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->free_a = PETSC_TRUE; 189 b->free_ij = PETSC_TRUE; 190 ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr); 191 b->j = ju; 192 b->i = iu; 193 b->diag = 0; 194 b->ilen = 0; 195 b->imax = 0; 196 b->row = perm; 197 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 198 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 199 b->icol = perm; 200 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 201 ierr = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 202 /* In b structure: Free imax, ilen, old a, old j. 203 Allocate idnew, solve_work, new a, new j */ 204 ierr = PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 205 b->maxnz = b->nz = iu[mbs]; 206 207 (*B)->factor = FACTOR_CHOLESKY; 208 (*B)->info.factor_mallocs = reallocs; 209 (*B)->info.fill_ratio_given = f; 210 if (ai[mbs] != 0) { 211 (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]); 212 } else { 213 (*B)->info.fill_ratio_needed = 0.0; 214 } 215 216 if (perm_identity){ 217 switch (bs) { 218 case 1: 219 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 220 (*B)->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 221 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 222 break; 223 case 2: 224 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 225 (*B)->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 226 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 227 break; 228 case 3: 229 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 230 (*B)->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 231 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 232 break; 233 case 4: 234 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 235 (*B)->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 236 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 237 break; 238 case 5: 239 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 240 (*B)->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 241 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 242 break; 243 case 6: 244 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 245 (*B)->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 246 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 247 break; 248 case 7: 249 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 250 (*B)->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 251 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 252 break; 253 default: 254 (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 255 (*B)->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 256 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 257 break; 258 } 259 } 260 PetscFunctionReturn(0); 261 } 262 /* 263 Symbolic U^T*D*U factorization for SBAIJ format. 264 */ 265 #include "petscbt.h" 266 #include "src/mat/utils/freespace.h" 267 #undef __FUNCT__ 268 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ" 269 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *fact) 270 { 271 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data; 272 Mat_SeqSBAIJ *b; 273 Mat B; 274 PetscErrorCode ierr; 275 PetscTruth perm_identity; 276 PetscReal fill = info->fill; 277 PetscInt *rip,i,mbs=a->mbs,bs=A->rmap.bs,*ai,*aj,reallocs=0,prow; 278 PetscInt *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow; 279 PetscInt nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr; 280 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 281 PetscBT lnkbt; 282 283 PetscFunctionBegin; 284 /* 285 This code originally uses Modified Sparse Row (MSR) storage 286 (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise! 287 Then it is rewritten so the factor B takes seqsbaij format. However the associated 288 MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity, 289 thus the original code in MSR format is still used for these cases. 290 The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever 291 MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor. 292 */ 293 if (bs > 1){ 294 ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(A,perm,info,fact);CHKERRQ(ierr); 295 PetscFunctionReturn(0); 296 } 297 298 /* check whether perm is the identity mapping */ 299 ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr); 300 301 if (perm_identity){ 302 a->permute = PETSC_FALSE; 303 ai = a->i; aj = a->j; 304 } else { 305 a->permute = PETSC_TRUE; 306 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 307 ai = a->inew; aj = a->jnew; 308 } 309 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 310 311 /* initialization */ 312 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 313 ui[0] = 0; 314 315 /* jl: linked list for storing indices of the pivot rows 316 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 317 ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr); 318 il = jl + mbs; 319 cols = il + mbs; 320 ui_ptr = (PetscInt**)(cols + mbs); 321 322 for (i=0; i<mbs; i++){ 323 jl[i] = mbs; il[i] = 0; 324 } 325 326 /* create and initialize a linked list for storing column indices of the active row k */ 327 nlnk = mbs + 1; 328 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 329 330 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 331 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 332 current_space = free_space; 333 334 for (k=0; k<mbs; k++){ /* for each active row k */ 335 /* initialize lnk by the column indices of row rip[k] of A */ 336 nzk = 0; 337 ncols = ai[rip[k]+1] - ai[rip[k]]; 338 for (j=0; j<ncols; j++){ 339 i = *(aj + ai[rip[k]] + j); 340 cols[j] = rip[i]; 341 } 342 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 343 nzk += nlnk; 344 345 /* update lnk by computing fill-in for each pivot row to be merged in */ 346 prow = jl[k]; /* 1st pivot row */ 347 348 while (prow < k){ 349 nextprow = jl[prow]; 350 /* merge prow into k-th row */ 351 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 352 jmax = ui[prow+1]; 353 ncols = jmax-jmin; 354 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 355 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 356 nzk += nlnk; 357 358 /* update il and jl for prow */ 359 if (jmin < jmax){ 360 il[prow] = jmin; 361 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 362 } 363 prow = nextprow; 364 } 365 366 /* if free space is not available, make more free space */ 367 if (current_space->local_remaining<nzk) { 368 i = mbs - k + 1; /* num of unfactored rows */ 369 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 370 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 371 reallocs++; 372 } 373 374 /* copy data into free space, then initialize lnk */ 375 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 376 377 /* add the k-th row into il and jl */ 378 if (nzk-1 > 0){ 379 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 380 jl[k] = jl[i]; jl[i] = k; 381 il[k] = ui[k] + 1; 382 } 383 ui_ptr[k] = current_space->array; 384 current_space->array += nzk; 385 current_space->local_used += nzk; 386 current_space->local_remaining -= nzk; 387 388 ui[k+1] = ui[k] + nzk; 389 } 390 391 #if defined(PETSC_USE_INFO) 392 if (ai[mbs] != 0) { 393 PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 394 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 395 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 396 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 397 } else { 398 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 399 } 400 #endif 401 402 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 403 ierr = PetscFree(jl);CHKERRQ(ierr); 404 405 /* destroy list of free space and other temporary array(s) */ 406 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 407 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 408 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 409 410 /* put together the new matrix in MATSEQSBAIJ format */ 411 ierr = MatCreate(PETSC_COMM_SELF,fact);CHKERRQ(ierr); 412 ierr = MatSetSizes(*fact,mbs,mbs,mbs,mbs);CHKERRQ(ierr); 413 B = *fact; 414 ierr = MatSetType(B,MATSEQSBAIJ);CHKERRQ(ierr); 415 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 416 417 b = (Mat_SeqSBAIJ*)B->data; 418 b->singlemalloc = PETSC_FALSE; 419 b->free_a = PETSC_TRUE; 420 b->free_ij = PETSC_TRUE; 421 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 422 b->j = uj; 423 b->i = ui; 424 b->diag = 0; 425 b->ilen = 0; 426 b->imax = 0; 427 b->row = perm; 428 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 429 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 430 b->icol = perm; 431 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 432 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 433 ierr = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 434 b->maxnz = b->nz = ui[mbs]; 435 436 B->factor = FACTOR_CHOLESKY; 437 B->info.factor_mallocs = reallocs; 438 B->info.fill_ratio_given = fill; 439 if (ai[mbs] != 0) { 440 B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 441 } else { 442 B->info.fill_ratio_needed = 0.0; 443 } 444 445 if (perm_identity){ 446 switch (bs) { 447 case 1: 448 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 449 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 450 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 451 break; 452 case 2: 453 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 454 B->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 455 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 456 break; 457 case 3: 458 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 459 B->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 460 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 461 break; 462 case 4: 463 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 464 B->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 465 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 466 break; 467 case 5: 468 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 469 B->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 470 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 471 break; 472 case 6: 473 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 474 B->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 475 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 476 break; 477 case 7: 478 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 479 B->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 480 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 481 break; 482 default: 483 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 484 B->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 485 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 486 break; 487 } 488 } 489 PetscFunctionReturn(0); 490 } 491 #undef __FUNCT__ 492 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 493 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,MatFactorInfo *info,Mat *B) 494 { 495 Mat C = *B; 496 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 497 IS perm = b->row; 498 PetscErrorCode ierr; 499 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 500 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 501 PetscInt bs=A->rmap.bs,bs2 = a->bs2; 502 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 503 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 504 MatScalar *work; 505 PetscInt *pivots; 506 507 PetscFunctionBegin; 508 /* initialization */ 509 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 510 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 511 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 512 jl = il + mbs; 513 for (i=0; i<mbs; i++) { 514 jl[i] = mbs; il[0] = 0; 515 } 516 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 517 uik = dk + bs2; 518 work = uik + bs2; 519 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 520 521 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 522 523 /* check permutation */ 524 if (!a->permute){ 525 ai = a->i; aj = a->j; aa = a->a; 526 } else { 527 ai = a->inew; aj = a->jnew; 528 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 529 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 530 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 531 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 532 533 for (i=0; i<mbs; i++){ 534 jmin = ai[i]; jmax = ai[i+1]; 535 for (j=jmin; j<jmax; j++){ 536 while (a2anew[j] != j){ 537 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 538 for (k1=0; k1<bs2; k1++){ 539 dk[k1] = aa[k*bs2+k1]; 540 aa[k*bs2+k1] = aa[j*bs2+k1]; 541 aa[j*bs2+k1] = dk[k1]; 542 } 543 } 544 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 545 if (i > aj[j]){ 546 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 547 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 548 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 549 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 550 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 551 } 552 } 553 } 554 } 555 ierr = PetscFree(a2anew);CHKERRQ(ierr); 556 } 557 558 /* for each row k */ 559 for (k = 0; k<mbs; k++){ 560 561 /*initialize k-th row with elements nonzero in row perm(k) of A */ 562 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 563 564 ap = aa + jmin*bs2; 565 for (j = jmin; j < jmax; j++){ 566 vj = perm_ptr[aj[j]]; /* block col. index */ 567 rtmp_ptr = rtmp + vj*bs2; 568 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 569 } 570 571 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 572 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 573 i = jl[k]; /* first row to be added to k_th row */ 574 575 while (i < k){ 576 nexti = jl[i]; /* next row to be added to k_th row */ 577 578 /* compute multiplier */ 579 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 580 581 /* uik = -inv(Di)*U_bar(i,k) */ 582 diag = ba + i*bs2; 583 u = ba + ili*bs2; 584 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 585 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 586 587 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 588 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 589 590 /* update -U(i,k) */ 591 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 592 593 /* add multiple of row i to k-th row ... */ 594 jmin = ili + 1; jmax = bi[i+1]; 595 if (jmin < jmax){ 596 for (j=jmin; j<jmax; j++) { 597 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 598 rtmp_ptr = rtmp + bj[j]*bs2; 599 u = ba + j*bs2; 600 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 601 } 602 603 /* ... add i to row list for next nonzero entry */ 604 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 605 j = bj[jmin]; 606 jl[i] = jl[j]; jl[j] = i; /* update jl */ 607 } 608 i = nexti; 609 } 610 611 /* save nonzero entries in k-th row of U ... */ 612 613 /* invert diagonal block */ 614 diag = ba+k*bs2; 615 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 616 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 617 618 jmin = bi[k]; jmax = bi[k+1]; 619 if (jmin < jmax) { 620 for (j=jmin; j<jmax; j++){ 621 vj = bj[j]; /* block col. index of U */ 622 u = ba + j*bs2; 623 rtmp_ptr = rtmp + vj*bs2; 624 for (k1=0; k1<bs2; k1++){ 625 *u++ = *rtmp_ptr; 626 *rtmp_ptr++ = 0.0; 627 } 628 } 629 630 /* ... add k to row list for first nonzero entry in k-th row */ 631 il[k] = jmin; 632 i = bj[jmin]; 633 jl[k] = jl[i]; jl[i] = k; 634 } 635 } 636 637 ierr = PetscFree(rtmp);CHKERRQ(ierr); 638 ierr = PetscFree(il);CHKERRQ(ierr); 639 ierr = PetscFree(dk);CHKERRQ(ierr); 640 ierr = PetscFree(pivots);CHKERRQ(ierr); 641 if (a->permute){ 642 ierr = PetscFree(aa);CHKERRQ(ierr); 643 } 644 645 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 646 C->factor = FACTOR_CHOLESKY; 647 C->assembled = PETSC_TRUE; 648 C->preallocated = PETSC_TRUE; 649 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 650 PetscFunctionReturn(0); 651 } 652 653 #undef __FUNCT__ 654 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 655 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 656 { 657 Mat C = *B; 658 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 659 PetscErrorCode ierr; 660 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 661 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 662 PetscInt bs=A->rmap.bs,bs2 = a->bs2; 663 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 664 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 665 MatScalar *work; 666 PetscInt *pivots; 667 668 PetscFunctionBegin; 669 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 670 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 671 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 672 jl = il + mbs; 673 for (i=0; i<mbs; i++) { 674 jl[i] = mbs; il[0] = 0; 675 } 676 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 677 uik = dk + bs2; 678 work = uik + bs2; 679 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 680 681 ai = a->i; aj = a->j; aa = a->a; 682 683 /* for each row k */ 684 for (k = 0; k<mbs; k++){ 685 686 /*initialize k-th row with elements nonzero in row k of A */ 687 jmin = ai[k]; jmax = ai[k+1]; 688 ap = aa + jmin*bs2; 689 for (j = jmin; j < jmax; j++){ 690 vj = aj[j]; /* block col. index */ 691 rtmp_ptr = rtmp + vj*bs2; 692 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 693 } 694 695 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 696 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 697 i = jl[k]; /* first row to be added to k_th row */ 698 699 while (i < k){ 700 nexti = jl[i]; /* next row to be added to k_th row */ 701 702 /* compute multiplier */ 703 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 704 705 /* uik = -inv(Di)*U_bar(i,k) */ 706 diag = ba + i*bs2; 707 u = ba + ili*bs2; 708 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 709 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 710 711 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 712 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 713 714 /* update -U(i,k) */ 715 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 716 717 /* add multiple of row i to k-th row ... */ 718 jmin = ili + 1; jmax = bi[i+1]; 719 if (jmin < jmax){ 720 for (j=jmin; j<jmax; j++) { 721 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 722 rtmp_ptr = rtmp + bj[j]*bs2; 723 u = ba + j*bs2; 724 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 725 } 726 727 /* ... add i to row list for next nonzero entry */ 728 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 729 j = bj[jmin]; 730 jl[i] = jl[j]; jl[j] = i; /* update jl */ 731 } 732 i = nexti; 733 } 734 735 /* save nonzero entries in k-th row of U ... */ 736 737 /* invert diagonal block */ 738 diag = ba+k*bs2; 739 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 740 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 741 742 jmin = bi[k]; jmax = bi[k+1]; 743 if (jmin < jmax) { 744 for (j=jmin; j<jmax; j++){ 745 vj = bj[j]; /* block col. index of U */ 746 u = ba + j*bs2; 747 rtmp_ptr = rtmp + vj*bs2; 748 for (k1=0; k1<bs2; k1++){ 749 *u++ = *rtmp_ptr; 750 *rtmp_ptr++ = 0.0; 751 } 752 } 753 754 /* ... add k to row list for first nonzero entry in k-th row */ 755 il[k] = jmin; 756 i = bj[jmin]; 757 jl[k] = jl[i]; jl[i] = k; 758 } 759 } 760 761 ierr = PetscFree(rtmp);CHKERRQ(ierr); 762 ierr = PetscFree(il);CHKERRQ(ierr); 763 ierr = PetscFree(dk);CHKERRQ(ierr); 764 ierr = PetscFree(pivots);CHKERRQ(ierr); 765 766 C->factor = FACTOR_CHOLESKY; 767 C->assembled = PETSC_TRUE; 768 C->preallocated = PETSC_TRUE; 769 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 770 PetscFunctionReturn(0); 771 } 772 773 /* 774 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 775 Version for blocks 2 by 2. 776 */ 777 #undef __FUNCT__ 778 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 779 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B) 780 { 781 Mat C = *B; 782 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 783 IS perm = b->row; 784 PetscErrorCode ierr; 785 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 786 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 787 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 788 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 789 790 PetscFunctionBegin; 791 /* initialization */ 792 /* il and jl record the first nonzero element in each row of the accessing 793 window U(0:k, k:mbs-1). 794 jl: list of rows to be added to uneliminated rows 795 i>= k: jl(i) is the first row to be added to row i 796 i< k: jl(i) is the row following row i in some list of rows 797 jl(i) = mbs indicates the end of a list 798 il(i): points to the first nonzero element in columns k,...,mbs-1 of 799 row i of U */ 800 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 801 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 802 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 803 jl = il + mbs; 804 for (i=0; i<mbs; i++) { 805 jl[i] = mbs; il[0] = 0; 806 } 807 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 808 uik = dk + 4; 809 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 810 811 /* check permutation */ 812 if (!a->permute){ 813 ai = a->i; aj = a->j; aa = a->a; 814 } else { 815 ai = a->inew; aj = a->jnew; 816 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 817 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 818 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 819 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 820 821 for (i=0; i<mbs; i++){ 822 jmin = ai[i]; jmax = ai[i+1]; 823 for (j=jmin; j<jmax; j++){ 824 while (a2anew[j] != j){ 825 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 826 for (k1=0; k1<4; k1++){ 827 dk[k1] = aa[k*4+k1]; 828 aa[k*4+k1] = aa[j*4+k1]; 829 aa[j*4+k1] = dk[k1]; 830 } 831 } 832 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 833 if (i > aj[j]){ 834 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 835 ap = aa + j*4; /* ptr to the beginning of the block */ 836 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 837 ap[1] = ap[2]; 838 ap[2] = dk[1]; 839 } 840 } 841 } 842 ierr = PetscFree(a2anew);CHKERRQ(ierr); 843 } 844 845 /* for each row k */ 846 for (k = 0; k<mbs; k++){ 847 848 /*initialize k-th row with elements nonzero in row perm(k) of A */ 849 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 850 ap = aa + jmin*4; 851 for (j = jmin; j < jmax; j++){ 852 vj = perm_ptr[aj[j]]; /* block col. index */ 853 rtmp_ptr = rtmp + vj*4; 854 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 855 } 856 857 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 858 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 859 i = jl[k]; /* first row to be added to k_th row */ 860 861 while (i < k){ 862 nexti = jl[i]; /* next row to be added to k_th row */ 863 864 /* compute multiplier */ 865 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 866 867 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 868 diag = ba + i*4; 869 u = ba + ili*4; 870 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 871 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 872 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 873 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 874 875 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 876 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 877 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 878 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 879 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 880 881 /* update -U(i,k): ba[ili] = uik */ 882 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 883 884 /* add multiple of row i to k-th row ... */ 885 jmin = ili + 1; jmax = bi[i+1]; 886 if (jmin < jmax){ 887 for (j=jmin; j<jmax; j++) { 888 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 889 rtmp_ptr = rtmp + bj[j]*4; 890 u = ba + j*4; 891 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 892 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 893 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 894 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 895 } 896 897 /* ... add i to row list for next nonzero entry */ 898 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 899 j = bj[jmin]; 900 jl[i] = jl[j]; jl[j] = i; /* update jl */ 901 } 902 i = nexti; 903 } 904 905 /* save nonzero entries in k-th row of U ... */ 906 907 /* invert diagonal block */ 908 diag = ba+k*4; 909 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 910 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 911 912 jmin = bi[k]; jmax = bi[k+1]; 913 if (jmin < jmax) { 914 for (j=jmin; j<jmax; j++){ 915 vj = bj[j]; /* block col. index of U */ 916 u = ba + j*4; 917 rtmp_ptr = rtmp + vj*4; 918 for (k1=0; k1<4; k1++){ 919 *u++ = *rtmp_ptr; 920 *rtmp_ptr++ = 0.0; 921 } 922 } 923 924 /* ... add k to row list for first nonzero entry in k-th row */ 925 il[k] = jmin; 926 i = bj[jmin]; 927 jl[k] = jl[i]; jl[i] = k; 928 } 929 } 930 931 ierr = PetscFree(rtmp);CHKERRQ(ierr); 932 ierr = PetscFree(il);CHKERRQ(ierr); 933 ierr = PetscFree(dk);CHKERRQ(ierr); 934 if (a->permute) { 935 ierr = PetscFree(aa);CHKERRQ(ierr); 936 } 937 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 938 C->factor = FACTOR_CHOLESKY; 939 C->assembled = PETSC_TRUE; 940 C->preallocated = PETSC_TRUE; 941 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 942 PetscFunctionReturn(0); 943 } 944 945 /* 946 Version for when blocks are 2 by 2 Using natural ordering 947 */ 948 #undef __FUNCT__ 949 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 950 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 951 { 952 Mat C = *B; 953 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 954 PetscErrorCode ierr; 955 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 956 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 957 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 958 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 959 960 PetscFunctionBegin; 961 /* initialization */ 962 /* il and jl record the first nonzero element in each row of the accessing 963 window U(0:k, k:mbs-1). 964 jl: list of rows to be added to uneliminated rows 965 i>= k: jl(i) is the first row to be added to row i 966 i< k: jl(i) is the row following row i in some list of rows 967 jl(i) = mbs indicates the end of a list 968 il(i): points to the first nonzero element in columns k,...,mbs-1 of 969 row i of U */ 970 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 971 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 972 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 973 jl = il + mbs; 974 for (i=0; i<mbs; i++) { 975 jl[i] = mbs; il[0] = 0; 976 } 977 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 978 uik = dk + 4; 979 980 ai = a->i; aj = a->j; aa = a->a; 981 982 /* for each row k */ 983 for (k = 0; k<mbs; k++){ 984 985 /*initialize k-th row with elements nonzero in row k of A */ 986 jmin = ai[k]; jmax = ai[k+1]; 987 ap = aa + jmin*4; 988 for (j = jmin; j < jmax; j++){ 989 vj = aj[j]; /* block col. index */ 990 rtmp_ptr = rtmp + vj*4; 991 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 992 } 993 994 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 995 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 996 i = jl[k]; /* first row to be added to k_th row */ 997 998 while (i < k){ 999 nexti = jl[i]; /* next row to be added to k_th row */ 1000 1001 /* compute multiplier */ 1002 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1003 1004 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1005 diag = ba + i*4; 1006 u = ba + ili*4; 1007 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1008 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1009 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1010 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1011 1012 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1013 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1014 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1015 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1016 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1017 1018 /* update -U(i,k): ba[ili] = uik */ 1019 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1020 1021 /* add multiple of row i to k-th row ... */ 1022 jmin = ili + 1; jmax = bi[i+1]; 1023 if (jmin < jmax){ 1024 for (j=jmin; j<jmax; j++) { 1025 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1026 rtmp_ptr = rtmp + bj[j]*4; 1027 u = ba + j*4; 1028 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1029 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1030 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1031 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1032 } 1033 1034 /* ... add i to row list for next nonzero entry */ 1035 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1036 j = bj[jmin]; 1037 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1038 } 1039 i = nexti; 1040 } 1041 1042 /* save nonzero entries in k-th row of U ... */ 1043 1044 /* invert diagonal block */ 1045 diag = ba+k*4; 1046 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1047 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1048 1049 jmin = bi[k]; jmax = bi[k+1]; 1050 if (jmin < jmax) { 1051 for (j=jmin; j<jmax; j++){ 1052 vj = bj[j]; /* block col. index of U */ 1053 u = ba + j*4; 1054 rtmp_ptr = rtmp + vj*4; 1055 for (k1=0; k1<4; k1++){ 1056 *u++ = *rtmp_ptr; 1057 *rtmp_ptr++ = 0.0; 1058 } 1059 } 1060 1061 /* ... add k to row list for first nonzero entry in k-th row */ 1062 il[k] = jmin; 1063 i = bj[jmin]; 1064 jl[k] = jl[i]; jl[i] = k; 1065 } 1066 } 1067 1068 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1069 ierr = PetscFree(il);CHKERRQ(ierr); 1070 ierr = PetscFree(dk);CHKERRQ(ierr); 1071 1072 C->factor = FACTOR_CHOLESKY; 1073 C->assembled = PETSC_TRUE; 1074 C->preallocated = PETSC_TRUE; 1075 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1076 PetscFunctionReturn(0); 1077 } 1078 1079 /* 1080 Numeric U^T*D*U factorization for SBAIJ format. 1081 Version for blocks are 1 by 1. 1082 */ 1083 #undef __FUNCT__ 1084 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1085 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B) 1086 { 1087 Mat C = *B; 1088 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1089 IS ip=b->row; 1090 PetscErrorCode ierr; 1091 PetscInt *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1092 PetscInt *ai,*aj,*a2anew; 1093 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1094 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1095 PetscReal zeropivot,rs,shiftnz; 1096 PetscReal shiftpd; 1097 ChShift_Ctx sctx; 1098 PetscInt newshift; 1099 1100 PetscFunctionBegin; 1101 /* initialization */ 1102 shiftnz = info->shiftnz; 1103 shiftpd = info->shiftpd; 1104 zeropivot = info->zeropivot; 1105 1106 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1107 if (!a->permute){ 1108 ai = a->i; aj = a->j; aa = a->a; 1109 } else { 1110 ai = a->inew; aj = a->jnew; 1111 nz = ai[mbs]; 1112 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1113 a2anew = a->a2anew; 1114 bval = a->a; 1115 for (j=0; j<nz; j++){ 1116 aa[a2anew[j]] = *(bval++); 1117 } 1118 } 1119 1120 /* initialization */ 1121 /* il and jl record the first nonzero element in each row of the accessing 1122 window U(0:k, k:mbs-1). 1123 jl: list of rows to be added to uneliminated rows 1124 i>= k: jl(i) is the first row to be added to row i 1125 i< k: jl(i) is the row following row i in some list of rows 1126 jl(i) = mbs indicates the end of a list 1127 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1128 row i of U */ 1129 nz = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar); 1130 ierr = PetscMalloc(nz,&il);CHKERRQ(ierr); 1131 jl = il + mbs; 1132 rtmp = (MatScalar*)(jl + mbs); 1133 1134 sctx.shift_amount = 0; 1135 sctx.nshift = 0; 1136 do { 1137 sctx.chshift = PETSC_FALSE; 1138 for (i=0; i<mbs; i++) { 1139 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1140 } 1141 1142 for (k = 0; k<mbs; k++){ 1143 /*initialize k-th row by the perm[k]-th row of A */ 1144 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1145 bval = ba + bi[k]; 1146 for (j = jmin; j < jmax; j++){ 1147 col = rip[aj[j]]; 1148 rtmp[col] = aa[j]; 1149 *bval++ = 0.0; /* for in-place factorization */ 1150 } 1151 1152 /* shift the diagonal of the matrix */ 1153 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1154 1155 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1156 dk = rtmp[k]; 1157 i = jl[k]; /* first row to be added to k_th row */ 1158 1159 while (i < k){ 1160 nexti = jl[i]; /* next row to be added to k_th row */ 1161 1162 /* compute multiplier, update diag(k) and U(i,k) */ 1163 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1164 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1165 dk += uikdi*ba[ili]; 1166 ba[ili] = uikdi; /* -U(i,k) */ 1167 1168 /* add multiple of row i to k-th row */ 1169 jmin = ili + 1; jmax = bi[i+1]; 1170 if (jmin < jmax){ 1171 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1172 /* update il and jl for row i */ 1173 il[i] = jmin; 1174 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1175 } 1176 i = nexti; 1177 } 1178 1179 /* shift the diagonals when zero pivot is detected */ 1180 /* compute rs=sum of abs(off-diagonal) */ 1181 rs = 0.0; 1182 jmin = bi[k]+1; 1183 nz = bi[k+1] - jmin; 1184 if (nz){ 1185 bcol = bj + jmin; 1186 while (nz--){ 1187 rs += PetscAbsScalar(rtmp[*bcol]); 1188 bcol++; 1189 } 1190 } 1191 1192 sctx.rs = rs; 1193 sctx.pv = dk; 1194 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1195 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1196 1197 /* copy data into U(k,:) */ 1198 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1199 jmin = bi[k]+1; jmax = bi[k+1]; 1200 if (jmin < jmax) { 1201 for (j=jmin; j<jmax; j++){ 1202 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1203 } 1204 /* add the k-th row into il and jl */ 1205 il[k] = jmin; 1206 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1207 } 1208 } 1209 } while (sctx.chshift); 1210 ierr = PetscFree(il);CHKERRQ(ierr); 1211 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1212 1213 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1214 C->factor = FACTOR_CHOLESKY; 1215 C->assembled = PETSC_TRUE; 1216 C->preallocated = PETSC_TRUE; 1217 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1218 if (sctx.nshift){ 1219 if (shiftnz) { 1220 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1221 } else if (shiftpd) { 1222 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1223 } 1224 } 1225 PetscFunctionReturn(0); 1226 } 1227 1228 /* 1229 Version for when blocks are 1 by 1 Using natural ordering 1230 */ 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1233 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 1234 { 1235 Mat C = *B; 1236 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1237 PetscErrorCode ierr; 1238 PetscInt i,j,mbs = a->mbs; 1239 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1240 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1241 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1242 PetscReal zeropivot,rs,shiftnz; 1243 PetscReal shiftpd; 1244 ChShift_Ctx sctx; 1245 PetscInt newshift; 1246 1247 PetscFunctionBegin; 1248 /* initialization */ 1249 shiftnz = info->shiftnz; 1250 shiftpd = info->shiftpd; 1251 zeropivot = info->zeropivot; 1252 1253 /* il and jl record the first nonzero element in each row of the accessing 1254 window U(0:k, k:mbs-1). 1255 jl: list of rows to be added to uneliminated rows 1256 i>= k: jl(i) is the first row to be added to row i 1257 i< k: jl(i) is the row following row i in some list of rows 1258 jl(i) = mbs indicates the end of a list 1259 il(i): points to the first nonzero element in U(i,k:mbs-1) 1260 */ 1261 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1262 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1263 jl = il + mbs; 1264 1265 sctx.shift_amount = 0; 1266 sctx.nshift = 0; 1267 do { 1268 sctx.chshift = PETSC_FALSE; 1269 for (i=0; i<mbs; i++) { 1270 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1271 } 1272 1273 for (k = 0; k<mbs; k++){ 1274 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1275 nz = ai[k+1] - ai[k]; 1276 acol = aj + ai[k]; 1277 aval = aa + ai[k]; 1278 bval = ba + bi[k]; 1279 while (nz -- ){ 1280 rtmp[*acol++] = *aval++; 1281 *bval++ = 0.0; /* for in-place factorization */ 1282 } 1283 1284 /* shift the diagonal of the matrix */ 1285 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1286 1287 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1288 dk = rtmp[k]; 1289 i = jl[k]; /* first row to be added to k_th row */ 1290 1291 while (i < k){ 1292 nexti = jl[i]; /* next row to be added to k_th row */ 1293 /* compute multiplier, update D(k) and U(i,k) */ 1294 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1295 uikdi = - ba[ili]*ba[bi[i]]; 1296 dk += uikdi*ba[ili]; 1297 ba[ili] = uikdi; /* -U(i,k) */ 1298 1299 /* add multiple of row i to k-th row ... */ 1300 jmin = ili + 1; 1301 nz = bi[i+1] - jmin; 1302 if (nz > 0){ 1303 bcol = bj + jmin; 1304 bval = ba + jmin; 1305 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1306 /* update il and jl for i-th row */ 1307 il[i] = jmin; 1308 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1309 } 1310 i = nexti; 1311 } 1312 1313 /* shift the diagonals when zero pivot is detected */ 1314 /* compute rs=sum of abs(off-diagonal) */ 1315 rs = 0.0; 1316 jmin = bi[k]+1; 1317 nz = bi[k+1] - jmin; 1318 if (nz){ 1319 bcol = bj + jmin; 1320 while (nz--){ 1321 rs += PetscAbsScalar(rtmp[*bcol]); 1322 bcol++; 1323 } 1324 } 1325 1326 sctx.rs = rs; 1327 sctx.pv = dk; 1328 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1329 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1330 1331 /* copy data into U(k,:) */ 1332 ba[bi[k]] = 1.0/dk; 1333 jmin = bi[k]+1; 1334 nz = bi[k+1] - jmin; 1335 if (nz){ 1336 bcol = bj + jmin; 1337 bval = ba + jmin; 1338 while (nz--){ 1339 *bval++ = rtmp[*bcol]; 1340 rtmp[*bcol++] = 0.0; 1341 } 1342 /* add k-th row into il and jl */ 1343 il[k] = jmin; 1344 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1345 } 1346 } /* end of for (k = 0; k<mbs; k++) */ 1347 } while (sctx.chshift); 1348 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1349 ierr = PetscFree(il);CHKERRQ(ierr); 1350 1351 C->factor = FACTOR_CHOLESKY; 1352 C->assembled = PETSC_TRUE; 1353 C->preallocated = PETSC_TRUE; 1354 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1355 if (sctx.nshift){ 1356 if (shiftnz) { 1357 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1358 } else if (shiftpd) { 1359 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1360 } 1361 } 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNCT__ 1366 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1367 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1368 { 1369 PetscErrorCode ierr; 1370 Mat C; 1371 1372 PetscFunctionBegin; 1373 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1374 ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr); 1375 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1376 PetscFunctionReturn(0); 1377 } 1378 1379 1380