 } 712 } 713 714 /* ... add k to row list for first nonzero entry in k-th row */ 715 il[k] = jmin; 716 i = bj[jmin]; 717 jl[k] = jl[i]; jl[i] = k; 718 } 719 } 720 721 ierr = PetscFree(rtmp);CHKERRQ(ierr); 722 ierr = PetscFree(il);CHKERRQ(ierr); 723 ierr = PetscFree(dk);CHKERRQ(ierr); 724 ierr = PetscFree(pivots);CHKERRQ(ierr); 725 726 C->factor = FACTOR_CHOLESKY; 727 C->assembled = PETSC_TRUE; 728 C->preallocated = PETSC_TRUE; 729 PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */ 730 PetscFunctionReturn(0); 731 } 732 733 /* 734 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 735 Version for blocks 2 by 2. 736 */ 737 #undef __FUNCT__ 738 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 739 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,Mat *B) 740 { 741 Mat C = *B; 742 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 743 IS perm = b->row; 744 PetscErrorCode ierr; 745 int *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 746 int *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 747 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 748 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 749 750 PetscFunctionBegin; 751 752 /* initialization */ 753 /* il and jl record the first nonzero element in each row of the accessing 754 window U(0:k, k:mbs-1). 755 jl: list of rows to be added to uneliminated rows 756 i>= k: jl(i) is the first row to be added to row i 757 i< k: jl(i) is the row following row i in some list of rows 758 jl(i) = mbs indicates the end of a list 759 il(i): points to the first nonzero element in columns k,...,mbs-1 of 760 row i of U */ 761 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 762 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 763 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 764 jl = il + mbs; 765 for (i=0; i<mbs; i++) { 766 jl[i] = mbs; il[0] = 0; 767 } 768 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 769 uik = dk + 4; 770 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 771 772 /* check permutation */ 773 if (!a->permute){ 774 ai = a->i; aj = a->j; aa = a->a; 775 } else { 776 ai = a->inew; aj = a->jnew; 777 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 778 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 779 ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr); 780 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 781 782 for (i=0; i<mbs; i++){ 783 jmin = ai[i]; jmax = ai[i+1]; 784 for (j=jmin; j<jmax; j++){ 785 while (a2anew[j] != j){ 786 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 787 for (k1=0; k1<4; k1++){ 788 dk[k1] = aa[k*4+k1]; 789 aa[k*4+k1] = aa[j*4+k1]; 790 aa[j*4+k1] = dk[k1]; 791 } 792 } 793 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 794 if (i > aj[j]){ 795 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 796 ap = aa + j*4; /* ptr to the beginning of the block */ 797 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 798 ap[1] = ap[2]; 799 ap[2] = dk[1]; 800 } 801 } 802 } 803 ierr = PetscFree(a2anew);CHKERRQ(ierr); 804 } 805 806 /* for each row k */ 807 for (k = 0; k<mbs; k++){ 808 809 /*initialize k-th row with elements nonzero in row perm(k) of A */ 810 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 811 ap = aa + jmin*4; 812 for (j = jmin; j < jmax; j++){ 813 vj = perm_ptr[aj[j]]; /* block col. index */ 814 rtmp_ptr = rtmp + vj*4; 815 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 816 } 817 818 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 819 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 820 i = jl[k]; /* first row to be added to k_th row */ 821 822 while (i < k){ 823 nexti = jl[i]; /* next row to be added to k_th row */ 824 825 /* compute multiplier */ 826 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 827 828 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 829 diag = ba + i*4; 830 u = ba + ili*4; 831 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 832 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 833 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 834 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 835 836 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 837 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 838 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 839 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 840 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 841 842 /* update -U(i,k): ba[ili] = uik */ 843 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 844 845 /* add multiple of row i to k-th row ... */ 846 jmin = ili + 1; jmax = bi[i+1]; 847 if (jmin < jmax){ 848 for (j=jmin; j<jmax; j++) { 849 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 850 rtmp_ptr = rtmp + bj[j]*4; 851 u = ba + j*4; 852 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 853 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 854 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 855 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 856 } 857 858 /* ... add i to row list for next nonzero entry */ 859 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 860 j = bj[jmin]; 861 jl[i] = jl[j]; jl[j] = i; /* update jl */ 862 } 863 i = nexti; 864 } 865 866 /* save nonzero entries in k-th row of U ... */ 867 868 /* invert diagonal block */ 869 diag = ba+k*4; 870 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 871 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 872 873 jmin = bi[k]; jmax = bi[k+1]; 874 if (jmin < jmax) { 875 for (j=jmin; j<jmax; j++){ 876 vj = bj[j]; /* block col. index of U */ 877 u = ba + j*4; 878 rtmp_ptr = rtmp + vj*4; 879 for (k1=0; k1<4; k1++){ 880 *u++ = *rtmp_ptr; 881 *rtmp_ptr++ = 0.0; 882 } 883 } 884 885 /* ... add k to row list for first nonzero entry in k-th row */ 886 il[k] = jmin; 887 i = bj[jmin]; 888 jl[k] = jl[i]; jl[i] = k; 889 } 890 } 891 892 ierr = PetscFree(rtmp);CHKERRQ(ierr); 893 ierr = PetscFree(il);CHKERRQ(ierr); 894 ierr = PetscFree(dk);CHKERRQ(ierr); 895 if (a->permute) { 896 ierr = PetscFree(aa);CHKERRQ(ierr); 897 } 898 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 899 C->factor = FACTOR_CHOLESKY; 900 C->assembled = PETSC_TRUE; 901 C->preallocated = PETSC_TRUE; 902 PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */ 903 PetscFunctionReturn(0); 904 } 905 906 /* 907 Version for when blocks are 2 by 2 Using natural ordering 908 */ 909 #undef __FUNCT__ 910 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 911 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,Mat *B) 912 { 913 Mat C = *B; 914 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 915 PetscErrorCode ierr; 916 int i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 917 int *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 918 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 919 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 920 921 PetscFunctionBegin; 922 923 /* initialization */ 924 /* il and jl record the first nonzero element in each row of the accessing 925 window U(0:k, k:mbs-1). 926 jl: list of rows to be added to uneliminated rows 927 i>= k: jl(i) is the first row to be added to row i 928 i< k: jl(i) is the row following row i in some list of rows 929 jl(i) = mbs indicates the end of a list 930 il(i): points to the first nonzero element in columns k,...,mbs-1 of 931 row i of U */ 932 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 933 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 934 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 935 jl = il + mbs; 936 for (i=0; i<mbs; i++) { 937 jl[i] = mbs; il[0] = 0; 938 } 939 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 940 uik = dk + 4; 941 942 ai = a->i; aj = a->j; aa = a->a; 943 944 /* for each row k */ 945 for (k = 0; k<mbs; k++){ 946 947 /*initialize k-th row with elements nonzero in row k of A */ 948 jmin = ai[k]; jmax = ai[k+1]; 949 ap = aa + jmin*4; 950 for (j = jmin; j < jmax; j++){ 951 vj = aj[j]; /* block col. index */ 952 rtmp_ptr = rtmp + vj*4; 953 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 954 } 955 956 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 957 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 958 i = jl[k]; /* first row to be added to k_th row */ 959 960 while (i < k){ 961 nexti = jl[i]; /* next row to be added to k_th row */ 962 963 /* compute multiplier */ 964 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 965 966 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 967 diag = ba + i*4; 968 u = ba + ili*4; 969 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 970 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 971 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 972 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 973 974 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 975 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 976 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 977 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 978 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 979 980 /* update -U(i,k): ba[ili] = uik */ 981 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 982 983 /* add multiple of row i to k-th row ... */ 984 jmin = ili + 1; jmax = bi[i+1]; 985 if (jmin < jmax){ 986 for (j=jmin; j<jmax; j++) { 987 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 988 rtmp_ptr = rtmp + bj[j]*4; 989 u = ba + j*4; 990 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 991 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 992 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 993 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 994 } 995 996 /* ... add i to row list for next nonzero entry */ 997 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 998 j = bj[jmin]; 999 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1000 } 1001 i = nexti; 1002 } 1003 1004 /* save nonzero entries in k-th row of U ... */ 1005 1006 /* invert diagonal block */ 1007 diag = ba+k*4; 1008 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1009 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1010 1011 jmin = bi[k]; jmax = bi[k+1]; 1012 if (jmin < jmax) { 1013 for (j=jmin; j<jmax; j++){ 1014 vj = bj[j]; /* block col. index of U */ 1015 u = ba + j*4; 1016 rtmp_ptr = rtmp + vj*4; 1017 for (k1=0; k1<4; k1++){ 1018 *u++ = *rtmp_ptr; 1019 *rtmp_ptr++ = 0.0; 1020 } 1021 } 1022 1023 /* ... add k to row list for first nonzero entry in k-th row */ 1024 il[k] = jmin; 1025 i = bj[jmin]; 1026 jl[k] = jl[i]; jl[i] = k; 1027 } 1028 } 1029 1030 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1031 ierr = PetscFree(il);CHKERRQ(ierr); 1032 ierr = PetscFree(dk);CHKERRQ(ierr); 1033 1034 C->factor = FACTOR_CHOLESKY; 1035 C->assembled = PETSC_TRUE; 1036 C->preallocated = PETSC_TRUE; 1037 PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */ 1038 PetscFunctionReturn(0); 1039 } 1040 1041 /* 1042 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 1043 Version for blocks are 1 by 1. 1044 */ 1045 #undef __FUNCT__ 1046 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1047 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,Mat *B) 1048 { 1049 Mat C = *B; 1050 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 1051 IS ip = b->row; 1052 PetscErrorCode ierr; 1053 int *rip,i,j,mbs = a->mbs,*bi = b->i,*bj = b->j; 1054 int *ai,*aj,*r; 1055 int k,jmin,jmax,*jl,*il,vj,nexti,ili; 1056 MatScalar *rtmp; 1057 MatScalar *ba = b->a,*aa,ak; 1058 MatScalar dk,uikdi; 1059 1060 PetscFunctionBegin; 1061 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1062 if (!a->permute){ 1063 ai = a->i; aj = a->j; aa = a->a; 1064 } else { 1065 ai = a->inew; aj = a->jnew; 1066 ierr = PetscMalloc(ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1067 ierr = PetscMemcpy(aa,a->a,ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 1068 ierr = PetscMalloc(ai[mbs]*sizeof(int),&r);CHKERRQ(ierr); 1069 ierr= PetscMemcpy(r,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 1070 1071 jmin = ai[0]; jmax = ai[mbs]; 1072 for (j=jmin; j<jmax; j++){ 1073 while (r[j] != j){ 1074 k = r[j]; r[j] = r[k]; r[k] = k; 1075 ak = aa[k]; aa[k] = aa[j]; aa[j] = ak; 1076 } 1077 } 1078 ierr = PetscFree(r);CHKERRQ(ierr); 1079 } 1080 1081 /* initialization */ 1082 /* il and jl record the first nonzero element in each row of the accessing 1083 window U(0:k, k:mbs-1). 1084 jl: list of rows to be added to uneliminated rows 1085 i>= k: jl(i) is the first row to be added to row i 1086 i< k: jl(i) is the row following row i in some list of rows 1087 jl(i) = mbs indicates the end of a list 1088 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1089 row i of U */ 1090 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1091 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 1092 jl = il + mbs; 1093 for (i=0; i<mbs; i++) { 1094 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1095 } 1096 1097 /* for each row k */ 1098 for (k = 0; k<mbs; k++){ 1099 1100 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1101 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1102 1103 for (j = jmin; j < jmax; j++){ 1104 vj = rip[aj[j]]; 1105 rtmp[vj] = aa[j]; 1106 } 1107 1108 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1109 dk = rtmp[k]; 1110 i = jl[k]; /* first row to be added to k_th row */ 1111 1112 while (i < k){ 1113 nexti = jl[i]; /* next row to be added to k_th row */ 1114 1115 /* compute multiplier, update D(k) and U(i,k) */ 1116 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1117 uikdi = - ba[ili]*ba[i]; 1118 dk += uikdi*ba[ili]; 1119 ba[ili] = uikdi; /* -U(i,k) */ 1120 1121 /* add multiple of row i to k-th row ... */ 1122 jmin = ili + 1; jmax = bi[i+1]; 1123 if (jmin < jmax){ 1124 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1125 /* ... add i to row list for next nonzero entry */ 1126 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1127 j = bj[jmin]; 1128 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1129 } 1130 i = nexti; 1131 } 1132 1133 /* check for zero pivot and save diagoanl element */ 1134 if (dk == 0.0){ 1135 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot"); 1136 /* 1137 } else if (PetscRealPart(dk) < 0.0){ 1138 SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Negative pivot: d[%d] = %g\n",k,dk); 1139 */ 1140 } 1141 1142 /* save nonzero entries in k-th row of U ... */ 1143 ba[k] = 1.0/dk; 1144 jmin = bi[k]; jmax = bi[k+1]; 1145 if (jmin < jmax) { 1146 for (j=jmin; j<jmax; j++){ 1147 vj = bj[j]; ba[j] = rtmp[vj]; rtmp[vj] = 0.0; 1148 } 1149 /* ... add k to row list for first nonzero entry in k-th row */ 1150 il[k] = jmin; 1151 i = bj[jmin]; 1152 jl[k] = jl[i]; jl[i] = k; 1153 } 1154 } 1155 1156 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1157 ierr = PetscFree(il);CHKERRQ(ierr); 1158 if (a->permute){ 1159 ierr = PetscFree(aa);CHKERRQ(ierr); 1160 } 1161 1162 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1163 C->factor = FACTOR_CHOLESKY; 1164 C->assembled = PETSC_TRUE; 1165 C->preallocated = PETSC_TRUE; 1166 PetscLogFlops(b->mbs); 1167 PetscFunctionReturn(0); 1168 } 1169 1170 /* 1171 Version for when blocks are 1 by 1 Using natural ordering 1172 */ 1173 #undef __FUNCT__ 1174 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1175 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,Mat *B) 1176 { 1177 Mat C = *B; 1178 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1179 PetscErrorCode ierr; 1180 int i,j,mbs = a->mbs; 1181 int *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1182 int k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz,ndamp = 0; 1183 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1184 PetscReal damping=b->factor_damping, zeropivot=b->factor_zeropivot,shift_amount; 1185 PetscTruth damp,chshift; 1186 int nshift=0; 1187 1188 PetscFunctionBegin; 1189 /* initialization */ 1190 /* il and jl record the first nonzero element in each row of the accessing 1191 window U(0:k, k:mbs-1). 1192 jl: list of rows to be added to uneliminated rows 1193 i>= k: jl(i) is the first row to be added to row i 1194 i< k: jl(i) is the row following row i in some list of rows 1195 jl(i) = mbs indicates the end of a list 1196 il(i): points to the first nonzero element in U(i,k:mbs-1) 1197 */ 1198 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1199 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 1200 jl = il + mbs; 1201 1202 shift_amount = 0; 1203 do { 1204 damp = PETSC_FALSE; 1205 chshift = PETSC_FALSE; 1206 for (i=0; i<mbs; i++) { 1207 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1208 } 1209 1210 for (k = 0; k<mbs; k++){ /* row k */ 1211 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1212 nz = ai[k+1] - ai[k]; 1213 acol = aj + ai[k]; 1214 aval = aa + ai[k]; 1215 bval = ba + bi[k]; 1216 while (nz -- ){ 1217 rtmp[*acol++] = *aval++; 1218 *bval++ = 0.0; /* for in-place factorization */ 1219 } 1220 /* damp the diagonal of the matrix */ 1221 if (ndamp||nshift) rtmp[k] += damping+shift_amount; 1222 1223 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1224 dk = rtmp[k]; 1225 i = jl[k]; /* first row to be added to k_th row */ 1226 1227 while (i < k){ 1228 nexti = jl[i]; /* next row to be added to k_th row */ 1229 1230 /* compute multiplier, update D(k) and U(i,k) */ 1231 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1232 uikdi = - ba[ili]*ba[bi[i]]; 1233 dk += uikdi*ba[ili]; 1234 ba[ili] = uikdi; /* -U(i,k) */ 1235 1236 /* add multiple of row i to k-th row ... */ 1237 jmin = ili + 1; 1238 nz = bi[i+1] - jmin; 1239 if (nz > 0){ 1240 bcol = bj + jmin; 1241 bval = ba + jmin; 1242 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1243 /* ... add i to row list for next nonzero entry */ 1244 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1245 j = bj[jmin]; 1246 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1247 } 1248 i = nexti; 1249 } 1250 1251 if (PetscRealPart(dk) < zeropivot && b->factor_shift){ 1252 /* calculate a shift that would make this row diagonally dominant */ 1253 PetscReal rs = PetscAbs(PetscRealPart(dk)); 1254 jmin = bi[k]+1; 1255 nz = bi[k+1] - jmin; 1256 if (nz){ 1257 bcol = bj + jmin; 1258 bval = ba + jmin; 1259 while (nz--){ 1260 rs += PetscAbsScalar(rtmp[*bcol++]); 1261 } 1262 } 1263 /* if this shift is less than the previous, just up the previous 1264 one by a bit */ 1265 shift_amount = PetscMax(rs,1.1*shift_amount); 1266 chshift = PETSC_TRUE; 1267 /* Unlike in the ILU case there is no exit condition on nshift: 1268 we increase the shift until it converges. There is no guarantee that 1269 this algorithm converges faster or slower, or is better or worse 1270 than the ILU algorithm. */ 1271 nshift++; 1272 break; 1273 } 1274 if (PetscRealPart(dk) < zeropivot){ 1275 if (damping == (PetscReal) PETSC_DECIDE) damping = -PetscRealPart(dk)/(k+1); 1276 if (damping > 0.0) { 1277 if (ndamp) damping *= 2.0; 1278 damp = PETSC_TRUE; 1279 ndamp++; 1280 break; 1281 } else if (PetscAbsScalar(dk) < zeropivot){ 1282 SETERRQ3(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot row %d value %g tolerance %g",k,PetscRealPart(dk),zeropivot); 1283 } else { 1284 PetscLogInfo((PetscObject)A,"Negative pivot %g in row %d of Cholesky factorization\n",PetscRealPart(dk),k); 1285 } 1286 } 1287 1288 /* save nonzero entries in k-th row of U ... */ 1289 /* printf("%d, dk: %g, 1/dk: %g\n",k,dk,1/dk); */ 1290 ba[bi[k]] = 1.0/dk; 1291 jmin = bi[k]+1; 1292 nz = bi[k+1] - jmin; 1293 if (nz){ 1294 bcol = bj + jmin; 1295 bval = ba + jmin; 1296 while (nz--){ 1297 *bval++ = rtmp[*bcol]; 1298 rtmp[*bcol++] = 0.0; 1299 } 1300 /* ... add k to row list for first nonzero entry in k-th row */ 1301 il[k] = jmin; 1302 i = bj[jmin]; 1303 jl[k] = jl[i]; jl[i] = k; 1304 } 1305 } /* end of for (k = 0; k<mbs; k++) */ 1306 } while (damp||chshift); 1307 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1308 ierr = PetscFree(il);CHKERRQ(ierr); 1309 1310 C->factor = FACTOR_CHOLESKY; 1311 C->assembled = PETSC_TRUE; 1312 C->preallocated = PETSC_TRUE; 1313 PetscLogFlops(b->mbs); 1314 if (ndamp) { 1315 PetscLogInfo(0,"MatCholeskyFactorNumerical_SeqSBAIJ_1_NaturalOrdering: number of damping tries %d damping value %g\n",ndamp,damping); 1316 } 1317 if (nshift) { 1318 PetscLogInfo(0,"MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering diagonal shifted %d shifts\n",nshift); 1319 } 1320 1321 PetscFunctionReturn(0); 1322 } 1323 1324 #undef __FUNCT__ 1325 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1326 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1327 { 1328 PetscErrorCode ierr; 1329 Mat C; 1330 1331 PetscFunctionBegin; 1332 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1333 ierr = MatCholeskyFactorNumeric(A,&C);CHKERRQ(ierr); 1334 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1335 PetscFunctionReturn(0); 1336 } 1337 1338 1339