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/inline/ilu.h" 6 #include "include/petscis.h" 7 8 #if !defined(PETSC_USE_COMPLEX) 9 /* 10 input: 11 F -- numeric factor 12 output: 13 nneg, nzero, npos: matrix inertia 14 */ 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetInertia_SeqSBAIJ" 18 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos) 19 { 20 Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data; 21 PetscScalar *dd = fact_ptr->a; 22 PetscInt mbs=fact_ptr->mbs,bs=F->rmap.bs,i,nneig_tmp,npos_tmp,*fi = fact_ptr->i; 23 24 PetscFunctionBegin; 25 if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"No support for bs: %D >1 yet",bs); 26 nneig_tmp = 0; npos_tmp = 0; 27 for (i=0; i<mbs; i++){ 28 if (PetscRealPart(dd[*fi]) > 0.0){ 29 npos_tmp++; 30 } else if (PetscRealPart(dd[*fi]) < 0.0){ 31 nneig_tmp++; 32 } 33 fi++; 34 } 35 if (nneig) *nneig = nneig_tmp; 36 if (npos) *npos = npos_tmp; 37 if (nzero) *nzero = mbs - nneig_tmp - npos_tmp; 38 39 PetscFunctionReturn(0); 40 } 41 #endif /* !defined(PETSC_USE_COMPLEX) */ 42 43 /* 44 Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP. 45 Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad. 46 */ 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR" 49 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat A,IS perm,MatFactorInfo *info,Mat *B) 50 { 51 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b; 52 PetscErrorCode ierr; 53 PetscInt *rip,i,mbs = a->mbs,*ai,*aj; 54 PetscInt *jutmp,bs = A->rmap.bs,bs2=a->bs2; 55 PetscInt m,reallocs = 0,prow; 56 PetscInt *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd; 57 PetscReal f = info->fill; 58 PetscTruth perm_identity; 59 60 PetscFunctionBegin; 61 /* check whether perm is the identity mapping */ 62 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 63 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 64 65 if (perm_identity){ /* without permutation */ 66 a->permute = PETSC_FALSE; 67 ai = a->i; aj = a->j; 68 } else { /* non-trivial permutation */ 69 a->permute = PETSC_TRUE; 70 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 71 ai = a->inew; aj = a->jnew; 72 } 73 74 /* initialization */ 75 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&iu);CHKERRQ(ierr); 76 umax = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1; 77 ierr = PetscMalloc(umax*sizeof(PetscInt),&ju);CHKERRQ(ierr); 78 iu[0] = mbs+1; 79 juidx = mbs + 1; /* index for ju */ 80 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&jl);CHKERRQ(ierr); /* linked list for pivot row */ 81 q = jl + mbs; /* linked list for col index */ 82 for (i=0; i<mbs; i++){ 83 jl[i] = mbs; 84 q[i] = 0; 85 } 86 87 /* for each row k */ 88 for (k=0; k<mbs; k++){ 89 for (i=0; i<mbs; i++) q[i] = 0; /* to be removed! */ 90 nzk = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */ 91 q[k] = mbs; 92 /* initialize nonzero structure of k-th row to row rip[k] of A */ 93 jmin = ai[rip[k]] +1; /* exclude diag[k] */ 94 jmax = ai[rip[k]+1]; 95 for (j=jmin; j<jmax; j++){ 96 vj = rip[aj[j]]; /* col. value */ 97 if(vj > k){ 98 qm = k; 99 do { 100 m = qm; qm = q[m]; 101 } while(qm < vj); 102 if (qm == vj) { 103 SETERRQ(PETSC_ERR_PLIB,"Duplicate entry in A\n"); 104 } 105 nzk++; 106 q[m] = vj; 107 q[vj] = qm; 108 } /* if(vj > k) */ 109 } /* for (j=jmin; j<jmax; j++) */ 110 111 /* modify nonzero structure of k-th row by computing fill-in 112 for each row i to be merged in */ 113 prow = k; 114 prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */ 115 116 while (prow < k){ 117 /* merge row prow into k-th row */ 118 jmin = iu[prow] + 1; jmax = iu[prow+1]; 119 qm = k; 120 for (j=jmin; j<jmax; j++){ 121 vj = ju[j]; 122 do { 123 m = qm; qm = q[m]; 124 } while (qm < vj); 125 if (qm != vj){ 126 nzk++; q[m] = vj; q[vj] = qm; qm = vj; 127 } 128 } 129 prow = jl[prow]; /* next pivot row */ 130 } 131 132 /* add k to row list for first nonzero element in k-th row */ 133 if (nzk > 0){ 134 i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */ 135 jl[k] = jl[i]; jl[i] = k; 136 } 137 iu[k+1] = iu[k] + nzk; 138 139 /* allocate more space to ju if needed */ 140 if (iu[k+1] > umax) { 141 /* estimate how much additional space we will need */ 142 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 143 /* just double the memory each time */ 144 maxadd = umax; 145 if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2; 146 umax += maxadd; 147 148 /* allocate a longer ju */ 149 ierr = PetscMalloc(umax*sizeof(PetscInt),&jutmp);CHKERRQ(ierr); 150 ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr); 151 ierr = PetscFree(ju);CHKERRQ(ierr); 152 ju = jutmp; 153 reallocs++; /* count how many times we realloc */ 154 } 155 156 /* save nonzero structure of k-th row in ju */ 157 i=k; 158 while (nzk --) { 159 i = q[i]; 160 ju[juidx++] = i; 161 } 162 } 163 164 #if defined(PETSC_USE_INFO) 165 if (ai[mbs] != 0) { 166 PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 167 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr); 168 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 169 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr); 170 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 171 } else { 172 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 173 } 174 #endif 175 176 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 177 ierr = PetscFree(jl);CHKERRQ(ierr); 178 179 /* put together the new matrix */ 180 ierr = MatCreate(A->comm,B);CHKERRQ(ierr); 181 ierr = MatSetSizes(*B,bs*mbs,bs*mbs,bs*mbs,bs*mbs);CHKERRQ(ierr); 182 ierr = MatSetType(*B,A->type_name);CHKERRQ(ierr); 183 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(*B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 184 185 /* ierr = PetscLogObjectParent(*B,iperm);CHKERRQ(ierr); */ 186 b = (Mat_SeqSBAIJ*)(*B)->data; 187 b->singlemalloc = PETSC_FALSE; 188 b->freedata = PETSC_TRUE; 189 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 190 b->j = ju; 191 b->i = iu; 192 b->diag = 0; 193 b->ilen = 0; 194 b->imax = 0; 195 b->row = perm; 196 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 197 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 198 b->icol = perm; 199 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 200 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 201 /* In b structure: Free imax, ilen, old a, old j. 202 Allocate idnew, solve_work, new a, new j */ 203 ierr = PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 204 b->maxnz = b->nz = iu[mbs]; 205 206 (*B)->factor = FACTOR_CHOLESKY; 207 (*B)->info.factor_mallocs = reallocs; 208 (*B)->info.fill_ratio_given = f; 209 if (ai[mbs] != 0) { 210 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 211 } else { 212 (*B)->info.fill_ratio_needed = 0.0; 213 } 214 215 if (perm_identity){ 216 switch (bs) { 217 case 1: 218 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 219 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 220 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 221 break; 222 case 2: 223 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 224 (*B)->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 225 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 226 break; 227 case 3: 228 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 229 (*B)->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 230 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 231 break; 232 case 4: 233 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 234 (*B)->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 235 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 236 break; 237 case 5: 238 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 239 (*B)->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 240 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 241 break; 242 case 6: 243 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 244 (*B)->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 245 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 246 break; 247 case 7: 248 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 249 (*B)->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 250 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 251 break; 252 default: 253 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 254 (*B)->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 255 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 256 break; 257 } 258 } 259 PetscFunctionReturn(0); 260 } 261 /* 262 Symbolic U^T*D*U factorization for SBAIJ format. 263 */ 264 #include "petscbt.h" 265 #include "src/mat/utils/freespace.h" 266 #undef __FUNCT__ 267 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 268 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *fact) 269 { 270 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 271 Mat_SeqSBAIJ *b; 272 Mat B; 273 PetscErrorCode ierr; 274 PetscTruth perm_identity; 275 PetscReal fill = info->fill; 276 PetscInt *rip,i,mbs=a->mbs,bs=A->rmap.bs,*ai,*aj,reallocs=0,prow; 277 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 278 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr; 279 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 280 PetscBT lnkbt; 281 282 PetscFunctionBegin; 283 /* 284 This code originally uses Modified Sparse Row (MSR) storage 285 (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise! 286 Then it is rewritten so the factor B takes seqsbaij format. However the associated 287 MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity, 288 thus the original code in MSR format is still used for these cases. 289 The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever 290 MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor. 291 */ 292 if (bs > 1){ 293 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(A,perm,info,fact);CHKERRQ(ierr); 294 PetscFunctionReturn(0); 295 } 296 297 /* check whether perm is the identity mapping */ 298 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 299 300 if (perm_identity){ 301 a->permute = PETSC_FALSE; 302 ai = a->i; aj = a->j; 303 } else { 304 a->permute = PETSC_TRUE; 305 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 306 ai = a->inew; aj = a->jnew; 307 } 308 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 309 310 /* initialization */ 311 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 312 ui[0] = 0; 313 314 /* jl: linked list for storing indices of the pivot rows 315 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 316 ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr); 317 il = jl + mbs; 318 cols = il + mbs; 319 ui_ptr = (PetscInt**)(cols + mbs); 320 321 for (i=0; i<mbs; i++){ 322 jl[i] = mbs; il[i] = 0; 323 } 324 325 /* create and initialize a linked list for storing column indices of the active row k */ 326 nlnk = mbs + 1; 327 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 328 329 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 330 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 331 current_space = free_space; 332 333 for (k=0; k<mbs; k++){ /* for each active row k */ 334 /* initialize lnk by the column indices of row rip[k] of A */ 335 nzk = 0; 336 ncols = ai[rip[k]+1] - ai[rip[k]]; 337 for (j=0; j<ncols; j++){ 338 i = *(aj + ai[rip[k]] + j); 339 cols[j] = rip[i]; 340 } 341 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 342 nzk += nlnk; 343 344 /* update lnk by computing fill-in for each pivot row to be merged in */ 345 prow = jl[k]; /* 1st pivot row */ 346 347 while (prow < k){ 348 nextprow = jl[prow]; 349 /* merge prow into k-th row */ 350 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 351 jmax = ui[prow+1]; 352 ncols = jmax-jmin; 353 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 354 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 355 nzk += nlnk; 356 357 /* update il and jl for prow */ 358 if (jmin < jmax){ 359 il[prow] = jmin; 360 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 361 } 362 prow = nextprow; 363 } 364 365 /* if free space is not available, make more free space */ 366 if (current_space->local_remaining<nzk) { 367 i = mbs - k + 1; /* num of unfactored rows */ 368 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 369 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 370 reallocs++; 371 } 372 373 /* copy data into free space, then initialize lnk */ 374 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 375 376 /* add the k-th row into il and jl */ 377 if (nzk-1 > 0){ 378 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 379 jl[k] = jl[i]; jl[i] = k; 380 il[k] = ui[k] + 1; 381 } 382 ui_ptr[k] = current_space->array; 383 current_space->array += nzk; 384 current_space->local_used += nzk; 385 current_space->local_remaining -= nzk; 386 387 ui[k+1] = ui[k] + nzk; 388 } 389 390 #if defined(PETSC_USE_INFO) 391 if (ai[mbs] != 0) { 392 PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 393 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 394 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 395 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 396 } else { 397 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 398 } 399 #endif 400 401 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 402 ierr = PetscFree(jl);CHKERRQ(ierr); 403 404 /* destroy list of free space and other temporary array(s) */ 405 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 406 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 407 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 408 409 /* put together the new matrix in MATSEQSBAIJ format */ 410 ierr = MatCreate(PETSC_COMM_SELF,fact);CHKERRQ(ierr); 411 ierr = MatSetSizes(*fact,mbs,mbs,mbs,mbs);CHKERRQ(ierr); 412 B = *fact; 413 ierr = MatSetType(B,MATSEQSBAIJ);CHKERRQ(ierr); 414 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 415 416 b = (Mat_SeqSBAIJ*)B->data; 417 b->singlemalloc = PETSC_FALSE; 418 b->freedata = PETSC_TRUE; 419 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 420 b->j = uj; 421 b->i = ui; 422 b->diag = 0; 423 b->ilen = 0; 424 b->imax = 0; 425 b->row = perm; 426 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 427 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 428 b->icol = perm; 429 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 430 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 431 ierr = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 432 b->maxnz = b->nz = ui[mbs]; 433 434 B->factor = FACTOR_CHOLESKY; 435 B->info.factor_mallocs = reallocs; 436 B->info.fill_ratio_given = fill; 437 if (ai[mbs] != 0) { 438 B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 439 } else { 440 B->info.fill_ratio_needed = 0.0; 441 } 442 443 if (perm_identity){ 444 switch (bs) { 445 case 1: 446 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 447 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 448 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 449 break; 450 case 2: 451 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 452 B->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 453 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 454 break; 455 case 3: 456 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 457 B->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 458 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 459 break; 460 case 4: 461 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 462 B->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 463 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 464 break; 465 case 5: 466 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 467 B->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 468 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 469 break; 470 case 6: 471 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 472 B->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 473 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 474 break; 475 case 7: 476 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 477 B->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 478 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 479 break; 480 default: 481 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 482 B->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 483 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 484 break; 485 } 486 } 487 PetscFunctionReturn(0); 488 } 489 #undef __FUNCT__ 490 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 491 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,MatFactorInfo *info,Mat *B) 492 { 493 Mat C = *B; 494 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 495 IS perm = b->row; 496 PetscErrorCode ierr; 497 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 498 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 499 PetscInt bs=A->rmap.bs,bs2 = a->bs2; 500 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 501 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 502 MatScalar *work; 503 PetscInt *pivots; 504 505 PetscFunctionBegin; 506 /* initialization */ 507 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 508 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 509 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 510 jl = il + mbs; 511 for (i=0; i<mbs; i++) { 512 jl[i] = mbs; il[0] = 0; 513 } 514 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 515 uik = dk + bs2; 516 work = uik + bs2; 517 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 518 519 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 520 521 /* check permutation */ 522 if (!a->permute){ 523 ai = a->i; aj = a->j; aa = a->a; 524 } else { 525 ai = a->inew; aj = a->jnew; 526 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 527 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 528 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 529 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 530 531 for (i=0; i<mbs; i++){ 532 jmin = ai[i]; jmax = ai[i+1]; 533 for (j=jmin; j<jmax; j++){ 534 while (a2anew[j] != j){ 535 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 536 for (k1=0; k1<bs2; k1++){ 537 dk[k1] = aa[k*bs2+k1]; 538 aa[k*bs2+k1] = aa[j*bs2+k1]; 539 aa[j*bs2+k1] = dk[k1]; 540 } 541 } 542 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 543 if (i > aj[j]){ 544 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 545 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 546 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 547 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 548 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 549 } 550 } 551 } 552 } 553 ierr = PetscFree(a2anew);CHKERRQ(ierr); 554 } 555 556 /* for each row k */ 557 for (k = 0; k<mbs; k++){ 558 559 /*initialize k-th row with elements nonzero in row perm(k) of A */ 560 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 561 562 ap = aa + jmin*bs2; 563 for (j = jmin; j < jmax; j++){ 564 vj = perm_ptr[aj[j]]; /* block col. index */ 565 rtmp_ptr = rtmp + vj*bs2; 566 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 567 } 568 569 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 570 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 571 i = jl[k]; /* first row to be added to k_th row */ 572 573 while (i < k){ 574 nexti = jl[i]; /* next row to be added to k_th row */ 575 576 /* compute multiplier */ 577 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 578 579 /* uik = -inv(Di)*U_bar(i,k) */ 580 diag = ba + i*bs2; 581 u = ba + ili*bs2; 582 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 583 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 584 585 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 586 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 587 588 /* update -U(i,k) */ 589 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 590 591 /* add multiple of row i to k-th row ... */ 592 jmin = ili + 1; jmax = bi[i+1]; 593 if (jmin < jmax){ 594 for (j=jmin; j<jmax; j++) { 595 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 596 rtmp_ptr = rtmp + bj[j]*bs2; 597 u = ba + j*bs2; 598 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 599 } 600 601 /* ... add i to row list for next nonzero entry */ 602 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 603 j = bj[jmin]; 604 jl[i] = jl[j]; jl[j] = i; /* update jl */ 605 } 606 i = nexti; 607 } 608 609 /* save nonzero entries in k-th row of U ... */ 610 611 /* invert diagonal block */ 612 diag = ba+k*bs2; 613 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 614 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 615 616 jmin = bi[k]; jmax = bi[k+1]; 617 if (jmin < jmax) { 618 for (j=jmin; j<jmax; j++){ 619 vj = bj[j]; /* block col. index of U */ 620 u = ba + j*bs2; 621 rtmp_ptr = rtmp + vj*bs2; 622 for (k1=0; k1<bs2; k1++){ 623 *u++ = *rtmp_ptr; 624 *rtmp_ptr++ = 0.0; 625 } 626 } 627 628 /* ... add k to row list for first nonzero entry in k-th row */ 629 il[k] = jmin; 630 i = bj[jmin]; 631 jl[k] = jl[i]; jl[i] = k; 632 } 633 } 634 635 ierr = PetscFree(rtmp);CHKERRQ(ierr); 636 ierr = PetscFree(il);CHKERRQ(ierr); 637 ierr = PetscFree(dk);CHKERRQ(ierr); 638 ierr = PetscFree(pivots);CHKERRQ(ierr); 639 if (a->permute){ 640 ierr = PetscFree(aa);CHKERRQ(ierr); 641 } 642 643 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 644 C->factor = FACTOR_CHOLESKY; 645 C->assembled = PETSC_TRUE; 646 C->preallocated = PETSC_TRUE; 647 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 648 PetscFunctionReturn(0); 649 } 650 651 #undef __FUNCT__ 652 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 653 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 654 { 655 Mat C = *B; 656 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 657 PetscErrorCode ierr; 658 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 659 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 660 PetscInt bs=A->rmap.bs,bs2 = a->bs2; 661 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 662 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 663 MatScalar *work; 664 PetscInt *pivots; 665 666 PetscFunctionBegin; 667 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 668 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 669 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 670 jl = il + mbs; 671 for (i=0; i<mbs; i++) { 672 jl[i] = mbs; il[0] = 0; 673 } 674 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 675 uik = dk + bs2; 676 work = uik + bs2; 677 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 678 679 ai = a->i; aj = a->j; aa = a->a; 680 681 /* for each row k */ 682 for (k = 0; k<mbs; k++){ 683 684 /*initialize k-th row with elements nonzero in row k of A */ 685 jmin = ai[k]; jmax = ai[k+1]; 686 ap = aa + jmin*bs2; 687 for (j = jmin; j < jmax; j++){ 688 vj = aj[j]; /* block col. index */ 689 rtmp_ptr = rtmp + vj*bs2; 690 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 691 } 692 693 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 694 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 695 i = jl[k]; /* first row to be added to k_th row */ 696 697 while (i < k){ 698 nexti = jl[i]; /* next row to be added to k_th row */ 699 700 /* compute multiplier */ 701 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 702 703 /* uik = -inv(Di)*U_bar(i,k) */ 704 diag = ba + i*bs2; 705 u = ba + ili*bs2; 706 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 707 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 708 709 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 710 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 711 712 /* update -U(i,k) */ 713 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 714 715 /* add multiple of row i to k-th row ... */ 716 jmin = ili + 1; jmax = bi[i+1]; 717 if (jmin < jmax){ 718 for (j=jmin; j<jmax; j++) { 719 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 720 rtmp_ptr = rtmp + bj[j]*bs2; 721 u = ba + j*bs2; 722 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 723 } 724 725 /* ... add i to row list for next nonzero entry */ 726 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 727 j = bj[jmin]; 728 jl[i] = jl[j]; jl[j] = i; /* update jl */ 729 } 730 i = nexti; 731 } 732 733 /* save nonzero entries in k-th row of U ... */ 734 735 /* invert diagonal block */ 736 diag = ba+k*bs2; 737 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 738 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 739 740 jmin = bi[k]; jmax = bi[k+1]; 741 if (jmin < jmax) { 742 for (j=jmin; j<jmax; j++){ 743 vj = bj[j]; /* block col. index of U */ 744 u = ba + j*bs2; 745 rtmp_ptr = rtmp + vj*bs2; 746 for (k1=0; k1<bs2; k1++){ 747 *u++ = *rtmp_ptr; 748 *rtmp_ptr++ = 0.0; 749 } 750 } 751 752 /* ... add k to row list for first nonzero entry in k-th row */ 753 il[k] = jmin; 754 i = bj[jmin]; 755 jl[k] = jl[i]; jl[i] = k; 756 } 757 } 758 759 ierr = PetscFree(rtmp);CHKERRQ(ierr); 760 ierr = PetscFree(il);CHKERRQ(ierr); 761 ierr = PetscFree(dk);CHKERRQ(ierr); 762 ierr = PetscFree(pivots);CHKERRQ(ierr); 763 764 C->factor = FACTOR_CHOLESKY; 765 C->assembled = PETSC_TRUE; 766 C->preallocated = PETSC_TRUE; 767 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 768 PetscFunctionReturn(0); 769 } 770 771 /* 772 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 773 Version for blocks 2 by 2. 774 */ 775 #undef __FUNCT__ 776 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 777 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B) 778 { 779 Mat C = *B; 780 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 781 IS perm = b->row; 782 PetscErrorCode ierr; 783 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 784 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 785 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 786 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 787 788 PetscFunctionBegin; 789 /* initialization */ 790 /* il and jl record the first nonzero element in each row of the accessing 791 window U(0:k, k:mbs-1). 792 jl: list of rows to be added to uneliminated rows 793 i>= k: jl(i) is the first row to be added to row i 794 i< k: jl(i) is the row following row i in some list of rows 795 jl(i) = mbs indicates the end of a list 796 il(i): points to the first nonzero element in columns k,...,mbs-1 of 797 row i of U */ 798 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 799 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 800 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 801 jl = il + mbs; 802 for (i=0; i<mbs; i++) { 803 jl[i] = mbs; il[0] = 0; 804 } 805 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 806 uik = dk + 4; 807 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 808 809 /* check permutation */ 810 if (!a->permute){ 811 ai = a->i; aj = a->j; aa = a->a; 812 } else { 813 ai = a->inew; aj = a->jnew; 814 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 815 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 816 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 817 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 818 819 for (i=0; i<mbs; i++){ 820 jmin = ai[i]; jmax = ai[i+1]; 821 for (j=jmin; j<jmax; j++){ 822 while (a2anew[j] != j){ 823 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 824 for (k1=0; k1<4; k1++){ 825 dk[k1] = aa[k*4+k1]; 826 aa[k*4+k1] = aa[j*4+k1]; 827 aa[j*4+k1] = dk[k1]; 828 } 829 } 830 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 831 if (i > aj[j]){ 832 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 833 ap = aa + j*4; /* ptr to the beginning of the block */ 834 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 835 ap[1] = ap[2]; 836 ap[2] = dk[1]; 837 } 838 } 839 } 840 ierr = PetscFree(a2anew);CHKERRQ(ierr); 841 } 842 843 /* for each row k */ 844 for (k = 0; k<mbs; k++){ 845 846 /*initialize k-th row with elements nonzero in row perm(k) of A */ 847 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 848 ap = aa + jmin*4; 849 for (j = jmin; j < jmax; j++){ 850 vj = perm_ptr[aj[j]]; /* block col. index */ 851 rtmp_ptr = rtmp + vj*4; 852 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 853 } 854 855 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 856 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 857 i = jl[k]; /* first row to be added to k_th row */ 858 859 while (i < k){ 860 nexti = jl[i]; /* next row to be added to k_th row */ 861 862 /* compute multiplier */ 863 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 864 865 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 866 diag = ba + i*4; 867 u = ba + ili*4; 868 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 869 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 870 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 871 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 872 873 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 874 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 875 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 876 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 877 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 878 879 /* update -U(i,k): ba[ili] = uik */ 880 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 881 882 /* add multiple of row i to k-th row ... */ 883 jmin = ili + 1; jmax = bi[i+1]; 884 if (jmin < jmax){ 885 for (j=jmin; j<jmax; j++) { 886 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 887 rtmp_ptr = rtmp + bj[j]*4; 888 u = ba + j*4; 889 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 890 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 891 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 892 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 893 } 894 895 /* ... add i to row list for next nonzero entry */ 896 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 897 j = bj[jmin]; 898 jl[i] = jl[j]; jl[j] = i; /* update jl */ 899 } 900 i = nexti; 901 } 902 903 /* save nonzero entries in k-th row of U ... */ 904 905 /* invert diagonal block */ 906 diag = ba+k*4; 907 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 908 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 909 910 jmin = bi[k]; jmax = bi[k+1]; 911 if (jmin < jmax) { 912 for (j=jmin; j<jmax; j++){ 913 vj = bj[j]; /* block col. index of U */ 914 u = ba + j*4; 915 rtmp_ptr = rtmp + vj*4; 916 for (k1=0; k1<4; k1++){ 917 *u++ = *rtmp_ptr; 918 *rtmp_ptr++ = 0.0; 919 } 920 } 921 922 /* ... add k to row list for first nonzero entry in k-th row */ 923 il[k] = jmin; 924 i = bj[jmin]; 925 jl[k] = jl[i]; jl[i] = k; 926 } 927 } 928 929 ierr = PetscFree(rtmp);CHKERRQ(ierr); 930 ierr = PetscFree(il);CHKERRQ(ierr); 931 ierr = PetscFree(dk);CHKERRQ(ierr); 932 if (a->permute) { 933 ierr = PetscFree(aa);CHKERRQ(ierr); 934 } 935 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 936 C->factor = FACTOR_CHOLESKY; 937 C->assembled = PETSC_TRUE; 938 C->preallocated = PETSC_TRUE; 939 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 940 PetscFunctionReturn(0); 941 } 942 943 /* 944 Version for when blocks are 2 by 2 Using natural ordering 945 */ 946 #undef __FUNCT__ 947 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 948 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 949 { 950 Mat C = *B; 951 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 952 PetscErrorCode ierr; 953 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 954 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 955 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 956 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 957 958 PetscFunctionBegin; 959 /* initialization */ 960 /* il and jl record the first nonzero element in each row of the accessing 961 window U(0:k, k:mbs-1). 962 jl: list of rows to be added to uneliminated rows 963 i>= k: jl(i) is the first row to be added to row i 964 i< k: jl(i) is the row following row i in some list of rows 965 jl(i) = mbs indicates the end of a list 966 il(i): points to the first nonzero element in columns k,...,mbs-1 of 967 row i of U */ 968 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 969 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 970 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 971 jl = il + mbs; 972 for (i=0; i<mbs; i++) { 973 jl[i] = mbs; il[0] = 0; 974 } 975 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 976 uik = dk + 4; 977 978 ai = a->i; aj = a->j; aa = a->a; 979 980 /* for each row k */ 981 for (k = 0; k<mbs; k++){ 982 983 /*initialize k-th row with elements nonzero in row k of A */ 984 jmin = ai[k]; jmax = ai[k+1]; 985 ap = aa + jmin*4; 986 for (j = jmin; j < jmax; j++){ 987 vj = aj[j]; /* block col. index */ 988 rtmp_ptr = rtmp + vj*4; 989 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 990 } 991 992 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 993 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 994 i = jl[k]; /* first row to be added to k_th row */ 995 996 while (i < k){ 997 nexti = jl[i]; /* next row to be added to k_th row */ 998 999 /* compute multiplier */ 1000 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1001 1002 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1003 diag = ba + i*4; 1004 u = ba + ili*4; 1005 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1006 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1007 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1008 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1009 1010 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1011 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1012 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1013 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1014 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1015 1016 /* update -U(i,k): ba[ili] = uik */ 1017 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1018 1019 /* add multiple of row i to k-th row ... */ 1020 jmin = ili + 1; jmax = bi[i+1]; 1021 if (jmin < jmax){ 1022 for (j=jmin; j<jmax; j++) { 1023 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1024 rtmp_ptr = rtmp + bj[j]*4; 1025 u = ba + j*4; 1026 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1027 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1028 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1029 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1030 } 1031 1032 /* ... add i to row list for next nonzero entry */ 1033 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1034 j = bj[jmin]; 1035 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1036 } 1037 i = nexti; 1038 } 1039 1040 /* save nonzero entries in k-th row of U ... */ 1041 1042 /* invert diagonal block */ 1043 diag = ba+k*4; 1044 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1045 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1046 1047 jmin = bi[k]; jmax = bi[k+1]; 1048 if (jmin < jmax) { 1049 for (j=jmin; j<jmax; j++){ 1050 vj = bj[j]; /* block col. index of U */ 1051 u = ba + j*4; 1052 rtmp_ptr = rtmp + vj*4; 1053 for (k1=0; k1<4; k1++){ 1054 *u++ = *rtmp_ptr; 1055 *rtmp_ptr++ = 0.0; 1056 } 1057 } 1058 1059 /* ... add k to row list for first nonzero entry in k-th row */ 1060 il[k] = jmin; 1061 i = bj[jmin]; 1062 jl[k] = jl[i]; jl[i] = k; 1063 } 1064 } 1065 1066 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1067 ierr = PetscFree(il);CHKERRQ(ierr); 1068 ierr = PetscFree(dk);CHKERRQ(ierr); 1069 1070 C->factor = FACTOR_CHOLESKY; 1071 C->assembled = PETSC_TRUE; 1072 C->preallocated = PETSC_TRUE; 1073 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1074 PetscFunctionReturn(0); 1075 } 1076 1077 /* 1078 Numeric U^T*D*U factorization for SBAIJ format. 1079 Version for blocks are 1 by 1. 1080 */ 1081 #undef __FUNCT__ 1082 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1083 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B) 1084 { 1085 Mat C = *B; 1086 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1087 IS ip=b->row; 1088 PetscErrorCode ierr; 1089 PetscInt *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1090 PetscInt *ai,*aj,*a2anew; 1091 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1092 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1093 PetscReal zeropivot,rs,shiftnz; 1094 PetscReal shiftpd; 1095 ChShift_Ctx sctx; 1096 PetscInt newshift; 1097 1098 PetscFunctionBegin; 1099 /* initialization */ 1100 shiftnz = info->shiftnz; 1101 shiftpd = info->shiftpd; 1102 zeropivot = info->zeropivot; 1103 1104 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1105 if (!a->permute){ 1106 ai = a->i; aj = a->j; aa = a->a; 1107 } else { 1108 ai = a->inew; aj = a->jnew; 1109 nz = ai[mbs]; 1110 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1111 a2anew = a->a2anew; 1112 bval = a->a; 1113 for (j=0; j<nz; j++){ 1114 aa[a2anew[j]] = *(bval++); 1115 } 1116 } 1117 1118 /* initialization */ 1119 /* il and jl record the first nonzero element in each row of the accessing 1120 window U(0:k, k:mbs-1). 1121 jl: list of rows to be added to uneliminated rows 1122 i>= k: jl(i) is the first row to be added to row i 1123 i< k: jl(i) is the row following row i in some list of rows 1124 jl(i) = mbs indicates the end of a list 1125 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1126 row i of U */ 1127 nz = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar); 1128 ierr = PetscMalloc(nz,&il);CHKERRQ(ierr); 1129 jl = il + mbs; 1130 rtmp = (MatScalar*)(jl + mbs); 1131 1132 sctx.shift_amount = 0; 1133 sctx.nshift = 0; 1134 do { 1135 sctx.chshift = PETSC_FALSE; 1136 for (i=0; i<mbs; i++) { 1137 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1138 } 1139 1140 for (k = 0; k<mbs; k++){ 1141 /*initialize k-th row by the perm[k]-th row of A */ 1142 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1143 bval = ba + bi[k]; 1144 for (j = jmin; j < jmax; j++){ 1145 col = rip[aj[j]]; 1146 rtmp[col] = aa[j]; 1147 *bval++ = 0.0; /* for in-place factorization */ 1148 } 1149 1150 /* shift the diagonal of the matrix */ 1151 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1152 1153 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1154 dk = rtmp[k]; 1155 i = jl[k]; /* first row to be added to k_th row */ 1156 1157 while (i < k){ 1158 nexti = jl[i]; /* next row to be added to k_th row */ 1159 1160 /* compute multiplier, update diag(k) and U(i,k) */ 1161 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1162 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1163 dk += uikdi*ba[ili]; 1164 ba[ili] = uikdi; /* -U(i,k) */ 1165 1166 /* add multiple of row i to k-th row */ 1167 jmin = ili + 1; jmax = bi[i+1]; 1168 if (jmin < jmax){ 1169 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1170 /* update il and jl for row i */ 1171 il[i] = jmin; 1172 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1173 } 1174 i = nexti; 1175 } 1176 1177 /* shift the diagonals when zero pivot is detected */ 1178 /* compute rs=sum of abs(off-diagonal) */ 1179 rs = 0.0; 1180 jmin = bi[k]+1; 1181 nz = bi[k+1] - jmin; 1182 if (nz){ 1183 bcol = bj + jmin; 1184 while (nz--){ 1185 rs += PetscAbsScalar(rtmp[*bcol]); 1186 bcol++; 1187 } 1188 } 1189 1190 sctx.rs = rs; 1191 sctx.pv = dk; 1192 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1193 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1194 1195 /* copy data into U(k,:) */ 1196 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1197 jmin = bi[k]+1; jmax = bi[k+1]; 1198 if (jmin < jmax) { 1199 for (j=jmin; j<jmax; j++){ 1200 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1201 } 1202 /* add the k-th row into il and jl */ 1203 il[k] = jmin; 1204 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1205 } 1206 } 1207 } while (sctx.chshift); 1208 ierr = PetscFree(il);CHKERRQ(ierr); 1209 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1210 1211 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1212 C->factor = FACTOR_CHOLESKY; 1213 C->assembled = PETSC_TRUE; 1214 C->preallocated = PETSC_TRUE; 1215 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1216 if (sctx.nshift){ 1217 if (shiftnz) { 1218 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1219 } else if (shiftpd) { 1220 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1221 } 1222 } 1223 PetscFunctionReturn(0); 1224 } 1225 1226 /* 1227 Version for when blocks are 1 by 1 Using natural ordering 1228 */ 1229 #undef __FUNCT__ 1230 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1231 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 1232 { 1233 Mat C = *B; 1234 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1235 PetscErrorCode ierr; 1236 PetscInt i,j,mbs = a->mbs; 1237 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1238 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1239 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1240 PetscReal zeropivot,rs,shiftnz; 1241 PetscReal shiftpd; 1242 ChShift_Ctx sctx; 1243 PetscInt newshift; 1244 1245 PetscFunctionBegin; 1246 /* initialization */ 1247 shiftnz = info->shiftnz; 1248 shiftpd = info->shiftpd; 1249 zeropivot = info->zeropivot; 1250 1251 /* il and jl record the first nonzero element in each row of the accessing 1252 window U(0:k, k:mbs-1). 1253 jl: list of rows to be added to uneliminated rows 1254 i>= k: jl(i) is the first row to be added to row i 1255 i< k: jl(i) is the row following row i in some list of rows 1256 jl(i) = mbs indicates the end of a list 1257 il(i): points to the first nonzero element in U(i,k:mbs-1) 1258 */ 1259 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1260 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1261 jl = il + mbs; 1262 1263 sctx.shift_amount = 0; 1264 sctx.nshift = 0; 1265 do { 1266 sctx.chshift = PETSC_FALSE; 1267 for (i=0; i<mbs; i++) { 1268 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1269 } 1270 1271 for (k = 0; k<mbs; k++){ 1272 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1273 nz = ai[k+1] - ai[k]; 1274 acol = aj + ai[k]; 1275 aval = aa + ai[k]; 1276 bval = ba + bi[k]; 1277 while (nz -- ){ 1278 rtmp[*acol++] = *aval++; 1279 *bval++ = 0.0; /* for in-place factorization */ 1280 } 1281 1282 /* shift the diagonal of the matrix */ 1283 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1284 1285 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1286 dk = rtmp[k]; 1287 i = jl[k]; /* first row to be added to k_th row */ 1288 1289 while (i < k){ 1290 nexti = jl[i]; /* next row to be added to k_th row */ 1291 /* compute multiplier, update D(k) and U(i,k) */ 1292 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1293 uikdi = - ba[ili]*ba[bi[i]]; 1294 dk += uikdi*ba[ili]; 1295 ba[ili] = uikdi; /* -U(i,k) */ 1296 1297 /* add multiple of row i to k-th row ... */ 1298 jmin = ili + 1; 1299 nz = bi[i+1] - jmin; 1300 if (nz > 0){ 1301 bcol = bj + jmin; 1302 bval = ba + jmin; 1303 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1304 /* update il and jl for i-th row */ 1305 il[i] = jmin; 1306 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1307 } 1308 i = nexti; 1309 } 1310 1311 /* shift the diagonals when zero pivot is detected */ 1312 /* compute rs=sum of abs(off-diagonal) */ 1313 rs = 0.0; 1314 jmin = bi[k]+1; 1315 nz = bi[k+1] - jmin; 1316 if (nz){ 1317 bcol = bj + jmin; 1318 while (nz--){ 1319 rs += PetscAbsScalar(rtmp[*bcol]); 1320 bcol++; 1321 } 1322 } 1323 1324 sctx.rs = rs; 1325 sctx.pv = dk; 1326 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1327 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1328 1329 /* copy data into U(k,:) */ 1330 ba[bi[k]] = 1.0/dk; 1331 jmin = bi[k]+1; 1332 nz = bi[k+1] - jmin; 1333 if (nz){ 1334 bcol = bj + jmin; 1335 bval = ba + jmin; 1336 while (nz--){ 1337 *bval++ = rtmp[*bcol]; 1338 rtmp[*bcol++] = 0.0; 1339 } 1340 /* add k-th row into il and jl */ 1341 il[k] = jmin; 1342 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1343 } 1344 } /* end of for (k = 0; k<mbs; k++) */ 1345 } while (sctx.chshift); 1346 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1347 ierr = PetscFree(il);CHKERRQ(ierr); 1348 1349 C->factor = FACTOR_CHOLESKY; 1350 C->assembled = PETSC_TRUE; 1351 C->preallocated = PETSC_TRUE; 1352 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1353 if (sctx.nshift){ 1354 if (shiftnz) { 1355 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1356 } else if (shiftpd) { 1357 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1358 } 1359 } 1360 PetscFunctionReturn(0); 1361 } 1362 1363 #undef __FUNCT__ 1364 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1365 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1366 { 1367 PetscErrorCode ierr; 1368 Mat C; 1369 1370 PetscFunctionBegin; 1371 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1372 ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr); 1373 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1374 PetscFunctionReturn(0); 1375 } 1376 1377 1378