1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/baij/seq/baij.h" 4 #include "src/mat/impls/sbaij/seq/sbaij.h" 5 #include "src/inline/ilu.h" 6 #include "include/petscis.h" 7 8 #if !defined(PETSC_USE_COMPLEX) 9 /* 10 input: 11 F -- numeric factor 12 output: 13 nneg, nzero, npos: matrix inertia 14 */ 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetInertia_SeqSBAIJ" 18 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos) 19 { 20 Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data; 21 PetscScalar *dd = fact_ptr->a; 22 PetscInt mbs=fact_ptr->mbs,bs=F->rmap.bs,i,nneig_tmp,npos_tmp,*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 /* 44 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 45 Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad. 46 */ 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR" 49 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat A,IS perm,MatFactorInfo *info,Mat *B) 50 { 51 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 52 PetscErrorCode ierr; 53 PetscInt *rip,i,mbs = a->mbs,*ai,*aj; 54 PetscInt *jutmp,bs = A->rmap.bs,bs2=a->bs2; 55 PetscInt m,reallocs = 0,prow; 56 PetscInt *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 57 PetscReal f = info->fill; 58 PetscTruth perm_identity; 59 60 PetscFunctionBegin; 61 /* check whether perm is the identity mapping */ 62 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 63 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 64 65 if (perm_identity){ /* without permutation */ 66 a->permute = PETSC_FALSE; 67 ai = a->i; aj = a->j; 68 } else { /* non-trivial permutation */ 69 a->permute = PETSC_TRUE; 70 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 71 ai = a->inew; aj = a->jnew; 72 } 73 74 /* initialization */ 75 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&iu);CHKERRQ(ierr); 76 umax = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1; 77 ierr = PetscMalloc(umax*sizeof(PetscInt),&ju);CHKERRQ(ierr); 78 iu[0] = mbs+1; 79 juidx = mbs + 1; /* index for ju */ 80 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&jl);CHKERRQ(ierr); /* linked list for pivot row */ 81 q = jl + mbs; /* linked list for col index */ 82 for (i=0; i<mbs; i++){ 83 jl[i] = mbs; 84 q[i] = 0; 85 } 86 87 /* for each row k */ 88 for (k=0; k<mbs; k++){ 89 for (i=0; i<mbs; i++) q[i] = 0; /* to be removed! */ 90 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 91 q[k] = mbs; 92 /* initialize nonzero structure of k-th row to row rip[k] of A */ 93 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 94 jmax = ai[rip[k]+1]; 95 for (j=jmin; j<jmax; j++){ 96 vj = rip[aj[j]]; /* col. value */ 97 if(vj > k){ 98 qm = k; 99 do { 100 m = qm; qm = q[m]; 101 } while(qm < vj); 102 if (qm == vj) { 103 SETERRQ(PETSC_ERR_PLIB,"Duplicate entry in A\n"); 104 } 105 nzk++; 106 q[m] = vj; 107 q[vj] = qm; 108 } /* if(vj > k) */ 109 } /* for (j=jmin; j<jmax; j++) */ 110 111 /* modify nonzero structure of k-th row by computing fill-in 112 for each row i to be merged in */ 113 prow = k; 114 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 115 116 while (prow < k){ 117 /* merge row prow into k-th row */ 118 jmin = iu[prow] + 1; jmax = iu[prow+1]; 119 qm = k; 120 for (j=jmin; j<jmax; j++){ 121 vj = ju[j]; 122 do { 123 m = qm; qm = q[m]; 124 } while (qm < vj); 125 if (qm != vj){ 126 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 127 } 128 } 129 prow = jl[prow]; /* next pivot row */ 130 } 131 132 /* add k to row list for first nonzero element in k-th row */ 133 if (nzk > 0){ 134 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 135 jl[k] = jl[i]; jl[i] = k; 136 } 137 iu[k+1] = iu[k] + nzk; 138 139 /* allocate more space to ju if needed */ 140 if (iu[k+1] > umax) { 141 /* estimate how much additional space we will need */ 142 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 143 /* just double the memory each time */ 144 maxadd = umax; 145 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 146 umax += maxadd; 147 148 /* allocate a longer ju */ 149 ierr = PetscMalloc(umax*sizeof(PetscInt),&jutmp);CHKERRQ(ierr); 150 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr); 151 ierr = PetscFree(ju);CHKERRQ(ierr); 152 ju = jutmp; 153 reallocs++; /* count how many times we realloc */ 154 } 155 156 /* save nonzero structure of k-th row in ju */ 157 i=k; 158 while (nzk --) { 159 i = q[i]; 160 ju[juidx++] = i; 161 } 162 } 163 164 #if defined(PETSC_USE_INFO) 165 if (ai[mbs] != 0) { 166 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 167 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr); 168 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 169 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr); 170 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 171 } else { 172 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 173 } 174 #endif 175 176 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 177 ierr = PetscFree(jl);CHKERRQ(ierr); 178 179 /* put together the new matrix */ 180 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 181 ierr = MatSetSizes(*B,bs*mbs,bs*mbs,bs*mbs,bs*mbs);CHKERRQ(ierr); 182 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 183 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(*B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 184 185 /* ierr = PetscLogObjectParent(*B,iperm);CHKERRQ(ierr); */ 186 b = (Mat_SeqSBAIJ*)(*B)->data; 187 b->singlemalloc = PETSC_FALSE; 188 b->free_a = PETSC_TRUE; 189 b->free_ij = PETSC_TRUE; 190 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 191 b->j = ju; 192 b->i = iu; 193 b->diag = 0; 194 b->ilen = 0; 195 b->imax = 0; 196 b->row = perm; 197 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 198 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 199 b->icol = perm; 200 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 201 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 202 /* In b structure: Free imax, ilen, old a, old j. 203 Allocate idnew, solve_work, new a, new j */ 204 ierr = PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 205 b->maxnz = b->nz = iu[mbs]; 206 207 (*B)->factor = FACTOR_CHOLESKY; 208 (*B)->info.factor_mallocs = reallocs; 209 (*B)->info.fill_ratio_given = f; 210 if (ai[mbs] != 0) { 211 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 212 } else { 213 (*B)->info.fill_ratio_needed = 0.0; 214 } 215 216 if (perm_identity){ 217 switch (bs) { 218 case 1: 219 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 220 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 221 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 222 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 223 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 224 break; 225 case 2: 226 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 227 (*B)->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 228 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering; 229 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering; 230 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 231 break; 232 case 3: 233 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 234 (*B)->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 235 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_3_NaturalOrdering; 236 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering; 237 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 238 break; 239 case 4: 240 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 241 (*B)->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 242 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_4_NaturalOrdering; 243 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering; 244 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 245 break; 246 case 5: 247 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 248 (*B)->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 249 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_5_NaturalOrdering; 250 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering; 251 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 252 break; 253 case 6: 254 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 255 (*B)->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 256 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_6_NaturalOrdering; 257 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering; 258 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 259 break; 260 case 7: 261 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 262 (*B)->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 263 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_7_NaturalOrdering; 264 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering; 265 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 266 break; 267 default: 268 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 269 (*B)->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 270 (*B)->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering; 271 (*B)->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering; 272 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 273 break; 274 } 275 } 276 PetscFunctionReturn(0); 277 } 278 /* 279 Symbolic U^T*D*U factorization for SBAIJ format. 280 */ 281 #include "petscbt.h" 282 #include "src/mat/utils/freespace.h" 283 #undef __FUNCT__ 284 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 285 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *fact) 286 { 287 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 288 Mat_SeqSBAIJ *b; 289 Mat B; 290 PetscErrorCode ierr; 291 PetscTruth perm_identity; 292 PetscReal fill = info->fill; 293 PetscInt *rip,i,mbs=a->mbs,bs=A->rmap.bs,*ai,*aj,reallocs=0,prow; 294 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 295 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr; 296 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 297 PetscBT lnkbt; 298 299 PetscFunctionBegin; 300 /* 301 This code originally uses Modified Sparse Row (MSR) storage 302 (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise! 303 Then it is rewritten so the factor B takes seqsbaij format. However the associated 304 MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity, 305 thus the original code in MSR format is still used for these cases. 306 The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever 307 MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor. 308 */ 309 if (bs > 1){ 310 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(A,perm,info,fact);CHKERRQ(ierr); 311 PetscFunctionReturn(0); 312 } 313 314 /* check whether perm is the identity mapping */ 315 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 316 317 if (perm_identity){ 318 a->permute = PETSC_FALSE; 319 ai = a->i; aj = a->j; 320 } else { 321 SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 322 /* There are bugs for reordeing. Needs further work. 323 MatReordering for sbaij cannot be efficient. User should use aij formt! */ 324 a->permute = PETSC_TRUE; 325 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 326 ai = a->inew; aj = a->jnew; 327 } 328 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 329 330 /* initialization */ 331 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 332 ui[0] = 0; 333 334 /* jl: linked list for storing indices of the pivot rows 335 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 336 ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr); 337 il = jl + mbs; 338 cols = il + mbs; 339 ui_ptr = (PetscInt**)(cols + mbs); 340 341 for (i=0; i<mbs; i++){ 342 jl[i] = mbs; il[i] = 0; 343 } 344 345 /* create and initialize a linked list for storing column indices of the active row k */ 346 nlnk = mbs + 1; 347 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 348 349 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 350 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 351 current_space = free_space; 352 353 for (k=0; k<mbs; k++){ /* for each active row k */ 354 /* initialize lnk by the column indices of row rip[k] of A */ 355 nzk = 0; 356 ncols = ai[rip[k]+1] - ai[rip[k]]; 357 for (j=0; j<ncols; j++){ 358 i = *(aj + ai[rip[k]] + j); 359 cols[j] = rip[i]; 360 } 361 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 362 nzk += nlnk; 363 364 /* update lnk by computing fill-in for each pivot row to be merged in */ 365 prow = jl[k]; /* 1st pivot row */ 366 367 while (prow < k){ 368 nextprow = jl[prow]; 369 /* merge prow into k-th row */ 370 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 371 jmax = ui[prow+1]; 372 ncols = jmax-jmin; 373 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 374 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 375 nzk += nlnk; 376 377 /* update il and jl for prow */ 378 if (jmin < jmax){ 379 il[prow] = jmin; 380 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 381 } 382 prow = nextprow; 383 } 384 385 /* if free space is not available, make more free space */ 386 if (current_space->local_remaining<nzk) { 387 i = mbs - k + 1; /* num of unfactored rows */ 388 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 389 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 390 reallocs++; 391 } 392 393 /* copy data into free space, then initialize lnk */ 394 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 395 396 /* add the k-th row into il and jl */ 397 if (nzk-1 > 0){ 398 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 399 jl[k] = jl[i]; jl[i] = k; 400 il[k] = ui[k] + 1; 401 } 402 ui_ptr[k] = current_space->array; 403 current_space->array += nzk; 404 current_space->local_used += nzk; 405 current_space->local_remaining -= nzk; 406 407 ui[k+1] = ui[k] + nzk; 408 } 409 410 #if defined(PETSC_USE_INFO) 411 if (ai[mbs] != 0) { 412 PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 413 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 414 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 415 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 416 } else { 417 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 418 } 419 #endif 420 421 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 422 ierr = PetscFree(jl);CHKERRQ(ierr); 423 424 /* destroy list of free space and other temporary array(s) */ 425 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 426 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 427 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 428 429 /* put together the new matrix in MATSEQSBAIJ format */ 430 ierr = MatCreate(PETSC_COMM_SELF,fact);CHKERRQ(ierr); 431 ierr = MatSetSizes(*fact,mbs,mbs,mbs,mbs);CHKERRQ(ierr); 432 B = *fact; 433 ierr = MatSetType(B,MATSEQSBAIJ);CHKERRQ(ierr); 434 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 435 436 b = (Mat_SeqSBAIJ*)B->data; 437 b->singlemalloc = PETSC_FALSE; 438 b->free_a = PETSC_TRUE; 439 b->free_ij = PETSC_TRUE; 440 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 441 b->j = uj; 442 b->i = ui; 443 b->diag = 0; 444 b->ilen = 0; 445 b->imax = 0; 446 b->row = perm; 447 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 448 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 449 b->icol = perm; 450 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 451 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 452 ierr = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 453 b->maxnz = b->nz = ui[mbs]; 454 455 B->factor = FACTOR_CHOLESKY; 456 B->info.factor_mallocs = reallocs; 457 B->info.fill_ratio_given = fill; 458 if (ai[mbs] != 0) { 459 B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 460 } else { 461 B->info.fill_ratio_needed = 0.0; 462 } 463 464 if (perm_identity){ 465 switch (bs) { 466 case 1: 467 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 468 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 469 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 470 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 471 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 472 break; 473 case 2: 474 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 475 B->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 476 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering; 477 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering; 478 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 479 break; 480 case 3: 481 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 482 B->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 483 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_3_NaturalOrdering; 484 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_3_NaturalOrdering; 485 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 486 break; 487 case 4: 488 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 489 B->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 490 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_4_NaturalOrdering; 491 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_4_NaturalOrdering; 492 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 493 break; 494 case 5: 495 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 496 B->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 497 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_5_NaturalOrdering; 498 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_5_NaturalOrdering; 499 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 500 break; 501 case 6: 502 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 503 B->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 504 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_6_NaturalOrdering; 505 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_6_NaturalOrdering; 506 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 507 break; 508 case 7: 509 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 510 B->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 511 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_7_NaturalOrdering; 512 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_7_NaturalOrdering; 513 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 514 break; 515 default: 516 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 517 B->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 518 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering; 519 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering; 520 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 521 break; 522 } 523 } 524 PetscFunctionReturn(0); 525 } 526 #undef __FUNCT__ 527 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 528 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,MatFactorInfo *info,Mat *B) 529 { 530 Mat C = *B; 531 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 532 IS perm = b->row; 533 PetscErrorCode ierr; 534 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 535 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 536 PetscInt bs=A->rmap.bs,bs2 = a->bs2,bslog = 0; 537 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 538 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 539 MatScalar *work; 540 PetscInt *pivots; 541 542 PetscFunctionBegin; 543 /* initialization */ 544 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 545 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 546 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 547 jl = il + mbs; 548 for (i=0; i<mbs; i++) { 549 jl[i] = mbs; il[0] = 0; 550 } 551 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 552 uik = dk + bs2; 553 work = uik + bs2; 554 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 555 556 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 557 558 /* check permutation */ 559 if (!a->permute){ 560 ai = a->i; aj = a->j; aa = a->a; 561 } else { 562 ai = a->inew; aj = a->jnew; 563 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 564 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 565 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 566 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 567 568 /* flops in while loop */ 569 bslog = 2*bs*bs2; 570 571 for (i=0; i<mbs; i++){ 572 jmin = ai[i]; jmax = ai[i+1]; 573 for (j=jmin; j<jmax; j++){ 574 while (a2anew[j] != j){ 575 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 576 for (k1=0; k1<bs2; k1++){ 577 dk[k1] = aa[k*bs2+k1]; 578 aa[k*bs2+k1] = aa[j*bs2+k1]; 579 aa[j*bs2+k1] = dk[k1]; 580 } 581 } 582 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 583 if (i > aj[j]){ 584 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 585 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 586 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 587 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 588 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 589 } 590 } 591 } 592 } 593 ierr = PetscFree(a2anew);CHKERRQ(ierr); 594 } 595 596 /* for each row k */ 597 for (k = 0; k<mbs; k++){ 598 599 /*initialize k-th row with elements nonzero in row perm(k) of A */ 600 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 601 602 ap = aa + jmin*bs2; 603 for (j = jmin; j < jmax; j++){ 604 vj = perm_ptr[aj[j]]; /* block col. index */ 605 rtmp_ptr = rtmp + vj*bs2; 606 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 607 } 608 609 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 610 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 611 i = jl[k]; /* first row to be added to k_th row */ 612 613 while (i < k){ 614 nexti = jl[i]; /* next row to be added to k_th row */ 615 616 /* compute multiplier */ 617 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 618 619 /* uik = -inv(Di)*U_bar(i,k) */ 620 diag = ba + i*bs2; 621 u = ba + ili*bs2; 622 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 623 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 624 625 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 626 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 627 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 628 629 /* update -U(i,k) */ 630 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 631 632 /* add multiple of row i to k-th row ... */ 633 jmin = ili + 1; jmax = bi[i+1]; 634 if (jmin < jmax){ 635 for (j=jmin; j<jmax; j++) { 636 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 637 rtmp_ptr = rtmp + bj[j]*bs2; 638 u = ba + j*bs2; 639 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 640 } 641 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 642 643 /* ... add i to row list for next nonzero entry */ 644 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 645 j = bj[jmin]; 646 jl[i] = jl[j]; jl[j] = i; /* update jl */ 647 } 648 i = nexti; 649 } 650 651 /* save nonzero entries in k-th row of U ... */ 652 653 /* invert diagonal block */ 654 diag = ba+k*bs2; 655 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 656 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 657 658 jmin = bi[k]; jmax = bi[k+1]; 659 if (jmin < jmax) { 660 for (j=jmin; j<jmax; j++){ 661 vj = bj[j]; /* block col. index of U */ 662 u = ba + j*bs2; 663 rtmp_ptr = rtmp + vj*bs2; 664 for (k1=0; k1<bs2; k1++){ 665 *u++ = *rtmp_ptr; 666 *rtmp_ptr++ = 0.0; 667 } 668 } 669 670 /* ... add k to row list for first nonzero entry in k-th row */ 671 il[k] = jmin; 672 i = bj[jmin]; 673 jl[k] = jl[i]; jl[i] = k; 674 } 675 } 676 677 ierr = PetscFree(rtmp);CHKERRQ(ierr); 678 ierr = PetscFree(il);CHKERRQ(ierr); 679 ierr = PetscFree(dk);CHKERRQ(ierr); 680 ierr = PetscFree(pivots);CHKERRQ(ierr); 681 if (a->permute){ 682 ierr = PetscFree(aa);CHKERRQ(ierr); 683 } 684 685 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 686 C->factor = FACTOR_CHOLESKY; 687 C->assembled = PETSC_TRUE; 688 C->preallocated = PETSC_TRUE; 689 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 690 PetscFunctionReturn(0); 691 } 692 693 #undef __FUNCT__ 694 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 695 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 696 { 697 Mat C = *B; 698 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 699 PetscErrorCode ierr; 700 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 701 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 702 PetscInt bs=A->rmap.bs,bs2 = a->bs2,bslog; 703 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 704 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 705 MatScalar *work; 706 PetscInt *pivots; 707 708 PetscFunctionBegin; 709 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 710 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 711 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&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((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 717 uik = dk + bs2; 718 work = uik + bs2; 719 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 720 721 ai = a->i; aj = a->j; aa = a->a; 722 723 /* flops in while loop */ 724 bslog = 2*bs*bs2; 725 726 /* for each row k */ 727 for (k = 0; k<mbs; k++){ 728 729 /*initialize k-th row with elements nonzero in row k of A */ 730 jmin = ai[k]; jmax = ai[k+1]; 731 ap = aa + jmin*bs2; 732 for (j = jmin; j < jmax; j++){ 733 vj = aj[j]; /* block col. index */ 734 rtmp_ptr = rtmp + vj*bs2; 735 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 736 } 737 738 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 739 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 740 i = jl[k]; /* first row to be added to k_th row */ 741 742 while (i < k){ 743 nexti = jl[i]; /* next row to be added to k_th row */ 744 745 /* compute multiplier */ 746 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 747 748 /* uik = -inv(Di)*U_bar(i,k) */ 749 diag = ba + i*bs2; 750 u = ba + ili*bs2; 751 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 752 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 753 754 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 755 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 756 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 757 758 /* update -U(i,k) */ 759 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 760 761 /* add multiple of row i to k-th row ... */ 762 jmin = ili + 1; jmax = bi[i+1]; 763 if (jmin < jmax){ 764 for (j=jmin; j<jmax; j++) { 765 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 766 rtmp_ptr = rtmp + bj[j]*bs2; 767 u = ba + j*bs2; 768 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 769 } 770 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 771 772 /* ... add i to row list for next nonzero entry */ 773 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 774 j = bj[jmin]; 775 jl[i] = jl[j]; jl[j] = i; /* update jl */ 776 } 777 i = nexti; 778 } 779 780 /* save nonzero entries in k-th row of U ... */ 781 782 /* invert diagonal block */ 783 diag = ba+k*bs2; 784 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 785 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 786 787 jmin = bi[k]; jmax = bi[k+1]; 788 if (jmin < jmax) { 789 for (j=jmin; j<jmax; j++){ 790 vj = bj[j]; /* block col. index of U */ 791 u = ba + j*bs2; 792 rtmp_ptr = rtmp + vj*bs2; 793 for (k1=0; k1<bs2; k1++){ 794 *u++ = *rtmp_ptr; 795 *rtmp_ptr++ = 0.0; 796 } 797 } 798 799 /* ... add k to row list for first nonzero entry in k-th row */ 800 il[k] = jmin; 801 i = bj[jmin]; 802 jl[k] = jl[i]; jl[i] = k; 803 } 804 } 805 806 ierr = PetscFree(rtmp);CHKERRQ(ierr); 807 ierr = PetscFree(il);CHKERRQ(ierr); 808 ierr = PetscFree(dk);CHKERRQ(ierr); 809 ierr = PetscFree(pivots);CHKERRQ(ierr); 810 811 C->factor = FACTOR_CHOLESKY; 812 C->assembled = PETSC_TRUE; 813 C->preallocated = PETSC_TRUE; 814 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* 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 2 by 2. 821 */ 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 824 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B) 825 { 826 Mat C = *B; 827 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 828 IS perm = b->row; 829 PetscErrorCode ierr; 830 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 831 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 832 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 833 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 834 835 PetscFunctionBegin; 836 /* initialization */ 837 /* il and jl record the first nonzero element in each row of the accessing 838 window U(0:k, k:mbs-1). 839 jl: list of rows to be added to uneliminated rows 840 i>= k: jl(i) is the first row to be added to row i 841 i< k: jl(i) is the row following row i in some list of rows 842 jl(i) = mbs indicates the end of a list 843 il(i): points to the first nonzero element in columns k,...,mbs-1 of 844 row i of U */ 845 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 846 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 847 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 848 jl = il + mbs; 849 for (i=0; i<mbs; i++) { 850 jl[i] = mbs; il[0] = 0; 851 } 852 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 853 uik = dk + 4; 854 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 855 856 /* check permutation */ 857 if (!a->permute){ 858 ai = a->i; aj = a->j; aa = a->a; 859 } else { 860 ai = a->inew; aj = a->jnew; 861 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 862 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 863 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 864 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 865 866 for (i=0; i<mbs; i++){ 867 jmin = ai[i]; jmax = ai[i+1]; 868 for (j=jmin; j<jmax; j++){ 869 while (a2anew[j] != j){ 870 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 871 for (k1=0; k1<4; k1++){ 872 dk[k1] = aa[k*4+k1]; 873 aa[k*4+k1] = aa[j*4+k1]; 874 aa[j*4+k1] = dk[k1]; 875 } 876 } 877 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 878 if (i > aj[j]){ 879 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 880 ap = aa + j*4; /* ptr to the beginning of the block */ 881 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 882 ap[1] = ap[2]; 883 ap[2] = dk[1]; 884 } 885 } 886 } 887 ierr = PetscFree(a2anew);CHKERRQ(ierr); 888 } 889 890 /* for each row k */ 891 for (k = 0; k<mbs; k++){ 892 893 /*initialize k-th row with elements nonzero in row perm(k) of A */ 894 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 895 ap = aa + jmin*4; 896 for (j = jmin; j < jmax; j++){ 897 vj = perm_ptr[aj[j]]; /* block col. index */ 898 rtmp_ptr = rtmp + vj*4; 899 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 900 } 901 902 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 903 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 904 i = jl[k]; /* first row to be added to k_th row */ 905 906 while (i < k){ 907 nexti = jl[i]; /* next row to be added to k_th row */ 908 909 /* compute multiplier */ 910 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 911 912 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 913 diag = ba + i*4; 914 u = ba + ili*4; 915 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 916 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 917 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 918 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 919 920 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 921 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 922 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 923 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 924 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 925 926 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 927 928 /* update -U(i,k): ba[ili] = uik */ 929 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 930 931 /* add multiple of row i to k-th row ... */ 932 jmin = ili + 1; jmax = bi[i+1]; 933 if (jmin < jmax){ 934 for (j=jmin; j<jmax; j++) { 935 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 936 rtmp_ptr = rtmp + bj[j]*4; 937 u = ba + j*4; 938 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 939 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 940 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 941 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 942 } 943 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 944 945 /* ... add i to row list for next nonzero entry */ 946 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 947 j = bj[jmin]; 948 jl[i] = jl[j]; jl[j] = i; /* update jl */ 949 } 950 i = nexti; 951 } 952 953 /* save nonzero entries in k-th row of U ... */ 954 955 /* invert diagonal block */ 956 diag = ba+k*4; 957 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 958 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 959 960 jmin = bi[k]; jmax = bi[k+1]; 961 if (jmin < jmax) { 962 for (j=jmin; j<jmax; j++){ 963 vj = bj[j]; /* block col. index of U */ 964 u = ba + j*4; 965 rtmp_ptr = rtmp + vj*4; 966 for (k1=0; k1<4; k1++){ 967 *u++ = *rtmp_ptr; 968 *rtmp_ptr++ = 0.0; 969 } 970 } 971 972 /* ... add k to row list for first nonzero entry in k-th row */ 973 il[k] = jmin; 974 i = bj[jmin]; 975 jl[k] = jl[i]; jl[i] = k; 976 } 977 } 978 979 ierr = PetscFree(rtmp);CHKERRQ(ierr); 980 ierr = PetscFree(il);CHKERRQ(ierr); 981 ierr = PetscFree(dk);CHKERRQ(ierr); 982 if (a->permute) { 983 ierr = PetscFree(aa);CHKERRQ(ierr); 984 } 985 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 986 C->factor = FACTOR_CHOLESKY; 987 C->assembled = PETSC_TRUE; 988 C->preallocated = PETSC_TRUE; 989 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 990 PetscFunctionReturn(0); 991 } 992 993 /* 994 Version for when blocks are 2 by 2 Using natural ordering 995 */ 996 #undef __FUNCT__ 997 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 998 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 999 { 1000 Mat C = *B; 1001 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 1002 PetscErrorCode ierr; 1003 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1004 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1005 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 1006 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1007 1008 PetscFunctionBegin; 1009 /* initialization */ 1010 /* il and jl record the first nonzero element in each row of the accessing 1011 window U(0:k, k:mbs-1). 1012 jl: list of rows to be added to uneliminated rows 1013 i>= k: jl(i) is the first row to be added to row i 1014 i< k: jl(i) is the row following row i in some list of rows 1015 jl(i) = mbs indicates the end of a list 1016 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1017 row i of U */ 1018 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1019 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1020 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1021 jl = il + mbs; 1022 for (i=0; i<mbs; i++) { 1023 jl[i] = mbs; il[0] = 0; 1024 } 1025 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 1026 uik = dk + 4; 1027 1028 ai = a->i; aj = a->j; aa = a->a; 1029 1030 /* for each row k */ 1031 for (k = 0; k<mbs; k++){ 1032 1033 /*initialize k-th row with elements nonzero in row k of A */ 1034 jmin = ai[k]; jmax = ai[k+1]; 1035 ap = aa + jmin*4; 1036 for (j = jmin; j < jmax; j++){ 1037 vj = aj[j]; /* block col. index */ 1038 rtmp_ptr = rtmp + vj*4; 1039 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1040 } 1041 1042 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1043 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1044 i = jl[k]; /* first row to be added to k_th row */ 1045 1046 while (i < k){ 1047 nexti = jl[i]; /* next row to be added to k_th row */ 1048 1049 /* compute multiplier */ 1050 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1051 1052 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1053 diag = ba + i*4; 1054 u = ba + ili*4; 1055 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1056 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1057 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1058 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1059 1060 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1061 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1062 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1063 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1064 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1065 1066 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 1067 1068 /* update -U(i,k): ba[ili] = uik */ 1069 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1070 1071 /* add multiple of row i to k-th row ... */ 1072 jmin = ili + 1; jmax = bi[i+1]; 1073 if (jmin < jmax){ 1074 for (j=jmin; j<jmax; j++) { 1075 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1076 rtmp_ptr = rtmp + bj[j]*4; 1077 u = ba + j*4; 1078 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1079 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1080 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1081 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1082 } 1083 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 1084 1085 /* ... add i to row list for next nonzero entry */ 1086 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1087 j = bj[jmin]; 1088 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1089 } 1090 i = nexti; 1091 } 1092 1093 /* save nonzero entries in k-th row of U ... */ 1094 1095 /* invert diagonal block */ 1096 diag = ba+k*4; 1097 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1098 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1099 1100 jmin = bi[k]; jmax = bi[k+1]; 1101 if (jmin < jmax) { 1102 for (j=jmin; j<jmax; j++){ 1103 vj = bj[j]; /* block col. index of U */ 1104 u = ba + j*4; 1105 rtmp_ptr = rtmp + vj*4; 1106 for (k1=0; k1<4; k1++){ 1107 *u++ = *rtmp_ptr; 1108 *rtmp_ptr++ = 0.0; 1109 } 1110 } 1111 1112 /* ... add k to row list for first nonzero entry in k-th row */ 1113 il[k] = jmin; 1114 i = bj[jmin]; 1115 jl[k] = jl[i]; jl[i] = k; 1116 } 1117 } 1118 1119 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1120 ierr = PetscFree(il);CHKERRQ(ierr); 1121 ierr = PetscFree(dk);CHKERRQ(ierr); 1122 1123 C->factor = FACTOR_CHOLESKY; 1124 C->assembled = PETSC_TRUE; 1125 C->preallocated = PETSC_TRUE; 1126 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1127 PetscFunctionReturn(0); 1128 } 1129 1130 /* 1131 Numeric U^T*D*U factorization for SBAIJ format. 1132 Version for blocks are 1 by 1. 1133 */ 1134 #undef __FUNCT__ 1135 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1136 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B) 1137 { 1138 Mat C = *B; 1139 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1140 IS ip=b->row; 1141 PetscErrorCode ierr; 1142 PetscInt *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1143 PetscInt *ai,*aj,*a2anew; 1144 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1145 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1146 PetscReal zeropivot,rs,shiftnz; 1147 PetscReal shiftpd; 1148 ChShift_Ctx sctx; 1149 PetscInt newshift; 1150 1151 PetscFunctionBegin; 1152 /* initialization */ 1153 shiftnz = info->shiftnz; 1154 shiftpd = info->shiftpd; 1155 zeropivot = info->zeropivot; 1156 1157 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1158 if (!a->permute){ 1159 ai = a->i; aj = a->j; aa = a->a; 1160 } else { 1161 ai = a->inew; aj = a->jnew; 1162 nz = ai[mbs]; 1163 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1164 a2anew = a->a2anew; 1165 bval = a->a; 1166 for (j=0; j<nz; j++){ 1167 aa[a2anew[j]] = *(bval++); 1168 } 1169 } 1170 1171 /* initialization */ 1172 /* il and jl record the first nonzero element in each row of the accessing 1173 window U(0:k, k:mbs-1). 1174 jl: list of rows to be added to uneliminated rows 1175 i>= k: jl(i) is the first row to be added to row i 1176 i< k: jl(i) is the row following row i in some list of rows 1177 jl(i) = mbs indicates the end of a list 1178 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1179 row i of U */ 1180 nz = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar); 1181 ierr = PetscMalloc(nz,&il);CHKERRQ(ierr); 1182 jl = il + mbs; 1183 rtmp = (MatScalar*)(jl + mbs); 1184 1185 sctx.shift_amount = 0; 1186 sctx.nshift = 0; 1187 do { 1188 sctx.chshift = PETSC_FALSE; 1189 for (i=0; i<mbs; i++) { 1190 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1191 } 1192 1193 for (k = 0; k<mbs; k++){ 1194 /*initialize k-th row by the perm[k]-th row of A */ 1195 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1196 bval = ba + bi[k]; 1197 for (j = jmin; j < jmax; j++){ 1198 col = rip[aj[j]]; 1199 rtmp[col] = aa[j]; 1200 *bval++ = 0.0; /* for in-place factorization */ 1201 } 1202 1203 /* shift the diagonal of the matrix */ 1204 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1205 1206 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1207 dk = rtmp[k]; 1208 i = jl[k]; /* first row to be added to k_th row */ 1209 1210 while (i < k){ 1211 nexti = jl[i]; /* next row to be added to k_th row */ 1212 1213 /* compute multiplier, update diag(k) and U(i,k) */ 1214 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1215 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1216 dk += uikdi*ba[ili]; 1217 ba[ili] = uikdi; /* -U(i,k) */ 1218 1219 /* add multiple of row i to k-th row */ 1220 jmin = ili + 1; jmax = bi[i+1]; 1221 if (jmin < jmax){ 1222 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1223 ierr = PetscLogFlops(2*(jmax-jmin));CHKERRQ(ierr); 1224 1225 /* update il and jl for row i */ 1226 il[i] = jmin; 1227 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1228 } 1229 i = nexti; 1230 } 1231 1232 /* shift the diagonals when zero pivot is detected */ 1233 /* compute rs=sum of abs(off-diagonal) */ 1234 rs = 0.0; 1235 jmin = bi[k]+1; 1236 nz = bi[k+1] - jmin; 1237 if (nz){ 1238 bcol = bj + jmin; 1239 while (nz--){ 1240 rs += PetscAbsScalar(rtmp[*bcol]); 1241 bcol++; 1242 } 1243 } 1244 1245 sctx.rs = rs; 1246 sctx.pv = dk; 1247 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1248 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1249 1250 /* copy data into U(k,:) */ 1251 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1252 jmin = bi[k]+1; jmax = bi[k+1]; 1253 if (jmin < jmax) { 1254 for (j=jmin; j<jmax; j++){ 1255 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1256 } 1257 /* add the k-th row into il and jl */ 1258 il[k] = jmin; 1259 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1260 } 1261 } 1262 } while (sctx.chshift); 1263 ierr = PetscFree(il);CHKERRQ(ierr); 1264 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1265 1266 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1267 C->factor = FACTOR_CHOLESKY; 1268 C->assembled = PETSC_TRUE; 1269 C->preallocated = PETSC_TRUE; 1270 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1271 if (sctx.nshift){ 1272 if (shiftnz) { 1273 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1274 } else if (shiftpd) { 1275 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1276 } 1277 } 1278 PetscFunctionReturn(0); 1279 } 1280 1281 /* 1282 Version for when blocks are 1 by 1 Using natural ordering 1283 */ 1284 #undef __FUNCT__ 1285 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1286 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 1287 { 1288 Mat C = *B; 1289 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1290 PetscErrorCode ierr; 1291 PetscInt i,j,mbs = a->mbs; 1292 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1293 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1294 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1295 PetscReal zeropivot,rs,shiftnz; 1296 PetscReal shiftpd; 1297 ChShift_Ctx sctx; 1298 PetscInt newshift; 1299 1300 PetscFunctionBegin; 1301 /* initialization */ 1302 shiftnz = info->shiftnz; 1303 shiftpd = info->shiftpd; 1304 zeropivot = info->zeropivot; 1305 1306 /* il and jl record the first nonzero element in each row of the accessing 1307 window U(0:k, k:mbs-1). 1308 jl: list of rows to be added to uneliminated rows 1309 i>= k: jl(i) is the first row to be added to row i 1310 i< k: jl(i) is the row following row i in some list of rows 1311 jl(i) = mbs indicates the end of a list 1312 il(i): points to the first nonzero element in U(i,k:mbs-1) 1313 */ 1314 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1315 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1316 jl = il + mbs; 1317 1318 sctx.shift_amount = 0; 1319 sctx.nshift = 0; 1320 do { 1321 sctx.chshift = PETSC_FALSE; 1322 for (i=0; i<mbs; i++) { 1323 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1324 } 1325 1326 for (k = 0; k<mbs; k++){ 1327 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1328 nz = ai[k+1] - ai[k]; 1329 acol = aj + ai[k]; 1330 aval = aa + ai[k]; 1331 bval = ba + bi[k]; 1332 while (nz -- ){ 1333 rtmp[*acol++] = *aval++; 1334 *bval++ = 0.0; /* for in-place factorization */ 1335 } 1336 1337 /* shift the diagonal of the matrix */ 1338 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1339 1340 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1341 dk = rtmp[k]; 1342 i = jl[k]; /* first row to be added to k_th row */ 1343 1344 while (i < k){ 1345 nexti = jl[i]; /* next row to be added to k_th row */ 1346 /* compute multiplier, update D(k) and U(i,k) */ 1347 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1348 uikdi = - ba[ili]*ba[bi[i]]; 1349 dk += uikdi*ba[ili]; 1350 ba[ili] = uikdi; /* -U(i,k) */ 1351 1352 /* add multiple of row i to k-th row ... */ 1353 jmin = ili + 1; 1354 nz = bi[i+1] - jmin; 1355 if (nz > 0){ 1356 bcol = bj + jmin; 1357 bval = ba + jmin; 1358 ierr = PetscLogFlops(2*nz);CHKERRQ(ierr); 1359 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1360 1361 /* update il and jl for i-th row */ 1362 il[i] = jmin; 1363 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1364 } 1365 i = nexti; 1366 } 1367 1368 /* shift the diagonals when zero pivot is detected */ 1369 /* compute rs=sum of abs(off-diagonal) */ 1370 rs = 0.0; 1371 jmin = bi[k]+1; 1372 nz = bi[k+1] - jmin; 1373 if (nz){ 1374 bcol = bj + jmin; 1375 while (nz--){ 1376 rs += PetscAbsScalar(rtmp[*bcol]); 1377 bcol++; 1378 } 1379 } 1380 1381 sctx.rs = rs; 1382 sctx.pv = dk; 1383 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1384 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1385 1386 /* copy data into U(k,:) */ 1387 ba[bi[k]] = 1.0/dk; 1388 jmin = bi[k]+1; 1389 nz = bi[k+1] - jmin; 1390 if (nz){ 1391 bcol = bj + jmin; 1392 bval = ba + jmin; 1393 while (nz--){ 1394 *bval++ = rtmp[*bcol]; 1395 rtmp[*bcol++] = 0.0; 1396 } 1397 /* add k-th row into il and jl */ 1398 il[k] = jmin; 1399 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1400 } 1401 } /* end of for (k = 0; k<mbs; k++) */ 1402 } while (sctx.chshift); 1403 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1404 ierr = PetscFree(il);CHKERRQ(ierr); 1405 1406 C->factor = FACTOR_CHOLESKY; 1407 C->assembled = PETSC_TRUE; 1408 C->preallocated = PETSC_TRUE; 1409 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1410 if (sctx.nshift){ 1411 if (shiftnz) { 1412 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1413 } else if (shiftpd) { 1414 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1415 } 1416 } 1417 PetscFunctionReturn(0); 1418 } 1419 1420 #undef __FUNCT__ 1421 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1422 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1423 { 1424 PetscErrorCode ierr; 1425 Mat C; 1426 1427 PetscFunctionBegin; 1428 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1429 ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr); 1430 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1431 PetscFunctionReturn(0); 1432 } 1433 1434 1435