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,bslog = 0; 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 /* flops in while loop */ 534 bslog = 2*bs*bs2; 535 536 for (i=0; i<mbs; i++){ 537 jmin = ai[i]; jmax = ai[i+1]; 538 for (j=jmin; j<jmax; j++){ 539 while (a2anew[j] != j){ 540 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 541 for (k1=0; k1<bs2; k1++){ 542 dk[k1] = aa[k*bs2+k1]; 543 aa[k*bs2+k1] = aa[j*bs2+k1]; 544 aa[j*bs2+k1] = dk[k1]; 545 } 546 } 547 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 548 if (i > aj[j]){ 549 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 550 ap = aa + j*bs2; /* ptr to the beginning of j-th block of aa */ 551 for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */ 552 for (k=0; k<bs; k++){ /* j-th block of aa <- dk^T */ 553 for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1]; 554 } 555 } 556 } 557 } 558 ierr = PetscFree(a2anew);CHKERRQ(ierr); 559 } 560 561 /* for each row k */ 562 for (k = 0; k<mbs; k++){ 563 564 /*initialize k-th row with elements nonzero in row perm(k) of A */ 565 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 566 567 ap = aa + jmin*bs2; 568 for (j = jmin; j < jmax; j++){ 569 vj = perm_ptr[aj[j]]; /* block col. index */ 570 rtmp_ptr = rtmp + vj*bs2; 571 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 572 } 573 574 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 575 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 576 i = jl[k]; /* first row to be added to k_th row */ 577 578 while (i < k){ 579 nexti = jl[i]; /* next row to be added to k_th row */ 580 581 /* compute multiplier */ 582 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 583 584 /* uik = -inv(Di)*U_bar(i,k) */ 585 diag = ba + i*bs2; 586 u = ba + ili*bs2; 587 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 588 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 589 590 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 591 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 592 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 593 594 /* update -U(i,k) */ 595 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 596 597 /* add multiple of row i to k-th row ... */ 598 jmin = ili + 1; jmax = bi[i+1]; 599 if (jmin < jmax){ 600 for (j=jmin; j<jmax; j++) { 601 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 602 rtmp_ptr = rtmp + bj[j]*bs2; 603 u = ba + j*bs2; 604 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 605 } 606 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 607 608 /* ... add i to row list for next nonzero entry */ 609 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 610 j = bj[jmin]; 611 jl[i] = jl[j]; jl[j] = i; /* update jl */ 612 } 613 i = nexti; 614 } 615 616 /* save nonzero entries in k-th row of U ... */ 617 618 /* invert diagonal block */ 619 diag = ba+k*bs2; 620 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 621 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 622 623 jmin = bi[k]; jmax = bi[k+1]; 624 if (jmin < jmax) { 625 for (j=jmin; j<jmax; j++){ 626 vj = bj[j]; /* block col. index of U */ 627 u = ba + j*bs2; 628 rtmp_ptr = rtmp + vj*bs2; 629 for (k1=0; k1<bs2; k1++){ 630 *u++ = *rtmp_ptr; 631 *rtmp_ptr++ = 0.0; 632 } 633 } 634 635 /* ... add k to row list for first nonzero entry in k-th row */ 636 il[k] = jmin; 637 i = bj[jmin]; 638 jl[k] = jl[i]; jl[i] = k; 639 } 640 } 641 642 ierr = PetscFree(rtmp);CHKERRQ(ierr); 643 ierr = PetscFree(il);CHKERRQ(ierr); 644 ierr = PetscFree(dk);CHKERRQ(ierr); 645 ierr = PetscFree(pivots);CHKERRQ(ierr); 646 if (a->permute){ 647 ierr = PetscFree(aa);CHKERRQ(ierr); 648 } 649 650 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 651 C->factor = FACTOR_CHOLESKY; 652 C->assembled = PETSC_TRUE; 653 C->preallocated = PETSC_TRUE; 654 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 655 PetscFunctionReturn(0); 656 } 657 658 #undef __FUNCT__ 659 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering" 660 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 661 { 662 Mat C = *B; 663 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 664 PetscErrorCode ierr; 665 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 666 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 667 PetscInt bs=A->rmap.bs,bs2 = a->bs2,bslog; 668 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 669 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 670 MatScalar *work; 671 PetscInt *pivots; 672 673 PetscFunctionBegin; 674 ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 675 ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr); 676 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 677 jl = il + mbs; 678 for (i=0; i<mbs; i++) { 679 jl[i] = mbs; il[0] = 0; 680 } 681 ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr); 682 uik = dk + bs2; 683 work = uik + bs2; 684 ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr); 685 686 ai = a->i; aj = a->j; aa = a->a; 687 688 /* flops in while loop */ 689 bslog = 2*bs*bs2; 690 691 /* for each row k */ 692 for (k = 0; k<mbs; k++){ 693 694 /*initialize k-th row with elements nonzero in row k of A */ 695 jmin = ai[k]; jmax = ai[k+1]; 696 ap = aa + jmin*bs2; 697 for (j = jmin; j < jmax; j++){ 698 vj = aj[j]; /* block col. index */ 699 rtmp_ptr = rtmp + vj*bs2; 700 for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++; 701 } 702 703 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 704 ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 705 i = jl[k]; /* first row to be added to k_th row */ 706 707 while (i < k){ 708 nexti = jl[i]; /* next row to be added to k_th row */ 709 710 /* compute multiplier */ 711 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 712 713 /* uik = -inv(Di)*U_bar(i,k) */ 714 diag = ba + i*bs2; 715 u = ba + ili*bs2; 716 ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 717 Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u); 718 719 /* update D(k) += -U(i,k)^T * U_bar(i,k) */ 720 Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u); 721 ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr); 722 723 /* update -U(i,k) */ 724 ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr); 725 726 /* add multiple of row i to k-th row ... */ 727 jmin = ili + 1; jmax = bi[i+1]; 728 if (jmin < jmax){ 729 for (j=jmin; j<jmax; j++) { 730 /* rtmp += -U(i,k)^T * U_bar(i,j) */ 731 rtmp_ptr = rtmp + bj[j]*bs2; 732 u = ba + j*bs2; 733 Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u); 734 } 735 ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr); 736 737 /* ... add i to row list for next nonzero entry */ 738 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 739 j = bj[jmin]; 740 jl[i] = jl[j]; jl[j] = i; /* update jl */ 741 } 742 i = nexti; 743 } 744 745 /* save nonzero entries in k-th row of U ... */ 746 747 /* invert diagonal block */ 748 diag = ba+k*bs2; 749 ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr); 750 ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr); 751 752 jmin = bi[k]; jmax = bi[k+1]; 753 if (jmin < jmax) { 754 for (j=jmin; j<jmax; j++){ 755 vj = bj[j]; /* block col. index of U */ 756 u = ba + j*bs2; 757 rtmp_ptr = rtmp + vj*bs2; 758 for (k1=0; k1<bs2; k1++){ 759 *u++ = *rtmp_ptr; 760 *rtmp_ptr++ = 0.0; 761 } 762 } 763 764 /* ... add k to row list for first nonzero entry in k-th row */ 765 il[k] = jmin; 766 i = bj[jmin]; 767 jl[k] = jl[i]; jl[i] = k; 768 } 769 } 770 771 ierr = PetscFree(rtmp);CHKERRQ(ierr); 772 ierr = PetscFree(il);CHKERRQ(ierr); 773 ierr = PetscFree(dk);CHKERRQ(ierr); 774 ierr = PetscFree(pivots);CHKERRQ(ierr); 775 776 C->factor = FACTOR_CHOLESKY; 777 C->assembled = PETSC_TRUE; 778 C->preallocated = PETSC_TRUE; 779 ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 780 PetscFunctionReturn(0); 781 } 782 783 /* 784 Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP. 785 Version for blocks 2 by 2. 786 */ 787 #undef __FUNCT__ 788 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2" 789 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B) 790 { 791 Mat C = *B; 792 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 793 IS perm = b->row; 794 PetscErrorCode ierr; 795 PetscInt *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 796 PetscInt *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 797 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 798 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 799 800 PetscFunctionBegin; 801 /* initialization */ 802 /* il and jl record the first nonzero element in each row of the accessing 803 window U(0:k, k:mbs-1). 804 jl: list of rows to be added to uneliminated rows 805 i>= k: jl(i) is the first row to be added to row i 806 i< k: jl(i) is the row following row i in some list of rows 807 jl(i) = mbs indicates the end of a list 808 il(i): points to the first nonzero element in columns k,...,mbs-1 of 809 row i of U */ 810 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 811 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 812 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 813 jl = il + mbs; 814 for (i=0; i<mbs; i++) { 815 jl[i] = mbs; il[0] = 0; 816 } 817 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 818 uik = dk + 4; 819 ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr); 820 821 /* check permutation */ 822 if (!a->permute){ 823 ai = a->i; aj = a->j; aa = a->a; 824 } else { 825 ai = a->inew; aj = a->jnew; 826 ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr); 827 ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr); 828 ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr); 829 ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr); 830 831 for (i=0; i<mbs; i++){ 832 jmin = ai[i]; jmax = ai[i+1]; 833 for (j=jmin; j<jmax; j++){ 834 while (a2anew[j] != j){ 835 k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k; 836 for (k1=0; k1<4; k1++){ 837 dk[k1] = aa[k*4+k1]; 838 aa[k*4+k1] = aa[j*4+k1]; 839 aa[j*4+k1] = dk[k1]; 840 } 841 } 842 /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */ 843 if (i > aj[j]){ 844 /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */ 845 ap = aa + j*4; /* ptr to the beginning of the block */ 846 dk[1] = ap[1]; /* swap ap[1] and ap[2] */ 847 ap[1] = ap[2]; 848 ap[2] = dk[1]; 849 } 850 } 851 } 852 ierr = PetscFree(a2anew);CHKERRQ(ierr); 853 } 854 855 /* for each row k */ 856 for (k = 0; k<mbs; k++){ 857 858 /*initialize k-th row with elements nonzero in row perm(k) of A */ 859 jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1]; 860 ap = aa + jmin*4; 861 for (j = jmin; j < jmax; j++){ 862 vj = perm_ptr[aj[j]]; /* block col. index */ 863 rtmp_ptr = rtmp + vj*4; 864 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 865 } 866 867 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 868 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 869 i = jl[k]; /* first row to be added to k_th row */ 870 871 while (i < k){ 872 nexti = jl[i]; /* next row to be added to k_th row */ 873 874 /* compute multiplier */ 875 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 876 877 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 878 diag = ba + i*4; 879 u = ba + ili*4; 880 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 881 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 882 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 883 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 884 885 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 886 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 887 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 888 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 889 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 890 891 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 892 893 /* update -U(i,k): ba[ili] = uik */ 894 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 895 896 /* add multiple of row i to k-th row ... */ 897 jmin = ili + 1; jmax = bi[i+1]; 898 if (jmin < jmax){ 899 for (j=jmin; j<jmax; j++) { 900 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 901 rtmp_ptr = rtmp + bj[j]*4; 902 u = ba + j*4; 903 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 904 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 905 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 906 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 907 } 908 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 909 910 /* ... add i to row list for next nonzero entry */ 911 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 912 j = bj[jmin]; 913 jl[i] = jl[j]; jl[j] = i; /* update jl */ 914 } 915 i = nexti; 916 } 917 918 /* save nonzero entries in k-th row of U ... */ 919 920 /* invert diagonal block */ 921 diag = ba+k*4; 922 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 923 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 924 925 jmin = bi[k]; jmax = bi[k+1]; 926 if (jmin < jmax) { 927 for (j=jmin; j<jmax; j++){ 928 vj = bj[j]; /* block col. index of U */ 929 u = ba + j*4; 930 rtmp_ptr = rtmp + vj*4; 931 for (k1=0; k1<4; k1++){ 932 *u++ = *rtmp_ptr; 933 *rtmp_ptr++ = 0.0; 934 } 935 } 936 937 /* ... add k to row list for first nonzero entry in k-th row */ 938 il[k] = jmin; 939 i = bj[jmin]; 940 jl[k] = jl[i]; jl[i] = k; 941 } 942 } 943 944 ierr = PetscFree(rtmp);CHKERRQ(ierr); 945 ierr = PetscFree(il);CHKERRQ(ierr); 946 ierr = PetscFree(dk);CHKERRQ(ierr); 947 if (a->permute) { 948 ierr = PetscFree(aa);CHKERRQ(ierr); 949 } 950 ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr); 951 C->factor = FACTOR_CHOLESKY; 952 C->assembled = PETSC_TRUE; 953 C->preallocated = PETSC_TRUE; 954 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 955 PetscFunctionReturn(0); 956 } 957 958 /* 959 Version for when blocks are 2 by 2 Using natural ordering 960 */ 961 #undef __FUNCT__ 962 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering" 963 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 964 { 965 Mat C = *B; 966 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data; 967 PetscErrorCode ierr; 968 PetscInt i,j,mbs=a->mbs,*bi=b->i,*bj=b->j; 969 PetscInt *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili; 970 MatScalar *ba = b->a,*aa,*ap,*dk,*uik; 971 MatScalar *u,*diag,*rtmp,*rtmp_ptr; 972 973 PetscFunctionBegin; 974 /* initialization */ 975 /* il and jl record the first nonzero element in each row of the accessing 976 window U(0:k, k:mbs-1). 977 jl: list of rows to be added to uneliminated rows 978 i>= k: jl(i) is the first row to be added to row i 979 i< k: jl(i) is the row following row i in some list of rows 980 jl(i) = mbs indicates the end of a list 981 il(i): points to the first nonzero element in columns k,...,mbs-1 of 982 row i of U */ 983 ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 984 ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr); 985 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 986 jl = il + mbs; 987 for (i=0; i<mbs; i++) { 988 jl[i] = mbs; il[0] = 0; 989 } 990 ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr); 991 uik = dk + 4; 992 993 ai = a->i; aj = a->j; aa = a->a; 994 995 /* for each row k */ 996 for (k = 0; k<mbs; k++){ 997 998 /*initialize k-th row with elements nonzero in row k of A */ 999 jmin = ai[k]; jmax = ai[k+1]; 1000 ap = aa + jmin*4; 1001 for (j = jmin; j < jmax; j++){ 1002 vj = aj[j]; /* block col. index */ 1003 rtmp_ptr = rtmp + vj*4; 1004 for (i=0; i<4; i++) *rtmp_ptr++ = *ap++; 1005 } 1006 1007 /* modify k-th row by adding in those rows i with U(i,k) != 0 */ 1008 ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr); 1009 i = jl[k]; /* first row to be added to k_th row */ 1010 1011 while (i < k){ 1012 nexti = jl[i]; /* next row to be added to k_th row */ 1013 1014 /* compute multiplier */ 1015 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1016 1017 /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */ 1018 diag = ba + i*4; 1019 u = ba + ili*4; 1020 uik[0] = -(diag[0]*u[0] + diag[2]*u[1]); 1021 uik[1] = -(diag[1]*u[0] + diag[3]*u[1]); 1022 uik[2] = -(diag[0]*u[2] + diag[2]*u[3]); 1023 uik[3] = -(diag[1]*u[2] + diag[3]*u[3]); 1024 1025 /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */ 1026 dk[0] += uik[0]*u[0] + uik[1]*u[1]; 1027 dk[1] += uik[2]*u[0] + uik[3]*u[1]; 1028 dk[2] += uik[0]*u[2] + uik[1]*u[3]; 1029 dk[3] += uik[2]*u[2] + uik[3]*u[3]; 1030 1031 ierr = PetscLogFlops(16*2);CHKERRQ(ierr); 1032 1033 /* update -U(i,k): ba[ili] = uik */ 1034 ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr); 1035 1036 /* add multiple of row i to k-th row ... */ 1037 jmin = ili + 1; jmax = bi[i+1]; 1038 if (jmin < jmax){ 1039 for (j=jmin; j<jmax; j++) { 1040 /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */ 1041 rtmp_ptr = rtmp + bj[j]*4; 1042 u = ba + j*4; 1043 rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1]; 1044 rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1]; 1045 rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3]; 1046 rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3]; 1047 } 1048 ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr); 1049 1050 /* ... add i to row list for next nonzero entry */ 1051 il[i] = jmin; /* update il(i) in column k+1, ... mbs-1 */ 1052 j = bj[jmin]; 1053 jl[i] = jl[j]; jl[j] = i; /* update jl */ 1054 } 1055 i = nexti; 1056 } 1057 1058 /* save nonzero entries in k-th row of U ... */ 1059 1060 /* invert diagonal block */ 1061 diag = ba+k*4; 1062 ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr); 1063 ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr); 1064 1065 jmin = bi[k]; jmax = bi[k+1]; 1066 if (jmin < jmax) { 1067 for (j=jmin; j<jmax; j++){ 1068 vj = bj[j]; /* block col. index of U */ 1069 u = ba + j*4; 1070 rtmp_ptr = rtmp + vj*4; 1071 for (k1=0; k1<4; k1++){ 1072 *u++ = *rtmp_ptr; 1073 *rtmp_ptr++ = 0.0; 1074 } 1075 } 1076 1077 /* ... add k to row list for first nonzero entry in k-th row */ 1078 il[k] = jmin; 1079 i = bj[jmin]; 1080 jl[k] = jl[i]; jl[i] = k; 1081 } 1082 } 1083 1084 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1085 ierr = PetscFree(il);CHKERRQ(ierr); 1086 ierr = PetscFree(dk);CHKERRQ(ierr); 1087 1088 C->factor = FACTOR_CHOLESKY; 1089 C->assembled = PETSC_TRUE; 1090 C->preallocated = PETSC_TRUE; 1091 ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 1092 PetscFunctionReturn(0); 1093 } 1094 1095 /* 1096 Numeric U^T*D*U factorization for SBAIJ format. 1097 Version for blocks are 1 by 1. 1098 */ 1099 #undef __FUNCT__ 1100 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1" 1101 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B) 1102 { 1103 Mat C = *B; 1104 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1105 IS ip=b->row; 1106 PetscErrorCode ierr; 1107 PetscInt *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol; 1108 PetscInt *ai,*aj,*a2anew; 1109 PetscInt k,jmin,jmax,*jl,*il,col,nexti,ili,nz; 1110 MatScalar *rtmp,*ba=b->a,*bval,*aa,dk,uikdi; 1111 PetscReal zeropivot,rs,shiftnz; 1112 PetscReal shiftpd; 1113 ChShift_Ctx sctx; 1114 PetscInt newshift; 1115 1116 PetscFunctionBegin; 1117 /* initialization */ 1118 shiftnz = info->shiftnz; 1119 shiftpd = info->shiftpd; 1120 zeropivot = info->zeropivot; 1121 1122 ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr); 1123 if (!a->permute){ 1124 ai = a->i; aj = a->j; aa = a->a; 1125 } else { 1126 ai = a->inew; aj = a->jnew; 1127 nz = ai[mbs]; 1128 ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr); 1129 a2anew = a->a2anew; 1130 bval = a->a; 1131 for (j=0; j<nz; j++){ 1132 aa[a2anew[j]] = *(bval++); 1133 } 1134 } 1135 1136 /* initialization */ 1137 /* il and jl record the first nonzero element in each row of the accessing 1138 window U(0:k, k:mbs-1). 1139 jl: list of rows to be added to uneliminated rows 1140 i>= k: jl(i) is the first row to be added to row i 1141 i< k: jl(i) is the row following row i in some list of rows 1142 jl(i) = mbs indicates the end of a list 1143 il(i): points to the first nonzero element in columns k,...,mbs-1 of 1144 row i of U */ 1145 nz = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar); 1146 ierr = PetscMalloc(nz,&il);CHKERRQ(ierr); 1147 jl = il + mbs; 1148 rtmp = (MatScalar*)(jl + mbs); 1149 1150 sctx.shift_amount = 0; 1151 sctx.nshift = 0; 1152 do { 1153 sctx.chshift = PETSC_FALSE; 1154 for (i=0; i<mbs; i++) { 1155 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1156 } 1157 1158 for (k = 0; k<mbs; k++){ 1159 /*initialize k-th row by the perm[k]-th row of A */ 1160 jmin = ai[rip[k]]; jmax = ai[rip[k]+1]; 1161 bval = ba + bi[k]; 1162 for (j = jmin; j < jmax; j++){ 1163 col = rip[aj[j]]; 1164 rtmp[col] = aa[j]; 1165 *bval++ = 0.0; /* for in-place factorization */ 1166 } 1167 1168 /* shift the diagonal of the matrix */ 1169 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1170 1171 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1172 dk = rtmp[k]; 1173 i = jl[k]; /* first row to be added to k_th row */ 1174 1175 while (i < k){ 1176 nexti = jl[i]; /* next row to be added to k_th row */ 1177 1178 /* compute multiplier, update diag(k) and U(i,k) */ 1179 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1180 uikdi = - ba[ili]*ba[bi[i]]; /* diagonal(k) */ 1181 dk += uikdi*ba[ili]; 1182 ba[ili] = uikdi; /* -U(i,k) */ 1183 1184 /* add multiple of row i to k-th row */ 1185 jmin = ili + 1; jmax = bi[i+1]; 1186 if (jmin < jmax){ 1187 for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j]; 1188 ierr = PetscLogFlops(2*(jmax-jmin));CHKERRQ(ierr); 1189 1190 /* update il and jl for row i */ 1191 il[i] = jmin; 1192 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1193 } 1194 i = nexti; 1195 } 1196 1197 /* shift the diagonals when zero pivot is detected */ 1198 /* compute rs=sum of abs(off-diagonal) */ 1199 rs = 0.0; 1200 jmin = bi[k]+1; 1201 nz = bi[k+1] - jmin; 1202 if (nz){ 1203 bcol = bj + jmin; 1204 while (nz--){ 1205 rs += PetscAbsScalar(rtmp[*bcol]); 1206 bcol++; 1207 } 1208 } 1209 1210 sctx.rs = rs; 1211 sctx.pv = dk; 1212 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1213 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1214 1215 /* copy data into U(k,:) */ 1216 ba[bi[k]] = 1.0/dk; /* U(k,k) */ 1217 jmin = bi[k]+1; jmax = bi[k+1]; 1218 if (jmin < jmax) { 1219 for (j=jmin; j<jmax; j++){ 1220 col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0; 1221 } 1222 /* add the k-th row into il and jl */ 1223 il[k] = jmin; 1224 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1225 } 1226 } 1227 } while (sctx.chshift); 1228 ierr = PetscFree(il);CHKERRQ(ierr); 1229 if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);} 1230 1231 ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr); 1232 C->factor = FACTOR_CHOLESKY; 1233 C->assembled = PETSC_TRUE; 1234 C->preallocated = PETSC_TRUE; 1235 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1236 if (sctx.nshift){ 1237 if (shiftnz) { 1238 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1239 } else if (shiftpd) { 1240 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1241 } 1242 } 1243 PetscFunctionReturn(0); 1244 } 1245 1246 /* 1247 Version for when blocks are 1 by 1 Using natural ordering 1248 */ 1249 #undef __FUNCT__ 1250 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering" 1251 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B) 1252 { 1253 Mat C = *B; 1254 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data; 1255 PetscErrorCode ierr; 1256 PetscInt i,j,mbs = a->mbs; 1257 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 1258 PetscInt k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz; 1259 MatScalar *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval; 1260 PetscReal zeropivot,rs,shiftnz; 1261 PetscReal shiftpd; 1262 ChShift_Ctx sctx; 1263 PetscInt newshift; 1264 1265 PetscFunctionBegin; 1266 /* initialization */ 1267 shiftnz = info->shiftnz; 1268 shiftpd = info->shiftpd; 1269 zeropivot = info->zeropivot; 1270 1271 /* il and jl record the first nonzero element in each row of the accessing 1272 window U(0:k, k:mbs-1). 1273 jl: list of rows to be added to uneliminated rows 1274 i>= k: jl(i) is the first row to be added to row i 1275 i< k: jl(i) is the row following row i in some list of rows 1276 jl(i) = mbs indicates the end of a list 1277 il(i): points to the first nonzero element in U(i,k:mbs-1) 1278 */ 1279 ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr); 1280 ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr); 1281 jl = il + mbs; 1282 1283 sctx.shift_amount = 0; 1284 sctx.nshift = 0; 1285 do { 1286 sctx.chshift = PETSC_FALSE; 1287 for (i=0; i<mbs; i++) { 1288 rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0; 1289 } 1290 1291 for (k = 0; k<mbs; k++){ 1292 /*initialize k-th row with elements nonzero in row perm(k) of A */ 1293 nz = ai[k+1] - ai[k]; 1294 acol = aj + ai[k]; 1295 aval = aa + ai[k]; 1296 bval = ba + bi[k]; 1297 while (nz -- ){ 1298 rtmp[*acol++] = *aval++; 1299 *bval++ = 0.0; /* for in-place factorization */ 1300 } 1301 1302 /* shift the diagonal of the matrix */ 1303 if (sctx.nshift) rtmp[k] += sctx.shift_amount; 1304 1305 /* modify k-th row by adding in those rows i with U(i,k)!=0 */ 1306 dk = rtmp[k]; 1307 i = jl[k]; /* first row to be added to k_th row */ 1308 1309 while (i < k){ 1310 nexti = jl[i]; /* next row to be added to k_th row */ 1311 /* compute multiplier, update D(k) and U(i,k) */ 1312 ili = il[i]; /* index of first nonzero element in U(i,k:bms-1) */ 1313 uikdi = - ba[ili]*ba[bi[i]]; 1314 dk += uikdi*ba[ili]; 1315 ba[ili] = uikdi; /* -U(i,k) */ 1316 1317 /* add multiple of row i to k-th row ... */ 1318 jmin = ili + 1; 1319 nz = bi[i+1] - jmin; 1320 if (nz > 0){ 1321 bcol = bj + jmin; 1322 bval = ba + jmin; 1323 ierr = PetscLogFlops(2*nz);CHKERRQ(ierr); 1324 while (nz --) rtmp[*bcol++] += uikdi*(*bval++); 1325 1326 /* update il and jl for i-th row */ 1327 il[i] = jmin; 1328 j = bj[jmin]; jl[i] = jl[j]; jl[j] = i; 1329 } 1330 i = nexti; 1331 } 1332 1333 /* shift the diagonals when zero pivot is detected */ 1334 /* compute rs=sum of abs(off-diagonal) */ 1335 rs = 0.0; 1336 jmin = bi[k]+1; 1337 nz = bi[k+1] - jmin; 1338 if (nz){ 1339 bcol = bj + jmin; 1340 while (nz--){ 1341 rs += PetscAbsScalar(rtmp[*bcol]); 1342 bcol++; 1343 } 1344 } 1345 1346 sctx.rs = rs; 1347 sctx.pv = dk; 1348 ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr); 1349 if (newshift == 1) break; /* sctx.shift_amount is updated */ 1350 1351 /* copy data into U(k,:) */ 1352 ba[bi[k]] = 1.0/dk; 1353 jmin = bi[k]+1; 1354 nz = bi[k+1] - jmin; 1355 if (nz){ 1356 bcol = bj + jmin; 1357 bval = ba + jmin; 1358 while (nz--){ 1359 *bval++ = rtmp[*bcol]; 1360 rtmp[*bcol++] = 0.0; 1361 } 1362 /* add k-th row into il and jl */ 1363 il[k] = jmin; 1364 i = bj[jmin]; jl[k] = jl[i]; jl[i] = k; 1365 } 1366 } /* end of for (k = 0; k<mbs; k++) */ 1367 } while (sctx.chshift); 1368 ierr = PetscFree(rtmp);CHKERRQ(ierr); 1369 ierr = PetscFree(il);CHKERRQ(ierr); 1370 1371 C->factor = FACTOR_CHOLESKY; 1372 C->assembled = PETSC_TRUE; 1373 C->preallocated = PETSC_TRUE; 1374 ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr); 1375 if (sctx.nshift){ 1376 if (shiftnz) { 1377 ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1378 } else if (shiftpd) { 1379 ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr); 1380 } 1381 } 1382 PetscFunctionReturn(0); 1383 } 1384 1385 #undef __FUNCT__ 1386 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ" 1387 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info) 1388 { 1389 PetscErrorCode ierr; 1390 Mat C; 1391 1392 PetscFunctionBegin; 1393 ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr); 1394 ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr); 1395 ierr = MatHeaderCopy(A,C);CHKERRQ(ierr); 1396 PetscFunctionReturn(0); 1397 } 1398 1399 1400