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(PetscRealIntMultTruncate(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 = PetscIntMultTruncate(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 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 428 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 429 430 /* initialization */ 431 ierr = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr); 432 ui[0] = 0; 433 434 /* jl: linked list for storing indices of the pivot rows 435 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 436 ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr); 437 for (i=0; i<mbs; i++) { 438 jl[i] = mbs; il[i] = 0; 439 } 440 441 /* create and initialize a linked list for storing column indices of the active row k */ 442 nlnk = mbs + 1; 443 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 444 445 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 446 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,ai[mbs]+1),&free_space);CHKERRQ(ierr); 447 current_space = free_space; 448 449 for (k=0; k<mbs; k++) { /* for each active row k */ 450 /* initialize lnk by the column indices of row rip[k] of A */ 451 nzk = 0; 452 ncols = ai[rip[k]+1] - ai[rip[k]]; 453 for (j=0; j<ncols; j++) { 454 i = *(aj + ai[rip[k]] + j); 455 cols[j] = rip[i]; 456 } 457 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 458 nzk += nlnk; 459 460 /* update lnk by computing fill-in for each pivot row to be merged in */ 461 prow = jl[k]; /* 1st pivot row */ 462 463 while (prow < k) { 464 nextprow = jl[prow]; 465 /* merge prow into k-th row */ 466 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 467 jmax = ui[prow+1]; 468 ncols = jmax-jmin; 469 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 470 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 471 nzk += nlnk; 472 473 /* update il and jl for prow */ 474 if (jmin < jmax) { 475 il[prow] = jmin; 476 477 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 478 } 479 prow = nextprow; 480 } 481 482 /* if free space is not available, make more free space */ 483 if (current_space->local_remaining<nzk) { 484 i = mbs - k + 1; /* num of unfactored rows */ 485 i = PetscMin(PetscIntMultTruncate(i,nzk), PetscIntMultTruncate(i,i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 486 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 487 reallocs++; 488 } 489 490 /* copy data into free space, then initialize lnk */ 491 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 492 493 /* add the k-th row into il and jl */ 494 if (nzk-1 > 0) { 495 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 496 jl[k] = jl[i]; jl[i] = k; 497 il[k] = ui[k] + 1; 498 } 499 ui_ptr[k] = current_space->array; 500 501 current_space->array += nzk; 502 current_space->local_used += nzk; 503 current_space->local_remaining -= nzk; 504 505 ui[k+1] = ui[k] + nzk; 506 } 507 508 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 509 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 510 511 /* destroy list of free space and other temporary array(s) */ 512 ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr); 513 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 514 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 515 516 /* put together the new matrix in MATSEQSBAIJ format */ 517 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 518 519 b = (Mat_SeqSBAIJ*)fact->data; 520 b->singlemalloc = PETSC_FALSE; 521 b->free_a = PETSC_TRUE; 522 b->free_ij = PETSC_TRUE; 523 524 ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr); 525 526 b->j = uj; 527 b->i = ui; 528 b->diag = 0; 529 b->ilen = 0; 530 b->imax = 0; 531 b->row = perm; 532 533 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 534 535 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 536 b->icol = perm; 537 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 538 ierr = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr); 539 ierr = PetscLogObjectMemory((PetscObject)fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 540 b->maxnz = b->nz = ui[mbs]; 541 542 fact->info.factor_mallocs = reallocs; 543 fact->info.fill_ratio_given = fill; 544 if (ai[mbs] != 0) { 545 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 546 } else { 547 fact->info.fill_ratio_needed = 0.0; 548 } 549 #if defined(PETSC_USE_INFO) 550 if (ai[mbs] != 0) { 551 PetscReal af = fact->info.fill_ratio_needed; 552 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr); 553 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 554 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr); 555 } else { 556 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 557 } 558 #endif 559 ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr); 560 PetscFunctionReturn(0); 561 } 562 563 #undef __FUNCT__ 564 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 565 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info) 566 { 567 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 568 IS perm = b->row; 569 PetscErrorCode ierr; 570 const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j; 571 PetscInt i,j; 572 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 573 PetscInt bs =A->rmap->bs,bs2 = a->bs2; 574 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 575 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 576 MatScalar *work; 577 PetscInt *pivots; 578 PetscBool allowzeropivot,zeropivotdetected; 579 580 PetscFunctionBegin; 581 /* initialization */ 582 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 583 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 584 allowzeropivot = PetscNot(A->erroriffailure); 585 586 for (i=0; i<mbs; i++) { 587 jl[i] = mbs; il[0] = 0; 588 } 589 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 590 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 591 592 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 593 594 /* check permutation */ 595 if (!a->permute) { 596 ai = a->i; aj = a->j; aa = a->a; 597 } else { 598 ai = a->inew; aj = a->jnew; 599 ierr = PetscMalloc1(bs2*ai[mbs],&aa);CHKERRQ(ierr); 600 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 601 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 602 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 603 604 for (i=0; i<mbs; i++) { 605 jmin = ai[i]; jmax = ai[i+1]; 606 for (j=jmin; j<jmax; j++) { 607 while (a2anew[j] != j) { 608 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 609 for (k1=0; k1<bs2; k1++) { 610 dk[k1] = aa[k*bs2+k1]; 611 aa[k*bs2+k1] = aa[j*bs2+k1]; 612 aa[j*bs2+k1] = dk[k1]; 613 } 614 } 615 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 616 if (i > aj[j]) { 617 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 618 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 619 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 620 for (k=0; k<bs; k++) { /* j-th block of aa <- dk^T */ 621 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 622 } 623 } 624 } 625 } 626 ierr = PetscFree(a2anew);CHKERRQ(ierr); 627 } 628 629 /* for each row k */ 630 for (k = 0; k<mbs; k++) { 631 632 /*initialize k-th row with elements nonzero in row perm(k) of A */ 633 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 634 635 ap = aa + jmin*bs2; 636 for (j = jmin; j < jmax; j++) { 637 vj = perm_ptr[aj[j]]; /* block col. index */ 638 rtmp_ptr = rtmp + vj*bs2; 639 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 640 } 641 642 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 643 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 644 i = jl[k]; /* first row to be added to k_th row */ 645 646 while (i < k) { 647 nexti = jl[i]; /* next row to be added to k_th row */ 648 649 /* compute multiplier */ 650 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 651 652 /* uik = -inv(Di)*U_bar(i,k) */ 653 diag = ba + i*bs2; 654 u = ba + ili*bs2; 655 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 656 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 657 658 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 659 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 660 ierr = PetscLogFlops(4.0*bs*bs2);CHKERRQ(ierr); 661 662 /* update -U(i,k) */ 663 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 664 665 /* add multiple of row i to k-th row ... */ 666 jmin = ili + 1; jmax = bi[i+1]; 667 if (jmin < jmax) { 668 for (j=jmin; j<jmax; j++) { 669 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 670 rtmp_ptr = rtmp + bj[j]*bs2; 671 u = ba + j*bs2; 672 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 673 } 674 ierr = PetscLogFlops(2.0*bs*bs2*(jmax-jmin));CHKERRQ(ierr); 675 676 /* ... add i to row list for next nonzero entry */ 677 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 678 j = bj[jmin]; 679 jl[i] = jl[j]; jl[j] = i; /* update jl */ 680 } 681 i = nexti; 682 } 683 684 /* save nonzero entries in k-th row of U ... */ 685 686 /* invert diagonal block */ 687 diag = ba+k*bs2; 688 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 689 690 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 691 if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 692 693 jmin = bi[k]; jmax = bi[k+1]; 694 if (jmin < jmax) { 695 for (j=jmin; j<jmax; j++) { 696 vj = bj[j]; /* block col. index of U */ 697 u = ba + j*bs2; 698 rtmp_ptr = rtmp + vj*bs2; 699 for (k1=0; k1<bs2; k1++) { 700 *u++ = *rtmp_ptr; 701 *rtmp_ptr++ = 0.0; 702 } 703 } 704 705 /* ... add k to row list for first nonzero entry in k-th row */ 706 il[k] = jmin; 707 i = bj[jmin]; 708 jl[k] = jl[i]; jl[i] = k; 709 } 710 } 711 712 ierr = PetscFree(rtmp);CHKERRQ(ierr); 713 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 714 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 715 ierr = PetscFree(pivots);CHKERRQ(ierr); 716 if (a->permute) { 717 ierr = PetscFree(aa);CHKERRQ(ierr); 718 } 719 720 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 721 722 C->ops->solve = MatSolve_SeqSBAIJ_N_inplace; 723 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace; 724 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_inplace; 725 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_inplace; 726 727 C->assembled = PETSC_TRUE; 728 C->preallocated = PETSC_TRUE; 729 730 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 731 PetscFunctionReturn(0); 732 } 733 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 736 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 737 { 738 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 739 PetscErrorCode ierr; 740 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 741 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 742 PetscInt bs =A->rmap->bs,bs2 = a->bs2; 743 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 744 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 745 MatScalar *work; 746 PetscInt *pivots; 747 PetscBool allowzeropivot,zeropivotdetected; 748 749 PetscFunctionBegin; 750 ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr); 751 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 752 for (i=0; i<mbs; i++) { 753 jl[i] = mbs; il[0] = 0; 754 } 755 ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr); 756 ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr); 757 allowzeropivot = PetscNot(A->erroriffailure); 758 759 ai = a->i; aj = a->j; aa = a->a; 760 761 /* for each row k */ 762 for (k = 0; k<mbs; k++) { 763 764 /*initialize k-th row with elements nonzero in row k of A */ 765 jmin = ai[k]; jmax = ai[k+1]; 766 ap = aa + jmin*bs2; 767 for (j = jmin; j < jmax; j++) { 768 vj = aj[j]; /* block col. index */ 769 rtmp_ptr = rtmp + vj*bs2; 770 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 771 } 772 773 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 774 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 775 i = jl[k]; /* first row to be added to k_th row */ 776 777 while (i < k) { 778 nexti = jl[i]; /* next row to be added to k_th row */ 779 780 /* compute multiplier */ 781 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 782 783 /* uik = -inv(Di)*U_bar(i,k) */ 784 diag = ba + i*bs2; 785 u = ba + ili*bs2; 786 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 787 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 788 789 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 790 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 791 ierr = PetscLogFlops(2.0*bs*bs2);CHKERRQ(ierr); 792 793 /* update -U(i,k) */ 794 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 795 796 /* add multiple of row i to k-th row ... */ 797 jmin = ili + 1; jmax = bi[i+1]; 798 if (jmin < jmax) { 799 for (j=jmin; j<jmax; j++) { 800 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 801 rtmp_ptr = rtmp + bj[j]*bs2; 802 u = ba + j*bs2; 803 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 804 } 805 ierr = PetscLogFlops(2.0*bs*bs2*(jmax-jmin));CHKERRQ(ierr); 806 807 /* ... add i to row list for next nonzero entry */ 808 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 809 j = bj[jmin]; 810 jl[i] = jl[j]; jl[j] = i; /* update jl */ 811 } 812 i = nexti; 813 } 814 815 /* save nonzero entries in k-th row of U ... */ 816 817 /* invert diagonal block */ 818 diag = ba+k*bs2; 819 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 820 821 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 822 if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 823 824 jmin = bi[k]; jmax = bi[k+1]; 825 if (jmin < jmax) { 826 for (j=jmin; j<jmax; j++) { 827 vj = bj[j]; /* block col. index of U */ 828 u = ba + j*bs2; 829 rtmp_ptr = rtmp + vj*bs2; 830 for (k1=0; k1<bs2; k1++) { 831 *u++ = *rtmp_ptr; 832 *rtmp_ptr++ = 0.0; 833 } 834 } 835 836 /* ... add k to row list for first nonzero entry in k-th row */ 837 il[k] = jmin; 838 i = bj[jmin]; 839 jl[k] = jl[i]; jl[i] = k; 840 } 841 } 842 843 ierr = PetscFree(rtmp);CHKERRQ(ierr); 844 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 845 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 846 ierr = PetscFree(pivots);CHKERRQ(ierr); 847 848 C->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 849 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 850 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 851 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 852 C->assembled = PETSC_TRUE; 853 C->preallocated = PETSC_TRUE; 854 855 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 856 PetscFunctionReturn(0); 857 } 858 859 /* 860 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 861 Version for blocks 2 by 2. 862 */ 863 #undef __FUNCT__ 864 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 865 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info) 866 { 867 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 868 IS perm = b->row; 869 PetscErrorCode ierr; 870 const PetscInt *ai,*aj,*perm_ptr; 871 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 872 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 873 MatScalar *ba = b->a,*aa,*ap; 874 MatScalar *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4]; 875 PetscReal shift = info->shiftamount; 876 PetscBool allowzeropivot,zeropivotdetected; 877 878 PetscFunctionBegin; 879 allowzeropivot = PetscNot(A->erroriffailure); 880 881 /* initialization */ 882 /* il and jl record the first nonzero element in each row of the accessing 883 window U(0:k, k:mbs-1). 884 jl: list of rows to be added to uneliminated rows 885 i>= k: jl(i) is the first row to be added to row i 886 i< k: jl(i) is the row following row i in some list of rows 887 jl(i) = mbs indicates the end of a list 888 il(i): points to the first nonzero element in columns k,...,mbs-1 of 889 row i of U */ 890 ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr); 891 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 892 for (i=0; i<mbs; i++) { 893 jl[i] = mbs; il[0] = 0; 894 } 895 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 896 897 /* check permutation */ 898 if (!a->permute) { 899 ai = a->i; aj = a->j; aa = a->a; 900 } else { 901 ai = a->inew; aj = a->jnew; 902 ierr = PetscMalloc1(4*ai[mbs],&aa);CHKERRQ(ierr); 903 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 904 ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr); 905 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 906 907 for (i=0; i<mbs; i++) { 908 jmin = ai[i]; jmax = ai[i+1]; 909 for (j=jmin; j<jmax; j++) { 910 while (a2anew[j] != j) { 911 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 912 for (k1=0; k1<4; k1++) { 913 dk[k1] = aa[k*4+k1]; 914 aa[k*4+k1] = aa[j*4+k1]; 915 aa[j*4+k1] = dk[k1]; 916 } 917 } 918 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 919 if (i > aj[j]) { 920 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 921 ap = aa + j*4; /* ptr to the beginning of the block */ 922 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 923 ap[1] = ap[2]; 924 ap[2] = dk[1]; 925 } 926 } 927 } 928 ierr = PetscFree(a2anew);CHKERRQ(ierr); 929 } 930 931 /* for each row k */ 932 for (k = 0; k<mbs; k++) { 933 934 /*initialize k-th row with elements nonzero in row perm(k) of A */ 935 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 936 ap = aa + jmin*4; 937 for (j = jmin; j < jmax; j++) { 938 vj = perm_ptr[aj[j]]; /* block col. index */ 939 rtmp_ptr = rtmp + vj*4; 940 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 941 } 942 943 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 944 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 945 i = jl[k]; /* first row to be added to k_th row */ 946 947 while (i < k) { 948 nexti = jl[i]; /* next row to be added to k_th row */ 949 950 /* compute multiplier */ 951 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 952 953 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 954 diag = ba + i*4; 955 u = ba + ili*4; 956 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 957 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 958 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 959 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 960 961 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 962 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 963 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 964 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 965 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 966 967 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 968 969 /* update -U(i,k): ba[ili] = uik */ 970 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 971 972 /* add multiple of row i to k-th row ... */ 973 jmin = ili + 1; jmax = bi[i+1]; 974 if (jmin < jmax) { 975 for (j=jmin; j<jmax; j++) { 976 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 977 rtmp_ptr = rtmp + bj[j]*4; 978 u = ba + j*4; 979 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 980 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 981 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 982 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 983 } 984 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 985 986 /* ... add i to row list for next nonzero entry */ 987 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 988 j = bj[jmin]; 989 jl[i] = jl[j]; jl[j] = i; /* update jl */ 990 } 991 i = nexti; 992 } 993 994 /* save nonzero entries in k-th row of U ... */ 995 996 /* invert diagonal block */ 997 diag = ba+k*4; 998 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 999 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1000 if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1001 1002 jmin = bi[k]; jmax = bi[k+1]; 1003 if (jmin < jmax) { 1004 for (j=jmin; j<jmax; j++) { 1005 vj = bj[j]; /* block col. index of U */ 1006 u = ba + j*4; 1007 rtmp_ptr = rtmp + vj*4; 1008 for (k1=0; k1<4; k1++) { 1009 *u++ = *rtmp_ptr; 1010 *rtmp_ptr++ = 0.0; 1011 } 1012 } 1013 1014 /* ... add k to row list for first nonzero entry in k-th row */ 1015 il[k] = jmin; 1016 i = bj[jmin]; 1017 jl[k] = jl[i]; jl[i] = k; 1018 } 1019 } 1020 1021 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1022 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1023 if (a->permute) { 1024 ierr = PetscFree(aa);CHKERRQ(ierr); 1025 } 1026 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 1027 1028 C->ops->solve = MatSolve_SeqSBAIJ_2_inplace; 1029 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace; 1030 C->assembled = PETSC_TRUE; 1031 C->preallocated = PETSC_TRUE; 1032 1033 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1034 PetscFunctionReturn(0); 1035 } 1036 1037 /* 1038 Version for when blocks are 2 by 2 Using natural ordering 1039 */ 1040 #undef __FUNCT__ 1041 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 1042 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 1043 { 1044 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 1045 PetscErrorCode ierr; 1046 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1047 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1048 MatScalar *ba = b->a,*aa,*ap,dk[8],uik[8]; 1049 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1050 PetscReal shift = info->shiftamount; 1051 PetscBool allowzeropivot,zeropivotdetected; 1052 1053 PetscFunctionBegin; 1054 allowzeropivot = PetscNot(A->erroriffailure); 1055 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,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1141 if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1142 1143 jmin = bi[k]; jmax = bi[k+1]; 1144 if (jmin < jmax) { 1145 for (j=jmin; j<jmax; j++) { 1146 vj = bj[j]; /* block col. index of U */ 1147 u = ba + j*4; 1148 rtmp_ptr = rtmp + vj*4; 1149 for (k1=0; k1<4; k1++) { 1150 *u++ = *rtmp_ptr; 1151 *rtmp_ptr++ = 0.0; 1152 } 1153 } 1154 1155 /* ... add k to row list for first nonzero entry in k-th row */ 1156 il[k] = jmin; 1157 i = bj[jmin]; 1158 jl[k] = jl[i]; jl[i] = k; 1159 } 1160 } 1161 1162 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1163 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1164 1165 C->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1166 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1167 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1168 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1169 C->assembled = PETSC_TRUE; 1170 C->preallocated = PETSC_TRUE; 1171 1172 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1173 PetscFunctionReturn(0); 1174 } 1175 1176 /* 1177 Numeric U^T*D*U factorization for SBAIJ format. 1178 Version for blocks are 1 by 1. 1179 */ 1180 #undef __FUNCT__ 1181 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace" 1182 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 1183 { 1184 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1185 IS ip=b->row; 1186 PetscErrorCode ierr; 1187 const PetscInt *ai,*aj,*rip; 1188 PetscInt *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1189 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1190 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1191 PetscReal rs; 1192 FactorShiftCtx sctx; 1193 1194 PetscFunctionBegin; 1195 /* MatPivotSetUp(): initialize shift context sctx */ 1196 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1197 1198 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1199 if (!a->permute) { 1200 ai = a->i; aj = a->j; aa = a->a; 1201 } else { 1202 ai = a->inew; aj = a->jnew; 1203 nz = ai[mbs]; 1204 ierr = PetscMalloc1(nz,&aa);CHKERRQ(ierr); 1205 a2anew = a->a2anew; 1206 bval = a->a; 1207 for (j=0; j<nz; j++) { 1208 aa[a2anew[j]] = *(bval++); 1209 } 1210 } 1211 1212 /* initialization */ 1213 /* il and jl record the first nonzero element in each row of the accessing 1214 window U(0:k, k:mbs-1). 1215 jl: list of rows to be added to uneliminated rows 1216 i>= k: jl(i) is the first row to be added to row i 1217 i< k: jl(i) is the row following row i in some list of rows 1218 jl(i) = mbs indicates the end of a list 1219 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1220 row i of U */ 1221 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&jl);CHKERRQ(ierr); 1222 1223 do { 1224 sctx.newshift = PETSC_FALSE; 1225 for (i=0; i<mbs; i++) { 1226 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1227 } 1228 1229 for (k = 0; k<mbs; k++) { 1230 /*initialize k-th row by the perm[k]-th row of A */ 1231 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1232 bval = ba + bi[k]; 1233 for (j = jmin; j < jmax; j++) { 1234 col = rip[aj[j]]; 1235 rtmp[col] = aa[j]; 1236 *bval++ = 0.0; /* for in-place factorization */ 1237 } 1238 1239 /* shift the diagonal of the matrix */ 1240 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1241 1242 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1243 dk = rtmp[k]; 1244 i = jl[k]; /* first row to be added to k_th row */ 1245 1246 while (i < k) { 1247 nexti = jl[i]; /* next row to be added to k_th row */ 1248 1249 /* compute multiplier, update diag(k) and U(i,k) */ 1250 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1251 uikdi = -ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1252 dk += uikdi*ba[ili]; 1253 ba[ili] = uikdi; /* -U(i,k) */ 1254 1255 /* add multiple of row i to k-th row */ 1256 jmin = ili + 1; jmax = bi[i+1]; 1257 if (jmin < jmax) { 1258 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1259 ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr); 1260 1261 /* update il and jl for row i */ 1262 il[i] = jmin; 1263 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1264 } 1265 i = nexti; 1266 } 1267 1268 /* shift the diagonals when zero pivot is detected */ 1269 /* compute rs=sum of abs(off-diagonal) */ 1270 rs = 0.0; 1271 jmin = bi[k]+1; 1272 nz = bi[k+1] - jmin; 1273 if (nz) { 1274 bcol = bj + jmin; 1275 while (nz--) { 1276 rs += PetscAbsScalar(rtmp[*bcol]); 1277 bcol++; 1278 } 1279 } 1280 1281 sctx.rs = rs; 1282 sctx.pv = dk; 1283 ierr = MatPivotCheck(C,A,info,&sctx,k);CHKERRQ(ierr); 1284 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1285 dk = sctx.pv; 1286 1287 /* copy data into U(k,:) */ 1288 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1289 jmin = bi[k]+1; jmax = bi[k+1]; 1290 if (jmin < jmax) { 1291 for (j=jmin; j<jmax; j++) { 1292 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1293 } 1294 /* add the k-th row into il and jl */ 1295 il[k] = jmin; 1296 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1297 } 1298 } 1299 } while (sctx.newshift); 1300 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 1301 if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);} 1302 1303 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1304 1305 C->ops->solve = MatSolve_SeqSBAIJ_1_inplace; 1306 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1307 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace; 1308 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace; 1309 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace; 1310 C->assembled = PETSC_TRUE; 1311 C->preallocated = PETSC_TRUE; 1312 1313 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1314 if (sctx.nshift) { 1315 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1316 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1317 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1318 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1319 } 1320 } 1321 PetscFunctionReturn(0); 1322 } 1323 1324 /* 1325 Version for when blocks are 1 by 1 Using natural ordering under new datastructure 1326 Modified from MatCholeskyFactorNumeric_SeqAIJ() 1327 */ 1328 #undef __FUNCT__ 1329 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1330 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 1331 { 1332 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 1333 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)B->data; 1334 PetscErrorCode ierr; 1335 PetscInt i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp; 1336 PetscInt *ai=a->i,*aj=a->j,*ajtmp; 1337 PetscInt k,jmin,jmax,*c2r,*il,col,nexti,ili,nz; 1338 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 1339 FactorShiftCtx sctx; 1340 PetscReal rs; 1341 MatScalar d,*v; 1342 1343 PetscFunctionBegin; 1344 ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&c2r);CHKERRQ(ierr); 1345 1346 /* MatPivotSetUp(): initialize shift context sctx */ 1347 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1348 1349 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */ 1350 sctx.shift_top = info->zeropivot; 1351 1352 ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr); 1353 1354 for (i=0; i<mbs; i++) { 1355 /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */ 1356 d = (aa)[a->diag[i]]; 1357 rtmp[i] += -PetscRealPart(d); /* diagonal entry */ 1358 ajtmp = aj + ai[i] + 1; /* exclude diagonal */ 1359 v = aa + ai[i] + 1; 1360 nz = ai[i+1] - ai[i] - 1; 1361 for (j=0; j<nz; j++) { 1362 rtmp[i] += PetscAbsScalar(v[j]); 1363 rtmp[ajtmp[j]] += PetscAbsScalar(v[j]); 1364 } 1365 if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]); 1366 } 1367 sctx.shift_top *= 1.1; 1368 sctx.nshift_max = 5; 1369 sctx.shift_lo = 0.; 1370 sctx.shift_hi = 1.; 1371 } 1372 1373 /* allocate working arrays 1374 c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col 1375 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 1376 */ 1377 do { 1378 sctx.newshift = PETSC_FALSE; 1379 1380 for (i=0; i<mbs; i++) c2r[i] = mbs; 1381 if (mbs) il[0] = 0; 1382 1383 for (k = 0; k<mbs; k++) { 1384 /* zero rtmp */ 1385 nz = bi[k+1] - bi[k]; 1386 bjtmp = bj + bi[k]; 1387 for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0; 1388 1389 /* load in initial unfactored row */ 1390 bval = ba + bi[k]; 1391 jmin = ai[k]; jmax = ai[k+1]; 1392 for (j = jmin; j < jmax; j++) { 1393 col = aj[j]; 1394 rtmp[col] = aa[j]; 1395 *bval++ = 0.0; /* for in-place factorization */ 1396 } 1397 /* shift the diagonal of the matrix: ZeropivotApply() */ 1398 rtmp[k] += sctx.shift_amount; /* shift the diagonal of the matrix */ 1399 1400 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1401 dk = rtmp[k]; 1402 i = c2r[k]; /* first row to be added to k_th row */ 1403 1404 while (i < k) { 1405 nexti = c2r[i]; /* next row to be added to k_th row */ 1406 1407 /* compute multiplier, update diag(k) and U(i,k) */ 1408 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1409 uikdi = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */ 1410 dk += uikdi*ba[ili]; /* update diag[k] */ 1411 ba[ili] = uikdi; /* -U(i,k) */ 1412 1413 /* add multiple of row i to k-th row */ 1414 jmin = ili + 1; jmax = bi[i+1]; 1415 if (jmin < jmax) { 1416 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1417 /* update il and c2r for row i */ 1418 il[i] = jmin; 1419 j = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i; 1420 } 1421 i = nexti; 1422 } 1423 1424 /* copy data into U(k,:) */ 1425 rs = 0.0; 1426 jmin = bi[k]; jmax = bi[k+1]-1; 1427 if (jmin < jmax) { 1428 for (j=jmin; j<jmax; j++) { 1429 col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]); 1430 } 1431 /* add the k-th row into il and c2r */ 1432 il[k] = jmin; 1433 i = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k; 1434 } 1435 1436 sctx.rs = rs; 1437 sctx.pv = dk; 1438 ierr = MatPivotCheck(B,A,info,&sctx,k);CHKERRQ(ierr); 1439 if (sctx.newshift) break; 1440 dk = sctx.pv; 1441 1442 ba[bdiag[k]] = 1.0/dk; /* U(k,k) */ 1443 } 1444 } while (sctx.newshift); 1445 1446 ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr); 1447 1448 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1449 B->ops->solves = MatSolves_SeqSBAIJ_1; 1450 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1451 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 1452 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 1453 1454 B->assembled = PETSC_TRUE; 1455 B->preallocated = PETSC_TRUE; 1456 1457 ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr); 1458 1459 /* MatPivotView() */ 1460 if (sctx.nshift) { 1461 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1462 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); 1463 } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1464 ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1465 } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) { 1466 ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %g\n",sctx.nshift,(double)info->shiftamount);CHKERRQ(ierr); 1467 } 1468 } 1469 PetscFunctionReturn(0); 1470 } 1471 1472 #undef __FUNCT__ 1473 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace" 1474 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 1475 { 1476 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1477 PetscErrorCode ierr; 1478 PetscInt i,j,mbs = a->mbs; 1479 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1480 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1481 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1482 PetscReal rs; 1483 FactorShiftCtx sctx; 1484 1485 PetscFunctionBegin; 1486 /* MatPivotSetUp(): initialize shift context sctx */ 1487 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1488 1489 /* initialization */ 1490 /* il and jl record the first nonzero element in each row of the accessing 1491 window U(0:k, k:mbs-1). 1492 jl: list of rows to be added to uneliminated rows 1493 i>= k: jl(i) is the first row to be added to row i 1494 i< k: jl(i) is the row following row i in some list of rows 1495 jl(i) = mbs indicates the end of a list 1496 il(i): points to the first nonzero element in U(i,k:mbs-1) 1497 */ 1498 ierr = PetscMalloc1(mbs,&rtmp);CHKERRQ(ierr); 1499 ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr); 1500 1501 do { 1502 sctx.newshift = PETSC_FALSE; 1503 for (i=0; i<mbs; i++) { 1504 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1505 } 1506 1507 for (k = 0; k<mbs; k++) { 1508 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1509 nz = ai[k+1] - ai[k]; 1510 acol = aj + ai[k]; 1511 aval = aa + ai[k]; 1512 bval = ba + bi[k]; 1513 while (nz--) { 1514 rtmp[*acol++] = *aval++; 1515 *bval++ = 0.0; /* for in-place factorization */ 1516 } 1517 1518 /* shift the diagonal of the matrix */ 1519 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1520 1521 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1522 dk = rtmp[k]; 1523 i = jl[k]; /* first row to be added to k_th row */ 1524 1525 while (i < k) { 1526 nexti = jl[i]; /* next row to be added to k_th row */ 1527 /* compute multiplier, update D(k) and U(i,k) */ 1528 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1529 uikdi = -ba[ili]*ba[bi[i]]; 1530 dk += uikdi*ba[ili]; 1531 ba[ili] = uikdi; /* -U(i,k) */ 1532 1533 /* add multiple of row i to k-th row ... */ 1534 jmin = ili + 1; 1535 nz = bi[i+1] - jmin; 1536 if (nz > 0) { 1537 bcol = bj + jmin; 1538 bval = ba + jmin; 1539 ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr); 1540 while (nz--) rtmp[*bcol++] += uikdi*(*bval++); 1541 1542 /* update il and jl for i-th row */ 1543 il[i] = jmin; 1544 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1545 } 1546 i = nexti; 1547 } 1548 1549 /* shift the diagonals when zero pivot is detected */ 1550 /* compute rs=sum of abs(off-diagonal) */ 1551 rs = 0.0; 1552 jmin = bi[k]+1; 1553 nz = bi[k+1] - jmin; 1554 if (nz) { 1555 bcol = bj + jmin; 1556 while (nz--) { 1557 rs += PetscAbsScalar(rtmp[*bcol]); 1558 bcol++; 1559 } 1560 } 1561 1562 sctx.rs = rs; 1563 sctx.pv = dk; 1564 ierr = MatPivotCheck(C,A,info,&sctx,k);CHKERRQ(ierr); 1565 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1566 dk = sctx.pv; 1567 1568 /* copy data into U(k,:) */ 1569 ba[bi[k]] = 1.0/dk; 1570 jmin = bi[k]+1; 1571 nz = bi[k+1] - jmin; 1572 if (nz) { 1573 bcol = bj + jmin; 1574 bval = ba + jmin; 1575 while (nz--) { 1576 *bval++ = rtmp[*bcol]; 1577 rtmp[*bcol++] = 0.0; 1578 } 1579 /* add k-th row into il and jl */ 1580 il[k] = jmin; 1581 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1582 } 1583 } /* end of for (k = 0; k<mbs; k++) */ 1584 } while (sctx.newshift); 1585 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1586 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1587 1588 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1589 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1590 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1591 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1592 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1593 1594 C->assembled = PETSC_TRUE; 1595 C->preallocated = PETSC_TRUE; 1596 1597 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1598 if (sctx.nshift) { 1599 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1600 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1601 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1602 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr); 1603 } 1604 } 1605 PetscFunctionReturn(0); 1606 } 1607 1608 #undef __FUNCT__ 1609 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1610 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info) 1611 { 1612 PetscErrorCode ierr; 1613 Mat C; 1614 1615 PetscFunctionBegin; 1616 ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr); 1617 ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr); 1618 ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr); 1619 1620 A->ops->solve = C->ops->solve; 1621 A->ops->solvetranspose = C->ops->solvetranspose; 1622 1623 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 1624 PetscFunctionReturn(0); 1625 } 1626 1627 1628