1 /*$Id: sbaijfact.c,v 1.61 2001/08/06 21:15:47 bsmith Exp $*/ 2 /* Using Modified Sparse Row (MSR) storage. 3 See page 85, "Iterative Methods ..." by Saad. */ 4 5 /* 6 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 7 */ 8 #include "src/mat/impls/baij/seq/baij.h" 9 #include "src/mat/impls/sbaij/seq/sbaij.h" 10 #include "src/vec/vecimpl.h" 11 #include "src/inline/ilu.h" 12 #include "include/petscis.h" 13 14 /* Use Modified Sparse Row storage for u and ju, see Sasd pp.85 */ 15 #undef __FUNCT__ 16 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 17 int MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,PetscReal f,Mat *B) 18 { 19 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 20 int *rip,ierr,i,mbs = a->mbs,*ai,*aj; 21 int *jutmp,bs = a->bs,bs2=a->bs2; 22 int m,realloc = 0,prow; 23 int *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 24 PetscTruth perm_identity; 25 26 PetscFunctionBegin; 27 28 /* check whether perm is the identity mapping */ 29 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 30 if (!perm_identity) a->permute = PETSC_TRUE; 31 32 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 33 34 if (perm_identity){ /* without permutation */ 35 ai = a->i; aj = a->j; 36 } else { /* non-trivial permutation */ 37 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 38 ai = a->inew; aj = a->jnew; 39 } 40 41 /* initialization */ 42 ierr = PetscMalloc((mbs+1)*sizeof(int),&iu);CHKERRQ(ierr); 43 umax = (int)(f*ai[mbs] + 1); umax += mbs + 1; 44 ierr = PetscMalloc(umax*sizeof(int),&ju);CHKERRQ(ierr); 45 iu[0] = mbs+1; 46 juidx = mbs + 1; /* index for ju */ 47 ierr = PetscMalloc(2*mbs*sizeof(int),&jl);CHKERRQ(ierr); /* linked list for pivot row */ 48 q = jl + mbs; /* linked list for col index */ 49 for (i=0; i<mbs; i++){ 50 jl[i] = mbs; 51 q[i] = 0; 52 } 53 54 /* for each row k */ 55 for (k=0; k<mbs; k++){ 56 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 57 q[k] = mbs; 58 /* initialize nonzero structure of k-th row to row rip[k] of A */ 59 jmin = ai[rip[k]]; 60 jmax = ai[rip[k]+1]; 61 for (j=jmin; j<jmax; j++){ 62 vj = rip[aj[j]]; /* col. value */ 63 if(vj > k){ 64 qm = k; 65 do { 66 m = qm; qm = q[m]; 67 } while(qm < vj); 68 if (qm == vj) { 69 SETERRQ(1," error: duplicate entry in A\n"); 70 } 71 nzk++; 72 q[m] = vj; 73 q[vj] = qm; 74 } /* if(vj > k) */ 75 } /* for (j=jmin; j<jmax; j++) */ 76 77 /* modify nonzero structure of k-th row by computing fill-in 78 for each row i to be merged in */ 79 prow = k; 80 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 81 82 while (prow < k){ 83 /* merge row prow into k-th row */ 84 jmin = iu[prow] + 1; jmax = iu[prow+1]; 85 qm = k; 86 for (j=jmin; j<jmax; j++){ 87 vj = ju[j]; 88 do { 89 m = qm; qm = q[m]; 90 } while (qm < vj); 91 if (qm != vj){ 92 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 93 } 94 } 95 prow = jl[prow]; /* next pivot row */ 96 } 97 98 /* add k to row list for first nonzero element in k-th row */ 99 if (nzk > 0){ 100 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 101 jl[k] = jl[i]; jl[i] = k; 102 } 103 iu[k+1] = iu[k] + nzk; 104 105 /* allocate more space to ju if needed */ 106 if (iu[k+1] > umax) { 107 /* estimate how much additional space we will need */ 108 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 109 /* just double the memory each time */ 110 maxadd = umax; 111 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 112 umax += maxadd; 113 114 /* allocate a longer ju */ 115 ierr = PetscMalloc(umax*sizeof(int),&jutmp);CHKERRQ(ierr); 116 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(int));CHKERRQ(ierr); 117 ierr = PetscFree(ju);CHKERRQ(ierr); 118 ju = jutmp; 119 realloc++; /* count how many times we realloc */ 120 } 121 122 /* save nonzero structure of k-th row in ju */ 123 i=k; 124 while (nzk --) { 125 i = q[i]; 126 ju[juidx++] = i; 127 } 128 } 129 130 if (ai[mbs] != 0) { 131 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 132 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Reallocs %d Fill ratio:given %g needed %g\n",realloc,f,af); 133 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Run with -pc_cholesky_fill %g or use \n",af); 134 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:PCCholeskySetFill(pc,%g);\n",af); 135 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:for best performance.\n"); 136 } else { 137 PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Empty matrix.\n"); 138 } 139 140 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 141 /* ierr = PetscFree(q);CHKERRQ(ierr); */ 142 ierr = PetscFree(jl);CHKERRQ(ierr); 143 144 /* put together the new matrix */ 145 ierr = MatCreateSeqSBAIJ(A->comm,bs,bs*mbs,bs*mbs,0,PETSC_NULL,B);CHKERRQ(ierr); 146 /* PetscLogObjectParent(*B,iperm); */ 147 b = (Mat_SeqSBAIJ*)(*B)->data; 148 ierr = PetscFree(b->imax);CHKERRQ(ierr); 149 b->singlemalloc = PETSC_FALSE; 150 /* the next line frees the default space generated by the Create() */ 151 ierr = PetscFree(b->a);CHKERRQ(ierr); 152 ierr = PetscFree(b->ilen);CHKERRQ(ierr); 153 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 154 b->j = ju; 155 b->i = iu; 156 b->diag = 0; 157 b->ilen = 0; 158 b->imax = 0; 159 b->row = perm; 160 b->pivotinblocks = PETSC_FALSE; /* need to get from MatCholeskyInfo */ 161 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 162 b->icol = perm; 163 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 164 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 165 /* In b structure: Free imax, ilen, old a, old j. 166 Allocate idnew, solve_work, new a, new j */ 167 PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(int)+sizeof(MatScalar))); 168 b->s_maxnz = b->s_nz = iu[mbs]; 169 170 (*B)->factor = FACTOR_CHOLESKY; 171 (*B)->info.factor_mallocs = realloc; 172 (*B)->info.fill_ratio_given = f; 173 if (ai[mbs] != 0) { 174 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 175 } else { 176 (*B)->info.fill_ratio_needed = 0.0; 177 } 178 179 if (perm_identity){ 180 switch (bs) { 181 case 1: 182 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 183 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 184 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=1\n"); 185 break; 186 case 2: 187 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 188 (*B)->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 189 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=2\n"); 190 break; 191 case 3: 192 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 193 (*B)->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 194 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:sing special in-place natural ordering factor and solve BS=3\n"); 195 break; 196 case 4: 197 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 198 (*B)->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 199 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=4\n"); 200 break; 201 case 5: 202 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 203 (*B)->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 204 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=5\n"); 205 break; 206 case 6: 207 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 208 (*B)->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 209 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=6\n"); 210 break; 211 case 7: 212 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 213 (*B)->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 214 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=7\n"); 215 break; 216 default: 217 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 218 (*B)->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 219 PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS>7\n"); 220 break; 221 } 222 } 223 224 PetscFunctionReturn(0); 225 } 226 227 228 #undef __FUNCT__ 229 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 230 int MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,Mat *B) 231 { 232 Mat C = *B; 233 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 234 IS perm = b->row; 235 int *perm_ptr,ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 236 int *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 237 int bs=a->bs,bs2 = a->bs2; 238 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 239 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 240 MatScalar *work; 241 int *pivots; 242 243 PetscFunctionBegin; 244 245 /* initialization */ 246 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 247 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 248 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 249 jl = il + mbs; 250 for (i=0; i<mbs; i++) { 251 jl[i] = mbs; il[0] = 0; 252 } 253 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 254 uik = dk + bs2; 255 work = uik + bs2; 256 ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr); 257 258 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 259 260 /* check permutation */ 261 if (!a->permute){ 262 ai = a->i; aj = a->j; aa = a->a; 263 } else { 264 ai = a->inew; aj = a->jnew; 265 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 266 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 267 ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr); 268 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 269 270 for (i=0; i<mbs; i++){ 271 jmin = ai[i]; jmax = ai[i+1]; 272 for (j=jmin; j<jmax; j++){ 273 while (a2anew[j] != j){ 274 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 275 for (k1=0; k1<bs2; k1++){ 276 dk[k1] = aa[k*bs2+k1]; 277 aa[k*bs2+k1] = aa[j*bs2+k1]; 278 aa[j*bs2+k1] = dk[k1]; 279 } 280 } 281 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 282 if (i > aj[j]){ 283 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 284 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 285 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 286 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 287 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 288 } 289 } 290 } 291 } 292 ierr = PetscFree(a2anew);CHKERRQ(ierr); 293 } 294 295 /* for each row k */ 296 for (k = 0; k<mbs; k++){ 297 298 /*initialize k-th row with elements nonzero in row perm(k) of A */ 299 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 300 301 ap = aa + jmin*bs2; 302 for (j = jmin; j < jmax; j++){ 303 vj = perm_ptr[aj[j]]; /* block col. index */ 304 rtmp_ptr = rtmp + vj*bs2; 305 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 306 } 307 308 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 309 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 310 i = jl[k]; /* first row to be added to k_th row */ 311 312 while (i < k){ 313 nexti = jl[i]; /* next row to be added to k_th row */ 314 315 /* compute multiplier */ 316 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 317 318 /* uik = -inv(Di)*U_bar(i,k) */ 319 diag = ba + i*bs2; 320 u = ba + ili*bs2; 321 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 322 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 323 324 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 325 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 326 327 /* update -U(i,k) */ 328 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 329 330 /* add multiple of row i to k-th row ... */ 331 jmin = ili + 1; jmax = bi[i+1]; 332 if (jmin < jmax){ 333 for (j=jmin; j<jmax; j++) { 334 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 335 rtmp_ptr = rtmp + bj[j]*bs2; 336 u = ba + j*bs2; 337 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 338 } 339 340 /* ... add i to row list for next nonzero entry */ 341 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 342 j = bj[jmin]; 343 jl[i] = jl[j]; jl[j] = i; /* update jl */ 344 } 345 i = nexti; 346 } 347 348 /* save nonzero entries in k-th row of U ... */ 349 350 /* invert diagonal block */ 351 diag = ba+k*bs2; 352 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 353 Kernel_A_gets_inverse_A(bs,diag,pivots,work); 354 355 jmin = bi[k]; jmax = bi[k+1]; 356 if (jmin < jmax) { 357 for (j=jmin; j<jmax; j++){ 358 vj = bj[j]; /* block col. index of U */ 359 u = ba + j*bs2; 360 rtmp_ptr = rtmp + vj*bs2; 361 for (k1=0; k1<bs2; k1++){ 362 *u++ = *rtmp_ptr; 363 *rtmp_ptr++ = 0.0; 364 } 365 } 366 367 /* ... add k to row list for first nonzero entry in k-th row */ 368 il[k] = jmin; 369 i = bj[jmin]; 370 jl[k] = jl[i]; jl[i] = k; 371 } 372 } 373 374 ierr = PetscFree(rtmp);CHKERRQ(ierr); 375 ierr = PetscFree(il);CHKERRQ(ierr); 376 ierr = PetscFree(dk);CHKERRQ(ierr); 377 ierr = PetscFree(pivots);CHKERRQ(ierr); 378 if (a->permute){ 379 ierr = PetscFree(aa);CHKERRQ(ierr); 380 } 381 382 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 383 C->factor = FACTOR_CHOLESKY; 384 C->assembled = PETSC_TRUE; 385 C->preallocated = PETSC_TRUE; 386 PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */ 387 PetscFunctionReturn(0); 388 } 389 390 #undef __FUNCT__ 391 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 392 int MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,Mat *B) 393 { 394 Mat C = *B; 395 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 396 int ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 397 int *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 398 int bs=a->bs,bs2 = a->bs2; 399 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 400 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 401 MatScalar *work; 402 int *pivots; 403 404 PetscFunctionBegin; 405 406 /* initialization */ 407 408 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 409 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 410 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 411 jl = il + mbs; 412 for (i=0; i<mbs; i++) { 413 jl[i] = mbs; il[0] = 0; 414 } 415 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 416 uik = dk + bs2; 417 work = uik + bs2; 418 ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr); 419 420 ai = a->i; aj = a->j; aa = a->a; 421 422 /* for each row k */ 423 for (k = 0; k<mbs; k++){ 424 425 /*initialize k-th row with elements nonzero in row k of A */ 426 jmin = ai[k]; jmax = ai[k+1]; 427 ap = aa + jmin*bs2; 428 for (j = jmin; j < jmax; j++){ 429 vj = aj[j]; /* block col. index */ 430 rtmp_ptr = rtmp + vj*bs2; 431 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 432 } 433 434 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 435 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 436 i = jl[k]; /* first row to be added to k_th row */ 437 438 while (i < k){ 439 nexti = jl[i]; /* next row to be added to k_th row */ 440 441 /* compute multiplier */ 442 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 443 444 /* uik = -inv(Di)*U_bar(i,k) */ 445 diag = ba + i*bs2; 446 u = ba + ili*bs2; 447 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 448 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 449 450 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 451 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 452 453 /* update -U(i,k) */ 454 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 455 456 /* add multiple of row i to k-th row ... */ 457 jmin = ili + 1; jmax = bi[i+1]; 458 if (jmin < jmax){ 459 for (j=jmin; j<jmax; j++) { 460 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 461 rtmp_ptr = rtmp + bj[j]*bs2; 462 u = ba + j*bs2; 463 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 464 } 465 466 /* ... add i to row list for next nonzero entry */ 467 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 468 j = bj[jmin]; 469 jl[i] = jl[j]; jl[j] = i; /* update jl */ 470 } 471 i = nexti; 472 } 473 474 /* save nonzero entries in k-th row of U ... */ 475 476 /* invert diagonal block */ 477 diag = ba+k*bs2; 478 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 479 Kernel_A_gets_inverse_A(bs,diag,pivots,work); 480 481 jmin = bi[k]; jmax = bi[k+1]; 482 if (jmin < jmax) { 483 for (j=jmin; j<jmax; j++){ 484 vj = bj[j]; /* block col. index of U */ 485 u = ba + j*bs2; 486 rtmp_ptr = rtmp + vj*bs2; 487 for (k1=0; k1<bs2; k1++){ 488 *u++ = *rtmp_ptr; 489 *rtmp_ptr++ = 0.0; 490 } 491 } 492 493 /* ... add k to row list for first nonzero entry in k-th row */ 494 il[k] = jmin; 495 i = bj[jmin]; 496 jl[k] = jl[i]; jl[i] = k; 497 } 498 } 499 500 ierr = PetscFree(rtmp);CHKERRQ(ierr); 501 ierr = PetscFree(il);CHKERRQ(ierr); 502 ierr = PetscFree(dk);CHKERRQ(ierr); 503 ierr = PetscFree(pivots);CHKERRQ(ierr); 504 505 C->factor = FACTOR_CHOLESKY; 506 C->assembled = PETSC_TRUE; 507 C->preallocated = PETSC_TRUE; 508 PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */ 509 PetscFunctionReturn(0); 510 } 511 512 /* 513 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 514 Version for blocks 2 by 2. 515 */ 516 #undef __FUNCT__ 517 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 518 int MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,Mat *B) 519 { 520 Mat C = *B; 521 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 522 IS perm = b->row; 523 int *perm_ptr,ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 524 int *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 525 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 526 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 527 528 PetscFunctionBegin; 529 530 /* initialization */ 531 /* il and jl record the first nonzero element in each row of the accessing 532 window U(0:k, k:mbs-1). 533 jl: list of rows to be added to uneliminated rows 534 i>= k: jl(i) is the first row to be added to row i 535 i< k: jl(i) is the row following row i in some list of rows 536 jl(i) = mbs indicates the end of a list 537 il(i): points to the first nonzero element in columns k,...,mbs-1 of 538 row i of U */ 539 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 540 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 541 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 542 jl = il + mbs; 543 for (i=0; i<mbs; i++) { 544 jl[i] = mbs; il[0] = 0; 545 } 546 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 547 uik = dk + 4; 548 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 549 550 /* check permutation */ 551 if (!a->permute){ 552 ai = a->i; aj = a->j; aa = a->a; 553 } else { 554 ai = a->inew; aj = a->jnew; 555 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 556 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 557 ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr); 558 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 559 560 for (i=0; i<mbs; i++){ 561 jmin = ai[i]; jmax = ai[i+1]; 562 for (j=jmin; j<jmax; j++){ 563 while (a2anew[j] != j){ 564 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 565 for (k1=0; k1<4; k1++){ 566 dk[k1] = aa[k*4+k1]; 567 aa[k*4+k1] = aa[j*4+k1]; 568 aa[j*4+k1] = dk[k1]; 569 } 570 } 571 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 572 if (i > aj[j]){ 573 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 574 ap = aa + j*4; /* ptr to the beginning of the block */ 575 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 576 ap[1] = ap[2]; 577 ap[2] = dk[1]; 578 } 579 } 580 } 581 ierr = PetscFree(a2anew);CHKERRQ(ierr); 582 } 583 584 /* for each row k */ 585 for (k = 0; k<mbs; k++){ 586 587 /*initialize k-th row with elements nonzero in row perm(k) of A */ 588 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 589 ap = aa + jmin*4; 590 for (j = jmin; j < jmax; j++){ 591 vj = perm_ptr[aj[j]]; /* block col. index */ 592 rtmp_ptr = rtmp + vj*4; 593 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 594 } 595 596 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 597 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 598 i = jl[k]; /* first row to be added to k_th row */ 599 600 while (i < k){ 601 nexti = jl[i]; /* next row to be added to k_th row */ 602 603 /* compute multiplier */ 604 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 605 606 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 607 diag = ba + i*4; 608 u = ba + ili*4; 609 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 610 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 611 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 612 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 613 614 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 615 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 616 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 617 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 618 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 619 620 /* update -U(i,k): ba[ili] = uik */ 621 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 622 623 /* add multiple of row i to k-th row ... */ 624 jmin = ili + 1; jmax = bi[i+1]; 625 if (jmin < jmax){ 626 for (j=jmin; j<jmax; j++) { 627 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 628 rtmp_ptr = rtmp + bj[j]*4; 629 u = ba + j*4; 630 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 631 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 632 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 633 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 634 } 635 636 /* ... add i to row list for next nonzero entry */ 637 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 638 j = bj[jmin]; 639 jl[i] = jl[j]; jl[j] = i; /* update jl */ 640 } 641 i = nexti; 642 } 643 644 /* save nonzero entries in k-th row of U ... */ 645 646 /* invert diagonal block */ 647 diag = ba+k*4; 648 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 649 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 650 651 jmin = bi[k]; jmax = bi[k+1]; 652 if (jmin < jmax) { 653 for (j=jmin; j<jmax; j++){ 654 vj = bj[j]; /* block col. index of U */ 655 u = ba + j*4; 656 rtmp_ptr = rtmp + vj*4; 657 for (k1=0; k1<4; k1++){ 658 *u++ = *rtmp_ptr; 659 *rtmp_ptr++ = 0.0; 660 } 661 } 662 663 /* ... add k to row list for first nonzero entry in k-th row */ 664 il[k] = jmin; 665 i = bj[jmin]; 666 jl[k] = jl[i]; jl[i] = k; 667 } 668 } 669 670 ierr = PetscFree(rtmp);CHKERRQ(ierr); 671 ierr = PetscFree(il);CHKERRQ(ierr); 672 ierr = PetscFree(dk);CHKERRQ(ierr); 673 if (a->permute) { 674 ierr = PetscFree(aa);CHKERRQ(ierr); 675 } 676 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 677 C->factor = FACTOR_CHOLESKY; 678 C->assembled = PETSC_TRUE; 679 C->preallocated = PETSC_TRUE; 680 PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */ 681 PetscFunctionReturn(0); 682 } 683 684 /* 685 Version for when blocks are 2 by 2 Using natural ordering 686 */ 687 #undef __FUNCT__ 688 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 689 int MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,Mat *B) 690 { 691 Mat C = *B; 692 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 693 int ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 694 int *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 695 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 696 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 697 698 PetscFunctionBegin; 699 700 /* initialization */ 701 /* il and jl record the first nonzero element in each row of the accessing 702 window U(0:k, k:mbs-1). 703 jl: list of rows to be added to uneliminated rows 704 i>= k: jl(i) is the first row to be added to row i 705 i< k: jl(i) is the row following row i in some list of rows 706 jl(i) = mbs indicates the end of a list 707 il(i): points to the first nonzero element in columns k,...,mbs-1 of 708 row i of U */ 709 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 710 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 711 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 712 jl = il + mbs; 713 for (i=0; i<mbs; i++) { 714 jl[i] = mbs; il[0] = 0; 715 } 716 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 717 uik = dk + 4; 718 719 ai = a->i; aj = a->j; aa = a->a; 720 721 /* for each row k */ 722 for (k = 0; k<mbs; k++){ 723 724 /*initialize k-th row with elements nonzero in row k of A */ 725 jmin = ai[k]; jmax = ai[k+1]; 726 ap = aa + jmin*4; 727 for (j = jmin; j < jmax; j++){ 728 vj = aj[j]; /* block col. index */ 729 rtmp_ptr = rtmp + vj*4; 730 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 731 } 732 733 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 734 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 735 i = jl[k]; /* first row to be added to k_th row */ 736 737 while (i < k){ 738 nexti = jl[i]; /* next row to be added to k_th row */ 739 740 /* compute multiplier */ 741 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 742 743 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 744 diag = ba + i*4; 745 u = ba + ili*4; 746 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 747 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 748 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 749 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 750 751 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 752 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 753 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 754 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 755 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 756 757 /* update -U(i,k): ba[ili] = uik */ 758 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 759 760 /* add multiple of row i to k-th row ... */ 761 jmin = ili + 1; jmax = bi[i+1]; 762 if (jmin < jmax){ 763 for (j=jmin; j<jmax; j++) { 764 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 765 rtmp_ptr = rtmp + bj[j]*4; 766 u = ba + j*4; 767 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 768 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 769 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 770 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 771 } 772 773 /* ... add i to row list for next nonzero entry */ 774 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 775 j = bj[jmin]; 776 jl[i] = jl[j]; jl[j] = i; /* update jl */ 777 } 778 i = nexti; 779 } 780 781 /* save nonzero entries in k-th row of U ... */ 782 783 /* invert diagonal block */ 784 diag = ba+k*4; 785 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 786 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 787 788 jmin = bi[k]; jmax = bi[k+1]; 789 if (jmin < jmax) { 790 for (j=jmin; j<jmax; j++){ 791 vj = bj[j]; /* block col. index of U */ 792 u = ba + j*4; 793 rtmp_ptr = rtmp + vj*4; 794 for (k1=0; k1<4; k1++){ 795 *u++ = *rtmp_ptr; 796 *rtmp_ptr++ = 0.0; 797 } 798 } 799 800 /* ... add k to row list for first nonzero entry in k-th row */ 801 il[k] = jmin; 802 i = bj[jmin]; 803 jl[k] = jl[i]; jl[i] = k; 804 } 805 } 806 807 ierr = PetscFree(rtmp);CHKERRQ(ierr); 808 ierr = PetscFree(il);CHKERRQ(ierr); 809 ierr = PetscFree(dk);CHKERRQ(ierr); 810 811 C->factor = FACTOR_CHOLESKY; 812 C->assembled = PETSC_TRUE; 813 C->preallocated = PETSC_TRUE; 814 PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */ 815 PetscFunctionReturn(0); 816 } 817 818 /* 819 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 820 Version for blocks are 1 by 1. 821 */ 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 824 int MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,Mat *B) 825 { 826 Mat C = *B; 827 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 828 IS ip = b->row; 829 int *rip,ierr,i,j,mbs = a->mbs,*bi = b->i,*bj = b->j; 830 int *ai,*aj,*r; 831 int k,jmin,jmax,*jl,*il,vj,nexti,ili; 832 MatScalar *rtmp; 833 MatScalar *ba = b->a,*aa,ak; 834 MatScalar dk,uikdi; 835 836 PetscFunctionBegin; 837 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 838 if (!a->permute){ 839 ai = a->i; aj = a->j; aa = a->a; 840 } else { 841 ai = a->inew; aj = a->jnew; 842 ierr = PetscMalloc(ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 843 ierr = PetscMemcpy(aa,a->a,ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 844 ierr = PetscMalloc(ai[mbs]*sizeof(int),&r);CHKERRQ(ierr); 845 ierr= PetscMemcpy(r,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr); 846 847 jmin = ai[0]; jmax = ai[mbs]; 848 for (j=jmin; j<jmax; j++){ 849 while (r[j] != j){ 850 k = r[j]; r[j] = r[k]; r[k] = k; 851 ak = aa[k]; aa[k] = aa[j]; aa[j] = ak; 852 } 853 } 854 ierr = PetscFree(r);CHKERRQ(ierr); 855 } 856 857 /* initialization */ 858 /* il and jl record the first nonzero element in each row of the accessing 859 window U(0:k, k:mbs-1). 860 jl: list of rows to be added to uneliminated rows 861 i>= k: jl(i) is the first row to be added to row i 862 i< k: jl(i) is the row following row i in some list of rows 863 jl(i) = mbs indicates the end of a list 864 il(i): points to the first nonzero element in columns k,...,mbs-1 of 865 row i of U */ 866 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 867 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 868 jl = il + mbs; 869 for (i=0; i<mbs; i++) { 870 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 871 } 872 873 /* for each row k */ 874 for (k = 0; k<mbs; k++){ 875 876 /*initialize k-th row with elements nonzero in row perm(k) of A */ 877 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 878 879 for (j = jmin; j < jmax; j++){ 880 vj = rip[aj[j]]; 881 rtmp[vj] = aa[j]; 882 } 883 884 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 885 dk = rtmp[k]; 886 i = jl[k]; /* first row to be added to k_th row */ 887 888 while (i < k){ 889 nexti = jl[i]; /* next row to be added to k_th row */ 890 891 /* compute multiplier, update D(k) and U(i,k) */ 892 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 893 uikdi = - ba[ili]*ba[i]; 894 dk += uikdi*ba[ili]; 895 ba[ili] = uikdi; /* -U(i,k) */ 896 897 /* add multiple of row i to k-th row ... */ 898 jmin = ili + 1; jmax = bi[i+1]; 899 if (jmin < jmax){ 900 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 901 /* ... add i to row list for next nonzero entry */ 902 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 903 j = bj[jmin]; 904 jl[i] = jl[j]; jl[j] = i; /* update jl */ 905 } 906 i = nexti; 907 } 908 909 /* check for zero pivot and save diagoanl element */ 910 if (dk == 0.0){ 911 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot"); 912 /* 913 } else if (PetscRealPart(dk) < 0.0){ 914 SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Negative pivot: d[%d] = %g\n",k,dk); 915 */ 916 } 917 918 /* save nonzero entries in k-th row of U ... */ 919 ba[k] = 1.0/dk; 920 jmin = bi[k]; jmax = bi[k+1]; 921 if (jmin < jmax) { 922 for (j=jmin; j<jmax; j++){ 923 vj = bj[j]; ba[j] = rtmp[vj]; rtmp[vj] = 0.0; 924 } 925 /* ... add k to row list for first nonzero entry in k-th row */ 926 il[k] = jmin; 927 i = bj[jmin]; 928 jl[k] = jl[i]; jl[i] = k; 929 } 930 } 931 932 ierr = PetscFree(rtmp);CHKERRQ(ierr); 933 ierr = PetscFree(il);CHKERRQ(ierr); 934 if (a->permute){ 935 ierr = PetscFree(aa);CHKERRQ(ierr); 936 } 937 938 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 939 C->factor = FACTOR_CHOLESKY; 940 C->assembled = PETSC_TRUE; 941 C->preallocated = PETSC_TRUE; 942 PetscLogFlops(b->mbs); 943 PetscFunctionReturn(0); 944 } 945 946 /* 947 Version for when blocks are 1 by 1 Using natural ordering 948 */ 949 #undef __FUNCT__ 950 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 951 int MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,Mat *B) 952 { 953 Mat C = *B; 954 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 955 int ierr,i,j,mbs = a->mbs,*bi = b->i,*bj = b->j; 956 int *ai,*aj; 957 int k,jmin,jmax,*jl,*il,vj,nexti,ili; 958 MatScalar *rtmp,*ba = b->a,*aa,dk,uikdi; 959 960 PetscFunctionBegin; 961 962 /* initialization */ 963 /* il and jl record the first nonzero element in each row of the accessing 964 window U(0:k, k:mbs-1). 965 jl: list of rows to be added to uneliminated rows 966 i>= k: jl(i) is the first row to be added to row i 967 i< k: jl(i) is the row following row i in some list of rows 968 jl(i) = mbs indicates the end of a list 969 il(i): points to the first nonzero element in columns k,...,mbs-1 of 970 row i of U */ 971 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 972 ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr); 973 jl = il + mbs; 974 for (i=0; i<mbs; i++) { 975 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 976 } 977 978 ai = a->i; aj = a->j; aa = a->a; 979 980 /* for each row k */ 981 for (k = 0; k<mbs; k++){ 982 983 /*initialize k-th row with elements nonzero in row perm(k) of A */ 984 jmin = ai[k]; jmax = ai[k+1]; 985 986 for (j = jmin; j < jmax; j++){ 987 vj = aj[j]; 988 rtmp[vj] = aa[j]; 989 } 990 991 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 992 dk = rtmp[k]; 993 i = jl[k]; /* first row to be added to k_th row */ 994 995 while (i < k){ 996 nexti = jl[i]; /* next row to be added to k_th row */ 997 998 /* compute multiplier, update D(k) and U(i,k) */ 999 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1000 uikdi = - ba[ili]*ba[i]; 1001 dk += uikdi*ba[ili]; 1002 ba[ili] = uikdi; /* -U(i,k) */ 1003 1004 /* add multiple of row i to k-th row ... */ 1005 jmin = ili + 1; jmax = bi[i+1]; 1006 if (jmin < jmax){ 1007 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1008 /* ... add i to row list for next nonzero entry */ 1009 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1010 j = bj[jmin]; 1011 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1012 } 1013 i = nexti; 1014 } 1015 1016 /* check for zero pivot and save diagoanl element */ 1017 if (dk == 0.0){ 1018 SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot"); 1019 /* 1020 } else if (PetscRealPart(dk) < 0){ 1021 SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Negative pivot: d[%d] = %g\n",k,dk); 1022 */ 1023 } 1024 1025 /* save nonzero entries in k-th row of U ... */ 1026 ba[k] = 1.0/dk; 1027 jmin = bi[k]; jmax = bi[k+1]; 1028 if (jmin < jmax) { 1029 for (j=jmin; j<jmax; j++){ 1030 vj = bj[j]; ba[j] = rtmp[vj]; rtmp[vj] = 0.0; 1031 } 1032 /* ... add k to row list for first nonzero entry in k-th row */ 1033 il[k] = jmin; 1034 i = bj[jmin]; 1035 jl[k] = jl[i]; jl[i] = k; 1036 } 1037 } 1038 1039 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1040 ierr = PetscFree(il);CHKERRQ(ierr); 1041 1042 C->factor = FACTOR_CHOLESKY; 1043 C->assembled = PETSC_TRUE; 1044 C->preallocated = PETSC_TRUE; 1045 PetscLogFlops(b->mbs); 1046 PetscFunctionReturn(0); 1047 } 1048 1049 #undef __FUNCT__ 1050 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1051 int MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,PetscReal f) 1052 { 1053 int ierr; 1054 Mat C; 1055 1056 PetscFunctionBegin; 1057 ierr = MatCholeskyFactorSymbolic(A,perm,f,&C);CHKERRQ(ierr); 1058 ierr = MatCholeskyFactorNumeric(A,&C);CHKERRQ(ierr); 1059 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1060 PetscFunctionReturn(0); 1061 } 1062 1063 1064