1 2 #include <../src/mat/impls/baij/seq/baij.h> 3 #include <../src/mat/impls/sbaij/seq/sbaij.h> 4 #include <../src/mat/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 = PetscMalloc((mbs+1)*sizeof(PetscInt),&iu);CHKERRQ(ierr); 72 umax = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1; 73 ierr = PetscMalloc(umax*sizeof(PetscInt),&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,PetscInt,&jl,mbs,PetscInt,&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 = PetscMalloc(umax*sizeof(PetscInt),&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,f,af);CHKERRQ(ierr); 162 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 163 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",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,PETSC_NULL);CHKERRQ(ierr); 175 176 /* ierr = PetscLogObjectParent(B,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 = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*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 = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&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(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,d; 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=PETSC_NULL,current_space=PETSC_NULL; 232 PetscBT lnkbt; 233 234 PetscFunctionBegin; 235 if (bs > 1) { 236 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(fact,A,perm,info);CHKERRQ(ierr); 237 PetscFunctionReturn(0); 238 } 239 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); 240 ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr); 241 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d); 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 = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 251 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&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,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&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 = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&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,PETSC_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 = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&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 = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 361 ierr = PetscLogObjectMemory(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,fill,af);CHKERRQ(ierr); 376 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 377 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",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=PETSC_NULL,current_space=PETSC_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 = PetscMalloc((mbs+1)*sizeof(PetscInt),&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,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&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 = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&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,PETSC_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 = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&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 = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 547 ierr = PetscLogObjectMemory(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,fill,af);CHKERRQ(ierr); 561 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 562 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",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 = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 590 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 591 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 592 for (i=0; i<mbs; i++) { 593 jl[i] = mbs; il[0] = 0; 594 } 595 ierr = PetscMalloc3(bs2,MatScalar,&dk,bs2,MatScalar,&uik,bs,MatScalar,&work);CHKERRQ(ierr); 596 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 597 598 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 599 600 /* check permutation */ 601 if (!a->permute) { 602 ai = a->i; aj = a->j; aa = a->a; 603 } else { 604 ai = a->inew; aj = a->jnew; 605 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 606 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 607 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 608 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 609 610 /* flops in while loop */ 611 bslog = 2*bs*bs2; 612 613 for (i=0; i<mbs; i++) { 614 jmin = ai[i]; jmax = ai[i+1]; 615 for (j=jmin; j<jmax; j++) { 616 while (a2anew[j] != j) { 617 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 618 for (k1=0; k1<bs2; k1++) { 619 dk[k1] = aa[k*bs2+k1]; 620 aa[k*bs2+k1] = aa[j*bs2+k1]; 621 aa[j*bs2+k1] = dk[k1]; 622 } 623 } 624 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 625 if (i > aj[j]) { 626 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 627 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 628 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 629 for (k=0; k<bs; k++) { /* j-th block of aa <- dk^T */ 630 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 631 } 632 } 633 } 634 } 635 ierr = PetscFree(a2anew);CHKERRQ(ierr); 636 } 637 638 /* for each row k */ 639 for (k = 0; k<mbs; k++) { 640 641 /*initialize k-th row with elements nonzero in row perm(k) of A */ 642 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 643 644 ap = aa + jmin*bs2; 645 for (j = jmin; j < jmax; j++) { 646 vj = perm_ptr[aj[j]]; /* block col. index */ 647 rtmp_ptr = rtmp + vj*bs2; 648 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 649 } 650 651 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 652 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 653 i = jl[k]; /* first row to be added to k_th row */ 654 655 while (i < k) { 656 nexti = jl[i]; /* next row to be added to k_th row */ 657 658 /* compute multiplier */ 659 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 660 661 /* uik = -inv(Di)*U_bar(i,k) */ 662 diag = ba + i*bs2; 663 u = ba + ili*bs2; 664 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 665 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 666 667 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 668 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 669 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 670 671 /* update -U(i,k) */ 672 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 673 674 /* add multiple of row i to k-th row ... */ 675 jmin = ili + 1; jmax = bi[i+1]; 676 if (jmin < jmax) { 677 for (j=jmin; j<jmax; j++) { 678 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 679 rtmp_ptr = rtmp + bj[j]*bs2; 680 u = ba + j*bs2; 681 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 682 } 683 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 684 685 /* ... add i to row list for next nonzero entry */ 686 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 687 j = bj[jmin]; 688 jl[i] = jl[j]; jl[j] = i; /* update jl */ 689 } 690 i = nexti; 691 } 692 693 /* save nonzero entries in k-th row of U ... */ 694 695 /* invert diagonal block */ 696 diag = ba+k*bs2; 697 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 698 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 699 700 jmin = bi[k]; jmax = bi[k+1]; 701 if (jmin < jmax) { 702 for (j=jmin; j<jmax; j++) { 703 vj = bj[j]; /* block col. index of U */ 704 u = ba + j*bs2; 705 rtmp_ptr = rtmp + vj*bs2; 706 for (k1=0; k1<bs2; k1++) { 707 *u++ = *rtmp_ptr; 708 *rtmp_ptr++ = 0.0; 709 } 710 } 711 712 /* ... add k to row list for first nonzero entry in k-th row */ 713 il[k] = jmin; 714 i = bj[jmin]; 715 jl[k] = jl[i]; jl[i] = k; 716 } 717 } 718 719 ierr = PetscFree(rtmp);CHKERRQ(ierr); 720 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 721 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 722 ierr = PetscFree(pivots);CHKERRQ(ierr); 723 if (a->permute) { 724 ierr = PetscFree(aa);CHKERRQ(ierr); 725 } 726 727 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 728 729 C->ops->solve = MatSolve_SeqSBAIJ_N_inplace; 730 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace; 731 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_inplace; 732 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_inplace; 733 734 C->assembled = PETSC_TRUE; 735 C->preallocated = PETSC_TRUE; 736 737 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 738 PetscFunctionReturn(0); 739 } 740 741 #undef __FUNCT__ 742 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 743 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 744 { 745 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 746 PetscErrorCode ierr; 747 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 748 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 749 PetscInt bs =A->rmap->bs,bs2 = a->bs2,bslog; 750 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 751 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 752 MatScalar *work; 753 PetscInt *pivots; 754 755 PetscFunctionBegin; 756 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 757 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 758 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 759 for (i=0; i<mbs; i++) { 760 jl[i] = mbs; il[0] = 0; 761 } 762 ierr = PetscMalloc3(bs2,MatScalar,&dk,bs2,MatScalar,&uik,bs,MatScalar,&work);CHKERRQ(ierr); 763 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 764 765 ai = a->i; aj = a->j; aa = a->a; 766 767 /* flops in while loop */ 768 bslog = 2*bs*bs2; 769 770 /* for each row k */ 771 for (k = 0; k<mbs; k++) { 772 773 /*initialize k-th row with elements nonzero in row k of A */ 774 jmin = ai[k]; jmax = ai[k+1]; 775 ap = aa + jmin*bs2; 776 for (j = jmin; j < jmax; j++) { 777 vj = aj[j]; /* block col. index */ 778 rtmp_ptr = rtmp + vj*bs2; 779 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 780 } 781 782 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 783 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 784 i = jl[k]; /* first row to be added to k_th row */ 785 786 while (i < k) { 787 nexti = jl[i]; /* next row to be added to k_th row */ 788 789 /* compute multiplier */ 790 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 791 792 /* uik = -inv(Di)*U_bar(i,k) */ 793 diag = ba + i*bs2; 794 u = ba + ili*bs2; 795 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 796 PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 797 798 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 799 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 800 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 801 802 /* update -U(i,k) */ 803 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 804 805 /* add multiple of row i to k-th row ... */ 806 jmin = ili + 1; jmax = bi[i+1]; 807 if (jmin < jmax) { 808 for (j=jmin; j<jmax; j++) { 809 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 810 rtmp_ptr = rtmp + bj[j]*bs2; 811 u = ba + j*bs2; 812 PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 813 } 814 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 815 816 /* ... add i to row list for next nonzero entry */ 817 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 818 j = bj[jmin]; 819 jl[i] = jl[j]; jl[j] = i; /* update jl */ 820 } 821 i = nexti; 822 } 823 824 /* save nonzero entries in k-th row of U ... */ 825 826 /* invert diagonal block */ 827 diag = ba+k*bs2; 828 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 829 ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 830 831 jmin = bi[k]; jmax = bi[k+1]; 832 if (jmin < jmax) { 833 for (j=jmin; j<jmax; j++) { 834 vj = bj[j]; /* block col. index of U */ 835 u = ba + j*bs2; 836 rtmp_ptr = rtmp + vj*bs2; 837 for (k1=0; k1<bs2; k1++) { 838 *u++ = *rtmp_ptr; 839 *rtmp_ptr++ = 0.0; 840 } 841 } 842 843 /* ... add k to row list for first nonzero entry in k-th row */ 844 il[k] = jmin; 845 i = bj[jmin]; 846 jl[k] = jl[i]; jl[i] = k; 847 } 848 } 849 850 ierr = PetscFree(rtmp);CHKERRQ(ierr); 851 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 852 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 853 ierr = PetscFree(pivots);CHKERRQ(ierr); 854 855 C->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 856 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 857 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 858 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 859 C->assembled = PETSC_TRUE; 860 C->preallocated = PETSC_TRUE; 861 862 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 863 PetscFunctionReturn(0); 864 } 865 866 /* 867 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 868 Version for blocks 2 by 2. 869 */ 870 #undef __FUNCT__ 871 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 872 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info) 873 { 874 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 875 IS perm = b->row; 876 PetscErrorCode ierr; 877 const PetscInt *ai,*aj,*perm_ptr; 878 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 879 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 880 MatScalar *ba = b->a,*aa,*ap; 881 MatScalar *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4]; 882 PetscReal shift = info->shiftamount; 883 884 PetscFunctionBegin; 885 /* initialization */ 886 /* il and jl record the first nonzero element in each row of the accessing 887 window U(0:k, k:mbs-1). 888 jl: list of rows to be added to uneliminated rows 889 i>= k: jl(i) is the first row to be added to row i 890 i< k: jl(i) is the row following row i in some list of rows 891 jl(i) = mbs indicates the end of a list 892 il(i): points to the first nonzero element in columns k,...,mbs-1 of 893 row i of U */ 894 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 895 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 896 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 897 for (i=0; i<mbs; i++) { 898 jl[i] = mbs; il[0] = 0; 899 } 900 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 901 902 /* check permutation */ 903 if (!a->permute) { 904 ai = a->i; aj = a->j; aa = a->a; 905 } else { 906 ai = a->inew; aj = a->jnew; 907 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 908 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 909 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 910 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 911 912 for (i=0; i<mbs; i++) { 913 jmin = ai[i]; jmax = ai[i+1]; 914 for (j=jmin; j<jmax; j++) { 915 while (a2anew[j] != j) { 916 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 917 for (k1=0; k1<4; k1++) { 918 dk[k1] = aa[k*4+k1]; 919 aa[k*4+k1] = aa[j*4+k1]; 920 aa[j*4+k1] = dk[k1]; 921 } 922 } 923 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 924 if (i > aj[j]) { 925 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 926 ap = aa + j*4; /* ptr to the beginning of the block */ 927 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 928 ap[1] = ap[2]; 929 ap[2] = dk[1]; 930 } 931 } 932 } 933 ierr = PetscFree(a2anew);CHKERRQ(ierr); 934 } 935 936 /* for each row k */ 937 for (k = 0; k<mbs; k++) { 938 939 /*initialize k-th row with elements nonzero in row perm(k) of A */ 940 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 941 ap = aa + jmin*4; 942 for (j = jmin; j < jmax; j++) { 943 vj = perm_ptr[aj[j]]; /* block col. index */ 944 rtmp_ptr = rtmp + vj*4; 945 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 946 } 947 948 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 949 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 950 i = jl[k]; /* first row to be added to k_th row */ 951 952 while (i < k) { 953 nexti = jl[i]; /* next row to be added to k_th row */ 954 955 /* compute multiplier */ 956 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 957 958 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 959 diag = ba + i*4; 960 u = ba + ili*4; 961 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 962 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 963 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 964 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 965 966 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 967 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 968 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 969 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 970 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 971 972 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 973 974 /* update -U(i,k): ba[ili] = uik */ 975 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 976 977 /* add multiple of row i to k-th row ... */ 978 jmin = ili + 1; jmax = bi[i+1]; 979 if (jmin < jmax) { 980 for (j=jmin; j<jmax; j++) { 981 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 982 rtmp_ptr = rtmp + bj[j]*4; 983 u = ba + j*4; 984 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 985 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 986 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 987 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 988 } 989 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 990 991 /* ... add i to row list for next nonzero entry */ 992 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 993 j = bj[jmin]; 994 jl[i] = jl[j]; jl[j] = i; /* update jl */ 995 } 996 i = nexti; 997 } 998 999 /* save nonzero entries in k-th row of U ... */ 1000 1001 /* invert diagonal block */ 1002 diag = ba+k*4; 1003 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1004 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1005 1006 jmin = bi[k]; jmax = bi[k+1]; 1007 if (jmin < jmax) { 1008 for (j=jmin; j<jmax; j++) { 1009 vj = bj[j]; /* block col. index of U */ 1010 u = ba + j*4; 1011 rtmp_ptr = rtmp + vj*4; 1012 for (k1=0; k1<4; k1++) { 1013 *u++ = *rtmp_ptr; 1014 *rtmp_ptr++ = 0.0; 1015 } 1016 } 1017 1018 /* ... add k to row list for first nonzero entry in k-th row */ 1019 il[k] = jmin; 1020 i = bj[jmin]; 1021 jl[k] = jl[i]; jl[i] = k; 1022 } 1023 } 1024 1025 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1026 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1027 if (a->permute) { 1028 ierr = PetscFree(aa);CHKERRQ(ierr); 1029 } 1030 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 1031 1032 C->ops->solve = MatSolve_SeqSBAIJ_2_inplace; 1033 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace; 1034 C->assembled = PETSC_TRUE; 1035 C->preallocated = PETSC_TRUE; 1036 1037 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1038 PetscFunctionReturn(0); 1039 } 1040 1041 /* 1042 Version for when blocks are 2 by 2 Using natural ordering 1043 */ 1044 #undef __FUNCT__ 1045 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 1046 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 1047 { 1048 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data; 1049 PetscErrorCode ierr; 1050 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1051 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1052 MatScalar *ba = b->a,*aa,*ap,dk[8],uik[8]; 1053 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1054 PetscReal shift = info->shiftamount; 1055 1056 PetscFunctionBegin; 1057 /* initialization */ 1058 /* il and jl record the first nonzero element in each row of the accessing 1059 window U(0:k, k:mbs-1). 1060 jl: list of rows to be added to uneliminated rows 1061 i>= k: jl(i) is the first row to be added to row i 1062 i< k: jl(i) is the row following row i in some list of rows 1063 jl(i) = mbs indicates the end of a list 1064 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1065 row i of U */ 1066 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1067 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1068 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1069 for (i=0; i<mbs; i++) { 1070 jl[i] = mbs; il[0] = 0; 1071 } 1072 ai = a->i; aj = a->j; aa = a->a; 1073 1074 /* for each row k */ 1075 for (k = 0; k<mbs; k++) { 1076 1077 /*initialize k-th row with elements nonzero in row k of A */ 1078 jmin = ai[k]; jmax = ai[k+1]; 1079 ap = aa + jmin*4; 1080 for (j = jmin; j < jmax; j++) { 1081 vj = aj[j]; /* block col. index */ 1082 rtmp_ptr = rtmp + vj*4; 1083 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1084 } 1085 1086 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1087 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1088 i = jl[k]; /* first row to be added to k_th row */ 1089 1090 while (i < k) { 1091 nexti = jl[i]; /* next row to be added to k_th row */ 1092 1093 /* compute multiplier */ 1094 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1095 1096 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1097 diag = ba + i*4; 1098 u = ba + ili*4; 1099 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1100 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1101 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1102 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1103 1104 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1105 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1106 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1107 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1108 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1109 1110 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 1111 1112 /* update -U(i,k): ba[ili] = uik */ 1113 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1114 1115 /* add multiple of row i to k-th row ... */ 1116 jmin = ili + 1; jmax = bi[i+1]; 1117 if (jmin < jmax) { 1118 for (j=jmin; j<jmax; j++) { 1119 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1120 rtmp_ptr = rtmp + bj[j]*4; 1121 u = ba + j*4; 1122 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1123 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1124 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1125 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1126 } 1127 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 1128 1129 /* ... add i to row list for next nonzero entry */ 1130 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1131 j = bj[jmin]; 1132 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1133 } 1134 i = nexti; 1135 } 1136 1137 /* save nonzero entries in k-th row of U ... */ 1138 1139 /* invert diagonal block */ 1140 diag = ba+k*4; 1141 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1142 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1143 1144 jmin = bi[k]; jmax = bi[k+1]; 1145 if (jmin < jmax) { 1146 for (j=jmin; j<jmax; j++) { 1147 vj = bj[j]; /* block col. index of U */ 1148 u = ba + j*4; 1149 rtmp_ptr = rtmp + vj*4; 1150 for (k1=0; k1<4; k1++) { 1151 *u++ = *rtmp_ptr; 1152 *rtmp_ptr++ = 0.0; 1153 } 1154 } 1155 1156 /* ... add k to row list for first nonzero entry in k-th row */ 1157 il[k] = jmin; 1158 i = bj[jmin]; 1159 jl[k] = jl[i]; jl[i] = k; 1160 } 1161 } 1162 1163 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1164 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1165 1166 C->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1167 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1168 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1169 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1170 C->assembled = PETSC_TRUE; 1171 C->preallocated = PETSC_TRUE; 1172 1173 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1174 PetscFunctionReturn(0); 1175 } 1176 1177 /* 1178 Numeric U^T*D*U factorization for SBAIJ format. 1179 Version for blocks are 1 by 1. 1180 */ 1181 #undef __FUNCT__ 1182 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace" 1183 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 1184 { 1185 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1186 IS ip=b->row; 1187 PetscErrorCode ierr; 1188 const PetscInt *ai,*aj,*rip; 1189 PetscInt *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1190 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1191 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1192 PetscReal rs; 1193 FactorShiftCtx sctx; 1194 1195 PetscFunctionBegin; 1196 /* MatPivotSetUp(): initialize shift context sctx */ 1197 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1198 1199 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1200 if (!a->permute) { 1201 ai = a->i; aj = a->j; aa = a->a; 1202 } else { 1203 ai = a->inew; aj = a->jnew; 1204 nz = ai[mbs]; 1205 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1206 a2anew = a->a2anew; 1207 bval = a->a; 1208 for (j=0; j<nz; j++) { 1209 aa[a2anew[j]] = *(bval++); 1210 } 1211 } 1212 1213 /* initialization */ 1214 /* il and jl record the first nonzero element in each row of the accessing 1215 window U(0:k, k:mbs-1). 1216 jl: list of rows to be added to uneliminated rows 1217 i>= k: jl(i) is the first row to be added to row i 1218 i< k: jl(i) is the row following row i in some list of rows 1219 jl(i) = mbs indicates the end of a list 1220 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1221 row i of U */ 1222 ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1223 1224 do { 1225 sctx.newshift = PETSC_FALSE; 1226 for (i=0; i<mbs; i++) { 1227 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1228 } 1229 1230 for (k = 0; k<mbs; k++) { 1231 /*initialize k-th row by the perm[k]-th row of A */ 1232 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1233 bval = ba + bi[k]; 1234 for (j = jmin; j < jmax; j++) { 1235 col = rip[aj[j]]; 1236 rtmp[col] = aa[j]; 1237 *bval++ = 0.0; /* for in-place factorization */ 1238 } 1239 1240 /* shift the diagonal of the matrix */ 1241 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1242 1243 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1244 dk = rtmp[k]; 1245 i = jl[k]; /* first row to be added to k_th row */ 1246 1247 while (i < k) { 1248 nexti = jl[i]; /* next row to be added to k_th row */ 1249 1250 /* compute multiplier, update diag(k) and U(i,k) */ 1251 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1252 uikdi = -ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1253 dk += uikdi*ba[ili]; 1254 ba[ili] = uikdi; /* -U(i,k) */ 1255 1256 /* add multiple of row i to k-th row */ 1257 jmin = ili + 1; jmax = bi[i+1]; 1258 if (jmin < jmax) { 1259 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1260 ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr); 1261 1262 /* update il and jl for row i */ 1263 il[i] = jmin; 1264 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1265 } 1266 i = nexti; 1267 } 1268 1269 /* shift the diagonals when zero pivot is detected */ 1270 /* compute rs=sum of abs(off-diagonal) */ 1271 rs = 0.0; 1272 jmin = bi[k]+1; 1273 nz = bi[k+1] - jmin; 1274 if (nz) { 1275 bcol = bj + jmin; 1276 while (nz--) { 1277 rs += PetscAbsScalar(rtmp[*bcol]); 1278 bcol++; 1279 } 1280 } 1281 1282 sctx.rs = rs; 1283 sctx.pv = dk; 1284 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1285 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1286 dk = sctx.pv; 1287 1288 /* copy data into U(k,:) */ 1289 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1290 jmin = bi[k]+1; jmax = bi[k+1]; 1291 if (jmin < jmax) { 1292 for (j=jmin; j<jmax; j++) { 1293 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1294 } 1295 /* add the k-th row into il and jl */ 1296 il[k] = jmin; 1297 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1298 } 1299 } 1300 } while (sctx.newshift); 1301 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 1302 if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);} 1303 1304 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1305 1306 C->ops->solve = MatSolve_SeqSBAIJ_1_inplace; 1307 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1308 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace; 1309 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace; 1310 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace; 1311 C->assembled = PETSC_TRUE; 1312 C->preallocated = PETSC_TRUE; 1313 1314 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1315 if (sctx.nshift) { 1316 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1317 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1318 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1319 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1320 } 1321 } 1322 PetscFunctionReturn(0); 1323 } 1324 1325 /* 1326 Version for when blocks are 1 by 1 Using natural ordering under new datastructure 1327 Modified from MatCholeskyFactorNumeric_SeqAIJ() 1328 */ 1329 #undef __FUNCT__ 1330 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1331 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 1332 { 1333 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 1334 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)B->data; 1335 PetscErrorCode ierr; 1336 PetscInt i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp; 1337 PetscInt *ai=a->i,*aj=a->j,*ajtmp; 1338 PetscInt k,jmin,jmax,*c2r,*il,col,nexti,ili,nz; 1339 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 1340 FactorShiftCtx sctx; 1341 PetscReal rs; 1342 MatScalar d,*v; 1343 1344 PetscFunctionBegin; 1345 ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&c2r);CHKERRQ(ierr); 1346 1347 /* MatPivotSetUp(): initialize shift context sctx */ 1348 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1349 1350 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */ 1351 sctx.shift_top = info->zeropivot; 1352 1353 ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr); 1354 1355 for (i=0; i<mbs; i++) { 1356 /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */ 1357 d = (aa)[a->diag[i]]; 1358 rtmp[i] += -PetscRealPart(d); /* diagonal entry */ 1359 ajtmp = aj + ai[i] + 1; /* exclude diagonal */ 1360 v = aa + ai[i] + 1; 1361 nz = ai[i+1] - ai[i] - 1; 1362 for (j=0; j<nz; j++) { 1363 rtmp[i] += PetscAbsScalar(v[j]); 1364 rtmp[ajtmp[j]] += PetscAbsScalar(v[j]); 1365 } 1366 if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]); 1367 } 1368 sctx.shift_top *= 1.1; 1369 sctx.nshift_max = 5; 1370 sctx.shift_lo = 0.; 1371 sctx.shift_hi = 1.; 1372 } 1373 1374 /* allocate working arrays 1375 c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col 1376 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 1377 */ 1378 do { 1379 sctx.newshift = PETSC_FALSE; 1380 1381 for (i=0; i<mbs; i++) c2r[i] = mbs; 1382 if (mbs) il[0] = 0; 1383 1384 for (k = 0; k<mbs; k++) { 1385 /* zero rtmp */ 1386 nz = bi[k+1] - bi[k]; 1387 bjtmp = bj + bi[k]; 1388 for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0; 1389 1390 /* load in initial unfactored row */ 1391 bval = ba + bi[k]; 1392 jmin = ai[k]; jmax = ai[k+1]; 1393 for (j = jmin; j < jmax; j++) { 1394 col = aj[j]; 1395 rtmp[col] = aa[j]; 1396 *bval++ = 0.0; /* for in-place factorization */ 1397 } 1398 /* shift the diagonal of the matrix: ZeropivotApply() */ 1399 rtmp[k] += sctx.shift_amount; /* shift the diagonal of the matrix */ 1400 1401 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1402 dk = rtmp[k]; 1403 i = c2r[k]; /* first row to be added to k_th row */ 1404 1405 while (i < k) { 1406 nexti = c2r[i]; /* next row to be added to k_th row */ 1407 1408 /* compute multiplier, update diag(k) and U(i,k) */ 1409 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1410 uikdi = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */ 1411 dk += uikdi*ba[ili]; /* update diag[k] */ 1412 ba[ili] = uikdi; /* -U(i,k) */ 1413 1414 /* add multiple of row i to k-th row */ 1415 jmin = ili + 1; jmax = bi[i+1]; 1416 if (jmin < jmax) { 1417 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1418 /* update il and c2r for row i */ 1419 il[i] = jmin; 1420 j = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i; 1421 } 1422 i = nexti; 1423 } 1424 1425 /* copy data into U(k,:) */ 1426 rs = 0.0; 1427 jmin = bi[k]; jmax = bi[k+1]-1; 1428 if (jmin < jmax) { 1429 for (j=jmin; j<jmax; j++) { 1430 col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]); 1431 } 1432 /* add the k-th row into il and c2r */ 1433 il[k] = jmin; 1434 i = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k; 1435 } 1436 1437 sctx.rs = rs; 1438 sctx.pv = dk; 1439 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1440 if (sctx.newshift) break; 1441 dk = sctx.pv; 1442 1443 ba[bdiag[k]] = 1.0/dk; /* U(k,k) */ 1444 } 1445 } while (sctx.newshift); 1446 1447 ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr); 1448 1449 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1450 B->ops->solves = MatSolves_SeqSBAIJ_1; 1451 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1452 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 1453 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 1454 1455 B->assembled = PETSC_TRUE; 1456 B->preallocated = PETSC_TRUE; 1457 1458 ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr); 1459 1460 /* MatPivotView() */ 1461 if (sctx.nshift) { 1462 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1463 ierr = PetscInfo4(A,"number of shift_pd tries %D, shift_amount %G, diagonal shifted up by %e fraction top_value %e\n",sctx.nshift,sctx.shift_amount,sctx.shift_fraction,sctx.shift_top);CHKERRQ(ierr); 1464 } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1465 ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1466 } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) { 1467 ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %G\n",sctx.nshift,info->shiftamount);CHKERRQ(ierr); 1468 } 1469 } 1470 PetscFunctionReturn(0); 1471 } 1472 1473 #undef __FUNCT__ 1474 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace" 1475 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 1476 { 1477 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data; 1478 PetscErrorCode ierr; 1479 PetscInt i,j,mbs = a->mbs; 1480 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1481 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1482 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1483 PetscReal rs; 1484 FactorShiftCtx sctx; 1485 1486 PetscFunctionBegin; 1487 /* MatPivotSetUp(): initialize shift context sctx */ 1488 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1489 1490 /* initialization */ 1491 /* il and jl record the first nonzero element in each row of the accessing 1492 window U(0:k, k:mbs-1). 1493 jl: list of rows to be added to uneliminated rows 1494 i>= k: jl(i) is the first row to be added to row i 1495 i< k: jl(i) is the row following row i in some list of rows 1496 jl(i) = mbs indicates the end of a list 1497 il(i): points to the first nonzero element in U(i,k:mbs-1) 1498 */ 1499 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1500 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1501 1502 do { 1503 sctx.newshift = PETSC_FALSE; 1504 for (i=0; i<mbs; i++) { 1505 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1506 } 1507 1508 for (k = 0; k<mbs; k++) { 1509 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1510 nz = ai[k+1] - ai[k]; 1511 acol = aj + ai[k]; 1512 aval = aa + ai[k]; 1513 bval = ba + bi[k]; 1514 while (nz--) { 1515 rtmp[*acol++] = *aval++; 1516 *bval++ = 0.0; /* for in-place factorization */ 1517 } 1518 1519 /* shift the diagonal of the matrix */ 1520 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1521 1522 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1523 dk = rtmp[k]; 1524 i = jl[k]; /* first row to be added to k_th row */ 1525 1526 while (i < k) { 1527 nexti = jl[i]; /* next row to be added to k_th row */ 1528 /* compute multiplier, update D(k) and U(i,k) */ 1529 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1530 uikdi = -ba[ili]*ba[bi[i]]; 1531 dk += uikdi*ba[ili]; 1532 ba[ili] = uikdi; /* -U(i,k) */ 1533 1534 /* add multiple of row i to k-th row ... */ 1535 jmin = ili + 1; 1536 nz = bi[i+1] - jmin; 1537 if (nz > 0) { 1538 bcol = bj + jmin; 1539 bval = ba + jmin; 1540 ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr); 1541 while (nz--) rtmp[*bcol++] += uikdi*(*bval++); 1542 1543 /* update il and jl for i-th row */ 1544 il[i] = jmin; 1545 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1546 } 1547 i = nexti; 1548 } 1549 1550 /* shift the diagonals when zero pivot is detected */ 1551 /* compute rs=sum of abs(off-diagonal) */ 1552 rs = 0.0; 1553 jmin = bi[k]+1; 1554 nz = bi[k+1] - jmin; 1555 if (nz) { 1556 bcol = bj + jmin; 1557 while (nz--) { 1558 rs += PetscAbsScalar(rtmp[*bcol]); 1559 bcol++; 1560 } 1561 } 1562 1563 sctx.rs = rs; 1564 sctx.pv = dk; 1565 ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr); 1566 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1567 dk = sctx.pv; 1568 1569 /* copy data into U(k,:) */ 1570 ba[bi[k]] = 1.0/dk; 1571 jmin = bi[k]+1; 1572 nz = bi[k+1] - jmin; 1573 if (nz) { 1574 bcol = bj + jmin; 1575 bval = ba + jmin; 1576 while (nz--) { 1577 *bval++ = rtmp[*bcol]; 1578 rtmp[*bcol++] = 0.0; 1579 } 1580 /* add k-th row into il and jl */ 1581 il[k] = jmin; 1582 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1583 } 1584 } /* end of for (k = 0; k<mbs; k++) */ 1585 } while (sctx.newshift); 1586 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1587 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1588 1589 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1590 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1591 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1592 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1593 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1594 1595 C->assembled = PETSC_TRUE; 1596 C->preallocated = PETSC_TRUE; 1597 1598 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1599 if (sctx.nshift) { 1600 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1601 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1602 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1603 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1604 } 1605 } 1606 PetscFunctionReturn(0); 1607 } 1608 1609 #undef __FUNCT__ 1610 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1611 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info) 1612 { 1613 PetscErrorCode ierr; 1614 Mat C; 1615 1616 PetscFunctionBegin; 1617 ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr); 1618 ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr); 1619 ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr); 1620 1621 A->ops->solve = C->ops->solve; 1622 A->ops->solvetranspose = C->ops->solvetranspose; 1623 1624 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1625 PetscFunctionReturn(0); 1626 } 1627 1628 1629