1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/baij/seq/baij.h" 4 #include "../src/mat/impls/sbaij/seq/sbaij.h" 5 #include "../src/mat/blockinvert.h" 6 #include "petscis.h" 7 8 /* 9 input: 10 F -- numeric factor 11 output: 12 nneg, nzero, npos: matrix inertia 13 */ 14 15 #undef __FUNCT__ 16 #define __FUNCT__ "MatGetInertia_SeqSBAIJ" 17 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos) 18 { 19 Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data; 20 MatScalar *dd = fact_ptr->a; 21 PetscInt mbs=fact_ptr->mbs,bs=F->rmap->bs,i,nneig_tmp,npos_tmp,*fi = fact_ptr->diag; 22 23 PetscFunctionBegin; 24 if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for bs: %D >1 yet",bs); 25 nneig_tmp = 0; npos_tmp = 0; 26 for (i=0; i<mbs; i++){ 27 if (PetscRealPart(dd[*fi]) > 0.0){ 28 npos_tmp++; 29 } else if (PetscRealPart(dd[*fi]) < 0.0){ 30 nneig_tmp++; 31 } 32 fi++; 33 } 34 if (nneig) *nneig = nneig_tmp; 35 if (npos) *npos = npos_tmp; 36 if (nzero) *nzero = mbs - nneig_tmp - npos_tmp; 37 38 PetscFunctionReturn(0); 39 } 40 41 /* 42 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 43 Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad. 44 */ 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR" 47 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat F,Mat A,IS perm,const MatFactorInfo *info) 48 { 49 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 50 PetscErrorCode ierr; 51 const PetscInt *rip,*ai,*aj; 52 PetscInt i,mbs = a->mbs,*jutmp,bs = A->rmap->bs,bs2=a->bs2; 53 PetscInt m,reallocs = 0,prow; 54 PetscInt *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 55 PetscReal f = info->fill; 56 PetscBool perm_identity; 57 58 PetscFunctionBegin; 59 /* check whether perm is the identity mapping */ 60 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 61 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 62 63 if (perm_identity){ /* without permutation */ 64 a->permute = PETSC_FALSE; 65 ai = a->i; aj = a->j; 66 } else { /* non-trivial permutation */ 67 a->permute = PETSC_TRUE; 68 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 69 ai = a->inew; aj = a->jnew; 70 } 71 72 /* initialization */ 73 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&iu);CHKERRQ(ierr); 74 umax = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1; 75 ierr = PetscMalloc(umax*sizeof(PetscInt),&ju);CHKERRQ(ierr); 76 iu[0] = mbs+1; 77 juidx = mbs + 1; /* index for ju */ 78 /* jl linked list for pivot row -- linked list for col index */ 79 ierr = PetscMalloc2(mbs,PetscInt,&jl,mbs,PetscInt,&q);CHKERRQ(ierr); 80 for (i=0; i<mbs; i++){ 81 jl[i] = mbs; 82 q[i] = 0; 83 } 84 85 /* for each row k */ 86 for (k=0; k<mbs; k++){ 87 for (i=0; i<mbs; i++) q[i] = 0; /* to be removed! */ 88 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 89 q[k] = mbs; 90 /* initialize nonzero structure of k-th row to row rip[k] of A */ 91 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 92 jmax = ai[rip[k]+1]; 93 for (j=jmin; j<jmax; j++){ 94 vj = rip[aj[j]]; /* col. value */ 95 if(vj > k){ 96 qm = k; 97 do { 98 m = qm; qm = q[m]; 99 } while(qm < vj); 100 if (qm == vj) { 101 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Duplicate entry in A\n"); 102 } 103 nzk++; 104 q[m] = vj; 105 q[vj] = qm; 106 } /* if(vj > k) */ 107 } /* for (j=jmin; j<jmax; j++) */ 108 109 /* modify nonzero structure of k-th row by computing fill-in 110 for each row i to be merged in */ 111 prow = k; 112 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 113 114 while (prow < k){ 115 /* merge row prow into k-th row */ 116 jmin = iu[prow] + 1; jmax = iu[prow+1]; 117 qm = k; 118 for (j=jmin; j<jmax; j++){ 119 vj = ju[j]; 120 do { 121 m = qm; qm = q[m]; 122 } while (qm < vj); 123 if (qm != vj){ 124 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 125 } 126 } 127 prow = jl[prow]; /* next pivot row */ 128 } 129 130 /* add k to row list for first nonzero element in k-th row */ 131 if (nzk > 0){ 132 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 133 jl[k] = jl[i]; jl[i] = k; 134 } 135 iu[k+1] = iu[k] + nzk; 136 137 /* allocate more space to ju if needed */ 138 if (iu[k+1] > umax) { 139 /* estimate how much additional space we will need */ 140 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 141 /* just double the memory each time */ 142 maxadd = umax; 143 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 144 umax += maxadd; 145 146 /* allocate a longer ju */ 147 ierr = PetscMalloc(umax*sizeof(PetscInt),&jutmp);CHKERRQ(ierr); 148 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr); 149 ierr = PetscFree(ju);CHKERRQ(ierr); 150 ju = jutmp; 151 reallocs++; /* count how many times we realloc */ 152 } 153 154 /* save nonzero structure of k-th row in ju */ 155 i=k; 156 while (nzk --) { 157 i = q[i]; 158 ju[juidx++] = i; 159 } 160 } 161 162 #if defined(PETSC_USE_INFO) 163 if (ai[mbs] != 0) { 164 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 165 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr); 166 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 167 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr); 168 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 169 } else { 170 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 171 } 172 #endif 173 174 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 175 ierr = PetscFree2(jl,q);CHKERRQ(ierr); 176 177 /* put together the new matrix */ 178 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(F,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 179 180 /* ierr = PetscLogObjectParent(B,iperm);CHKERRQ(ierr); */ 181 b = (Mat_SeqSBAIJ*)(F)->data; 182 b->singlemalloc = PETSC_FALSE; 183 b->free_a = PETSC_TRUE; 184 b->free_ij = PETSC_TRUE; 185 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 186 b->j = ju; 187 b->i = iu; 188 b->diag = 0; 189 b->ilen = 0; 190 b->imax = 0; 191 b->row = perm; 192 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 193 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 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 current_space->array += nzk; 321 current_space->local_used += nzk; 322 current_space->local_remaining -= nzk; 323 324 ui[k+1] = ui[k] + nzk; 325 } 326 327 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 328 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 329 330 /* destroy list of free space and other temporary array(s) */ 331 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 332 ierr = PetscFreeSpaceContiguous_Cholesky(&free_space,uj,mbs,ui,udiag);CHKERRQ(ierr); /* store matrix factor */ 333 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 334 335 /* put together the new matrix in MATSEQSBAIJ format */ 336 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 337 338 b = (Mat_SeqSBAIJ*)fact->data; 339 b->singlemalloc = PETSC_FALSE; 340 b->free_a = PETSC_TRUE; 341 b->free_ij = PETSC_TRUE; 342 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 343 b->j = uj; 344 b->i = ui; 345 b->diag = udiag; 346 b->free_diag = PETSC_TRUE; 347 b->ilen = 0; 348 b->imax = 0; 349 b->row = perm; 350 b->icol = perm; 351 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 352 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 353 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 354 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 355 ierr = PetscLogObjectMemory(fact,ui[mbs]*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 356 b->maxnz = b->nz = ui[mbs]; 357 358 fact->info.factor_mallocs = reallocs; 359 fact->info.fill_ratio_given = fill; 360 if (ai[mbs] != 0) { 361 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 362 } else { 363 fact->info.fill_ratio_needed = 0.0; 364 } 365 #if defined(PETSC_USE_INFO) 366 if (ai[mbs] != 0) { 367 PetscReal af = fact->info.fill_ratio_needed; 368 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 369 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 370 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 371 } else { 372 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 373 } 374 #endif 375 fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 376 PetscFunctionReturn(0); 377 } 378 379 #undef __FUNCT__ 380 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_inplace" 381 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(Mat fact,Mat A,IS perm,const MatFactorInfo *info) 382 { 383 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 384 Mat_SeqSBAIJ *b; 385 PetscErrorCode ierr; 386 PetscBool perm_identity,missing; 387 PetscReal fill = info->fill; 388 const PetscInt *rip,*ai,*aj; 389 PetscInt i,mbs=a->mbs,bs=A->rmap->bs,reallocs=0,prow,d; 390 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 391 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr; 392 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 393 PetscBT lnkbt; 394 395 PetscFunctionBegin; 396 ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr); 397 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d); 398 399 /* 400 This code originally uses Modified Sparse Row (MSR) storage 401 (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise! 402 Then it is rewritten so the factor B takes seqsbaij format. However the associated 403 MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity, 404 thus the original code in MSR format is still used for these cases. 405 The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever 406 MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor. 407 */ 408 if (bs > 1){ 409 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(fact,A,perm,info);CHKERRQ(ierr); 410 PetscFunctionReturn(0); 411 } 412 413 /* check whether perm is the identity mapping */ 414 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 415 416 if (perm_identity){ 417 a->permute = PETSC_FALSE; 418 ai = a->i; aj = a->j; 419 } else { 420 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 421 /* There are bugs for reordeing. Needs further work. 422 MatReordering for sbaij cannot be efficient. User should use aij formt! */ 423 a->permute = PETSC_TRUE; 424 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 425 ai = a->inew; aj = a->jnew; 426 } 427 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 428 429 /* initialization */ 430 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 431 ui[0] = 0; 432 433 /* jl: linked list for storing indices of the pivot rows 434 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 435 ierr = PetscMalloc4(mbs,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&cols);CHKERRQ(ierr); 436 for (i=0; i<mbs; i++){ 437 jl[i] = mbs; il[i] = 0; 438 } 439 440 /* create and initialize a linked list for storing column indices of the active row k */ 441 nlnk = mbs + 1; 442 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 443 444 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 445 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 446 current_space = free_space; 447 448 for (k=0; k<mbs; k++){ /* for each active row k */ 449 /* initialize lnk by the column indices of row rip[k] of A */ 450 nzk = 0; 451 ncols = ai[rip[k]+1] - ai[rip[k]]; 452 for (j=0; j<ncols; j++){ 453 i = *(aj + ai[rip[k]] + j); 454 cols[j] = rip[i]; 455 } 456 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 457 nzk += nlnk; 458 459 /* update lnk by computing fill-in for each pivot row to be merged in */ 460 prow = jl[k]; /* 1st pivot row */ 461 462 while (prow < k){ 463 nextprow = jl[prow]; 464 /* merge prow into k-th row */ 465 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 466 jmax = ui[prow+1]; 467 ncols = jmax-jmin; 468 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 469 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 470 nzk += nlnk; 471 472 /* update il and jl for prow */ 473 if (jmin < jmax){ 474 il[prow] = jmin; 475 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 476 } 477 prow = nextprow; 478 } 479 480 /* if free space is not available, make more free space */ 481 if (current_space->local_remaining<nzk) { 482 i = mbs - k + 1; /* num of unfactored rows */ 483 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 484 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 485 reallocs++; 486 } 487 488 /* copy data into free space, then initialize lnk */ 489 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 490 491 /* add the k-th row into il and jl */ 492 if (nzk-1 > 0){ 493 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 494 jl[k] = jl[i]; jl[i] = k; 495 il[k] = ui[k] + 1; 496 } 497 ui_ptr[k] = current_space->array; 498 current_space->array += nzk; 499 current_space->local_used += nzk; 500 current_space->local_remaining -= nzk; 501 502 ui[k+1] = ui[k] + nzk; 503 } 504 505 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 506 ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr); 507 508 /* destroy list of free space and other temporary array(s) */ 509 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 510 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 511 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 512 513 /* put together the new matrix in MATSEQSBAIJ format */ 514 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 515 516 b = (Mat_SeqSBAIJ*)fact->data; 517 b->singlemalloc = PETSC_FALSE; 518 b->free_a = PETSC_TRUE; 519 b->free_ij = PETSC_TRUE; 520 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 521 b->j = uj; 522 b->i = ui; 523 b->diag = 0; 524 b->ilen = 0; 525 b->imax = 0; 526 b->row = perm; 527 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 528 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 529 b->icol = perm; 530 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 531 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 532 ierr = PetscLogObjectMemory(fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 533 b->maxnz = b->nz = ui[mbs]; 534 535 fact->info.factor_mallocs = reallocs; 536 fact->info.fill_ratio_given = fill; 537 if (ai[mbs] != 0) { 538 fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs]; 539 } else { 540 fact->info.fill_ratio_needed = 0.0; 541 } 542 #if defined(PETSC_USE_INFO) 543 if (ai[mbs] != 0) { 544 PetscReal af = fact->info.fill_ratio_needed; 545 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 546 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 547 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 548 } else { 549 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 550 } 551 #endif 552 ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr); 553 PetscFunctionReturn(0); 554 } 555 556 #undef __FUNCT__ 557 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 558 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info) 559 { 560 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 561 IS perm = b->row; 562 PetscErrorCode ierr; 563 const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j; 564 PetscInt i,j; 565 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 566 PetscInt bs=A->rmap->bs,bs2 = a->bs2,bslog = 0; 567 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 568 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 569 MatScalar *work; 570 PetscInt *pivots; 571 572 PetscFunctionBegin; 573 /* initialization */ 574 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 575 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 576 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 577 for (i=0; i<mbs; i++) { 578 jl[i] = mbs; il[0] = 0; 579 } 580 ierr = PetscMalloc3(bs2,MatScalar,&dk,bs2,MatScalar,&uik,bs,MatScalar,&work);CHKERRQ(ierr); 581 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 582 583 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 584 585 /* check permutation */ 586 if (!a->permute){ 587 ai = a->i; aj = a->j; aa = a->a; 588 } else { 589 ai = a->inew; aj = a->jnew; 590 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 591 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 592 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 593 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 594 595 /* flops in while loop */ 596 bslog = 2*bs*bs2; 597 598 for (i=0; i<mbs; i++){ 599 jmin = ai[i]; jmax = ai[i+1]; 600 for (j=jmin; j<jmax; j++){ 601 while (a2anew[j] != j){ 602 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 603 for (k1=0; k1<bs2; k1++){ 604 dk[k1] = aa[k*bs2+k1]; 605 aa[k*bs2+k1] = aa[j*bs2+k1]; 606 aa[j*bs2+k1] = dk[k1]; 607 } 608 } 609 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 610 if (i > aj[j]){ 611 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 612 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 613 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 614 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 615 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 616 } 617 } 618 } 619 } 620 ierr = PetscFree(a2anew);CHKERRQ(ierr); 621 } 622 623 /* for each row k */ 624 for (k = 0; k<mbs; k++){ 625 626 /*initialize k-th row with elements nonzero in row perm(k) of A */ 627 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 628 629 ap = aa + jmin*bs2; 630 for (j = jmin; j < jmax; j++){ 631 vj = perm_ptr[aj[j]]; /* block col. index */ 632 rtmp_ptr = rtmp + vj*bs2; 633 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 634 } 635 636 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 637 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 638 i = jl[k]; /* first row to be added to k_th row */ 639 640 while (i < k){ 641 nexti = jl[i]; /* next row to be added to k_th row */ 642 643 /* compute multiplier */ 644 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 645 646 /* uik = -inv(Di)*U_bar(i,k) */ 647 diag = ba + i*bs2; 648 u = ba + ili*bs2; 649 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 650 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 651 652 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 653 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 654 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 655 656 /* update -U(i,k) */ 657 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 658 659 /* add multiple of row i to k-th row ... */ 660 jmin = ili + 1; jmax = bi[i+1]; 661 if (jmin < jmax){ 662 for (j=jmin; j<jmax; j++) { 663 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 664 rtmp_ptr = rtmp + bj[j]*bs2; 665 u = ba + j*bs2; 666 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 667 } 668 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 669 670 /* ... add i to row list for next nonzero entry */ 671 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 672 j = bj[jmin]; 673 jl[i] = jl[j]; jl[j] = i; /* update jl */ 674 } 675 i = nexti; 676 } 677 678 /* save nonzero entries in k-th row of U ... */ 679 680 /* invert diagonal block */ 681 diag = ba+k*bs2; 682 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 683 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 684 685 jmin = bi[k]; jmax = bi[k+1]; 686 if (jmin < jmax) { 687 for (j=jmin; j<jmax; j++){ 688 vj = bj[j]; /* block col. index of U */ 689 u = ba + j*bs2; 690 rtmp_ptr = rtmp + vj*bs2; 691 for (k1=0; k1<bs2; k1++){ 692 *u++ = *rtmp_ptr; 693 *rtmp_ptr++ = 0.0; 694 } 695 } 696 697 /* ... add k to row list for first nonzero entry in k-th row */ 698 il[k] = jmin; 699 i = bj[jmin]; 700 jl[k] = jl[i]; jl[i] = k; 701 } 702 } 703 704 ierr = PetscFree(rtmp);CHKERRQ(ierr); 705 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 706 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 707 ierr = PetscFree(pivots);CHKERRQ(ierr); 708 if (a->permute){ 709 ierr = PetscFree(aa);CHKERRQ(ierr); 710 } 711 712 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 713 C->ops->solve = MatSolve_SeqSBAIJ_N_inplace; 714 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace; 715 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_inplace; 716 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_inplace; 717 718 C->assembled = PETSC_TRUE; 719 C->preallocated = PETSC_TRUE; 720 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 721 PetscFunctionReturn(0); 722 } 723 724 #undef __FUNCT__ 725 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 726 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 727 { 728 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 729 PetscErrorCode ierr; 730 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 731 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 732 PetscInt bs=A->rmap->bs,bs2 = a->bs2,bslog; 733 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 734 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 735 MatScalar *work; 736 PetscInt *pivots; 737 738 PetscFunctionBegin; 739 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 740 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 741 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 742 for (i=0; i<mbs; i++) { 743 jl[i] = mbs; il[0] = 0; 744 } 745 ierr = PetscMalloc3(bs2,MatScalar,&dk,bs2,MatScalar,&uik,bs,MatScalar,&work);CHKERRQ(ierr); 746 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 747 748 ai = a->i; aj = a->j; aa = a->a; 749 750 /* flops in while loop */ 751 bslog = 2*bs*bs2; 752 753 /* for each row k */ 754 for (k = 0; k<mbs; k++){ 755 756 /*initialize k-th row with elements nonzero in row k of A */ 757 jmin = ai[k]; jmax = ai[k+1]; 758 ap = aa + jmin*bs2; 759 for (j = jmin; j < jmax; j++){ 760 vj = aj[j]; /* block col. index */ 761 rtmp_ptr = rtmp + vj*bs2; 762 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 763 } 764 765 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 766 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 767 i = jl[k]; /* first row to be added to k_th row */ 768 769 while (i < k){ 770 nexti = jl[i]; /* next row to be added to k_th row */ 771 772 /* compute multiplier */ 773 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 774 775 /* uik = -inv(Di)*U_bar(i,k) */ 776 diag = ba + i*bs2; 777 u = ba + ili*bs2; 778 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 779 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 780 781 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 782 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 783 ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr); 784 785 /* update -U(i,k) */ 786 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 787 788 /* add multiple of row i to k-th row ... */ 789 jmin = ili + 1; jmax = bi[i+1]; 790 if (jmin < jmax){ 791 for (j=jmin; j<jmax; j++) { 792 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 793 rtmp_ptr = rtmp + bj[j]*bs2; 794 u = ba + j*bs2; 795 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 796 } 797 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 798 799 /* ... add i to row list for next nonzero entry */ 800 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 801 j = bj[jmin]; 802 jl[i] = jl[j]; jl[j] = i; /* update jl */ 803 } 804 i = nexti; 805 } 806 807 /* save nonzero entries in k-th row of U ... */ 808 809 /* invert diagonal block */ 810 diag = ba+k*bs2; 811 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 812 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 813 814 jmin = bi[k]; jmax = bi[k+1]; 815 if (jmin < jmax) { 816 for (j=jmin; j<jmax; j++){ 817 vj = bj[j]; /* block col. index of U */ 818 u = ba + j*bs2; 819 rtmp_ptr = rtmp + vj*bs2; 820 for (k1=0; k1<bs2; k1++){ 821 *u++ = *rtmp_ptr; 822 *rtmp_ptr++ = 0.0; 823 } 824 } 825 826 /* ... add k to row list for first nonzero entry in k-th row */ 827 il[k] = jmin; 828 i = bj[jmin]; 829 jl[k] = jl[i]; jl[i] = k; 830 } 831 } 832 833 ierr = PetscFree(rtmp);CHKERRQ(ierr); 834 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 835 ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr); 836 ierr = PetscFree(pivots);CHKERRQ(ierr); 837 838 C->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 839 C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 840 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 841 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace; 842 C->assembled = PETSC_TRUE; 843 C->preallocated = PETSC_TRUE; 844 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 845 PetscFunctionReturn(0); 846 } 847 848 /* 849 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 850 Version for blocks 2 by 2. 851 */ 852 #undef __FUNCT__ 853 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 854 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info) 855 { 856 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 857 IS perm = b->row; 858 PetscErrorCode ierr; 859 const PetscInt *ai,*aj,*perm_ptr; 860 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 861 PetscInt *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 862 MatScalar *ba = b->a,*aa,*ap; 863 MatScalar *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4]; 864 PetscReal shift = info->shiftamount; 865 866 PetscFunctionBegin; 867 /* initialization */ 868 /* il and jl record the first nonzero element in each row of the accessing 869 window U(0:k, k:mbs-1). 870 jl: list of rows to be added to uneliminated rows 871 i>= k: jl(i) is the first row to be added to row i 872 i< k: jl(i) is the row following row i in some list of rows 873 jl(i) = mbs indicates the end of a list 874 il(i): points to the first nonzero element in columns k,...,mbs-1 of 875 row i of U */ 876 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 877 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 878 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 879 for (i=0; i<mbs; i++) { 880 jl[i] = mbs; il[0] = 0; 881 } 882 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 883 884 /* check permutation */ 885 if (!a->permute){ 886 ai = a->i; aj = a->j; aa = a->a; 887 } else { 888 ai = a->inew; aj = a->jnew; 889 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 890 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 891 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 892 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 893 894 for (i=0; i<mbs; i++){ 895 jmin = ai[i]; jmax = ai[i+1]; 896 for (j=jmin; j<jmax; j++){ 897 while (a2anew[j] != j){ 898 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 899 for (k1=0; k1<4; k1++){ 900 dk[k1] = aa[k*4+k1]; 901 aa[k*4+k1] = aa[j*4+k1]; 902 aa[j*4+k1] = dk[k1]; 903 } 904 } 905 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 906 if (i > aj[j]){ 907 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 908 ap = aa + j*4; /* ptr to the beginning of the block */ 909 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 910 ap[1] = ap[2]; 911 ap[2] = dk[1]; 912 } 913 } 914 } 915 ierr = PetscFree(a2anew);CHKERRQ(ierr); 916 } 917 918 /* for each row k */ 919 for (k = 0; k<mbs; k++){ 920 921 /*initialize k-th row with elements nonzero in row perm(k) of A */ 922 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 923 ap = aa + jmin*4; 924 for (j = jmin; j < jmax; j++){ 925 vj = perm_ptr[aj[j]]; /* block col. index */ 926 rtmp_ptr = rtmp + vj*4; 927 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 928 } 929 930 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 931 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 932 i = jl[k]; /* first row to be added to k_th row */ 933 934 while (i < k){ 935 nexti = jl[i]; /* next row to be added to k_th row */ 936 937 /* compute multiplier */ 938 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 939 940 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 941 diag = ba + i*4; 942 u = ba + ili*4; 943 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 944 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 945 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 946 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 947 948 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 949 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 950 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 951 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 952 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 953 954 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 955 956 /* update -U(i,k): ba[ili] = uik */ 957 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 958 959 /* add multiple of row i to k-th row ... */ 960 jmin = ili + 1; jmax = bi[i+1]; 961 if (jmin < jmax){ 962 for (j=jmin; j<jmax; j++) { 963 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 964 rtmp_ptr = rtmp + bj[j]*4; 965 u = ba + j*4; 966 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 967 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 968 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 969 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 970 } 971 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 972 973 /* ... add i to row list for next nonzero entry */ 974 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 975 j = bj[jmin]; 976 jl[i] = jl[j]; jl[j] = i; /* update jl */ 977 } 978 i = nexti; 979 } 980 981 /* save nonzero entries in k-th row of U ... */ 982 983 /* invert diagonal block */ 984 diag = ba+k*4; 985 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 986 ierr = Kernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 987 988 jmin = bi[k]; jmax = bi[k+1]; 989 if (jmin < jmax) { 990 for (j=jmin; j<jmax; j++){ 991 vj = bj[j]; /* block col. index of U */ 992 u = ba + j*4; 993 rtmp_ptr = rtmp + vj*4; 994 for (k1=0; k1<4; k1++){ 995 *u++ = *rtmp_ptr; 996 *rtmp_ptr++ = 0.0; 997 } 998 } 999 1000 /* ... add k to row list for first nonzero entry in k-th row */ 1001 il[k] = jmin; 1002 i = bj[jmin]; 1003 jl[k] = jl[i]; jl[i] = k; 1004 } 1005 } 1006 1007 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1008 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1009 if (a->permute) { 1010 ierr = PetscFree(aa);CHKERRQ(ierr); 1011 } 1012 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 1013 C->ops->solve = MatSolve_SeqSBAIJ_2_inplace; 1014 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace; 1015 C->assembled = PETSC_TRUE; 1016 C->preallocated = PETSC_TRUE; 1017 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1018 PetscFunctionReturn(0); 1019 } 1020 1021 /* 1022 Version for when blocks are 2 by 2 Using natural ordering 1023 */ 1024 #undef __FUNCT__ 1025 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 1026 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info) 1027 { 1028 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 1029 PetscErrorCode ierr; 1030 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 1031 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 1032 MatScalar *ba = b->a,*aa,*ap,dk[8],uik[8]; 1033 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 1034 PetscReal shift = info->shiftamount; 1035 1036 PetscFunctionBegin; 1037 /* initialization */ 1038 /* il and jl record the first nonzero element in each row of the accessing 1039 window U(0:k, k:mbs-1). 1040 jl: list of rows to be added to uneliminated rows 1041 i>= k: jl(i) is the first row to be added to row i 1042 i< k: jl(i) is the row following row i in some list of rows 1043 jl(i) = mbs indicates the end of a list 1044 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1045 row i of U */ 1046 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1047 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 1048 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1049 for (i=0; i<mbs; i++) { 1050 jl[i] = mbs; il[0] = 0; 1051 } 1052 ai = a->i; aj = a->j; aa = a->a; 1053 1054 /* for each row k */ 1055 for (k = 0; k<mbs; k++){ 1056 1057 /*initialize k-th row with elements nonzero in row k of A */ 1058 jmin = ai[k]; jmax = ai[k+1]; 1059 ap = aa + jmin*4; 1060 for (j = jmin; j < jmax; j++){ 1061 vj = aj[j]; /* block col. index */ 1062 rtmp_ptr = rtmp + vj*4; 1063 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1064 } 1065 1066 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1067 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1068 i = jl[k]; /* first row to be added to k_th row */ 1069 1070 while (i < k){ 1071 nexti = jl[i]; /* next row to be added to k_th row */ 1072 1073 /* compute multiplier */ 1074 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1075 1076 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1077 diag = ba + i*4; 1078 u = ba + ili*4; 1079 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1080 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1081 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1082 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1083 1084 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1085 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1086 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1087 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1088 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1089 1090 ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr); 1091 1092 /* update -U(i,k): ba[ili] = uik */ 1093 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1094 1095 /* add multiple of row i to k-th row ... */ 1096 jmin = ili + 1; jmax = bi[i+1]; 1097 if (jmin < jmax){ 1098 for (j=jmin; j<jmax; j++) { 1099 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1100 rtmp_ptr = rtmp + bj[j]*4; 1101 u = ba + j*4; 1102 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1103 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1104 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1105 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1106 } 1107 ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr); 1108 1109 /* ... add i to row list for next nonzero entry */ 1110 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1111 j = bj[jmin]; 1112 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1113 } 1114 i = nexti; 1115 } 1116 1117 /* save nonzero entries in k-th row of U ... */ 1118 1119 /* invert diagonal block */ 1120 diag = ba+k*4; 1121 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1122 ierr = Kernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 1123 1124 jmin = bi[k]; jmax = bi[k+1]; 1125 if (jmin < jmax) { 1126 for (j=jmin; j<jmax; j++){ 1127 vj = bj[j]; /* block col. index of U */ 1128 u = ba + j*4; 1129 rtmp_ptr = rtmp + vj*4; 1130 for (k1=0; k1<4; k1++){ 1131 *u++ = *rtmp_ptr; 1132 *rtmp_ptr++ = 0.0; 1133 } 1134 } 1135 1136 /* ... add k to row list for first nonzero entry in k-th row */ 1137 il[k] = jmin; 1138 i = bj[jmin]; 1139 jl[k] = jl[i]; jl[i] = k; 1140 } 1141 } 1142 1143 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1144 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1145 1146 C->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1147 C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1148 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1149 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace; 1150 C->assembled = PETSC_TRUE; 1151 C->preallocated = PETSC_TRUE; 1152 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1153 PetscFunctionReturn(0); 1154 } 1155 1156 /* 1157 Numeric U^T*D*U factorization for SBAIJ format. 1158 Version for blocks are 1 by 1. 1159 */ 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace" 1162 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info) 1163 { 1164 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1165 IS ip=b->row; 1166 PetscErrorCode ierr; 1167 const PetscInt *ai,*aj,*rip; 1168 PetscInt *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1169 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1170 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1171 PetscReal rs; 1172 FactorShiftCtx sctx; 1173 1174 PetscFunctionBegin; 1175 /* MatPivotSetUp(): initialize shift context sctx */ 1176 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1177 1178 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1179 if (!a->permute){ 1180 ai = a->i; aj = a->j; aa = a->a; 1181 } else { 1182 ai = a->inew; aj = a->jnew; 1183 nz = ai[mbs]; 1184 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1185 a2anew = a->a2anew; 1186 bval = a->a; 1187 for (j=0; j<nz; j++){ 1188 aa[a2anew[j]] = *(bval++); 1189 } 1190 } 1191 1192 /* initialization */ 1193 /* il and jl record the first nonzero element in each row of the accessing 1194 window U(0:k, k:mbs-1). 1195 jl: list of rows to be added to uneliminated rows 1196 i>= k: jl(i) is the first row to be added to row i 1197 i< k: jl(i) is the row following row i in some list of rows 1198 jl(i) = mbs indicates the end of a list 1199 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1200 row i of U */ 1201 ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1202 1203 do { 1204 sctx.newshift = PETSC_FALSE; 1205 for (i=0; i<mbs; i++) { 1206 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1207 } 1208 1209 for (k = 0; k<mbs; k++){ 1210 /*initialize k-th row by the perm[k]-th row of A */ 1211 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1212 bval = ba + bi[k]; 1213 for (j = jmin; j < jmax; j++){ 1214 col = rip[aj[j]]; 1215 rtmp[col] = aa[j]; 1216 *bval++ = 0.0; /* for in-place factorization */ 1217 } 1218 1219 /* shift the diagonal of the matrix */ 1220 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1221 1222 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1223 dk = rtmp[k]; 1224 i = jl[k]; /* first row to be added to k_th row */ 1225 1226 while (i < k){ 1227 nexti = jl[i]; /* next row to be added to k_th row */ 1228 1229 /* compute multiplier, update diag(k) and U(i,k) */ 1230 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1231 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1232 dk += uikdi*ba[ili]; 1233 ba[ili] = uikdi; /* -U(i,k) */ 1234 1235 /* add multiple of row i to k-th row */ 1236 jmin = ili + 1; jmax = bi[i+1]; 1237 if (jmin < jmax){ 1238 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1239 ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr); 1240 1241 /* update il and jl for row i */ 1242 il[i] = jmin; 1243 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1244 } 1245 i = nexti; 1246 } 1247 1248 /* shift the diagonals when zero pivot is detected */ 1249 /* compute rs=sum of abs(off-diagonal) */ 1250 rs = 0.0; 1251 jmin = bi[k]+1; 1252 nz = bi[k+1] - jmin; 1253 if (nz){ 1254 bcol = bj + jmin; 1255 while (nz--){ 1256 rs += PetscAbsScalar(rtmp[*bcol]); 1257 bcol++; 1258 } 1259 } 1260 1261 sctx.rs = rs; 1262 sctx.pv = dk; 1263 ierr = MatPivotCheck(info,&sctx,k);CHKERRQ(ierr); 1264 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1265 dk = sctx.pv; 1266 1267 /* copy data into U(k,:) */ 1268 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1269 jmin = bi[k]+1; jmax = bi[k+1]; 1270 if (jmin < jmax) { 1271 for (j=jmin; j<jmax; j++){ 1272 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1273 } 1274 /* add the k-th row into il and jl */ 1275 il[k] = jmin; 1276 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1277 } 1278 } 1279 } while (sctx.newshift); 1280 ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr); 1281 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1282 1283 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1284 C->ops->solve = MatSolve_SeqSBAIJ_1_inplace; 1285 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1286 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace; 1287 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_inplace; 1288 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_inplace; 1289 C->assembled = PETSC_TRUE; 1290 C->preallocated = PETSC_TRUE; 1291 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1292 if (sctx.nshift){ 1293 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1294 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1295 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1296 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1297 } 1298 } 1299 PetscFunctionReturn(0); 1300 } 1301 1302 /* 1303 Version for when blocks are 1 by 1 Using natural ordering under new datastructure 1304 Modified from MatCholeskyFactorNumeric_SeqAIJ() 1305 */ 1306 #undef __FUNCT__ 1307 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1308 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 1309 { 1310 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data; 1311 Mat_SeqSBAIJ *b=(Mat_SeqSBAIJ*)B->data; 1312 PetscErrorCode ierr; 1313 PetscInt i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp; 1314 PetscInt *ai=a->i,*aj=a->j,*ajtmp; 1315 PetscInt k,jmin,jmax,*c2r,*il,col,nexti,ili,nz; 1316 MatScalar *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi; 1317 FactorShiftCtx sctx; 1318 PetscReal rs; 1319 MatScalar d,*v; 1320 1321 PetscFunctionBegin; 1322 ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&c2r);CHKERRQ(ierr); 1323 1324 /* MatPivotSetUp(): initialize shift context sctx */ 1325 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1326 1327 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */ 1328 sctx.shift_top = info->zeropivot; 1329 ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr); 1330 for (i=0; i<mbs; i++) { 1331 /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */ 1332 d = (aa)[a->diag[i]]; 1333 rtmp[i] += - PetscRealPart(d); /* diagonal entry */ 1334 ajtmp = aj + ai[i] + 1; /* exclude diagonal */ 1335 v = aa + ai[i] + 1; 1336 nz = ai[i+1] - ai[i] - 1 ; 1337 for (j=0; j<nz; j++){ 1338 rtmp[i] += PetscAbsScalar(v[j]); 1339 rtmp[ajtmp[j]] += PetscAbsScalar(v[j]); 1340 } 1341 if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]); 1342 } 1343 sctx.shift_top *= 1.1; 1344 sctx.nshift_max = 5; 1345 sctx.shift_lo = 0.; 1346 sctx.shift_hi = 1.; 1347 } 1348 1349 /* allocate working arrays 1350 c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col 1351 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 1352 */ 1353 do { 1354 sctx.newshift = PETSC_FALSE; 1355 1356 for (i=0; i<mbs; i++) c2r[i] = mbs; 1357 il[0] = 0; 1358 1359 for (k = 0; k<mbs; k++){ 1360 /* zero rtmp */ 1361 nz = bi[k+1] - bi[k]; 1362 bjtmp = bj + bi[k]; 1363 for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0; 1364 1365 /* load in initial unfactored row */ 1366 bval = ba + bi[k]; 1367 jmin = ai[k]; jmax = ai[k+1]; 1368 for (j = jmin; j < jmax; j++){ 1369 col = aj[j]; 1370 rtmp[col] = aa[j]; 1371 *bval++ = 0.0; /* for in-place factorization */ 1372 } 1373 /* shift the diagonal of the matrix: ZeropivotApply() */ 1374 rtmp[k] += sctx.shift_amount; /* shift the diagonal of the matrix */ 1375 1376 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1377 dk = rtmp[k]; 1378 i = c2r[k]; /* first row to be added to k_th row */ 1379 1380 while (i < k){ 1381 nexti = c2r[i]; /* next row to be added to k_th row */ 1382 1383 /* compute multiplier, update diag(k) and U(i,k) */ 1384 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1385 uikdi = - ba[ili]*ba[bdiag[i]]; /* diagonal(k) */ 1386 dk += uikdi*ba[ili]; /* update diag[k] */ 1387 ba[ili] = uikdi; /* -U(i,k) */ 1388 1389 /* add multiple of row i to k-th row */ 1390 jmin = ili + 1; jmax = bi[i+1]; 1391 if (jmin < jmax){ 1392 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1393 /* update il and c2r for row i */ 1394 il[i] = jmin; 1395 j = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i; 1396 } 1397 i = nexti; 1398 } 1399 1400 /* copy data into U(k,:) */ 1401 rs = 0.0; 1402 jmin = bi[k]; jmax = bi[k+1]-1; 1403 if (jmin < jmax) { 1404 for (j=jmin; j<jmax; j++){ 1405 col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]); 1406 } 1407 /* add the k-th row into il and c2r */ 1408 il[k] = jmin; 1409 i = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k; 1410 } 1411 1412 sctx.rs = rs; 1413 sctx.pv = dk; 1414 ierr = MatPivotCheck(info,&sctx,k);CHKERRQ(ierr); 1415 if(sctx.newshift) break; 1416 dk = sctx.pv; 1417 1418 ba[bdiag[k]] = 1.0/dk; /* U(k,k) */ 1419 } 1420 } while (sctx.newshift); 1421 1422 ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr); 1423 1424 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1425 B->ops->solves = MatSolves_SeqSBAIJ_1; 1426 B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering; 1427 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 1428 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 1429 1430 B->assembled = PETSC_TRUE; 1431 B->preallocated = PETSC_TRUE; 1432 ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr); 1433 1434 /* MatPivotView() */ 1435 if (sctx.nshift){ 1436 if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1437 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); 1438 } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1439 ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1440 } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS){ 1441 ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %G\n",sctx.nshift,info->shiftamount);CHKERRQ(ierr); 1442 } 1443 } 1444 PetscFunctionReturn(0); 1445 } 1446 1447 #undef __FUNCT__ 1448 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace" 1449 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info) 1450 { 1451 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1452 PetscErrorCode ierr; 1453 PetscInt i,j,mbs = a->mbs; 1454 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1455 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1456 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1457 PetscReal rs; 1458 FactorShiftCtx sctx; 1459 1460 PetscFunctionBegin; 1461 /* MatPivotSetUp(): initialize shift context sctx */ 1462 ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr); 1463 1464 /* initialization */ 1465 /* il and jl record the first nonzero element in each row of the accessing 1466 window U(0:k, k:mbs-1). 1467 jl: list of rows to be added to uneliminated rows 1468 i>= k: jl(i) is the first row to be added to row i 1469 i< k: jl(i) is the row following row i in some list of rows 1470 jl(i) = mbs indicates the end of a list 1471 il(i): points to the first nonzero element in U(i,k:mbs-1) 1472 */ 1473 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1474 ierr = PetscMalloc2(mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr); 1475 1476 do { 1477 sctx.newshift = PETSC_FALSE; 1478 for (i=0; i<mbs; i++) { 1479 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1480 } 1481 1482 for (k = 0; k<mbs; k++){ 1483 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1484 nz = ai[k+1] - ai[k]; 1485 acol = aj + ai[k]; 1486 aval = aa + ai[k]; 1487 bval = ba + bi[k]; 1488 while (nz -- ){ 1489 rtmp[*acol++] = *aval++; 1490 *bval++ = 0.0; /* for in-place factorization */ 1491 } 1492 1493 /* shift the diagonal of the matrix */ 1494 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1495 1496 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1497 dk = rtmp[k]; 1498 i = jl[k]; /* first row to be added to k_th row */ 1499 1500 while (i < k){ 1501 nexti = jl[i]; /* next row to be added to k_th row */ 1502 /* compute multiplier, update D(k) and U(i,k) */ 1503 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1504 uikdi = - ba[ili]*ba[bi[i]]; 1505 dk += uikdi*ba[ili]; 1506 ba[ili] = uikdi; /* -U(i,k) */ 1507 1508 /* add multiple of row i to k-th row ... */ 1509 jmin = ili + 1; 1510 nz = bi[i+1] - jmin; 1511 if (nz > 0){ 1512 bcol = bj + jmin; 1513 bval = ba + jmin; 1514 ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr); 1515 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1516 1517 /* update il and jl for i-th row */ 1518 il[i] = jmin; 1519 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1520 } 1521 i = nexti; 1522 } 1523 1524 /* shift the diagonals when zero pivot is detected */ 1525 /* compute rs=sum of abs(off-diagonal) */ 1526 rs = 0.0; 1527 jmin = bi[k]+1; 1528 nz = bi[k+1] - jmin; 1529 if (nz){ 1530 bcol = bj + jmin; 1531 while (nz--){ 1532 rs += PetscAbsScalar(rtmp[*bcol]); 1533 bcol++; 1534 } 1535 } 1536 1537 sctx.rs = rs; 1538 sctx.pv = dk; 1539 ierr = MatPivotCheck(info,&sctx,k);CHKERRQ(ierr); 1540 if (sctx.newshift) break; /* sctx.shift_amount is updated */ 1541 dk = sctx.pv; 1542 1543 /* copy data into U(k,:) */ 1544 ba[bi[k]] = 1.0/dk; 1545 jmin = bi[k]+1; 1546 nz = bi[k+1] - jmin; 1547 if (nz){ 1548 bcol = bj + jmin; 1549 bval = ba + jmin; 1550 while (nz--){ 1551 *bval++ = rtmp[*bcol]; 1552 rtmp[*bcol++] = 0.0; 1553 } 1554 /* add k-th row into il and jl */ 1555 il[k] = jmin; 1556 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1557 } 1558 } /* end of for (k = 0; k<mbs; k++) */ 1559 } while (sctx.newshift); 1560 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1561 ierr = PetscFree2(il,jl);CHKERRQ(ierr); 1562 1563 C->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1564 C->ops->solves = MatSolves_SeqSBAIJ_1_inplace; 1565 C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1566 C->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1567 C->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace; 1568 1569 C->assembled = PETSC_TRUE; 1570 C->preallocated = PETSC_TRUE; 1571 ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr); 1572 if (sctx.nshift){ 1573 if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) { 1574 ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1575 } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { 1576 ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1577 } 1578 } 1579 PetscFunctionReturn(0); 1580 } 1581 1582 #undef __FUNCT__ 1583 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1584 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info) 1585 { 1586 PetscErrorCode ierr; 1587 Mat C; 1588 1589 PetscFunctionBegin; 1590 ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr); 1591 ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr); 1592 ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr); 1593 A->ops->solve = C->ops->solve; 1594 A->ops->solvetranspose = C->ops->solvetranspose; 1595 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1596 PetscFunctionReturn(0); 1597 } 1598 1599 1600