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 /* There are bugs for reordeing. Needs further work. 430 MatReordering for sbaij cannot be efficient. User should use aij formt! */ 431 a->permute = PETSC_TRUE; 432 433 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 434 ai = a->inew; aj = a->jnew; 435 } 436 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 437 438 /* initialization */ 439 ierr = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr); 440 ui[0] = 0; 441 442 /* jl: linked list for storing indices of the pivot rows 443 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 444 ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr); 445 for (i=0; i<mbs; i++) { 446 jl[i] = mbs; il[i] = 0; 447 } 448 449 /* create and initialize a linked list for storing column indices of the active row k */ 450 nlnk = mbs + 1; 451 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 452 453 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 454 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 455 current_space = free_space; 456 457 for (k=0; k<mbs; k++) { /* for each active row k */ 458 /* initialize lnk by the column indices of row rip[k] of A */ 459 nzk = 0; 460 ncols = ai[rip[k]+1] - ai[rip[k]]; 461 for (j=0; j<ncols; j++) { 462 i = *(aj + ai[rip[k]] + j); 463 cols[j] = rip[i]; 464 } 465 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 466 nzk += nlnk; 467 468 /* update lnk by computing fill-in for each pivot row to be merged in */ 469 prow = jl[k]; /* 1st pivot row */ 470 471 while (prow < k) { 472 nextprow = jl[prow]; 473 /* merge prow into k-th row */ 474 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 475 jmax = ui[prow+1]; 476 ncols = jmax-jmin; 477 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 478 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 479 nzk += nlnk; 480 481 /* update il and jl for prow */ 482 if (jmin < jmax) { 483 il[prow] = jmin; 484 485 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 486 } 487 prow = nextprow; 488 } 489 490 /* if free space is not available, make more free space */ 491 if (current_space->local_remaining<nzk) { 492 i = mbs - k + 1; /* num of unfactored rows */ 493 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 494 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 495 reallocs++; 496 } 497 498 /* copy data into free space, then initialize lnk */ 499 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 500 501 /* add the k-th row into il and jl */ 502 if (nzk-1 > 0) { 503 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 504 jl[k] = jl[i]; jl[i] = k; 505 il[k] = ui[k] + 1; 506 } 507 ui_ptr[k] = current_space->array; 508 509 current_space->array += nzk; 510 current_space->local_used += nzk; 511 current_space->local_remaining -= nzk; 512 513 ui[k+1] = ui[k] + nzk; 514 } 515 516 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 517 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 518 519 /* destroy list of free space and other temporary array(s) */ 520 ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr); 521 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 522 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 523 524 /* put together the new matrix in MATSEQSBAIJ format */ 525 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 526 527 b = (Mat_SeqSBAIJ*)fact->data; 528 b->singlemalloc = PETSC_FALSE; 529 b->free_a = PETSC_TRUE; 530 b->free_ij = PETSC_TRUE; 531 532 ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr); 533 534 b->j = uj; 535 b->i = ui; 536 b->diag = 0; 537 b->ilen = 0; 538 b->imax = 0; 539 b->row = perm; 540 541 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 542 543 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 544 b->icol = perm; 545 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 546 ierr = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr); 547 ierr = PetscLogObjectMemory((PetscObject)fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 548 b->maxnz = b->nz = ui[mbs]; 549 550 fact->info.factor_mallocs = reallocs; 551 fact->info.fill_ratio_given = fill; 552 if (ai[mbs] != 0) { 553 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 554 } else { 555 fact->info.fill_ratio_needed = 0.0; 556 } 557 #if defined(PETSC_USE_INFO) 558 if (ai[mbs] != 0) { 559 PetscReal af = fact->info.fill_ratio_needed; 560 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr); 561 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 562 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr); 563 } else { 564 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 565 } 566 #endif 567 ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr); 568 PetscFunctionReturn(0); 569 } 570 571 #undef __FUNCT__ 572 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 573 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info) 574 { 575 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 576 IS perm = b->row; 577 PetscErrorCode ierr; 578 const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j; 579 PetscInt i,j; 580 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 581 PetscInt bs =A->rmap->bs,bs2 = a->bs2,bslog = 0; 582 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 583 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 584 MatScalar *work; 585 PetscInt *pivots; 586 587 PetscFunctionBegin; 588 /* initialization */ 589 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 590 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 591 for (i=0; i<mbs; i++) { 592 jl[i] = mbs; il[0] = 0; 593 } 594 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 595 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 596 597 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 598 599 /* check permutation */ 600 if (!a->permute) { 601 ai = a->i; aj = a->j; aa = a->a; 602 } else { 603 ai = a->inew; aj = a->jnew; 604 ierr = PetscMalloc1(bs2*ai[mbs],&aa);CHKERRQ(ierr); 605 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 606 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 607 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 608 609 /* flops in while loop */ 610 bslog = 2*bs*bs2; 611 612 for (i=0; i<mbs; i++) { 613 jmin = ai[i]; jmax = ai[i+1]; 614 for (j=jmin; j<jmax; j++) { 615 while (a2anew[j] != j) { 616 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 617 for (k1=0; k1<bs2; k1++) { 618 dk[k1] = aa[k*bs2+k1]; 619 aa[k*bs2+k1] = aa[j*bs2+k1]; 620 aa[j*bs2+k1] = dk[k1]; 621 } 622 } 623 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 624 if (i > aj[j]) { 625 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 626 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 627 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 628 for (k=0; k<bs; k++) { /* j-th block of aa <- dk^T */ 629 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 630 } 631 } 632 } 633 } 634 ierr = PetscFree(a2anew);CHKERRQ(ierr); 635 } 636 637 /* for each row k */ 638 for (k = 0; k<mbs; k++) { 639 640 /*initialize k-th row with elements nonzero in row perm(k) of A */ 641 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 642 643 ap = aa + jmin*bs2; 644 for (j = jmin; j < jmax; j++) { 645 vj = perm_ptr[aj[j]]; /* block col. index */ 646 rtmp_ptr = rtmp + vj*bs2; 647 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 648 } 649 650 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 651 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 652 i = jl[k]; /* first row to be added to k_th row */ 653 654 while (i < k) { 655 nexti = jl[i]; /* next row to be added to k_th row */ 656 657 /* compute multiplier */ 658 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 659 660 /* uik = -inv(Di)*U_bar(i,k) */ 661 diag = ba + i*bs2; 662 u = ba + ili*bs2; 663 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 664 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 665 666 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 667 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 668 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 669 670 /* update -U(i,k) */ 671 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 672 673 /* add multiple of row i to k-th row ... */ 674 jmin = ili + 1; jmax = bi[i+1]; 675 if (jmin < jmax) { 676 for (j=jmin; j<jmax; j++) { 677 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 678 rtmp_ptr = rtmp + bj[j]*bs2; 679 u = ba + j*bs2; 680 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 681 } 682 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 683 684 /* ... add i to row list for next nonzero entry */ 685 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 686 j = bj[jmin]; 687 jl[i] = jl[j]; jl[j] = i; /* update jl */ 688 } 689 i = nexti; 690 } 691 692 /* save nonzero entries in k-th row of U ... */ 693 694 /* invert diagonal block */ 695 diag = ba+k*bs2; 696 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 697 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 698 699 jmin = bi[k]; jmax = bi[k+1]; 700 if (jmin < jmax) { 701 for (j=jmin; j<jmax; j++) { 702 vj = bj[j]; /* block col. index of U */ 703 u = ba + j*bs2; 704 rtmp_ptr = rtmp + vj*bs2; 705 for (k1=0; k1<bs2; k1++) { 706 *u++ = *rtmp_ptr; 707 *rtmp_ptr++ = 0.0; 708 } 709 } 710 711 /* ... add k to row list for first nonzero entry in k-th row */ 712 il[k] = jmin; 713 i = bj[jmin]; 714 jl[k] = jl[i]; jl[i] = k; 715 } 716 } 717 718 ierr = PetscFree(rtmp);CHKERRQ(ierr); 719 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 720 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 721 ierr = PetscFree(pivots);CHKERRQ(ierr); 722 if (a->permute) { 723 ierr = PetscFree(aa);CHKERRQ(ierr); 724 } 725 726 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 727 728 C->ops->solve = MatSolve_SeqSBAIJ_N_inplace; 729 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace; 730 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_inplace; 731 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_inplace; 732 733 C->assembled = PETSC_TRUE; 734 C->preallocated = PETSC_TRUE; 735 736 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 737 PetscFunctionReturn(0); 738 } 739 740 #undef __FUNCT__ 741 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 742 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 743 { 744 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 745 PetscErrorCode ierr; 746 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 747 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 748 PetscInt bs =A->rmap->bs,bs2 = a->bs2,bslog; 749 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 750 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 751 MatScalar *work; 752 PetscInt *pivots; 753 754 PetscFunctionBegin; 755 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 756 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 757 for (i=0; i<mbs; i++) { 758 jl[i] = mbs; il[0] = 0; 759 } 760 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 761 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 762 763 ai = a->i; aj = a->j; aa = a->a; 764 765 /* flops in while loop */ 766 bslog = 2*bs*bs2; 767 768 /* for each row k */ 769 for (k = 0; k<mbs; k++) { 770 771 /*initialize k-th row with elements nonzero in row k of A */ 772 jmin = ai[k]; jmax = ai[k+1]; 773 ap = aa + jmin*bs2; 774 for (j = jmin; j < jmax; j++) { 775 vj = aj[j]; /* block col. index */ 776 rtmp_ptr = rtmp + vj*bs2; 777 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 778 } 779 780 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 781 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 782 i = jl[k]; /* first row to be added to k_th row */ 783 784 while (i < k) { 785 nexti = jl[i]; /* next row to be added to k_th row */ 786 787 /* compute multiplier */ 788 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 789 790 /* uik = -inv(Di)*U_bar(i,k) */ 791 diag = ba + i*bs2; 792 u = ba + ili*bs2; 793 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 794 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 795 796 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 797 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 798 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 799 800 /* update -U(i,k) */ 801 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 802 803 /* add multiple of row i to k-th row ... */ 804 jmin = ili + 1; jmax = bi[i+1]; 805 if (jmin < jmax) { 806 for (j=jmin; j<jmax; j++) { 807 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 808 rtmp_ptr = rtmp + bj[j]*bs2; 809 u = ba + j*bs2; 810 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 811 } 812 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 813 814 /* ... add i to row list for next nonzero entry */ 815 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 816 j = bj[jmin]; 817 jl[i] = jl[j]; jl[j] = i; /* update jl */ 818 } 819 i = nexti; 820 } 821 822 /* save nonzero entries in k-th row of U ... */ 823 824 /* invert diagonal block */ 825 diag = ba+k*bs2; 826 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 827 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 828 829 jmin = bi[k]; jmax = bi[k+1]; 830 if (jmin < jmax) { 831 for (j=jmin; j<jmax; j++) { 832 vj = bj[j]; /* block col. index of U */ 833 u = ba + j*bs2; 834 rtmp_ptr = rtmp + vj*bs2; 835 for (k1=0; k1<bs2; k1++) { 836 *u++ = *rtmp_ptr; 837 *rtmp_ptr++ = 0.0; 838 } 839 } 840 841 /* ... add k to row list for first nonzero entry in k-th row */ 842 il[k] = jmin; 843 i = bj[jmin]; 844 jl[k] = jl[i]; jl[i] = k; 845 } 846 } 847 848 ierr = PetscFree(rtmp);CHKERRQ(ierr); 849 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 850 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 851 ierr = PetscFree(pivots);CHKERRQ(ierr); 852 853 C->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 854 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 855 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 856 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 857 C->assembled = PETSC_TRUE; 858 C->preallocated = PETSC_TRUE; 859 860 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 861 PetscFunctionReturn(0); 862 } 863 864 /* 865 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 866 Version for blocks 2 by 2. 867 */ 868 #undef __FUNCT__ 869 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 870 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info) 871 { 872 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 873 IS perm = b->row; 874 PetscErrorCode ierr; 875 const PetscInt *ai,*aj,*perm_ptr; 876 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 877 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 878 MatScalar *ba = b->a,*aa,*ap; 879 MatScalar *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4]; 880 PetscReal shift = info->shiftamount; 881 882 PetscFunctionBegin; 883 /* initialization */ 884 /* il and jl record the first nonzero element in each row of the accessing 885 window U(0:k, k:mbs-1). 886 jl: list of rows to be added to uneliminated rows 887 i>= k: jl(i) is the first row to be added to row i 888 i< k: jl(i) is the row following row i in some list of rows 889 jl(i) = mbs indicates the end of a list 890 il(i): points to the first nonzero element in columns k,...,mbs-1 of 891 row i of U */ 892 ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr); 893 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 894 for (i=0; i<mbs; i++) { 895 jl[i] = mbs; il[0] = 0; 896 } 897 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 898 899 /* check permutation */ 900 if (!a->permute) { 901 ai = a->i; aj = a->j; aa = a->a; 902 } else { 903 ai = a->inew; aj = a->jnew; 904 ierr = PetscMalloc1(4*ai[mbs],&aa);CHKERRQ(ierr); 905 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 906 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 907 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 908 909 for (i=0; i<mbs; i++) { 910 jmin = ai[i]; jmax = ai[i+1]; 911 for (j=jmin; j<jmax; j++) { 912 while (a2anew[j] != j) { 913 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 914 for (k1=0; k1<4; k1++) { 915 dk[k1] = aa[k*4+k1]; 916 aa[k*4+k1] = aa[j*4+k1]; 917 aa[j*4+k1] = dk[k1]; 918 } 919 } 920 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 921 if (i > aj[j]) { 922 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 923 ap = aa + j*4; /* ptr to the beginning of the block */ 924 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 925 ap[1] = ap[2]; 926 ap[2] = dk[1]; 927 } 928 } 929 } 930 ierr = PetscFree(a2anew);CHKERRQ(ierr); 931 } 932 933 /* for each row k */ 934 for (k = 0; k<mbs; k++) { 935 936 /*initialize k-th row with elements nonzero in row perm(k) of A */ 937 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 938 ap = aa + jmin*4; 939 for (j = jmin; j < jmax; j++) { 940 vj = perm_ptr[aj[j]]; /* block col. index */ 941 rtmp_ptr = rtmp + vj*4; 942 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 943 } 944 945 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 946 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 947 i = jl[k]; /* first row to be added to k_th row */ 948 949 while (i < k) { 950 nexti = jl[i]; /* next row to be added to k_th row */ 951 952 /* compute multiplier */ 953 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 954 955 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 956 diag = ba + i*4; 957 u = ba + ili*4; 958 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 959 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 960 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 961 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 962 963 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 964 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 965 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 966 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 967 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 968 969 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 970 971 /* update -U(i,k): ba[ili] = uik */ 972 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 973 974 /* add multiple of row i to k-th row ... */ 975 jmin = ili + 1; jmax = bi[i+1]; 976 if (jmin < jmax) { 977 for (j=jmin; j<jmax; j++) { 978 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 979 rtmp_ptr = rtmp + bj[j]*4; 980 u = ba + j*4; 981 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 982 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 983 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 984 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 985 } 986 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 987 988 /* ... add i to row list for next nonzero entry */ 989 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 990 j = bj[jmin]; 991 jl[i] = jl[j]; jl[j] = i; /* update jl */ 992 } 993 i = nexti; 994 } 995 996 /* save nonzero entries in k-th row of U ... */ 997 998 /* invert diagonal block */ 999 diag = ba+k*4; 1000 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1001 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1002 1003 jmin = bi[k]; jmax = bi[k+1]; 1004 if (jmin < jmax) { 1005 for (j=jmin; j<jmax; j++) { 1006 vj = bj[j]; /* block col. index of U */ 1007 u = ba + j*4; 1008 rtmp_ptr = rtmp + vj*4; 1009 for (k1=0; k1<4; k1++) { 1010 *u++ = *rtmp_ptr; 1011 *rtmp_ptr++ = 0.0; 1012 } 1013 } 1014 1015 /* ... add k to row list for first nonzero entry in k-th row */ 1016 il[k] = jmin; 1017 i = bj[jmin]; 1018 jl[k] = jl[i]; jl[i] = k; 1019 } 1020 } 1021 1022 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1023 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1024 if (a->permute) { 1025 ierr = PetscFree(aa);CHKERRQ(ierr); 1026 } 1027 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 1028 1029 C->ops->solve = MatSolve_SeqSBAIJ_2_inplace; 1030 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace; 1031 C->assembled = PETSC_TRUE; 1032 C->preallocated = PETSC_TRUE; 1033 1034 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1035 PetscFunctionReturn(0); 1036 } 1037 1038 /* 1039 Version for when blocks are 2 by 2 Using natural ordering 1040 */ 1041 #undef __FUNCT__ 1042 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 1043 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 1044 { 1045 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 1046 PetscErrorCode ierr; 1047 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1048 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1049 MatScalar *ba = b->a,*aa,*ap,dk[8],uik[8]; 1050 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1051 PetscReal shift = info->shiftamount; 1052 1053 PetscFunctionBegin; 1054 /* initialization */ 1055 /* il and jl record the first nonzero element in each row of the accessing 1056 window U(0:k, k:mbs-1). 1057 jl: list of rows to be added to uneliminated rows 1058 i>= k: jl(i) is the first row to be added to row i 1059 i< k: jl(i) is the row following row i in some list of rows 1060 jl(i) = mbs indicates the end of a list 1061 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1062 row i of U */ 1063 ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr); 1064 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 1065 for (i=0; i<mbs; i++) { 1066 jl[i] = mbs; il[0] = 0; 1067 } 1068 ai = a->i; aj = a->j; aa = a->a; 1069 1070 /* for each row k */ 1071 for (k = 0; k<mbs; k++) { 1072 1073 /*initialize k-th row with elements nonzero in row k of A */ 1074 jmin = ai[k]; jmax = ai[k+1]; 1075 ap = aa + jmin*4; 1076 for (j = jmin; j < jmax; j++) { 1077 vj = aj[j]; /* block col. index */ 1078 rtmp_ptr = rtmp + vj*4; 1079 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1080 } 1081 1082 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1083 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1084 i = jl[k]; /* first row to be added to k_th row */ 1085 1086 while (i < k) { 1087 nexti = jl[i]; /* next row to be added to k_th row */ 1088 1089 /* compute multiplier */ 1090 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1091 1092 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1093 diag = ba + i*4; 1094 u = ba + ili*4; 1095 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1096 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1097 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1098 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1099 1100 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1101 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1102 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1103 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1104 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1105 1106 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 1107 1108 /* update -U(i,k): ba[ili] = uik */ 1109 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1110 1111 /* add multiple of row i to k-th row ... */ 1112 jmin = ili + 1; jmax = bi[i+1]; 1113 if (jmin < jmax) { 1114 for (j=jmin; j<jmax; j++) { 1115 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1116 rtmp_ptr = rtmp + bj[j]*4; 1117 u = ba + j*4; 1118 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1119 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1120 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1121 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1122 } 1123 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 1124 1125 /* ... add i to row list for next nonzero entry */ 1126 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1127 j = bj[jmin]; 1128 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1129 } 1130 i = nexti; 1131 } 1132 1133 /* save nonzero entries in k-th row of U ... */ 1134 1135 /* invert diagonal block */ 1136 diag = ba+k*4; 1137 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1138 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1139 1140 jmin = bi[k]; jmax = bi[k+1]; 1141 if (jmin < jmax) { 1142 for (j=jmin; j<jmax; j++) { 1143 vj = bj[j]; /* block col. index of U */ 1144 u = ba + j*4; 1145 rtmp_ptr = rtmp + vj*4; 1146 for (k1=0; k1<4; k1++) { 1147 *u++ = *rtmp_ptr; 1148 *rtmp_ptr++ = 0.0; 1149 } 1150 } 1151 1152 /* ... add k to row list for first nonzero entry in k-th row */ 1153 il[k] = jmin; 1154 i = bj[jmin]; 1155 jl[k] = jl[i]; jl[i] = k; 1156 } 1157 } 1158 1159 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1160 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1161 1162 C->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1163 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1164 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1165 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1166 C->assembled = PETSC_TRUE; 1167 C->preallocated = PETSC_TRUE; 1168 1169 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1170 PetscFunctionReturn(0); 1171 } 1172 1173 /* 1174 Numeric U^T*D*U factorization for SBAIJ format. 1175 Version for blocks are 1 by 1. 1176 */ 1177 #undef __FUNCT__ 1178 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace" 1179 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 1180 { 1181 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1182 IS ip=b->row; 1183 PetscErrorCode ierr; 1184 const PetscInt *ai,*aj,*rip; 1185 PetscInt *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1186 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1187 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1188 PetscReal rs; 1189 FactorShiftCtx sctx; 1190 1191 PetscFunctionBegin; 1192 /* MatPivotSetUp(): initialize shift context sctx */ 1193 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1194 1195 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1196 if (!a->permute) { 1197 ai = a->i; aj = a->j; aa = a->a; 1198 } else { 1199 ai = a->inew; aj = a->jnew; 1200 nz = ai[mbs]; 1201 ierr = PetscMalloc1(nz,&aa);CHKERRQ(ierr); 1202 a2anew = a->a2anew; 1203 bval = a->a; 1204 for (j=0; j<nz; j++) { 1205 aa[a2anew[j]] = *(bval++); 1206 } 1207 } 1208 1209 /* initialization */ 1210 /* il and jl record the first nonzero element in each row of the accessing 1211 window U(0:k, k:mbs-1). 1212 jl: list of rows to be added to uneliminated rows 1213 i>= k: jl(i) is the first row to be added to row i 1214 i< k: jl(i) is the row following row i in some list of rows 1215 jl(i) = mbs indicates the end of a list 1216 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1217 row i of U */ 1218 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&jl);CHKERRQ(ierr); 1219 1220 do { 1221 sctx.newshift = PETSC_FALSE; 1222 for (i=0; i<mbs; i++) { 1223 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1224 } 1225 1226 for (k = 0; k<mbs; k++) { 1227 /*initialize k-th row by the perm[k]-th row of A */ 1228 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1229 bval = ba + bi[k]; 1230 for (j = jmin; j < jmax; j++) { 1231 col = rip[aj[j]]; 1232 rtmp[col] = aa[j]; 1233 *bval++ = 0.0; /* for in-place factorization */ 1234 } 1235 1236 /* shift the diagonal of the matrix */ 1237 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1238 1239 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1240 dk = rtmp[k]; 1241 i = jl[k]; /* first row to be added to k_th row */ 1242 1243 while (i < k) { 1244 nexti = jl[i]; /* next row to be added to k_th row */ 1245 1246 /* compute multiplier, update diag(k) and U(i,k) */ 1247 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1248 uikdi = -ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1249 dk += uikdi*ba[ili]; 1250 ba[ili] = uikdi; /* -U(i,k) */ 1251 1252 /* add multiple of row i to k-th row */ 1253 jmin = ili + 1; jmax = bi[i+1]; 1254 if (jmin < jmax) { 1255 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1256 ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr); 1257 1258 /* update il and jl for row i */ 1259 il[i] = jmin; 1260 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1261 } 1262 i = nexti; 1263 } 1264 1265 /* shift the diagonals when zero pivot is detected */ 1266 /* compute rs=sum of abs(off-diagonal) */ 1267 rs = 0.0; 1268 jmin = bi[k]+1; 1269 nz = bi[k+1] - jmin; 1270 if (nz) { 1271 bcol = bj + jmin; 1272 while (nz--) { 1273 rs += PetscAbsScalar(rtmp[*bcol]); 1274 bcol++; 1275 } 1276 } 1277 1278 sctx.rs = rs; 1279 sctx.pv = dk; 1280 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1281 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1282 dk = sctx.pv; 1283 1284 /* copy data into U(k,:) */ 1285 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1286 jmin = bi[k]+1; jmax = bi[k+1]; 1287 if (jmin < jmax) { 1288 for (j=jmin; j<jmax; j++) { 1289 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1290 } 1291 /* add the k-th row into il and jl */ 1292 il[k] = jmin; 1293 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1294 } 1295 } 1296 } while (sctx.newshift); 1297 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 1298 if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);} 1299 1300 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1301 1302 C->ops->solve = MatSolve_SeqSBAIJ_1_inplace; 1303 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1304 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace; 1305 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace; 1306 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace; 1307 C->assembled = PETSC_TRUE; 1308 C->preallocated = PETSC_TRUE; 1309 1310 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1311 if (sctx.nshift) { 1312 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1313 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1314 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1315 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1316 } 1317 } 1318 PetscFunctionReturn(0); 1319 } 1320 1321 /* 1322 Version for when blocks are 1 by 1 Using natural ordering under new datastructure 1323 Modified from MatCholeskyFactorNumeric_SeqAIJ() 1324 */ 1325 #undef __FUNCT__ 1326 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1327 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 1328 { 1329 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 1330 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)B->data; 1331 PetscErrorCode ierr; 1332 PetscInt i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp; 1333 PetscInt *ai=a->i,*aj=a->j,*ajtmp; 1334 PetscInt k,jmin,jmax,*c2r,*il,col,nexti,ili,nz; 1335 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 1336 FactorShiftCtx sctx; 1337 PetscReal rs; 1338 MatScalar d,*v; 1339 1340 PetscFunctionBegin; 1341 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&c2r);CHKERRQ(ierr); 1342 1343 /* MatPivotSetUp(): initialize shift context sctx */ 1344 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1345 1346 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */ 1347 sctx.shift_top = info->zeropivot; 1348 1349 ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr); 1350 1351 for (i=0; i<mbs; i++) { 1352 /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */ 1353 d = (aa)[a->diag[i]]; 1354 rtmp[i] += -PetscRealPart(d); /* diagonal entry */ 1355 ajtmp = aj + ai[i] + 1; /* exclude diagonal */ 1356 v = aa + ai[i] + 1; 1357 nz = ai[i+1] - ai[i] - 1; 1358 for (j=0; j<nz; j++) { 1359 rtmp[i] += PetscAbsScalar(v[j]); 1360 rtmp[ajtmp[j]] += PetscAbsScalar(v[j]); 1361 } 1362 if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]); 1363 } 1364 sctx.shift_top *= 1.1; 1365 sctx.nshift_max = 5; 1366 sctx.shift_lo = 0.; 1367 sctx.shift_hi = 1.; 1368 } 1369 1370 /* allocate working arrays 1371 c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col 1372 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 1373 */ 1374 do { 1375 sctx.newshift = PETSC_FALSE; 1376 1377 for (i=0; i<mbs; i++) c2r[i] = mbs; 1378 if (mbs) il[0] = 0; 1379 1380 for (k = 0; k<mbs; k++) { 1381 /* zero rtmp */ 1382 nz = bi[k+1] - bi[k]; 1383 bjtmp = bj + bi[k]; 1384 for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0; 1385 1386 /* load in initial unfactored row */ 1387 bval = ba + bi[k]; 1388 jmin = ai[k]; jmax = ai[k+1]; 1389 for (j = jmin; j < jmax; j++) { 1390 col = aj[j]; 1391 rtmp[col] = aa[j]; 1392 *bval++ = 0.0; /* for in-place factorization */ 1393 } 1394 /* shift the diagonal of the matrix: ZeropivotApply() */ 1395 rtmp[k] += sctx.shift_amount; /* shift the diagonal of the matrix */ 1396 1397 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1398 dk = rtmp[k]; 1399 i = c2r[k]; /* first row to be added to k_th row */ 1400 1401 while (i < k) { 1402 nexti = c2r[i]; /* next row to be added to k_th row */ 1403 1404 /* compute multiplier, update diag(k) and U(i,k) */ 1405 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1406 uikdi = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */ 1407 dk += uikdi*ba[ili]; /* update diag[k] */ 1408 ba[ili] = uikdi; /* -U(i,k) */ 1409 1410 /* add multiple of row i to k-th row */ 1411 jmin = ili + 1; jmax = bi[i+1]; 1412 if (jmin < jmax) { 1413 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1414 /* update il and c2r for row i */ 1415 il[i] = jmin; 1416 j = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i; 1417 } 1418 i = nexti; 1419 } 1420 1421 /* copy data into U(k,:) */ 1422 rs = 0.0; 1423 jmin = bi[k]; jmax = bi[k+1]-1; 1424 if (jmin < jmax) { 1425 for (j=jmin; j<jmax; j++) { 1426 col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]); 1427 } 1428 /* add the k-th row into il and c2r */ 1429 il[k] = jmin; 1430 i = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k; 1431 } 1432 1433 sctx.rs = rs; 1434 sctx.pv = dk; 1435 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1436 if (sctx.newshift) break; 1437 dk = sctx.pv; 1438 1439 ba[bdiag[k]] = 1.0/dk; /* U(k,k) */ 1440 } 1441 } while (sctx.newshift); 1442 1443 ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr); 1444 1445 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1446 B->ops->solves = MatSolves_SeqSBAIJ_1; 1447 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1448 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 1449 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 1450 1451 B->assembled = PETSC_TRUE; 1452 B->preallocated = PETSC_TRUE; 1453 1454 ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr); 1455 1456 /* MatPivotView() */ 1457 if (sctx.nshift) { 1458 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1459 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); 1460 } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1461 ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1462 } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) { 1463 ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %g\n",sctx.nshift,(double)info->shiftamount);CHKERRQ(ierr); 1464 } 1465 } 1466 PetscFunctionReturn(0); 1467 } 1468 1469 #undef __FUNCT__ 1470 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace" 1471 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 1472 { 1473 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1474 PetscErrorCode ierr; 1475 PetscInt i,j,mbs = a->mbs; 1476 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1477 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1478 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1479 PetscReal rs; 1480 FactorShiftCtx sctx; 1481 1482 PetscFunctionBegin; 1483 /* MatPivotSetUp(): initialize shift context sctx */ 1484 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1485 1486 /* initialization */ 1487 /* il and jl record the first nonzero element in each row of the accessing 1488 window U(0:k, k:mbs-1). 1489 jl: list of rows to be added to uneliminated rows 1490 i>= k: jl(i) is the first row to be added to row i 1491 i< k: jl(i) is the row following row i in some list of rows 1492 jl(i) = mbs indicates the end of a list 1493 il(i): points to the first nonzero element in U(i,k:mbs-1) 1494 */ 1495 ierr = PetscMalloc1(mbs,&rtmp);CHKERRQ(ierr); 1496 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 1497 1498 do { 1499 sctx.newshift = PETSC_FALSE; 1500 for (i=0; i<mbs; i++) { 1501 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1502 } 1503 1504 for (k = 0; k<mbs; k++) { 1505 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1506 nz = ai[k+1] - ai[k]; 1507 acol = aj + ai[k]; 1508 aval = aa + ai[k]; 1509 bval = ba + bi[k]; 1510 while (nz--) { 1511 rtmp[*acol++] = *aval++; 1512 *bval++ = 0.0; /* for in-place factorization */ 1513 } 1514 1515 /* shift the diagonal of the matrix */ 1516 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1517 1518 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1519 dk = rtmp[k]; 1520 i = jl[k]; /* first row to be added to k_th row */ 1521 1522 while (i < k) { 1523 nexti = jl[i]; /* next row to be added to k_th row */ 1524 /* compute multiplier, update D(k) and U(i,k) */ 1525 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1526 uikdi = -ba[ili]*ba[bi[i]]; 1527 dk += uikdi*ba[ili]; 1528 ba[ili] = uikdi; /* -U(i,k) */ 1529 1530 /* add multiple of row i to k-th row ... */ 1531 jmin = ili + 1; 1532 nz = bi[i+1] - jmin; 1533 if (nz > 0) { 1534 bcol = bj + jmin; 1535 bval = ba + jmin; 1536 ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr); 1537 while (nz--) rtmp[*bcol++] += uikdi*(*bval++); 1538 1539 /* update il and jl for i-th row */ 1540 il[i] = jmin; 1541 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1542 } 1543 i = nexti; 1544 } 1545 1546 /* shift the diagonals when zero pivot is detected */ 1547 /* compute rs=sum of abs(off-diagonal) */ 1548 rs = 0.0; 1549 jmin = bi[k]+1; 1550 nz = bi[k+1] - jmin; 1551 if (nz) { 1552 bcol = bj + jmin; 1553 while (nz--) { 1554 rs += PetscAbsScalar(rtmp[*bcol]); 1555 bcol++; 1556 } 1557 } 1558 1559 sctx.rs = rs; 1560 sctx.pv = dk; 1561 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1562 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1563 dk = sctx.pv; 1564 1565 /* copy data into U(k,:) */ 1566 ba[bi[k]] = 1.0/dk; 1567 jmin = bi[k]+1; 1568 nz = bi[k+1] - jmin; 1569 if (nz) { 1570 bcol = bj + jmin; 1571 bval = ba + jmin; 1572 while (nz--) { 1573 *bval++ = rtmp[*bcol]; 1574 rtmp[*bcol++] = 0.0; 1575 } 1576 /* add k-th row into il and jl */ 1577 il[k] = jmin; 1578 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1579 } 1580 } /* end of for (k = 0; k<mbs; k++) */ 1581 } while (sctx.newshift); 1582 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1583 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1584 1585 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1586 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1587 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1588 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1589 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1590 1591 C->assembled = PETSC_TRUE; 1592 C->preallocated = PETSC_TRUE; 1593 1594 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1595 if (sctx.nshift) { 1596 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1597 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1598 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1599 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1600 } 1601 } 1602 PetscFunctionReturn(0); 1603 } 1604 1605 #undef __FUNCT__ 1606 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1607 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info) 1608 { 1609 PetscErrorCode ierr; 1610 Mat C; 1611 1612 PetscFunctionBegin; 1613 ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr); 1614 ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr); 1615 ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr); 1616 1617 A->ops->solve = C->ops->solve; 1618 A->ops->solvetranspose = C->ops->solvetranspose; 1619 1620 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1621 PetscFunctionReturn(0); 1622 } 1623 1624 1625