1 2 /* 3 Factorization code for BAIJ format. 4 */ 5 6 #include <../src/mat/impls/baij/seq/baij.h> 7 #include <petsc/private/kernels/blockinvert.h> 8 #include <petscbt.h> 9 #include <../src/mat/utils/freespace.h> 10 11 /* ----------------------------------------------------------------*/ 12 extern PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat,Mat,MatDuplicateOption,PetscBool); 13 14 /* 15 This is not much faster than MatLUFactorNumeric_SeqBAIJ_N() but the solve is faster at least sometimes 16 */ 17 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_15_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info) 18 { 19 Mat C =B; 20 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)C->data; 21 PetscErrorCode ierr; 22 PetscInt i,j,k,ipvt[15]; 23 const PetscInt n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*ajtmp,*bjtmp,*bdiag=b->diag,*pj; 24 PetscInt nz,nzL,row; 25 MatScalar *rtmp,*pc,*mwork,*pv,*vv,work[225]; 26 const MatScalar *v,*aa=a->a; 27 PetscInt bs2 = a->bs2,bs=A->rmap->bs,flg; 28 PetscInt sol_ver; 29 PetscBool allowzeropivot,zeropivotdetected; 30 31 PetscFunctionBegin; 32 allowzeropivot = PetscNot(A->erroriffailure); 33 ierr = PetscOptionsGetInt(NULL,((PetscObject)A)->prefix,"-sol_ver",&sol_ver,NULL);CHKERRQ(ierr); 34 35 /* generate work space needed by the factorization */ 36 ierr = PetscMalloc2(bs2*n,&rtmp,bs2,&mwork);CHKERRQ(ierr); 37 ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr); 38 39 for (i=0; i<n; i++) { 40 /* zero rtmp */ 41 /* L part */ 42 nz = bi[i+1] - bi[i]; 43 bjtmp = bj + bi[i]; 44 for (j=0; j<nz; j++) { 45 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 46 } 47 48 /* U part */ 49 nz = bdiag[i] - bdiag[i+1]; 50 bjtmp = bj + bdiag[i+1]+1; 51 for (j=0; j<nz; j++) { 52 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 53 } 54 55 /* load in initial (unfactored row) */ 56 nz = ai[i+1] - ai[i]; 57 ajtmp = aj + ai[i]; 58 v = aa + bs2*ai[i]; 59 for (j=0; j<nz; j++) { 60 ierr = PetscMemcpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr); 61 } 62 63 /* elimination */ 64 bjtmp = bj + bi[i]; 65 nzL = bi[i+1] - bi[i]; 66 for (k=0; k < nzL; k++) { 67 row = bjtmp[k]; 68 pc = rtmp + bs2*row; 69 for (flg=0,j=0; j<bs2; j++) { 70 if (pc[j]!=0.0) { 71 flg = 1; 72 break; 73 } 74 } 75 if (flg) { 76 pv = b->a + bs2*bdiag[row]; 77 PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork); 78 /*ierr = PetscKernel_A_gets_A_times_B_15(pc,pv,mwork);CHKERRQ(ierr);*/ 79 pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */ 80 pv = b->a + bs2*(bdiag[row+1]+1); 81 nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */ 82 for (j=0; j<nz; j++) { 83 vv = rtmp + bs2*pj[j]; 84 PetscKernel_A_gets_A_minus_B_times_C(bs,vv,pc,pv); 85 /* ierr = PetscKernel_A_gets_A_minus_B_times_C_15(vv,pc,pv);CHKERRQ(ierr); */ 86 pv += bs2; 87 } 88 ierr = PetscLogFlops(2*bs2*bs*(nz+1)-bs2);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */ 89 } 90 } 91 92 /* finished row so stick it into b->a */ 93 /* L part */ 94 pv = b->a + bs2*bi[i]; 95 pj = b->j + bi[i]; 96 nz = bi[i+1] - bi[i]; 97 for (j=0; j<nz; j++) { 98 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 99 } 100 101 /* Mark diagonal and invert diagonal for simplier triangular solves */ 102 pv = b->a + bs2*bdiag[i]; 103 pj = b->j + bdiag[i]; 104 ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr); 105 ierr = PetscKernel_A_gets_inverse_A_15(pv,ipvt,work,info->shiftamount,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 106 if (zeropivotdetected) C->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 107 108 /* U part */ 109 pv = b->a + bs2*(bdiag[i+1]+1); 110 pj = b->j + bdiag[i+1]+1; 111 nz = bdiag[i] - bdiag[i+1] - 1; 112 for (j=0; j<nz; j++) { 113 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 114 } 115 } 116 117 ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr); 118 119 C->ops->solve = MatSolve_SeqBAIJ_15_NaturalOrdering_ver1; 120 C->ops->solvetranspose = MatSolve_SeqBAIJ_N_NaturalOrdering; 121 C->assembled = PETSC_TRUE; 122 123 ierr = PetscLogFlops(1.333333333333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 124 PetscFunctionReturn(0); 125 } 126 127 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_N(Mat B,Mat A,const MatFactorInfo *info) 128 { 129 Mat C =B; 130 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)C->data; 131 IS isrow = b->row,isicol = b->icol; 132 PetscErrorCode ierr; 133 const PetscInt *r,*ic; 134 PetscInt i,j,k,n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 135 PetscInt *ajtmp,*bjtmp,nz,nzL,row,*bdiag=b->diag,*pj; 136 MatScalar *rtmp,*pc,*mwork,*v,*pv,*aa=a->a; 137 PetscInt bs=A->rmap->bs,bs2 = a->bs2,*v_pivots,flg; 138 MatScalar *v_work; 139 PetscBool col_identity,row_identity,both_identity; 140 PetscBool allowzeropivot,zeropivotdetected; 141 142 PetscFunctionBegin; 143 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 144 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 145 allowzeropivot = PetscNot(A->erroriffailure); 146 147 ierr = PetscMalloc1(bs2*n,&rtmp);CHKERRQ(ierr); 148 ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr); 149 150 /* generate work space needed by dense LU factorization */ 151 ierr = PetscMalloc3(bs,&v_work,bs2,&mwork,bs,&v_pivots);CHKERRQ(ierr); 152 153 for (i=0; i<n; i++) { 154 /* zero rtmp */ 155 /* L part */ 156 nz = bi[i+1] - bi[i]; 157 bjtmp = bj + bi[i]; 158 for (j=0; j<nz; j++) { 159 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 160 } 161 162 /* U part */ 163 nz = bdiag[i] - bdiag[i+1]; 164 bjtmp = bj + bdiag[i+1]+1; 165 for (j=0; j<nz; j++) { 166 ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 167 } 168 169 /* load in initial (unfactored row) */ 170 nz = ai[r[i]+1] - ai[r[i]]; 171 ajtmp = aj + ai[r[i]]; 172 v = aa + bs2*ai[r[i]]; 173 for (j=0; j<nz; j++) { 174 ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr); 175 } 176 177 /* elimination */ 178 bjtmp = bj + bi[i]; 179 nzL = bi[i+1] - bi[i]; 180 for (k=0; k < nzL; k++) { 181 row = bjtmp[k]; 182 pc = rtmp + bs2*row; 183 for (flg=0,j=0; j<bs2; j++) { 184 if (pc[j]!=0.0) { 185 flg = 1; 186 break; 187 } 188 } 189 if (flg) { 190 pv = b->a + bs2*bdiag[row]; 191 PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork); /* *pc = *pc * (*pv); */ 192 pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */ 193 pv = b->a + bs2*(bdiag[row+1]+1); 194 nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */ 195 for (j=0; j<nz; j++) { 196 PetscKernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); 197 } 198 ierr = PetscLogFlops(2*bs2*bs*(nz+1)-bs2);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */ 199 } 200 } 201 202 /* finished row so stick it into b->a */ 203 /* L part */ 204 pv = b->a + bs2*bi[i]; 205 pj = b->j + bi[i]; 206 nz = bi[i+1] - bi[i]; 207 for (j=0; j<nz; j++) { 208 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 209 } 210 211 /* Mark diagonal and invert diagonal for simplier triangular solves */ 212 pv = b->a + bs2*bdiag[i]; 213 pj = b->j + bdiag[i]; 214 ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr); 215 216 ierr = PetscKernel_A_gets_inverse_A(bs,pv,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 217 if (zeropivotdetected) B->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 218 219 /* U part */ 220 pv = b->a + bs2*(bdiag[i+1]+1); 221 pj = b->j + bdiag[i+1]+1; 222 nz = bdiag[i] - bdiag[i+1] - 1; 223 for (j=0; j<nz; j++) { 224 ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr); 225 } 226 } 227 228 ierr = PetscFree(rtmp);CHKERRQ(ierr); 229 ierr = PetscFree3(v_work,mwork,v_pivots);CHKERRQ(ierr); 230 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 231 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 232 233 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 234 ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr); 235 236 both_identity = (PetscBool) (row_identity && col_identity); 237 if (both_identity) { 238 switch (bs) { 239 case 11: 240 C->ops->solve = MatSolve_SeqBAIJ_11_NaturalOrdering; 241 break; 242 case 12: 243 C->ops->solve = MatSolve_SeqBAIJ_12_NaturalOrdering; 244 break; 245 case 13: 246 C->ops->solve = MatSolve_SeqBAIJ_13_NaturalOrdering; 247 break; 248 case 14: 249 C->ops->solve = MatSolve_SeqBAIJ_14_NaturalOrdering; 250 break; 251 default: 252 C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering; 253 break; 254 } 255 } else { 256 C->ops->solve = MatSolve_SeqBAIJ_N; 257 } 258 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_N; 259 260 C->assembled = PETSC_TRUE; 261 262 ierr = PetscLogFlops(1.333333333333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 263 PetscFunctionReturn(0); 264 } 265 266 /* 267 ilu(0) with natural ordering under new data structure. 268 See MatILUFactorSymbolic_SeqAIJ_ilu0() for detailed description 269 because this code is almost identical to MatILUFactorSymbolic_SeqAIJ_ilu0_inplace(). 270 */ 271 272 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_ilu0(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 273 { 274 275 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 276 PetscErrorCode ierr; 277 PetscInt n=a->mbs,*ai=a->i,*aj,*adiag=a->diag,bs2 = a->bs2; 278 PetscInt i,j,nz,*bi,*bj,*bdiag,bi_temp; 279 280 PetscFunctionBegin; 281 ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_FALSE);CHKERRQ(ierr); 282 b = (Mat_SeqBAIJ*)(fact)->data; 283 284 /* allocate matrix arrays for new data structure */ 285 ierr = PetscMalloc3(bs2*ai[n]+1,&b->a,ai[n]+1,&b->j,n+1,&b->i);CHKERRQ(ierr); 286 ierr = PetscLogObjectMemory((PetscObject)fact,ai[n]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(n+1)*sizeof(PetscInt));CHKERRQ(ierr); 287 288 b->singlemalloc = PETSC_TRUE; 289 b->free_a = PETSC_TRUE; 290 b->free_ij = PETSC_TRUE; 291 fact->preallocated = PETSC_TRUE; 292 fact->assembled = PETSC_TRUE; 293 if (!b->diag) { 294 ierr = PetscMalloc1(n+1,&b->diag);CHKERRQ(ierr); 295 ierr = PetscLogObjectMemory((PetscObject)fact,(n+1)*sizeof(PetscInt));CHKERRQ(ierr); 296 } 297 bdiag = b->diag; 298 299 if (n > 0) { 300 ierr = PetscMemzero(b->a,bs2*ai[n]*sizeof(MatScalar));CHKERRQ(ierr); 301 } 302 303 /* set bi and bj with new data structure */ 304 bi = b->i; 305 bj = b->j; 306 307 /* L part */ 308 bi[0] = 0; 309 for (i=0; i<n; i++) { 310 nz = adiag[i] - ai[i]; 311 bi[i+1] = bi[i] + nz; 312 aj = a->j + ai[i]; 313 for (j=0; j<nz; j++) { 314 *bj = aj[j]; bj++; 315 } 316 } 317 318 /* U part */ 319 bi_temp = bi[n]; 320 bdiag[n] = bi[n]-1; 321 for (i=n-1; i>=0; i--) { 322 nz = ai[i+1] - adiag[i] - 1; 323 bi_temp = bi_temp + nz + 1; 324 aj = a->j + adiag[i] + 1; 325 for (j=0; j<nz; j++) { 326 *bj = aj[j]; bj++; 327 } 328 /* diag[i] */ 329 *bj = i; bj++; 330 bdiag[i] = bi_temp - 1; 331 } 332 PetscFunctionReturn(0); 333 } 334 335 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 336 { 337 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 338 IS isicol; 339 PetscErrorCode ierr; 340 const PetscInt *r,*ic; 341 PetscInt n=a->mbs,*ai=a->i,*aj=a->j,d; 342 PetscInt *bi,*cols,nnz,*cols_lvl; 343 PetscInt *bdiag,prow,fm,nzbd,reallocs=0,dcount=0; 344 PetscInt i,levels,diagonal_fill; 345 PetscBool col_identity,row_identity,both_identity; 346 PetscReal f; 347 PetscInt nlnk,*lnk,*lnk_lvl=NULL; 348 PetscBT lnkbt; 349 PetscInt nzi,*bj,**bj_ptr,**bjlvl_ptr; 350 PetscFreeSpaceList free_space =NULL,current_space=NULL; 351 PetscFreeSpaceList free_space_lvl=NULL,current_space_lvl=NULL; 352 PetscBool missing; 353 PetscInt bs=A->rmap->bs,bs2=a->bs2; 354 355 PetscFunctionBegin; 356 if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must be square matrix, rows %D columns %D",A->rmap->n,A->cmap->n); 357 if (bs>1) { /* check shifttype */ 358 if (info->shifttype == MAT_SHIFT_NONZERO || info->shifttype == MAT_SHIFT_POSITIVE_DEFINITE) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only MAT_SHIFT_NONE and MAT_SHIFT_INBLOCKS are supported for BAIJ matrix"); 359 } 360 361 ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr); 362 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d); 363 364 f = info->fill; 365 levels = (PetscInt)info->levels; 366 diagonal_fill = (PetscInt)info->diagonal_fill; 367 368 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 369 370 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 371 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 372 373 both_identity = (PetscBool) (row_identity && col_identity); 374 375 if (!levels && both_identity) { 376 /* special case: ilu(0) with natural ordering */ 377 ierr = MatILUFactorSymbolic_SeqBAIJ_ilu0(fact,A,isrow,iscol,info);CHKERRQ(ierr); 378 ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr); 379 380 fact->factortype = MAT_FACTOR_ILU; 381 (fact)->info.factor_mallocs = 0; 382 (fact)->info.fill_ratio_given = info->fill; 383 (fact)->info.fill_ratio_needed = 1.0; 384 385 b = (Mat_SeqBAIJ*)(fact)->data; 386 b->row = isrow; 387 b->col = iscol; 388 b->icol = isicol; 389 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 390 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 391 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 392 393 ierr = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr); 394 PetscFunctionReturn(0); 395 } 396 397 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 398 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 399 400 /* get new row pointers */ 401 ierr = PetscMalloc1(n+1,&bi);CHKERRQ(ierr); 402 bi[0] = 0; 403 /* bdiag is location of diagonal in factor */ 404 ierr = PetscMalloc1(n+1,&bdiag);CHKERRQ(ierr); 405 bdiag[0] = 0; 406 407 ierr = PetscMalloc2(n,&bj_ptr,n,&bjlvl_ptr);CHKERRQ(ierr); 408 409 /* create a linked list for storing column indices of the active row */ 410 nlnk = n + 1; 411 ierr = PetscIncompleteLLCreate(n,n,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 412 413 /* initial FreeSpace size is f*(ai[n]+1) */ 414 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space);CHKERRQ(ierr); 415 current_space = free_space; 416 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space_lvl);CHKERRQ(ierr); 417 current_space_lvl = free_space_lvl; 418 419 for (i=0; i<n; i++) { 420 nzi = 0; 421 /* copy current row into linked list */ 422 nnz = ai[r[i]+1] - ai[r[i]]; 423 if (!nnz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i); 424 cols = aj + ai[r[i]]; 425 lnk[i] = -1; /* marker to indicate if diagonal exists */ 426 ierr = PetscIncompleteLLInit(nnz,cols,n,ic,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 427 nzi += nlnk; 428 429 /* make sure diagonal entry is included */ 430 if (diagonal_fill && lnk[i] == -1) { 431 fm = n; 432 while (lnk[fm] < i) fm = lnk[fm]; 433 lnk[i] = lnk[fm]; /* insert diagonal into linked list */ 434 lnk[fm] = i; 435 lnk_lvl[i] = 0; 436 nzi++; dcount++; 437 } 438 439 /* add pivot rows into the active row */ 440 nzbd = 0; 441 prow = lnk[n]; 442 while (prow < i) { 443 nnz = bdiag[prow]; 444 cols = bj_ptr[prow] + nnz + 1; 445 cols_lvl = bjlvl_ptr[prow] + nnz + 1; 446 nnz = bi[prow+1] - bi[prow] - nnz - 1; 447 448 ierr = PetscILULLAddSorted(nnz,cols,levels,cols_lvl,prow,nlnk,lnk,lnk_lvl,lnkbt,prow);CHKERRQ(ierr); 449 nzi += nlnk; 450 prow = lnk[prow]; 451 nzbd++; 452 } 453 bdiag[i] = nzbd; 454 bi[i+1] = bi[i] + nzi; 455 456 /* if free space is not available, make more free space */ 457 if (current_space->local_remaining<nzi) { 458 nnz = PetscIntMultTruncate(2,PetscIntMultTruncate(nzi,(n - i))); /* estimated and max additional space needed */ 459 ierr = PetscFreeSpaceGet(nnz,¤t_space);CHKERRQ(ierr); 460 ierr = PetscFreeSpaceGet(nnz,¤t_space_lvl);CHKERRQ(ierr); 461 reallocs++; 462 } 463 464 /* copy data into free_space and free_space_lvl, then initialize lnk */ 465 ierr = PetscIncompleteLLClean(n,n,nzi,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr); 466 467 bj_ptr[i] = current_space->array; 468 bjlvl_ptr[i] = current_space_lvl->array; 469 470 /* make sure the active row i has diagonal entry */ 471 if (*(bj_ptr[i]+bdiag[i]) != i) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Row %D has missing diagonal in factored matrix\ntry running with -pc_factor_nonzeros_along_diagonal or -pc_factor_diagonal_fill",i); 472 473 current_space->array += nzi; 474 current_space->local_used += nzi; 475 current_space->local_remaining -= nzi; 476 477 current_space_lvl->array += nzi; 478 current_space_lvl->local_used += nzi; 479 current_space_lvl->local_remaining -= nzi; 480 } 481 482 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 483 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 484 485 /* copy free_space into bj and free free_space; set bi, bj, bdiag in new datastructure; */ 486 ierr = PetscMalloc1(bi[n]+1,&bj);CHKERRQ(ierr); 487 ierr = PetscFreeSpaceContiguous_LU(&free_space,bj,n,bi,bdiag);CHKERRQ(ierr); 488 489 ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 490 ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr); 491 ierr = PetscFree2(bj_ptr,bjlvl_ptr);CHKERRQ(ierr); 492 493 #if defined(PETSC_USE_INFO) 494 { 495 PetscReal af = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]); 496 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)f,(double)af);CHKERRQ(ierr); 497 ierr = PetscInfo1(A,"Run with -[sub_]pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 498 ierr = PetscInfo1(A,"PCFactorSetFill([sub]pc,%g);\n",(double)af);CHKERRQ(ierr); 499 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 500 if (diagonal_fill) { 501 ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr); 502 } 503 } 504 #endif 505 506 /* put together the new matrix */ 507 ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 508 ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr); 509 510 b = (Mat_SeqBAIJ*)(fact)->data; 511 b->free_a = PETSC_TRUE; 512 b->free_ij = PETSC_TRUE; 513 b->singlemalloc = PETSC_FALSE; 514 515 ierr = PetscMalloc1(bs2*(bdiag[0]+1),&b->a);CHKERRQ(ierr); 516 517 b->j = bj; 518 b->i = bi; 519 b->diag = bdiag; 520 b->free_diag = PETSC_TRUE; 521 b->ilen = 0; 522 b->imax = 0; 523 b->row = isrow; 524 b->col = iscol; 525 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 526 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 527 b->icol = isicol; 528 529 ierr = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr); 530 /* In b structure: Free imax, ilen, old a, old j. 531 Allocate bdiag, solve_work, new a, new j */ 532 ierr = PetscLogObjectMemory((PetscObject)fact,(bdiag[0]+1) * (sizeof(PetscInt)+bs2*sizeof(PetscScalar)));CHKERRQ(ierr); 533 b->maxnz = b->nz = bdiag[0]+1; 534 535 fact->info.factor_mallocs = reallocs; 536 fact->info.fill_ratio_given = f; 537 fact->info.fill_ratio_needed = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]); 538 539 ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr); 540 PetscFunctionReturn(0); 541 } 542 543 /* 544 This code is virtually identical to MatILUFactorSymbolic_SeqAIJ 545 except that the data structure of Mat_SeqAIJ is slightly different. 546 Not a good example of code reuse. 547 */ 548 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_inplace(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 549 { 550 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 551 IS isicol; 552 PetscErrorCode ierr; 553 const PetscInt *r,*ic,*ai = a->i,*aj = a->j,*xi; 554 PetscInt prow,n = a->mbs,*ainew,*ajnew,jmax,*fill,nz,*im,*ajfill,*flev,*xitmp; 555 PetscInt *dloc,idx,row,m,fm,nzf,nzi,reallocate = 0,dcount = 0; 556 PetscInt incrlev,nnz,i,bs = A->rmap->bs,bs2 = a->bs2,levels,diagonal_fill,dd; 557 PetscBool col_identity,row_identity,both_identity,flg; 558 PetscReal f; 559 560 PetscFunctionBegin; 561 ierr = MatMissingDiagonal_SeqBAIJ(A,&flg,&dd);CHKERRQ(ierr); 562 if (flg) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix A is missing diagonal entry in row %D",dd); 563 564 f = info->fill; 565 levels = (PetscInt)info->levels; 566 diagonal_fill = (PetscInt)info->diagonal_fill; 567 568 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 569 570 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 571 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 572 both_identity = (PetscBool) (row_identity && col_identity); 573 574 if (!levels && both_identity) { /* special case copy the nonzero structure */ 575 ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 576 ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr); 577 578 fact->factortype = MAT_FACTOR_ILU; 579 b = (Mat_SeqBAIJ*)fact->data; 580 b->row = isrow; 581 b->col = iscol; 582 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 583 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 584 b->icol = isicol; 585 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 586 587 ierr = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr); 588 PetscFunctionReturn(0); 589 } 590 591 /* general case perform the symbolic factorization */ 592 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 593 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 594 595 /* get new row pointers */ 596 ierr = PetscMalloc1(n+1,&ainew);CHKERRQ(ierr); 597 ainew[0] = 0; 598 /* don't know how many column pointers are needed so estimate */ 599 jmax = (PetscInt)(f*ai[n] + 1); 600 ierr = PetscMalloc1(jmax,&ajnew);CHKERRQ(ierr); 601 /* ajfill is level of fill for each fill entry */ 602 ierr = PetscMalloc1(jmax,&ajfill);CHKERRQ(ierr); 603 /* fill is a linked list of nonzeros in active row */ 604 ierr = PetscMalloc1(n+1,&fill);CHKERRQ(ierr); 605 /* im is level for each filled value */ 606 ierr = PetscMalloc1(n+1,&im);CHKERRQ(ierr); 607 /* dloc is location of diagonal in factor */ 608 ierr = PetscMalloc1(n+1,&dloc);CHKERRQ(ierr); 609 dloc[0] = 0; 610 for (prow=0; prow<n; prow++) { 611 612 /* copy prow into linked list */ 613 nzf = nz = ai[r[prow]+1] - ai[r[prow]]; 614 if (!nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[prow],prow); 615 xi = aj + ai[r[prow]]; 616 fill[n] = n; 617 fill[prow] = -1; /* marker for diagonal entry */ 618 while (nz--) { 619 fm = n; 620 idx = ic[*xi++]; 621 do { 622 m = fm; 623 fm = fill[m]; 624 } while (fm < idx); 625 fill[m] = idx; 626 fill[idx] = fm; 627 im[idx] = 0; 628 } 629 630 /* make sure diagonal entry is included */ 631 if (diagonal_fill && fill[prow] == -1) { 632 fm = n; 633 while (fill[fm] < prow) fm = fill[fm]; 634 fill[prow] = fill[fm]; /* insert diagonal into linked list */ 635 fill[fm] = prow; 636 im[prow] = 0; 637 nzf++; 638 dcount++; 639 } 640 641 nzi = 0; 642 row = fill[n]; 643 while (row < prow) { 644 incrlev = im[row] + 1; 645 nz = dloc[row]; 646 xi = ajnew + ainew[row] + nz + 1; 647 flev = ajfill + ainew[row] + nz + 1; 648 nnz = ainew[row+1] - ainew[row] - nz - 1; 649 fm = row; 650 while (nnz-- > 0) { 651 idx = *xi++; 652 if (*flev + incrlev > levels) { 653 flev++; 654 continue; 655 } 656 do { 657 m = fm; 658 fm = fill[m]; 659 } while (fm < idx); 660 if (fm != idx) { 661 im[idx] = *flev + incrlev; 662 fill[m] = idx; 663 fill[idx] = fm; 664 fm = idx; 665 nzf++; 666 } else if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev; 667 flev++; 668 } 669 row = fill[row]; 670 nzi++; 671 } 672 /* copy new filled row into permanent storage */ 673 ainew[prow+1] = ainew[prow] + nzf; 674 if (ainew[prow+1] > jmax) { 675 676 /* estimate how much additional space we will need */ 677 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 678 /* just double the memory each time */ 679 PetscInt maxadd = jmax; 680 /* maxadd = (int)(((f*ai[n]+1)*(n-prow+5))/n); */ 681 if (maxadd < nzf) maxadd = (n-prow)*(nzf+1); 682 jmax += maxadd; 683 684 /* allocate a longer ajnew and ajfill */ 685 ierr = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr); 686 ierr = PetscMemcpy(xitmp,ajnew,ainew[prow]*sizeof(PetscInt));CHKERRQ(ierr); 687 ierr = PetscFree(ajnew);CHKERRQ(ierr); 688 ajnew = xitmp; 689 ierr = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr); 690 ierr = PetscMemcpy(xitmp,ajfill,ainew[prow]*sizeof(PetscInt));CHKERRQ(ierr); 691 ierr = PetscFree(ajfill);CHKERRQ(ierr); 692 ajfill = xitmp; 693 reallocate++; /* count how many reallocations are needed */ 694 } 695 xitmp = ajnew + ainew[prow]; 696 flev = ajfill + ainew[prow]; 697 dloc[prow] = nzi; 698 fm = fill[n]; 699 while (nzf--) { 700 *xitmp++ = fm; 701 *flev++ = im[fm]; 702 fm = fill[fm]; 703 } 704 /* make sure row has diagonal entry */ 705 if (ajnew[ainew[prow]+dloc[prow]] != prow) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Row %D has missing diagonal in factored matrix\n\ 706 try running with -pc_factor_nonzeros_along_diagonal or -pc_factor_diagonal_fill",prow); 707 } 708 ierr = PetscFree(ajfill);CHKERRQ(ierr); 709 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 710 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 711 ierr = PetscFree(fill);CHKERRQ(ierr); 712 ierr = PetscFree(im);CHKERRQ(ierr); 713 714 #if defined(PETSC_USE_INFO) 715 { 716 PetscReal af = ((PetscReal)ainew[n])/((PetscReal)ai[n]); 717 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocate,(double)f,(double)af);CHKERRQ(ierr); 718 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 719 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g);\n",(double)af);CHKERRQ(ierr); 720 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 721 if (diagonal_fill) { 722 ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr); 723 } 724 } 725 #endif 726 727 /* put together the new matrix */ 728 ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 729 ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr); 730 b = (Mat_SeqBAIJ*)fact->data; 731 732 b->free_a = PETSC_TRUE; 733 b->free_ij = PETSC_TRUE; 734 b->singlemalloc = PETSC_FALSE; 735 736 ierr = PetscMalloc1(bs2*ainew[n],&b->a);CHKERRQ(ierr); 737 738 b->j = ajnew; 739 b->i = ainew; 740 for (i=0; i<n; i++) dloc[i] += ainew[i]; 741 b->diag = dloc; 742 b->free_diag = PETSC_TRUE; 743 b->ilen = 0; 744 b->imax = 0; 745 b->row = isrow; 746 b->col = iscol; 747 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 748 749 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 750 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 751 b->icol = isicol; 752 ierr = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr); 753 /* In b structure: Free imax, ilen, old a, old j. 754 Allocate dloc, solve_work, new a, new j */ 755 ierr = PetscLogObjectMemory((PetscObject)fact,(ainew[n]-n)*(sizeof(PetscInt))+bs2*ainew[n]*sizeof(PetscScalar));CHKERRQ(ierr); 756 b->maxnz = b->nz = ainew[n]; 757 758 fact->info.factor_mallocs = reallocate; 759 fact->info.fill_ratio_given = f; 760 fact->info.fill_ratio_needed = ((PetscReal)ainew[n])/((PetscReal)ai[prow]); 761 762 ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr); 763 PetscFunctionReturn(0); 764 } 765 766 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE(Mat A) 767 { 768 /* Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; */ 769 /* int i,*AJ=a->j,nz=a->nz; */ 770 771 PetscFunctionBegin; 772 /* Undo Column scaling */ 773 /* while (nz--) { */ 774 /* AJ[i] = AJ[i]/4; */ 775 /* } */ 776 /* This should really invoke a push/pop logic, but we don't have that yet. */ 777 A->ops->setunfactored = NULL; 778 PetscFunctionReturn(0); 779 } 780 781 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE_usj(Mat A) 782 { 783 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 784 PetscInt *AJ=a->j,nz=a->nz; 785 unsigned short *aj=(unsigned short*)AJ; 786 787 PetscFunctionBegin; 788 /* Is this really necessary? */ 789 while (nz--) { 790 AJ[nz] = (int)((unsigned int)aj[nz]); /* First extend, then convert to signed. */ 791 } 792 A->ops->setunfactored = NULL; 793 PetscFunctionReturn(0); 794 } 795 796 797