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 SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format"); 306 /* There are bugs for reordeing. Needs further work. 307 MatReordering for sbaij cannot be efficient. User should use aij formt! */ 308 a->permute = PETSC_TRUE; 309 ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr); 310 ai = a->inew; aj = a->jnew; 311 } 312 ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr); 313 314 /* initialization */ 315 ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr); 316 ui[0] = 0; 317 318 /* jl: linked list for storing indices of the pivot rows 319 il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */ 320 ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr); 321 il = jl + mbs; 322 cols = il + mbs; 323 ui_ptr = (PetscInt**)(cols + mbs); 324 325 for (i=0; i<mbs; i++){ 326 jl[i] = mbs; il[i] = 0; 327 } 328 329 /* create and initialize a linked list for storing column indices of the active row k */ 330 nlnk = mbs + 1; 331 ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 332 333 /* initial FreeSpace size is fill*(ai[mbs]+1) */ 334 ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr); 335 current_space = free_space; 336 337 for (k=0; k<mbs; k++){ /* for each active row k */ 338 /* initialize lnk by the column indices of row rip[k] of A */ 339 nzk = 0; 340 ncols = ai[rip[k]+1] - ai[rip[k]]; 341 for (j=0; j<ncols; j++){ 342 i = *(aj + ai[rip[k]] + j); 343 cols[j] = rip[i]; 344 } 345 ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 346 nzk += nlnk; 347 348 /* update lnk by computing fill-in for each pivot row to be merged in */ 349 prow = jl[k]; /* 1st pivot row */ 350 351 while (prow < k){ 352 nextprow = jl[prow]; 353 /* merge prow into k-th row */ 354 jmin = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */ 355 jmax = ui[prow+1]; 356 ncols = jmax-jmin; 357 uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */ 358 ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr); 359 nzk += nlnk; 360 361 /* update il and jl for prow */ 362 if (jmin < jmax){ 363 il[prow] = jmin; 364 j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow; 365 } 366 prow = nextprow; 367 } 368 369 /* if free space is not available, make more free space */ 370 if (current_space->local_remaining<nzk) { 371 i = mbs - k + 1; /* num of unfactored rows */ 372 i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */ 373 ierr = PetscFreeSpaceGet(i,¤t_space);CHKERRQ(ierr); 374 reallocs++; 375 } 376 377 /* copy data into free space, then initialize lnk */ 378 ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 379 380 /* add the k-th row into il and jl */ 381 if (nzk-1 > 0){ 382 i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */ 383 jl[k] = jl[i]; jl[i] = k; 384 il[k] = ui[k] + 1; 385 } 386 ui_ptr[k] = current_space->array; 387 current_space->array += nzk; 388 current_space->local_used += nzk; 389 current_space->local_remaining -= nzk; 390 391 ui[k+1] = ui[k] + nzk; 392 } 393 394 #if defined(PETSC_USE_INFO) 395 if (ai[mbs] != 0) { 396 PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 397 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr); 398 ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr); 399 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr); 400 } else { 401 ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr); 402 } 403 #endif 404 405 ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr); 406 ierr = PetscFree(jl);CHKERRQ(ierr); 407 408 /* destroy list of free space and other temporary array(s) */ 409 ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr); 410 ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr); 411 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 412 413 /* put together the new matrix in MATSEQSBAIJ format */ 414 ierr = MatCreate(PETSC_COMM_SELF,fact);CHKERRQ(ierr); 415 ierr = MatSetSizes(*fact,mbs,mbs,mbs,mbs);CHKERRQ(ierr); 416 B = *fact; 417 ierr = MatSetType(B,MATSEQSBAIJ);CHKERRQ(ierr); 418 ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr); 419 420 b = (Mat_SeqSBAIJ*)B->data; 421 b->singlemalloc = PETSC_FALSE; 422 b->free_a = PETSC_TRUE; 423 b->free_ij = PETSC_TRUE; 424 ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr); 425 b->j = uj; 426 b->i = ui; 427 b->diag = 0; 428 b->ilen = 0; 429 b->imax = 0; 430 b->row = perm; 431 b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */ 432 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 433 b->icol = perm; 434 ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr); 435 ierr = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr); 436 ierr = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr); 437 b->maxnz = b->nz = ui[mbs]; 438 439 B->factor = FACTOR_CHOLESKY; 440 B->info.factor_mallocs = reallocs; 441 B->info.fill_ratio_given = fill; 442 if (ai[mbs] != 0) { 443 B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]); 444 } else { 445 B->info.fill_ratio_needed = 0.0; 446 } 447 448 if (perm_identity){ 449 switch (bs) { 450 case 1: 451 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering; 452 B->ops->solve = MatSolve_SeqSBAIJ_1_NaturalOrdering; 453 B->ops->forwardsolve = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering; 454 B->ops->backwardsolve = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering; 455 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr); 456 break; 457 case 2: 458 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering; 459 B->ops->solve = MatSolve_SeqSBAIJ_2_NaturalOrdering; 460 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr); 461 break; 462 case 3: 463 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering; 464 B->ops->solve = MatSolve_SeqSBAIJ_3_NaturalOrdering; 465 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr); 466 break; 467 case 4: 468 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering; 469 B->ops->solve = MatSolve_SeqSBAIJ_4_NaturalOrdering; 470 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr); 471 break; 472 case 5: 473 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering; 474 B->ops->solve = MatSolve_SeqSBAIJ_5_NaturalOrdering; 475 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr); 476 break; 477 case 6: 478 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering; 479 B->ops->solve = MatSolve_SeqSBAIJ_6_NaturalOrdering; 480 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr); 481 break; 482 case 7: 483 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering; 484 B->ops->solve = MatSolve_SeqSBAIJ_7_NaturalOrdering; 485 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr); 486 break; 487 default: 488 B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering; 489 B->ops->solve = MatSolve_SeqSBAIJ_N_NaturalOrdering; 490 ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr); 491 break; 492 } 493 } 494 PetscFunctionReturn(0); 495 } 496 #undef __FUNCT__ 497 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N" 498 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,MatFactorInfo *info,Mat *B) 499 { 500 Mat C = *B; 501 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 502 IS perm = b->row; 503 PetscErrorCode ierr; 504 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 505 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 506 PetscInt bs=A->rmap.bs,bs2 = a->bs2,bslog = 0; 507 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 508 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 509 MatScalar *work; 510 PetscInt *pivots; 511 512 PetscFunctionBegin; 513 /* initialization */ 514 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 515 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 516 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 517 jl = il + mbs; 518 for (i=0; i<mbs; i++) { 519 jl[i] = mbs; il[0] = 0; 520 } 521 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 522 uik = dk + bs2; 523 work = uik + bs2; 524 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 525 526 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 527 528 /* check permutation */ 529 if (!a->permute){ 530 ai = a->i; aj = a->j; aa = a->a; 531 } else { 532 ai = a->inew; aj = a->jnew; 533 ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 534 ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 535 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 536 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 537 538 /* flops in while loop */ 539 bslog = 2*bs*bs2; 540 541 for (i=0; i<mbs; i++){ 542 jmin = ai[i]; jmax = ai[i+1]; 543 for (j=jmin; j<jmax; j++){ 544 while (a2anew[j] != j){ 545 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 546 for (k1=0; k1<bs2; k1++){ 547 dk[k1] = aa[k*bs2+k1]; 548 aa[k*bs2+k1] = aa[j*bs2+k1]; 549 aa[j*bs2+k1] = dk[k1]; 550 } 551 } 552 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 553 if (i > aj[j]){ 554 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 555 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 556 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 557 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 558 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 559 } 560 } 561 } 562 } 563 ierr = PetscFree(a2anew);CHKERRQ(ierr); 564 } 565 566 /* for each row k */ 567 for (k = 0; k<mbs; k++){ 568 569 /*initialize k-th row with elements nonzero in row perm(k) of A */ 570 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 571 572 ap = aa + jmin*bs2; 573 for (j = jmin; j < jmax; j++){ 574 vj = perm_ptr[aj[j]]; /* block col. index */ 575 rtmp_ptr = rtmp + vj*bs2; 576 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 577 } 578 579 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 580 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 581 i = jl[k]; /* first row to be added to k_th row */ 582 583 while (i < k){ 584 nexti = jl[i]; /* next row to be added to k_th row */ 585 586 /* compute multiplier */ 587 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 588 589 /* uik = -inv(Di)*U_bar(i,k) */ 590 diag = ba + i*bs2; 591 u = ba + ili*bs2; 592 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 593 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 594 595 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 596 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 597 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 598 599 /* update -U(i,k) */ 600 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 601 602 /* add multiple of row i to k-th row ... */ 603 jmin = ili + 1; jmax = bi[i+1]; 604 if (jmin < jmax){ 605 for (j=jmin; j<jmax; j++) { 606 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 607 rtmp_ptr = rtmp + bj[j]*bs2; 608 u = ba + j*bs2; 609 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 610 } 611 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 612 613 /* ... add i to row list for next nonzero entry */ 614 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 615 j = bj[jmin]; 616 jl[i] = jl[j]; jl[j] = i; /* update jl */ 617 } 618 i = nexti; 619 } 620 621 /* save nonzero entries in k-th row of U ... */ 622 623 /* invert diagonal block */ 624 diag = ba+k*bs2; 625 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 626 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 627 628 jmin = bi[k]; jmax = bi[k+1]; 629 if (jmin < jmax) { 630 for (j=jmin; j<jmax; j++){ 631 vj = bj[j]; /* block col. index of U */ 632 u = ba + j*bs2; 633 rtmp_ptr = rtmp + vj*bs2; 634 for (k1=0; k1<bs2; k1++){ 635 *u++ = *rtmp_ptr; 636 *rtmp_ptr++ = 0.0; 637 } 638 } 639 640 /* ... add k to row list for first nonzero entry in k-th row */ 641 il[k] = jmin; 642 i = bj[jmin]; 643 jl[k] = jl[i]; jl[i] = k; 644 } 645 } 646 647 ierr = PetscFree(rtmp);CHKERRQ(ierr); 648 ierr = PetscFree(il);CHKERRQ(ierr); 649 ierr = PetscFree(dk);CHKERRQ(ierr); 650 ierr = PetscFree(pivots);CHKERRQ(ierr); 651 if (a->permute){ 652 ierr = PetscFree(aa);CHKERRQ(ierr); 653 } 654 655 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 656 C->factor = FACTOR_CHOLESKY; 657 C->assembled = PETSC_TRUE; 658 C->preallocated = PETSC_TRUE; 659 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 660 PetscFunctionReturn(0); 661 } 662 663 #undef __FUNCT__ 664 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 665 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 666 { 667 Mat C = *B; 668 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 669 PetscErrorCode ierr; 670 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 671 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 672 PetscInt bs=A->rmap.bs,bs2 = a->bs2,bslog; 673 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 674 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 675 MatScalar *work; 676 PetscInt *pivots; 677 678 PetscFunctionBegin; 679 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 680 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 681 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 682 jl = il + mbs; 683 for (i=0; i<mbs; i++) { 684 jl[i] = mbs; il[0] = 0; 685 } 686 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 687 uik = dk + bs2; 688 work = uik + bs2; 689 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 690 691 ai = a->i; aj = a->j; aa = a->a; 692 693 /* flops in while loop */ 694 bslog = 2*bs*bs2; 695 696 /* for each row k */ 697 for (k = 0; k<mbs; k++){ 698 699 /*initialize k-th row with elements nonzero in row k of A */ 700 jmin = ai[k]; jmax = ai[k+1]; 701 ap = aa + jmin*bs2; 702 for (j = jmin; j < jmax; j++){ 703 vj = aj[j]; /* block col. index */ 704 rtmp_ptr = rtmp + vj*bs2; 705 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 706 } 707 708 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 709 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 710 i = jl[k]; /* first row to be added to k_th row */ 711 712 while (i < k){ 713 nexti = jl[i]; /* next row to be added to k_th row */ 714 715 /* compute multiplier */ 716 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 717 718 /* uik = -inv(Di)*U_bar(i,k) */ 719 diag = ba + i*bs2; 720 u = ba + ili*bs2; 721 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 722 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 723 724 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 725 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 726 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 727 728 /* update -U(i,k) */ 729 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 730 731 /* add multiple of row i to k-th row ... */ 732 jmin = ili + 1; jmax = bi[i+1]; 733 if (jmin < jmax){ 734 for (j=jmin; j<jmax; j++) { 735 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 736 rtmp_ptr = rtmp + bj[j]*bs2; 737 u = ba + j*bs2; 738 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 739 } 740 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 741 742 /* ... add i to row list for next nonzero entry */ 743 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 744 j = bj[jmin]; 745 jl[i] = jl[j]; jl[j] = i; /* update jl */ 746 } 747 i = nexti; 748 } 749 750 /* save nonzero entries in k-th row of U ... */ 751 752 /* invert diagonal block */ 753 diag = ba+k*bs2; 754 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 755 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 756 757 jmin = bi[k]; jmax = bi[k+1]; 758 if (jmin < jmax) { 759 for (j=jmin; j<jmax; j++){ 760 vj = bj[j]; /* block col. index of U */ 761 u = ba + j*bs2; 762 rtmp_ptr = rtmp + vj*bs2; 763 for (k1=0; k1<bs2; k1++){ 764 *u++ = *rtmp_ptr; 765 *rtmp_ptr++ = 0.0; 766 } 767 } 768 769 /* ... add k to row list for first nonzero entry in k-th row */ 770 il[k] = jmin; 771 i = bj[jmin]; 772 jl[k] = jl[i]; jl[i] = k; 773 } 774 } 775 776 ierr = PetscFree(rtmp);CHKERRQ(ierr); 777 ierr = PetscFree(il);CHKERRQ(ierr); 778 ierr = PetscFree(dk);CHKERRQ(ierr); 779 ierr = PetscFree(pivots);CHKERRQ(ierr); 780 781 C->factor = FACTOR_CHOLESKY; 782 C->assembled = PETSC_TRUE; 783 C->preallocated = PETSC_TRUE; 784 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 785 PetscFunctionReturn(0); 786 } 787 788 /* 789 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 790 Version for blocks 2 by 2. 791 */ 792 #undef __FUNCT__ 793 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 794 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B) 795 { 796 Mat C = *B; 797 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 798 IS perm = b->row; 799 PetscErrorCode ierr; 800 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 801 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 802 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 803 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 804 805 PetscFunctionBegin; 806 /* initialization */ 807 /* il and jl record the first nonzero element in each row of the accessing 808 window U(0:k, k:mbs-1). 809 jl: list of rows to be added to uneliminated rows 810 i>= k: jl(i) is the first row to be added to row i 811 i< k: jl(i) is the row following row i in some list of rows 812 jl(i) = mbs indicates the end of a list 813 il(i): points to the first nonzero element in columns k,...,mbs-1 of 814 row i of U */ 815 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 816 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 817 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 818 jl = il + mbs; 819 for (i=0; i<mbs; i++) { 820 jl[i] = mbs; il[0] = 0; 821 } 822 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 823 uik = dk + 4; 824 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 825 826 /* check permutation */ 827 if (!a->permute){ 828 ai = a->i; aj = a->j; aa = a->a; 829 } else { 830 ai = a->inew; aj = a->jnew; 831 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 832 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 833 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 834 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 835 836 for (i=0; i<mbs; i++){ 837 jmin = ai[i]; jmax = ai[i+1]; 838 for (j=jmin; j<jmax; j++){ 839 while (a2anew[j] != j){ 840 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 841 for (k1=0; k1<4; k1++){ 842 dk[k1] = aa[k*4+k1]; 843 aa[k*4+k1] = aa[j*4+k1]; 844 aa[j*4+k1] = dk[k1]; 845 } 846 } 847 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 848 if (i > aj[j]){ 849 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 850 ap = aa + j*4; /* ptr to the beginning of the block */ 851 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 852 ap[1] = ap[2]; 853 ap[2] = dk[1]; 854 } 855 } 856 } 857 ierr = PetscFree(a2anew);CHKERRQ(ierr); 858 } 859 860 /* for each row k */ 861 for (k = 0; k<mbs; k++){ 862 863 /*initialize k-th row with elements nonzero in row perm(k) of A */ 864 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 865 ap = aa + jmin*4; 866 for (j = jmin; j < jmax; j++){ 867 vj = perm_ptr[aj[j]]; /* block col. index */ 868 rtmp_ptr = rtmp + vj*4; 869 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 870 } 871 872 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 873 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 874 i = jl[k]; /* first row to be added to k_th row */ 875 876 while (i < k){ 877 nexti = jl[i]; /* next row to be added to k_th row */ 878 879 /* compute multiplier */ 880 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 881 882 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 883 diag = ba + i*4; 884 u = ba + ili*4; 885 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 886 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 887 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 888 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 889 890 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 891 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 892 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 893 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 894 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 895 896 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 897 898 /* update -U(i,k): ba[ili] = uik */ 899 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 900 901 /* add multiple of row i to k-th row ... */ 902 jmin = ili + 1; jmax = bi[i+1]; 903 if (jmin < jmax){ 904 for (j=jmin; j<jmax; j++) { 905 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 906 rtmp_ptr = rtmp + bj[j]*4; 907 u = ba + j*4; 908 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 909 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 910 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 911 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 912 } 913 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 914 915 /* ... add i to row list for next nonzero entry */ 916 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 917 j = bj[jmin]; 918 jl[i] = jl[j]; jl[j] = i; /* update jl */ 919 } 920 i = nexti; 921 } 922 923 /* save nonzero entries in k-th row of U ... */ 924 925 /* invert diagonal block */ 926 diag = ba+k*4; 927 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 928 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 929 930 jmin = bi[k]; jmax = bi[k+1]; 931 if (jmin < jmax) { 932 for (j=jmin; j<jmax; j++){ 933 vj = bj[j]; /* block col. index of U */ 934 u = ba + j*4; 935 rtmp_ptr = rtmp + vj*4; 936 for (k1=0; k1<4; k1++){ 937 *u++ = *rtmp_ptr; 938 *rtmp_ptr++ = 0.0; 939 } 940 } 941 942 /* ... add k to row list for first nonzero entry in k-th row */ 943 il[k] = jmin; 944 i = bj[jmin]; 945 jl[k] = jl[i]; jl[i] = k; 946 } 947 } 948 949 ierr = PetscFree(rtmp);CHKERRQ(ierr); 950 ierr = PetscFree(il);CHKERRQ(ierr); 951 ierr = PetscFree(dk);CHKERRQ(ierr); 952 if (a->permute) { 953 ierr = PetscFree(aa);CHKERRQ(ierr); 954 } 955 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 956 C->factor = FACTOR_CHOLESKY; 957 C->assembled = PETSC_TRUE; 958 C->preallocated = PETSC_TRUE; 959 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 960 PetscFunctionReturn(0); 961 } 962 963 /* 964 Version for when blocks are 2 by 2 Using natural ordering 965 */ 966 #undef __FUNCT__ 967 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 968 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 969 { 970 Mat C = *B; 971 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 972 PetscErrorCode ierr; 973 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 974 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 975 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 976 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 977 978 PetscFunctionBegin; 979 /* initialization */ 980 /* il and jl record the first nonzero element in each row of the accessing 981 window U(0:k, k:mbs-1). 982 jl: list of rows to be added to uneliminated rows 983 i>= k: jl(i) is the first row to be added to row i 984 i< k: jl(i) is the row following row i in some list of rows 985 jl(i) = mbs indicates the end of a list 986 il(i): points to the first nonzero element in columns k,...,mbs-1 of 987 row i of U */ 988 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 989 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 990 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 991 jl = il + mbs; 992 for (i=0; i<mbs; i++) { 993 jl[i] = mbs; il[0] = 0; 994 } 995 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 996 uik = dk + 4; 997 998 ai = a->i; aj = a->j; aa = a->a; 999 1000 /* for each row k */ 1001 for (k = 0; k<mbs; k++){ 1002 1003 /*initialize k-th row with elements nonzero in row k of A */ 1004 jmin = ai[k]; jmax = ai[k+1]; 1005 ap = aa + jmin*4; 1006 for (j = jmin; j < jmax; j++){ 1007 vj = aj[j]; /* block col. index */ 1008 rtmp_ptr = rtmp + vj*4; 1009 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1010 } 1011 1012 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1013 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1014 i = jl[k]; /* first row to be added to k_th row */ 1015 1016 while (i < k){ 1017 nexti = jl[i]; /* next row to be added to k_th row */ 1018 1019 /* compute multiplier */ 1020 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1021 1022 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1023 diag = ba + i*4; 1024 u = ba + ili*4; 1025 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1026 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1027 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1028 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1029 1030 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1031 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1032 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1033 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1034 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1035 1036 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 1037 1038 /* update -U(i,k): ba[ili] = uik */ 1039 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1040 1041 /* add multiple of row i to k-th row ... */ 1042 jmin = ili + 1; jmax = bi[i+1]; 1043 if (jmin < jmax){ 1044 for (j=jmin; j<jmax; j++) { 1045 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1046 rtmp_ptr = rtmp + bj[j]*4; 1047 u = ba + j*4; 1048 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1049 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1050 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1051 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1052 } 1053 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 1054 1055 /* ... add i to row list for next nonzero entry */ 1056 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1057 j = bj[jmin]; 1058 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1059 } 1060 i = nexti; 1061 } 1062 1063 /* save nonzero entries in k-th row of U ... */ 1064 1065 /* invert diagonal block */ 1066 diag = ba+k*4; 1067 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1068 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1069 1070 jmin = bi[k]; jmax = bi[k+1]; 1071 if (jmin < jmax) { 1072 for (j=jmin; j<jmax; j++){ 1073 vj = bj[j]; /* block col. index of U */ 1074 u = ba + j*4; 1075 rtmp_ptr = rtmp + vj*4; 1076 for (k1=0; k1<4; k1++){ 1077 *u++ = *rtmp_ptr; 1078 *rtmp_ptr++ = 0.0; 1079 } 1080 } 1081 1082 /* ... add k to row list for first nonzero entry in k-th row */ 1083 il[k] = jmin; 1084 i = bj[jmin]; 1085 jl[k] = jl[i]; jl[i] = k; 1086 } 1087 } 1088 1089 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1090 ierr = PetscFree(il);CHKERRQ(ierr); 1091 ierr = PetscFree(dk);CHKERRQ(ierr); 1092 1093 C->factor = FACTOR_CHOLESKY; 1094 C->assembled = PETSC_TRUE; 1095 C->preallocated = PETSC_TRUE; 1096 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1097 PetscFunctionReturn(0); 1098 } 1099 1100 /* 1101 Numeric U^T*D*U factorization for SBAIJ format. 1102 Version for blocks are 1 by 1. 1103 */ 1104 #undef __FUNCT__ 1105 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1106 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B) 1107 { 1108 Mat C = *B; 1109 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1110 IS ip=b->row; 1111 PetscErrorCode ierr; 1112 PetscInt *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1113 PetscInt *ai,*aj,*a2anew; 1114 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1115 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1116 PetscReal zeropivot,rs,shiftnz; 1117 PetscReal shiftpd; 1118 ChShift_Ctx sctx; 1119 PetscInt newshift; 1120 1121 PetscFunctionBegin; 1122 /* initialization */ 1123 shiftnz = info->shiftnz; 1124 shiftpd = info->shiftpd; 1125 zeropivot = info->zeropivot; 1126 1127 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1128 if (!a->permute){ 1129 ai = a->i; aj = a->j; aa = a->a; 1130 } else { 1131 ai = a->inew; aj = a->jnew; 1132 nz = ai[mbs]; 1133 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1134 a2anew = a->a2anew; 1135 bval = a->a; 1136 for (j=0; j<nz; j++){ 1137 aa[a2anew[j]] = *(bval++); 1138 } 1139 } 1140 1141 /* initialization */ 1142 /* il and jl record the first nonzero element in each row of the accessing 1143 window U(0:k, k:mbs-1). 1144 jl: list of rows to be added to uneliminated rows 1145 i>= k: jl(i) is the first row to be added to row i 1146 i< k: jl(i) is the row following row i in some list of rows 1147 jl(i) = mbs indicates the end of a list 1148 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1149 row i of U */ 1150 nz = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar); 1151 ierr = PetscMalloc(nz,&il);CHKERRQ(ierr); 1152 jl = il + mbs; 1153 rtmp = (MatScalar*)(jl + mbs); 1154 1155 sctx.shift_amount = 0; 1156 sctx.nshift = 0; 1157 do { 1158 sctx.chshift = PETSC_FALSE; 1159 for (i=0; i<mbs; i++) { 1160 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1161 } 1162 1163 for (k = 0; k<mbs; k++){ 1164 /*initialize k-th row by the perm[k]-th row of A */ 1165 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1166 bval = ba + bi[k]; 1167 for (j = jmin; j < jmax; j++){ 1168 col = rip[aj[j]]; 1169 rtmp[col] = aa[j]; 1170 *bval++ = 0.0; /* for in-place factorization */ 1171 } 1172 1173 /* shift the diagonal of the matrix */ 1174 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1175 1176 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1177 dk = rtmp[k]; 1178 i = jl[k]; /* first row to be added to k_th row */ 1179 1180 while (i < k){ 1181 nexti = jl[i]; /* next row to be added to k_th row */ 1182 1183 /* compute multiplier, update diag(k) and U(i,k) */ 1184 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1185 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1186 dk += uikdi*ba[ili]; 1187 ba[ili] = uikdi; /* -U(i,k) */ 1188 1189 /* add multiple of row i to k-th row */ 1190 jmin = ili + 1; jmax = bi[i+1]; 1191 if (jmin < jmax){ 1192 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1193 ierr = PetscLogFlops(2*(jmax-jmin));CHKERRQ(ierr); 1194 1195 /* update il and jl for row i */ 1196 il[i] = jmin; 1197 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1198 } 1199 i = nexti; 1200 } 1201 1202 /* shift the diagonals when zero pivot is detected */ 1203 /* compute rs=sum of abs(off-diagonal) */ 1204 rs = 0.0; 1205 jmin = bi[k]+1; 1206 nz = bi[k+1] - jmin; 1207 if (nz){ 1208 bcol = bj + jmin; 1209 while (nz--){ 1210 rs += PetscAbsScalar(rtmp[*bcol]); 1211 bcol++; 1212 } 1213 } 1214 1215 sctx.rs = rs; 1216 sctx.pv = dk; 1217 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1218 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1219 1220 /* copy data into U(k,:) */ 1221 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1222 jmin = bi[k]+1; jmax = bi[k+1]; 1223 if (jmin < jmax) { 1224 for (j=jmin; j<jmax; j++){ 1225 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1226 } 1227 /* add the k-th row into il and jl */ 1228 il[k] = jmin; 1229 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1230 } 1231 } 1232 } while (sctx.chshift); 1233 ierr = PetscFree(il);CHKERRQ(ierr); 1234 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1235 1236 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1237 C->factor = FACTOR_CHOLESKY; 1238 C->assembled = PETSC_TRUE; 1239 C->preallocated = PETSC_TRUE; 1240 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1241 if (sctx.nshift){ 1242 if (shiftnz) { 1243 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1244 } else if (shiftpd) { 1245 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1246 } 1247 } 1248 PetscFunctionReturn(0); 1249 } 1250 1251 /* 1252 Version for when blocks are 1 by 1 Using natural ordering 1253 */ 1254 #undef __FUNCT__ 1255 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1256 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 1257 { 1258 Mat C = *B; 1259 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1260 PetscErrorCode ierr; 1261 PetscInt i,j,mbs = a->mbs; 1262 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1263 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1264 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1265 PetscReal zeropivot,rs,shiftnz; 1266 PetscReal shiftpd; 1267 ChShift_Ctx sctx; 1268 PetscInt newshift; 1269 1270 PetscFunctionBegin; 1271 /* initialization */ 1272 shiftnz = info->shiftnz; 1273 shiftpd = info->shiftpd; 1274 zeropivot = info->zeropivot; 1275 1276 /* il and jl record the first nonzero element in each row of the accessing 1277 window U(0:k, k:mbs-1). 1278 jl: list of rows to be added to uneliminated rows 1279 i>= k: jl(i) is the first row to be added to row i 1280 i< k: jl(i) is the row following row i in some list of rows 1281 jl(i) = mbs indicates the end of a list 1282 il(i): points to the first nonzero element in U(i,k:mbs-1) 1283 */ 1284 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1285 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1286 jl = il + mbs; 1287 1288 sctx.shift_amount = 0; 1289 sctx.nshift = 0; 1290 do { 1291 sctx.chshift = PETSC_FALSE; 1292 for (i=0; i<mbs; i++) { 1293 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1294 } 1295 1296 for (k = 0; k<mbs; k++){ 1297 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1298 nz = ai[k+1] - ai[k]; 1299 acol = aj + ai[k]; 1300 aval = aa + ai[k]; 1301 bval = ba + bi[k]; 1302 while (nz -- ){ 1303 rtmp[*acol++] = *aval++; 1304 *bval++ = 0.0; /* for in-place factorization */ 1305 } 1306 1307 /* shift the diagonal of the matrix */ 1308 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1309 1310 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1311 dk = rtmp[k]; 1312 i = jl[k]; /* first row to be added to k_th row */ 1313 1314 while (i < k){ 1315 nexti = jl[i]; /* next row to be added to k_th row */ 1316 /* compute multiplier, update D(k) and U(i,k) */ 1317 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1318 uikdi = - ba[ili]*ba[bi[i]]; 1319 dk += uikdi*ba[ili]; 1320 ba[ili] = uikdi; /* -U(i,k) */ 1321 1322 /* add multiple of row i to k-th row ... */ 1323 jmin = ili + 1; 1324 nz = bi[i+1] - jmin; 1325 if (nz > 0){ 1326 bcol = bj + jmin; 1327 bval = ba + jmin; 1328 ierr = PetscLogFlops(2*nz);CHKERRQ(ierr); 1329 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1330 1331 /* update il and jl for i-th row */ 1332 il[i] = jmin; 1333 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1334 } 1335 i = nexti; 1336 } 1337 1338 /* shift the diagonals when zero pivot is detected */ 1339 /* compute rs=sum of abs(off-diagonal) */ 1340 rs = 0.0; 1341 jmin = bi[k]+1; 1342 nz = bi[k+1] - jmin; 1343 if (nz){ 1344 bcol = bj + jmin; 1345 while (nz--){ 1346 rs += PetscAbsScalar(rtmp[*bcol]); 1347 bcol++; 1348 } 1349 } 1350 1351 sctx.rs = rs; 1352 sctx.pv = dk; 1353 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1354 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1355 1356 /* copy data into U(k,:) */ 1357 ba[bi[k]] = 1.0/dk; 1358 jmin = bi[k]+1; 1359 nz = bi[k+1] - jmin; 1360 if (nz){ 1361 bcol = bj + jmin; 1362 bval = ba + jmin; 1363 while (nz--){ 1364 *bval++ = rtmp[*bcol]; 1365 rtmp[*bcol++] = 0.0; 1366 } 1367 /* add k-th row into il and jl */ 1368 il[k] = jmin; 1369 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1370 } 1371 } /* end of for (k = 0; k<mbs; k++) */ 1372 } while (sctx.chshift); 1373 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1374 ierr = PetscFree(il);CHKERRQ(ierr); 1375 1376 C->factor = FACTOR_CHOLESKY; 1377 C->assembled = PETSC_TRUE; 1378 C->preallocated = PETSC_TRUE; 1379 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1380 if (sctx.nshift){ 1381 if (shiftnz) { 1382 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1383 } else if (shiftpd) { 1384 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1385 } 1386 } 1387 PetscFunctionReturn(0); 1388 } 1389 1390 #undef __FUNCT__ 1391 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1392 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1393 { 1394 PetscErrorCode ierr; 1395 Mat C; 1396 1397 PetscFunctionBegin; 1398 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1399 ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr); 1400 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1401 PetscFunctionReturn(0); 1402 } 1403 1404 1405