1 2 #include <../src/mat/impls/baij/seq/baij.h> 3 #include <../src/mat/impls/sbaij/seq/sbaij.h> 4 #include <petsc/private/kernels/blockinvert.h> 5 #include <petscis.h> 6 7 /* 8 input: 9 F -- numeric factor 10 output: 11 nneg, nzero, npos: matrix inertia 12 */ 13 14 #undef __FUNCT__ 15 #define __FUNCT__ "MatGetInertia_SeqSBAIJ" 16 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos) 17 { 18 Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data; 19 MatScalar *dd = fact_ptr->a; 20 PetscInt mbs =fact_ptr->mbs,bs=F->rmap->bs,i,nneig_tmp,npos_tmp,*fi = fact_ptr->diag; 21 22 PetscFunctionBegin; 23 if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for bs: %D >1 yet",bs); 24 nneig_tmp = 0; npos_tmp = 0; 25 for (i=0; i<mbs; i++) { 26 if (PetscRealPart(dd[*fi]) > 0.0) npos_tmp++; 27 else if (PetscRealPart(dd[*fi]) < 0.0) nneig_tmp++; 28 fi++; 29 } 30 if (nneig) *nneig = nneig_tmp; 31 if (npos) *npos = npos_tmp; 32 if (nzero) *nzero = mbs - nneig_tmp - npos_tmp; 33 PetscFunctionReturn(0); 34 } 35 36 /* 37 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 38 Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad. 39 */ 40 #undef __FUNCT__ 41 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR" 42 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat F,Mat A,IS perm,const MatFactorInfo *info) 43 { 44 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 45 PetscErrorCode ierr; 46 const PetscInt *rip,*ai,*aj; 47 PetscInt i,mbs = a->mbs,*jutmp,bs = A->rmap->bs,bs2=a->bs2; 48 PetscInt m,reallocs = 0,prow; 49 PetscInt *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 50 PetscReal f = info->fill; 51 PetscBool perm_identity; 52 53 PetscFunctionBegin; 54 /* check whether perm is the identity mapping */ 55 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 56 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 57 58 if (perm_identity) { /* without permutation */ 59 a->permute = PETSC_FALSE; 60 61 ai = a->i; aj = a->j; 62 } else { /* non-trivial permutation */ 63 a->permute = PETSC_TRUE; 64 65 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 66 67 ai = a->inew; aj = a->jnew; 68 } 69 70 /* initialization */ 71 ierr = PetscMalloc1(mbs+1,&iu);CHKERRQ(ierr); 72 umax = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1; 73 ierr = PetscMalloc1(umax,&ju);CHKERRQ(ierr); 74 iu[0] = mbs+1; 75 juidx = mbs + 1; /* index for ju */ 76 /* jl linked list for pivot row -- linked list for col index */ 77 ierr = PetscMalloc2(mbs,&jl,mbs,&q);CHKERRQ(ierr); 78 for (i=0; i<mbs; i++) { 79 jl[i] = mbs; 80 q[i] = 0; 81 } 82 83 /* for each row k */ 84 for (k=0; k<mbs; k++) { 85 for (i=0; i<mbs; i++) q[i] = 0; /* to be removed! */ 86 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 87 q[k] = mbs; 88 /* initialize nonzero structure of k-th row to row rip[k] of A */ 89 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 90 jmax = ai[rip[k]+1]; 91 for (j=jmin; j<jmax; j++) { 92 vj = rip[aj[j]]; /* col. value */ 93 if (vj > k) { 94 qm = k; 95 do { 96 m = qm; qm = q[m]; 97 } while (qm < vj); 98 if (qm == vj) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Duplicate entry in A\n"); 99 nzk++; 100 q[m] = vj; 101 q[vj] = qm; 102 } /* if (vj > k) */ 103 } /* for (j=jmin; j<jmax; j++) */ 104 105 /* modify nonzero structure of k-th row by computing fill-in 106 for each row i to be merged in */ 107 prow = k; 108 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 109 110 while (prow < k) { 111 /* merge row prow into k-th row */ 112 jmin = iu[prow] + 1; jmax = iu[prow+1]; 113 qm = k; 114 for (j=jmin; j<jmax; j++) { 115 vj = ju[j]; 116 do { 117 m = qm; qm = q[m]; 118 } while (qm < vj); 119 if (qm != vj) { 120 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 121 } 122 } 123 prow = jl[prow]; /* next pivot row */ 124 } 125 126 /* add k to row list for first nonzero element in k-th row */ 127 if (nzk > 0) { 128 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 129 jl[k] = jl[i]; jl[i] = k; 130 } 131 iu[k+1] = iu[k] + nzk; 132 133 /* allocate more space to ju if needed */ 134 if (iu[k+1] > umax) { 135 /* estimate how much additional space we will need */ 136 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 137 /* just double the memory each time */ 138 maxadd = umax; 139 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 140 umax += maxadd; 141 142 /* allocate a longer ju */ 143 ierr = PetscMalloc1(umax,&jutmp);CHKERRQ(ierr); 144 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr); 145 ierr = PetscFree(ju);CHKERRQ(ierr); 146 ju = jutmp; 147 reallocs++; /* count how many times we realloc */ 148 } 149 150 /* save nonzero structure of k-th row in ju */ 151 i=k; 152 while (nzk--) { 153 i = q[i]; 154 ju[juidx++] = i; 155 } 156 } 157 158 #if defined(PETSC_USE_INFO) 159 if (ai[mbs] != 0) { 160 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 161 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)f,(double)af);CHKERRQ(ierr); 162 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 163 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g);\n",(double)af);CHKERRQ(ierr); 164 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 165 } else { 166 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 167 } 168 #endif 169 170 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 171 ierr = PetscFree2(jl,q);CHKERRQ(ierr); 172 173 /* put together the new matrix */ 174 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(F,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 175 176 /* ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)iperm);CHKERRQ(ierr); */ 177 b = (Mat_SeqSBAIJ*)(F)->data; 178 b->singlemalloc = PETSC_FALSE; 179 b->free_a = PETSC_TRUE; 180 b->free_ij = PETSC_TRUE; 181 182 ierr = PetscMalloc1((iu[mbs]+1)*bs2,&b->a);CHKERRQ(ierr); 183 b->j = ju; 184 b->i = iu; 185 b->diag = 0; 186 b->ilen = 0; 187 b->imax = 0; 188 b->row = perm; 189 190 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 191 192 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 193 194 b->icol = perm; 195 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 196 ierr = PetscMalloc1(bs*mbs+bs,&b->solve_work);CHKERRQ(ierr); 197 /* In b structure: Free imax, ilen, old a, old j. 198 Allocate idnew, solve_work, new a, new j */ 199 ierr = PetscLogObjectMemory((PetscObject)F,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 200 b->maxnz = b->nz = iu[mbs]; 201 202 (F)->info.factor_mallocs = reallocs; 203 (F)->info.fill_ratio_given = f; 204 if (ai[mbs] != 0) { 205 (F)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 206 } else { 207 (F)->info.fill_ratio_needed = 0.0; 208 } 209 ierr = MatSeqSBAIJSetNumericFactorization_inplace(F,perm_identity);CHKERRQ(ierr); 210 PetscFunctionReturn(0); 211 } 212 /* 213 Symbolic U^T*D*U factorization for SBAIJ format. 214 See MatICCFactorSymbolic_SeqAIJ() for description of its data structure. 215 */ 216 #include <petscbt.h> 217 #include <../src/mat/utils/freespace.h> 218 #undef __FUNCT__ 219 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 220 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info) 221 { 222 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 223 Mat_SeqSBAIJ *b; 224 PetscErrorCode ierr; 225 PetscBool perm_identity,missing; 226 PetscReal fill = info->fill; 227 const PetscInt *rip,*ai=a->i,*aj=a->j; 228 PetscInt i,mbs=a->mbs,bs=A->rmap->bs,reallocs=0,prow; 229 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 230 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr,*udiag; 231 PetscFreeSpaceList free_space=NULL,current_space=NULL; 232 PetscBT lnkbt; 233 234 PetscFunctionBegin; 235 if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must be square matrix, rows %D columns %D",A->rmap->n,A->cmap->n); 236 ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr); 237 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i); 238 if (bs > 1) { 239 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(fact,A,perm,info);CHKERRQ(ierr); 240 PetscFunctionReturn(0); 241 } 242 243 /* check whether perm is the identity mapping */ 244 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 245 if (!perm_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 246 a->permute = PETSC_FALSE; 247 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 248 249 /* initialization */ 250 ierr = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr); 251 ierr = PetscMalloc1(mbs+1,&udiag);CHKERRQ(ierr); 252 ui[0] = 0; 253 254 /* jl: linked list for storing indices of the pivot rows 255 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 256 ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr); 257 for (i=0; i<mbs; i++) { 258 jl[i] = mbs; il[i] = 0; 259 } 260 261 /* create and initialize a linked list for storing column indices of the active row k */ 262 nlnk = mbs + 1; 263 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 264 265 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 266 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 267 current_space = free_space; 268 269 for (k=0; k<mbs; k++) { /* for each active row k */ 270 /* initialize lnk by the column indices of row rip[k] of A */ 271 nzk = 0; 272 ncols = ai[k+1] - ai[k]; 273 if (!ncols) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Empty row %D in matrix ",k); 274 for (j=0; j<ncols; j++) { 275 i = *(aj + ai[k] + j); 276 cols[j] = i; 277 } 278 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 279 nzk += nlnk; 280 281 /* update lnk by computing fill-in for each pivot row to be merged in */ 282 prow = jl[k]; /* 1st pivot row */ 283 284 while (prow < k) { 285 nextprow = jl[prow]; 286 /* merge prow into k-th row */ 287 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 288 jmax = ui[prow+1]; 289 ncols = jmax-jmin; 290 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 291 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 292 nzk += nlnk; 293 294 /* update il and jl for prow */ 295 if (jmin < jmax) { 296 il[prow] = jmin; 297 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 298 } 299 prow = nextprow; 300 } 301 302 /* if free space is not available, make more free space */ 303 if (current_space->local_remaining<nzk) { 304 i = mbs - k + 1; /* num of unfactored rows */ 305 i *= PetscMin(nzk, i-1); /* i*nzk, i*(i-1): estimated and max additional space needed */ 306 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 307 reallocs++; 308 } 309 310 /* copy data into free space, then initialize lnk */ 311 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 312 313 /* add the k-th row into il and jl */ 314 if (nzk > 1) { 315 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 316 jl[k] = jl[i]; jl[i] = k; 317 il[k] = ui[k] + 1; 318 } 319 ui_ptr[k] = current_space->array; 320 321 current_space->array += nzk; 322 current_space->local_used += nzk; 323 current_space->local_remaining -= nzk; 324 325 ui[k+1] = ui[k] + nzk; 326 } 327 328 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 329 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 330 331 /* destroy list of free space and other temporary array(s) */ 332 ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr); 333 ierr = PetscFreeSpaceContiguous_Cholesky(&free_space,uj,mbs,ui,udiag);CHKERRQ(ierr); /* store matrix factor */ 334 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 335 336 /* put together the new matrix in MATSEQSBAIJ format */ 337 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 338 339 b = (Mat_SeqSBAIJ*)fact->data; 340 b->singlemalloc = PETSC_FALSE; 341 b->free_a = PETSC_TRUE; 342 b->free_ij = PETSC_TRUE; 343 344 ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr); 345 346 b->j = uj; 347 b->i = ui; 348 b->diag = udiag; 349 b->free_diag = PETSC_TRUE; 350 b->ilen = 0; 351 b->imax = 0; 352 b->row = perm; 353 b->icol = perm; 354 355 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 356 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 357 358 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 359 360 ierr = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr); 361 ierr = PetscLogObjectMemory((PetscObject)fact,ui[mbs]*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 362 363 b->maxnz = b->nz = ui[mbs]; 364 365 fact->info.factor_mallocs = reallocs; 366 fact->info.fill_ratio_given = fill; 367 if (ai[mbs] != 0) { 368 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 369 } else { 370 fact->info.fill_ratio_needed = 0.0; 371 } 372 #if defined(PETSC_USE_INFO) 373 if (ai[mbs] != 0) { 374 PetscReal af = fact->info.fill_ratio_needed; 375 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr); 376 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 377 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr); 378 } else { 379 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 380 } 381 #endif 382 fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 383 PetscFunctionReturn(0); 384 } 385 386 #undef __FUNCT__ 387 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_inplace" 388 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(Mat fact,Mat A,IS perm,const MatFactorInfo *info) 389 { 390 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 391 Mat_SeqSBAIJ *b; 392 PetscErrorCode ierr; 393 PetscBool perm_identity,missing; 394 PetscReal fill = info->fill; 395 const PetscInt *rip,*ai,*aj; 396 PetscInt i,mbs=a->mbs,bs=A->rmap->bs,reallocs=0,prow,d; 397 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 398 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr; 399 PetscFreeSpaceList free_space=NULL,current_space=NULL; 400 PetscBT lnkbt; 401 402 PetscFunctionBegin; 403 ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr); 404 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d); 405 406 /* 407 This code originally uses Modified Sparse Row (MSR) storage 408 (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise! 409 Then it is rewritten so the factor B takes seqsbaij format. However the associated 410 MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity, 411 thus the original code in MSR format is still used for these cases. 412 The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever 413 MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor. 414 */ 415 if (bs > 1) { 416 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(fact,A,perm,info);CHKERRQ(ierr); 417 PetscFunctionReturn(0); 418 } 419 420 /* check whether perm is the identity mapping */ 421 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 422 423 if (perm_identity) { 424 a->permute = PETSC_FALSE; 425 426 ai = a->i; aj = a->j; 427 } else { 428 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 429 #if 0 430 /* There are bugs for reordeing. Needs further work. 431 MatReordering for sbaij cannot be efficient. User should use aij formt! */ 432 a->permute = PETSC_TRUE; 433 434 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 435 ai = a->inew; aj = a->jnew; 436 #endif 437 } 438 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 439 440 /* initialization */ 441 ierr = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr); 442 ui[0] = 0; 443 444 /* jl: linked list for storing indices of the pivot rows 445 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 446 ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr); 447 for (i=0; i<mbs; i++) { 448 jl[i] = mbs; il[i] = 0; 449 } 450 451 /* create and initialize a linked list for storing column indices of the active row k */ 452 nlnk = mbs + 1; 453 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 454 455 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 456 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 457 current_space = free_space; 458 459 for (k=0; k<mbs; k++) { /* for each active row k */ 460 /* initialize lnk by the column indices of row rip[k] of A */ 461 nzk = 0; 462 ncols = ai[rip[k]+1] - ai[rip[k]]; 463 for (j=0; j<ncols; j++) { 464 i = *(aj + ai[rip[k]] + j); 465 cols[j] = rip[i]; 466 } 467 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 468 nzk += nlnk; 469 470 /* update lnk by computing fill-in for each pivot row to be merged in */ 471 prow = jl[k]; /* 1st pivot row */ 472 473 while (prow < k) { 474 nextprow = jl[prow]; 475 /* merge prow into k-th row */ 476 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 477 jmax = ui[prow+1]; 478 ncols = jmax-jmin; 479 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 480 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 481 nzk += nlnk; 482 483 /* update il and jl for prow */ 484 if (jmin < jmax) { 485 il[prow] = jmin; 486 487 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 488 } 489 prow = nextprow; 490 } 491 492 /* if free space is not available, make more free space */ 493 if (current_space->local_remaining<nzk) { 494 i = mbs - k + 1; /* num of unfactored rows */ 495 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 496 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 497 reallocs++; 498 } 499 500 /* copy data into free space, then initialize lnk */ 501 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 502 503 /* add the k-th row into il and jl */ 504 if (nzk-1 > 0) { 505 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 506 jl[k] = jl[i]; jl[i] = k; 507 il[k] = ui[k] + 1; 508 } 509 ui_ptr[k] = current_space->array; 510 511 current_space->array += nzk; 512 current_space->local_used += nzk; 513 current_space->local_remaining -= nzk; 514 515 ui[k+1] = ui[k] + nzk; 516 } 517 518 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 519 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 520 521 /* destroy list of free space and other temporary array(s) */ 522 ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr); 523 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 524 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 525 526 /* put together the new matrix in MATSEQSBAIJ format */ 527 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 528 529 b = (Mat_SeqSBAIJ*)fact->data; 530 b->singlemalloc = PETSC_FALSE; 531 b->free_a = PETSC_TRUE; 532 b->free_ij = PETSC_TRUE; 533 534 ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr); 535 536 b->j = uj; 537 b->i = ui; 538 b->diag = 0; 539 b->ilen = 0; 540 b->imax = 0; 541 b->row = perm; 542 543 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 544 545 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 546 b->icol = perm; 547 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 548 ierr = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr); 549 ierr = PetscLogObjectMemory((PetscObject)fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 550 b->maxnz = b->nz = ui[mbs]; 551 552 fact->info.factor_mallocs = reallocs; 553 fact->info.fill_ratio_given = fill; 554 if (ai[mbs] != 0) { 555 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 556 } else { 557 fact->info.fill_ratio_needed = 0.0; 558 } 559 #if defined(PETSC_USE_INFO) 560 if (ai[mbs] != 0) { 561 PetscReal af = fact->info.fill_ratio_needed; 562 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr); 563 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 564 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr); 565 } else { 566 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 567 } 568 #endif 569 ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr); 570 PetscFunctionReturn(0); 571 } 572 573 #undef __FUNCT__ 574 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 575 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info) 576 { 577 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 578 IS perm = b->row; 579 PetscErrorCode ierr; 580 const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j; 581 PetscInt i,j; 582 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 583 PetscInt bs =A->rmap->bs,bs2 = a->bs2,bslog = 0; 584 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 585 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 586 MatScalar *work; 587 PetscInt *pivots; 588 589 PetscFunctionBegin; 590 /* initialization */ 591 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 592 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 593 for (i=0; i<mbs; i++) { 594 jl[i] = mbs; il[0] = 0; 595 } 596 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 597 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 598 599 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 600 601 /* check permutation */ 602 if (!a->permute) { 603 ai = a->i; aj = a->j; aa = a->a; 604 } else { 605 ai = a->inew; aj = a->jnew; 606 ierr = PetscMalloc1(bs2*ai[mbs],&aa);CHKERRQ(ierr); 607 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 608 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 609 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 610 611 /* flops in while loop */ 612 bslog = 2*bs*bs2; 613 614 for (i=0; i<mbs; i++) { 615 jmin = ai[i]; jmax = ai[i+1]; 616 for (j=jmin; j<jmax; j++) { 617 while (a2anew[j] != j) { 618 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 619 for (k1=0; k1<bs2; k1++) { 620 dk[k1] = aa[k*bs2+k1]; 621 aa[k*bs2+k1] = aa[j*bs2+k1]; 622 aa[j*bs2+k1] = dk[k1]; 623 } 624 } 625 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 626 if (i > aj[j]) { 627 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 628 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 629 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 630 for (k=0; k<bs; k++) { /* j-th block of aa <- dk^T */ 631 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 632 } 633 } 634 } 635 } 636 ierr = PetscFree(a2anew);CHKERRQ(ierr); 637 } 638 639 /* for each row k */ 640 for (k = 0; k<mbs; k++) { 641 642 /*initialize k-th row with elements nonzero in row perm(k) of A */ 643 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 644 645 ap = aa + jmin*bs2; 646 for (j = jmin; j < jmax; j++) { 647 vj = perm_ptr[aj[j]]; /* block col. index */ 648 rtmp_ptr = rtmp + vj*bs2; 649 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 650 } 651 652 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 653 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 654 i = jl[k]; /* first row to be added to k_th row */ 655 656 while (i < k) { 657 nexti = jl[i]; /* next row to be added to k_th row */ 658 659 /* compute multiplier */ 660 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 661 662 /* uik = -inv(Di)*U_bar(i,k) */ 663 diag = ba + i*bs2; 664 u = ba + ili*bs2; 665 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 666 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 667 668 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 669 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 670 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 671 672 /* update -U(i,k) */ 673 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 674 675 /* add multiple of row i to k-th row ... */ 676 jmin = ili + 1; jmax = bi[i+1]; 677 if (jmin < jmax) { 678 for (j=jmin; j<jmax; j++) { 679 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 680 rtmp_ptr = rtmp + bj[j]*bs2; 681 u = ba + j*bs2; 682 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 683 } 684 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 685 686 /* ... add i to row list for next nonzero entry */ 687 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 688 j = bj[jmin]; 689 jl[i] = jl[j]; jl[j] = i; /* update jl */ 690 } 691 i = nexti; 692 } 693 694 /* save nonzero entries in k-th row of U ... */ 695 696 /* invert diagonal block */ 697 diag = ba+k*bs2; 698 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 699 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 700 701 jmin = bi[k]; jmax = bi[k+1]; 702 if (jmin < jmax) { 703 for (j=jmin; j<jmax; j++) { 704 vj = bj[j]; /* block col. index of U */ 705 u = ba + j*bs2; 706 rtmp_ptr = rtmp + vj*bs2; 707 for (k1=0; k1<bs2; k1++) { 708 *u++ = *rtmp_ptr; 709 *rtmp_ptr++ = 0.0; 710 } 711 } 712 713 /* ... add k to row list for first nonzero entry in k-th row */ 714 il[k] = jmin; 715 i = bj[jmin]; 716 jl[k] = jl[i]; jl[i] = k; 717 } 718 } 719 720 ierr = PetscFree(rtmp);CHKERRQ(ierr); 721 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 722 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 723 ierr = PetscFree(pivots);CHKERRQ(ierr); 724 if (a->permute) { 725 ierr = PetscFree(aa);CHKERRQ(ierr); 726 } 727 728 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 729 730 C->ops->solve = MatSolve_SeqSBAIJ_N_inplace; 731 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace; 732 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_inplace; 733 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_inplace; 734 735 C->assembled = PETSC_TRUE; 736 C->preallocated = PETSC_TRUE; 737 738 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 739 PetscFunctionReturn(0); 740 } 741 742 #undef __FUNCT__ 743 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 744 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 745 { 746 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 747 PetscErrorCode ierr; 748 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 749 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 750 PetscInt bs =A->rmap->bs,bs2 = a->bs2,bslog; 751 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 752 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 753 MatScalar *work; 754 PetscInt *pivots; 755 756 PetscFunctionBegin; 757 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 758 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 759 for (i=0; i<mbs; i++) { 760 jl[i] = mbs; il[0] = 0; 761 } 762 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 763 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 764 765 ai = a->i; aj = a->j; aa = a->a; 766 767 /* flops in while loop */ 768 bslog = 2*bs*bs2; 769 770 /* for each row k */ 771 for (k = 0; k<mbs; k++) { 772 773 /*initialize k-th row with elements nonzero in row k of A */ 774 jmin = ai[k]; jmax = ai[k+1]; 775 ap = aa + jmin*bs2; 776 for (j = jmin; j < jmax; j++) { 777 vj = aj[j]; /* block col. index */ 778 rtmp_ptr = rtmp + vj*bs2; 779 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 780 } 781 782 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 783 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 784 i = jl[k]; /* first row to be added to k_th row */ 785 786 while (i < k) { 787 nexti = jl[i]; /* next row to be added to k_th row */ 788 789 /* compute multiplier */ 790 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 791 792 /* uik = -inv(Di)*U_bar(i,k) */ 793 diag = ba + i*bs2; 794 u = ba + ili*bs2; 795 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 796 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 797 798 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 799 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 800 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 801 802 /* update -U(i,k) */ 803 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 804 805 /* add multiple of row i to k-th row ... */ 806 jmin = ili + 1; jmax = bi[i+1]; 807 if (jmin < jmax) { 808 for (j=jmin; j<jmax; j++) { 809 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 810 rtmp_ptr = rtmp + bj[j]*bs2; 811 u = ba + j*bs2; 812 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 813 } 814 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 815 816 /* ... add i to row list for next nonzero entry */ 817 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 818 j = bj[jmin]; 819 jl[i] = jl[j]; jl[j] = i; /* update jl */ 820 } 821 i = nexti; 822 } 823 824 /* save nonzero entries in k-th row of U ... */ 825 826 /* invert diagonal block */ 827 diag = ba+k*bs2; 828 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 829 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 830 831 jmin = bi[k]; jmax = bi[k+1]; 832 if (jmin < jmax) { 833 for (j=jmin; j<jmax; j++) { 834 vj = bj[j]; /* block col. index of U */ 835 u = ba + j*bs2; 836 rtmp_ptr = rtmp + vj*bs2; 837 for (k1=0; k1<bs2; k1++) { 838 *u++ = *rtmp_ptr; 839 *rtmp_ptr++ = 0.0; 840 } 841 } 842 843 /* ... add k to row list for first nonzero entry in k-th row */ 844 il[k] = jmin; 845 i = bj[jmin]; 846 jl[k] = jl[i]; jl[i] = k; 847 } 848 } 849 850 ierr = PetscFree(rtmp);CHKERRQ(ierr); 851 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 852 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 853 ierr = PetscFree(pivots);CHKERRQ(ierr); 854 855 C->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 856 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 857 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 858 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 859 C->assembled = PETSC_TRUE; 860 C->preallocated = PETSC_TRUE; 861 862 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 863 PetscFunctionReturn(0); 864 } 865 866 /* 867 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 868 Version for blocks 2 by 2. 869 */ 870 #undef __FUNCT__ 871 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 872 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info) 873 { 874 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 875 IS perm = b->row; 876 PetscErrorCode ierr; 877 const PetscInt *ai,*aj,*perm_ptr; 878 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 879 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 880 MatScalar *ba = b->a,*aa,*ap; 881 MatScalar *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4]; 882 PetscReal shift = info->shiftamount; 883 884 PetscFunctionBegin; 885 /* initialization */ 886 /* il and jl record the first nonzero element in each row of the accessing 887 window U(0:k, k:mbs-1). 888 jl: list of rows to be added to uneliminated rows 889 i>= k: jl(i) is the first row to be added to row i 890 i< k: jl(i) is the row following row i in some list of rows 891 jl(i) = mbs indicates the end of a list 892 il(i): points to the first nonzero element in columns k,...,mbs-1 of 893 row i of U */ 894 ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr); 895 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 896 for (i=0; i<mbs; i++) { 897 jl[i] = mbs; il[0] = 0; 898 } 899 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 900 901 /* check permutation */ 902 if (!a->permute) { 903 ai = a->i; aj = a->j; aa = a->a; 904 } else { 905 ai = a->inew; aj = a->jnew; 906 ierr = PetscMalloc1(4*ai[mbs],&aa);CHKERRQ(ierr); 907 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 908 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 909 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 910 911 for (i=0; i<mbs; i++) { 912 jmin = ai[i]; jmax = ai[i+1]; 913 for (j=jmin; j<jmax; j++) { 914 while (a2anew[j] != j) { 915 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 916 for (k1=0; k1<4; k1++) { 917 dk[k1] = aa[k*4+k1]; 918 aa[k*4+k1] = aa[j*4+k1]; 919 aa[j*4+k1] = dk[k1]; 920 } 921 } 922 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 923 if (i > aj[j]) { 924 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 925 ap = aa + j*4; /* ptr to the beginning of the block */ 926 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 927 ap[1] = ap[2]; 928 ap[2] = dk[1]; 929 } 930 } 931 } 932 ierr = PetscFree(a2anew);CHKERRQ(ierr); 933 } 934 935 /* for each row k */ 936 for (k = 0; k<mbs; k++) { 937 938 /*initialize k-th row with elements nonzero in row perm(k) of A */ 939 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 940 ap = aa + jmin*4; 941 for (j = jmin; j < jmax; j++) { 942 vj = perm_ptr[aj[j]]; /* block col. index */ 943 rtmp_ptr = rtmp + vj*4; 944 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 945 } 946 947 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 948 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 949 i = jl[k]; /* first row to be added to k_th row */ 950 951 while (i < k) { 952 nexti = jl[i]; /* next row to be added to k_th row */ 953 954 /* compute multiplier */ 955 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 956 957 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 958 diag = ba + i*4; 959 u = ba + ili*4; 960 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 961 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 962 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 963 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 964 965 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 966 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 967 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 968 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 969 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 970 971 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 972 973 /* update -U(i,k): ba[ili] = uik */ 974 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 975 976 /* add multiple of row i to k-th row ... */ 977 jmin = ili + 1; jmax = bi[i+1]; 978 if (jmin < jmax) { 979 for (j=jmin; j<jmax; j++) { 980 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 981 rtmp_ptr = rtmp + bj[j]*4; 982 u = ba + j*4; 983 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 984 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 985 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 986 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 987 } 988 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 989 990 /* ... add i to row list for next nonzero entry */ 991 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 992 j = bj[jmin]; 993 jl[i] = jl[j]; jl[j] = i; /* update jl */ 994 } 995 i = nexti; 996 } 997 998 /* save nonzero entries in k-th row of U ... */ 999 1000 /* invert diagonal block */ 1001 diag = ba+k*4; 1002 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1003 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1004 1005 jmin = bi[k]; jmax = bi[k+1]; 1006 if (jmin < jmax) { 1007 for (j=jmin; j<jmax; j++) { 1008 vj = bj[j]; /* block col. index of U */ 1009 u = ba + j*4; 1010 rtmp_ptr = rtmp + vj*4; 1011 for (k1=0; k1<4; k1++) { 1012 *u++ = *rtmp_ptr; 1013 *rtmp_ptr++ = 0.0; 1014 } 1015 } 1016 1017 /* ... add k to row list for first nonzero entry in k-th row */ 1018 il[k] = jmin; 1019 i = bj[jmin]; 1020 jl[k] = jl[i]; jl[i] = k; 1021 } 1022 } 1023 1024 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1025 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1026 if (a->permute) { 1027 ierr = PetscFree(aa);CHKERRQ(ierr); 1028 } 1029 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 1030 1031 C->ops->solve = MatSolve_SeqSBAIJ_2_inplace; 1032 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace; 1033 C->assembled = PETSC_TRUE; 1034 C->preallocated = PETSC_TRUE; 1035 1036 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1037 PetscFunctionReturn(0); 1038 } 1039 1040 /* 1041 Version for when blocks are 2 by 2 Using natural ordering 1042 */ 1043 #undef __FUNCT__ 1044 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 1045 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 1046 { 1047 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 1048 PetscErrorCode ierr; 1049 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1050 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1051 MatScalar *ba = b->a,*aa,*ap,dk[8],uik[8]; 1052 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1053 PetscReal shift = info->shiftamount; 1054 1055 PetscFunctionBegin; 1056 /* initialization */ 1057 /* il and jl record the first nonzero element in each row of the accessing 1058 window U(0:k, k:mbs-1). 1059 jl: list of rows to be added to uneliminated rows 1060 i>= k: jl(i) is the first row to be added to row i 1061 i< k: jl(i) is the row following row i in some list of rows 1062 jl(i) = mbs indicates the end of a list 1063 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1064 row i of U */ 1065 ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr); 1066 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 1067 for (i=0; i<mbs; i++) { 1068 jl[i] = mbs; il[0] = 0; 1069 } 1070 ai = a->i; aj = a->j; aa = a->a; 1071 1072 /* for each row k */ 1073 for (k = 0; k<mbs; k++) { 1074 1075 /*initialize k-th row with elements nonzero in row k of A */ 1076 jmin = ai[k]; jmax = ai[k+1]; 1077 ap = aa + jmin*4; 1078 for (j = jmin; j < jmax; j++) { 1079 vj = aj[j]; /* block col. index */ 1080 rtmp_ptr = rtmp + vj*4; 1081 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1082 } 1083 1084 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1085 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1086 i = jl[k]; /* first row to be added to k_th row */ 1087 1088 while (i < k) { 1089 nexti = jl[i]; /* next row to be added to k_th row */ 1090 1091 /* compute multiplier */ 1092 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1093 1094 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1095 diag = ba + i*4; 1096 u = ba + ili*4; 1097 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1098 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1099 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1100 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1101 1102 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1103 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1104 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1105 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1106 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1107 1108 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 1109 1110 /* update -U(i,k): ba[ili] = uik */ 1111 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1112 1113 /* add multiple of row i to k-th row ... */ 1114 jmin = ili + 1; jmax = bi[i+1]; 1115 if (jmin < jmax) { 1116 for (j=jmin; j<jmax; j++) { 1117 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1118 rtmp_ptr = rtmp + bj[j]*4; 1119 u = ba + j*4; 1120 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1121 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1122 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1123 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1124 } 1125 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 1126 1127 /* ... add i to row list for next nonzero entry */ 1128 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1129 j = bj[jmin]; 1130 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1131 } 1132 i = nexti; 1133 } 1134 1135 /* save nonzero entries in k-th row of U ... */ 1136 1137 /* invert diagonal block */ 1138 diag = ba+k*4; 1139 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1140 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1141 1142 jmin = bi[k]; jmax = bi[k+1]; 1143 if (jmin < jmax) { 1144 for (j=jmin; j<jmax; j++) { 1145 vj = bj[j]; /* block col. index of U */ 1146 u = ba + j*4; 1147 rtmp_ptr = rtmp + vj*4; 1148 for (k1=0; k1<4; k1++) { 1149 *u++ = *rtmp_ptr; 1150 *rtmp_ptr++ = 0.0; 1151 } 1152 } 1153 1154 /* ... add k to row list for first nonzero entry in k-th row */ 1155 il[k] = jmin; 1156 i = bj[jmin]; 1157 jl[k] = jl[i]; jl[i] = k; 1158 } 1159 } 1160 1161 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1162 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1163 1164 C->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1165 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1166 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1167 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1168 C->assembled = PETSC_TRUE; 1169 C->preallocated = PETSC_TRUE; 1170 1171 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1172 PetscFunctionReturn(0); 1173 } 1174 1175 /* 1176 Numeric U^T*D*U factorization for SBAIJ format. 1177 Version for blocks are 1 by 1. 1178 */ 1179 #undef __FUNCT__ 1180 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace" 1181 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 1182 { 1183 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1184 IS ip=b->row; 1185 PetscErrorCode ierr; 1186 const PetscInt *ai,*aj,*rip; 1187 PetscInt *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1188 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1189 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1190 PetscReal rs; 1191 FactorShiftCtx sctx; 1192 1193 PetscFunctionBegin; 1194 /* MatPivotSetUp(): initialize shift context sctx */ 1195 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1196 1197 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1198 if (!a->permute) { 1199 ai = a->i; aj = a->j; aa = a->a; 1200 } else { 1201 ai = a->inew; aj = a->jnew; 1202 nz = ai[mbs]; 1203 ierr = PetscMalloc1(nz,&aa);CHKERRQ(ierr); 1204 a2anew = a->a2anew; 1205 bval = a->a; 1206 for (j=0; j<nz; j++) { 1207 aa[a2anew[j]] = *(bval++); 1208 } 1209 } 1210 1211 /* initialization */ 1212 /* il and jl record the first nonzero element in each row of the accessing 1213 window U(0:k, k:mbs-1). 1214 jl: list of rows to be added to uneliminated rows 1215 i>= k: jl(i) is the first row to be added to row i 1216 i< k: jl(i) is the row following row i in some list of rows 1217 jl(i) = mbs indicates the end of a list 1218 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1219 row i of U */ 1220 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&jl);CHKERRQ(ierr); 1221 1222 do { 1223 sctx.newshift = PETSC_FALSE; 1224 for (i=0; i<mbs; i++) { 1225 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1226 } 1227 1228 for (k = 0; k<mbs; k++) { 1229 /*initialize k-th row by the perm[k]-th row of A */ 1230 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1231 bval = ba + bi[k]; 1232 for (j = jmin; j < jmax; j++) { 1233 col = rip[aj[j]]; 1234 rtmp[col] = aa[j]; 1235 *bval++ = 0.0; /* for in-place factorization */ 1236 } 1237 1238 /* shift the diagonal of the matrix */ 1239 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1240 1241 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1242 dk = rtmp[k]; 1243 i = jl[k]; /* first row to be added to k_th row */ 1244 1245 while (i < k) { 1246 nexti = jl[i]; /* next row to be added to k_th row */ 1247 1248 /* compute multiplier, update diag(k) and U(i,k) */ 1249 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1250 uikdi = -ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1251 dk += uikdi*ba[ili]; 1252 ba[ili] = uikdi; /* -U(i,k) */ 1253 1254 /* add multiple of row i to k-th row */ 1255 jmin = ili + 1; jmax = bi[i+1]; 1256 if (jmin < jmax) { 1257 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1258 ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr); 1259 1260 /* update il and jl for row i */ 1261 il[i] = jmin; 1262 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1263 } 1264 i = nexti; 1265 } 1266 1267 /* shift the diagonals when zero pivot is detected */ 1268 /* compute rs=sum of abs(off-diagonal) */ 1269 rs = 0.0; 1270 jmin = bi[k]+1; 1271 nz = bi[k+1] - jmin; 1272 if (nz) { 1273 bcol = bj + jmin; 1274 while (nz--) { 1275 rs += PetscAbsScalar(rtmp[*bcol]); 1276 bcol++; 1277 } 1278 } 1279 1280 sctx.rs = rs; 1281 sctx.pv = dk; 1282 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1283 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1284 dk = sctx.pv; 1285 1286 /* copy data into U(k,:) */ 1287 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1288 jmin = bi[k]+1; jmax = bi[k+1]; 1289 if (jmin < jmax) { 1290 for (j=jmin; j<jmax; j++) { 1291 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1292 } 1293 /* add the k-th row into il and jl */ 1294 il[k] = jmin; 1295 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1296 } 1297 } 1298 } while (sctx.newshift); 1299 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 1300 if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);} 1301 1302 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1303 1304 C->ops->solve = MatSolve_SeqSBAIJ_1_inplace; 1305 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1306 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace; 1307 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace; 1308 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace; 1309 C->assembled = PETSC_TRUE; 1310 C->preallocated = PETSC_TRUE; 1311 1312 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1313 if (sctx.nshift) { 1314 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1315 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1316 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1317 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1318 } 1319 } 1320 PetscFunctionReturn(0); 1321 } 1322 1323 /* 1324 Version for when blocks are 1 by 1 Using natural ordering under new datastructure 1325 Modified from MatCholeskyFactorNumeric_SeqAIJ() 1326 */ 1327 #undef __FUNCT__ 1328 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1329 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 1330 { 1331 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 1332 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)B->data; 1333 PetscErrorCode ierr; 1334 PetscInt i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp; 1335 PetscInt *ai=a->i,*aj=a->j,*ajtmp; 1336 PetscInt k,jmin,jmax,*c2r,*il,col,nexti,ili,nz; 1337 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 1338 FactorShiftCtx sctx; 1339 PetscReal rs; 1340 MatScalar d,*v; 1341 1342 PetscFunctionBegin; 1343 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&c2r);CHKERRQ(ierr); 1344 1345 /* MatPivotSetUp(): initialize shift context sctx */ 1346 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1347 1348 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */ 1349 sctx.shift_top = info->zeropivot; 1350 1351 ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr); 1352 1353 for (i=0; i<mbs; i++) { 1354 /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */ 1355 d = (aa)[a->diag[i]]; 1356 rtmp[i] += -PetscRealPart(d); /* diagonal entry */ 1357 ajtmp = aj + ai[i] + 1; /* exclude diagonal */ 1358 v = aa + ai[i] + 1; 1359 nz = ai[i+1] - ai[i] - 1; 1360 for (j=0; j<nz; j++) { 1361 rtmp[i] += PetscAbsScalar(v[j]); 1362 rtmp[ajtmp[j]] += PetscAbsScalar(v[j]); 1363 } 1364 if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]); 1365 } 1366 sctx.shift_top *= 1.1; 1367 sctx.nshift_max = 5; 1368 sctx.shift_lo = 0.; 1369 sctx.shift_hi = 1.; 1370 } 1371 1372 /* allocate working arrays 1373 c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col 1374 il: for active k row, il[i] gives the index of the 1st nonzero entry in U[i,k:n-1] in bj and ba arrays 1375 */ 1376 do { 1377 sctx.newshift = PETSC_FALSE; 1378 1379 for (i=0; i<mbs; i++) c2r[i] = mbs; 1380 if (mbs) il[0] = 0; 1381 1382 for (k = 0; k<mbs; k++) { 1383 /* zero rtmp */ 1384 nz = bi[k+1] - bi[k]; 1385 bjtmp = bj + bi[k]; 1386 for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0; 1387 1388 /* load in initial unfactored row */ 1389 bval = ba + bi[k]; 1390 jmin = ai[k]; jmax = ai[k+1]; 1391 for (j = jmin; j < jmax; j++) { 1392 col = aj[j]; 1393 rtmp[col] = aa[j]; 1394 *bval++ = 0.0; /* for in-place factorization */ 1395 } 1396 /* shift the diagonal of the matrix: ZeropivotApply() */ 1397 rtmp[k] += sctx.shift_amount; /* shift the diagonal of the matrix */ 1398 1399 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1400 dk = rtmp[k]; 1401 i = c2r[k]; /* first row to be added to k_th row */ 1402 1403 while (i < k) { 1404 nexti = c2r[i]; /* next row to be added to k_th row */ 1405 1406 /* compute multiplier, update diag(k) and U(i,k) */ 1407 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1408 uikdi = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */ 1409 dk += uikdi*ba[ili]; /* update diag[k] */ 1410 ba[ili] = uikdi; /* -U(i,k) */ 1411 1412 /* add multiple of row i to k-th row */ 1413 jmin = ili + 1; jmax = bi[i+1]; 1414 if (jmin < jmax) { 1415 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1416 /* update il and c2r for row i */ 1417 il[i] = jmin; 1418 j = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i; 1419 } 1420 i = nexti; 1421 } 1422 1423 /* copy data into U(k,:) */ 1424 rs = 0.0; 1425 jmin = bi[k]; jmax = bi[k+1]-1; 1426 if (jmin < jmax) { 1427 for (j=jmin; j<jmax; j++) { 1428 col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]); 1429 } 1430 /* add the k-th row into il and c2r */ 1431 il[k] = jmin; 1432 i = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k; 1433 } 1434 1435 sctx.rs = rs; 1436 sctx.pv = dk; 1437 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1438 if (sctx.newshift) break; 1439 dk = sctx.pv; 1440 1441 ba[bdiag[k]] = 1.0/dk; /* U(k,k) */ 1442 } 1443 } while (sctx.newshift); 1444 1445 ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr); 1446 1447 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1448 B->ops->solves = MatSolves_SeqSBAIJ_1; 1449 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1450 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 1451 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 1452 1453 B->assembled = PETSC_TRUE; 1454 B->preallocated = PETSC_TRUE; 1455 1456 ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr); 1457 1458 /* MatPivotView() */ 1459 if (sctx.nshift) { 1460 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1461 ierr = PetscInfo4(A,"number of shift_pd tries %D, shift_amount %g, diagonal shifted up by %e fraction top_value %e\n",sctx.nshift,(double)sctx.shift_amount,(double)sctx.shift_fraction,(double)sctx.shift_top);CHKERRQ(ierr); 1462 } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1463 ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1464 } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) { 1465 ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %g\n",sctx.nshift,(double)info->shiftamount);CHKERRQ(ierr); 1466 } 1467 } 1468 PetscFunctionReturn(0); 1469 } 1470 1471 #undef __FUNCT__ 1472 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace" 1473 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 1474 { 1475 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1476 PetscErrorCode ierr; 1477 PetscInt i,j,mbs = a->mbs; 1478 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1479 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1480 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1481 PetscReal rs; 1482 FactorShiftCtx sctx; 1483 1484 PetscFunctionBegin; 1485 /* MatPivotSetUp(): initialize shift context sctx */ 1486 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1487 1488 /* initialization */ 1489 /* il and jl record the first nonzero element in each row of the accessing 1490 window U(0:k, k:mbs-1). 1491 jl: list of rows to be added to uneliminated rows 1492 i>= k: jl(i) is the first row to be added to row i 1493 i< k: jl(i) is the row following row i in some list of rows 1494 jl(i) = mbs indicates the end of a list 1495 il(i): points to the first nonzero element in U(i,k:mbs-1) 1496 */ 1497 ierr = PetscMalloc1(mbs,&rtmp);CHKERRQ(ierr); 1498 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 1499 1500 do { 1501 sctx.newshift = PETSC_FALSE; 1502 for (i=0; i<mbs; i++) { 1503 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1504 } 1505 1506 for (k = 0; k<mbs; k++) { 1507 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1508 nz = ai[k+1] - ai[k]; 1509 acol = aj + ai[k]; 1510 aval = aa + ai[k]; 1511 bval = ba + bi[k]; 1512 while (nz--) { 1513 rtmp[*acol++] = *aval++; 1514 *bval++ = 0.0; /* for in-place factorization */ 1515 } 1516 1517 /* shift the diagonal of the matrix */ 1518 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1519 1520 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1521 dk = rtmp[k]; 1522 i = jl[k]; /* first row to be added to k_th row */ 1523 1524 while (i < k) { 1525 nexti = jl[i]; /* next row to be added to k_th row */ 1526 /* compute multiplier, update D(k) and U(i,k) */ 1527 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1528 uikdi = -ba[ili]*ba[bi[i]]; 1529 dk += uikdi*ba[ili]; 1530 ba[ili] = uikdi; /* -U(i,k) */ 1531 1532 /* add multiple of row i to k-th row ... */ 1533 jmin = ili + 1; 1534 nz = bi[i+1] - jmin; 1535 if (nz > 0) { 1536 bcol = bj + jmin; 1537 bval = ba + jmin; 1538 ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr); 1539 while (nz--) rtmp[*bcol++] += uikdi*(*bval++); 1540 1541 /* update il and jl for i-th row */ 1542 il[i] = jmin; 1543 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1544 } 1545 i = nexti; 1546 } 1547 1548 /* shift the diagonals when zero pivot is detected */ 1549 /* compute rs=sum of abs(off-diagonal) */ 1550 rs = 0.0; 1551 jmin = bi[k]+1; 1552 nz = bi[k+1] - jmin; 1553 if (nz) { 1554 bcol = bj + jmin; 1555 while (nz--) { 1556 rs += PetscAbsScalar(rtmp[*bcol]); 1557 bcol++; 1558 } 1559 } 1560 1561 sctx.rs = rs; 1562 sctx.pv = dk; 1563 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1564 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1565 dk = sctx.pv; 1566 1567 /* copy data into U(k,:) */ 1568 ba[bi[k]] = 1.0/dk; 1569 jmin = bi[k]+1; 1570 nz = bi[k+1] - jmin; 1571 if (nz) { 1572 bcol = bj + jmin; 1573 bval = ba + jmin; 1574 while (nz--) { 1575 *bval++ = rtmp[*bcol]; 1576 rtmp[*bcol++] = 0.0; 1577 } 1578 /* add k-th row into il and jl */ 1579 il[k] = jmin; 1580 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1581 } 1582 } /* end of for (k = 0; k<mbs; k++) */ 1583 } while (sctx.newshift); 1584 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1585 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1586 1587 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1588 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1589 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1590 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1591 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1592 1593 C->assembled = PETSC_TRUE; 1594 C->preallocated = PETSC_TRUE; 1595 1596 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1597 if (sctx.nshift) { 1598 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1599 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1600 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1601 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1602 } 1603 } 1604 PetscFunctionReturn(0); 1605 } 1606 1607 #undef __FUNCT__ 1608 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1609 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info) 1610 { 1611 PetscErrorCode ierr; 1612 Mat C; 1613 1614 PetscFunctionBegin; 1615 ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr); 1616 ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr); 1617 ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr); 1618 1619 A->ops->solve = C->ops->solve; 1620 A->ops->solvetranspose = C->ops->solvetranspose; 1621 1622 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1623 PetscFunctionReturn(0); 1624 } 1625 1626 1627