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 9: 240 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) 241 C->ops->solve = MatSolve_SeqBAIJ_9_NaturalOrdering; 242 #else 243 C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering; 244 #endif 245 break; 246 case 11: 247 C->ops->solve = MatSolve_SeqBAIJ_11_NaturalOrdering; 248 break; 249 case 12: 250 C->ops->solve = MatSolve_SeqBAIJ_12_NaturalOrdering; 251 break; 252 case 13: 253 C->ops->solve = MatSolve_SeqBAIJ_13_NaturalOrdering; 254 break; 255 case 14: 256 C->ops->solve = MatSolve_SeqBAIJ_14_NaturalOrdering; 257 break; 258 default: 259 C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering; 260 break; 261 } 262 } else { 263 C->ops->solve = MatSolve_SeqBAIJ_N; 264 } 265 C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_N; 266 267 C->assembled = PETSC_TRUE; 268 269 ierr = PetscLogFlops(1.333333333333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */ 270 PetscFunctionReturn(0); 271 } 272 273 /* 274 ilu(0) with natural ordering under new data structure. 275 See MatILUFactorSymbolic_SeqAIJ_ilu0() for detailed description 276 because this code is almost identical to MatILUFactorSymbolic_SeqAIJ_ilu0_inplace(). 277 */ 278 279 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_ilu0(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 280 { 281 282 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 283 PetscErrorCode ierr; 284 PetscInt n=a->mbs,*ai=a->i,*aj,*adiag=a->diag,bs2 = a->bs2; 285 PetscInt i,j,nz,*bi,*bj,*bdiag,bi_temp; 286 287 PetscFunctionBegin; 288 ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_FALSE);CHKERRQ(ierr); 289 b = (Mat_SeqBAIJ*)(fact)->data; 290 291 /* allocate matrix arrays for new data structure */ 292 ierr = PetscMalloc3(bs2*ai[n]+1,&b->a,ai[n]+1,&b->j,n+1,&b->i);CHKERRQ(ierr); 293 ierr = PetscLogObjectMemory((PetscObject)fact,ai[n]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(n+1)*sizeof(PetscInt));CHKERRQ(ierr); 294 295 b->singlemalloc = PETSC_TRUE; 296 b->free_a = PETSC_TRUE; 297 b->free_ij = PETSC_TRUE; 298 fact->preallocated = PETSC_TRUE; 299 fact->assembled = PETSC_TRUE; 300 if (!b->diag) { 301 ierr = PetscMalloc1(n+1,&b->diag);CHKERRQ(ierr); 302 ierr = PetscLogObjectMemory((PetscObject)fact,(n+1)*sizeof(PetscInt));CHKERRQ(ierr); 303 } 304 bdiag = b->diag; 305 306 if (n > 0) { 307 ierr = PetscMemzero(b->a,bs2*ai[n]*sizeof(MatScalar));CHKERRQ(ierr); 308 } 309 310 /* set bi and bj with new data structure */ 311 bi = b->i; 312 bj = b->j; 313 314 /* L part */ 315 bi[0] = 0; 316 for (i=0; i<n; i++) { 317 nz = adiag[i] - ai[i]; 318 bi[i+1] = bi[i] + nz; 319 aj = a->j + ai[i]; 320 for (j=0; j<nz; j++) { 321 *bj = aj[j]; bj++; 322 } 323 } 324 325 /* U part */ 326 bi_temp = bi[n]; 327 bdiag[n] = bi[n]-1; 328 for (i=n-1; i>=0; i--) { 329 nz = ai[i+1] - adiag[i] - 1; 330 bi_temp = bi_temp + nz + 1; 331 aj = a->j + adiag[i] + 1; 332 for (j=0; j<nz; j++) { 333 *bj = aj[j]; bj++; 334 } 335 /* diag[i] */ 336 *bj = i; bj++; 337 bdiag[i] = bi_temp - 1; 338 } 339 PetscFunctionReturn(0); 340 } 341 342 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 343 { 344 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 345 IS isicol; 346 PetscErrorCode ierr; 347 const PetscInt *r,*ic; 348 PetscInt n=a->mbs,*ai=a->i,*aj=a->j,d; 349 PetscInt *bi,*cols,nnz,*cols_lvl; 350 PetscInt *bdiag,prow,fm,nzbd,reallocs=0,dcount=0; 351 PetscInt i,levels,diagonal_fill; 352 PetscBool col_identity,row_identity,both_identity; 353 PetscReal f; 354 PetscInt nlnk,*lnk,*lnk_lvl=NULL; 355 PetscBT lnkbt; 356 PetscInt nzi,*bj,**bj_ptr,**bjlvl_ptr; 357 PetscFreeSpaceList free_space =NULL,current_space=NULL; 358 PetscFreeSpaceList free_space_lvl=NULL,current_space_lvl=NULL; 359 PetscBool missing; 360 PetscInt bs=A->rmap->bs,bs2=a->bs2; 361 362 PetscFunctionBegin; 363 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); 364 if (bs>1) { /* check shifttype */ 365 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"); 366 } 367 368 ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr); 369 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d); 370 371 f = info->fill; 372 levels = (PetscInt)info->levels; 373 diagonal_fill = (PetscInt)info->diagonal_fill; 374 375 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 376 377 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 378 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 379 380 both_identity = (PetscBool) (row_identity && col_identity); 381 382 if (!levels && both_identity) { 383 /* special case: ilu(0) with natural ordering */ 384 ierr = MatILUFactorSymbolic_SeqBAIJ_ilu0(fact,A,isrow,iscol,info);CHKERRQ(ierr); 385 ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr); 386 387 fact->factortype = MAT_FACTOR_ILU; 388 (fact)->info.factor_mallocs = 0; 389 (fact)->info.fill_ratio_given = info->fill; 390 (fact)->info.fill_ratio_needed = 1.0; 391 392 b = (Mat_SeqBAIJ*)(fact)->data; 393 b->row = isrow; 394 b->col = iscol; 395 b->icol = isicol; 396 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 397 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 398 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 399 400 ierr = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr); 401 PetscFunctionReturn(0); 402 } 403 404 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 405 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 406 407 /* get new row pointers */ 408 ierr = PetscMalloc1(n+1,&bi);CHKERRQ(ierr); 409 bi[0] = 0; 410 /* bdiag is location of diagonal in factor */ 411 ierr = PetscMalloc1(n+1,&bdiag);CHKERRQ(ierr); 412 bdiag[0] = 0; 413 414 ierr = PetscMalloc2(n,&bj_ptr,n,&bjlvl_ptr);CHKERRQ(ierr); 415 416 /* create a linked list for storing column indices of the active row */ 417 nlnk = n + 1; 418 ierr = PetscIncompleteLLCreate(n,n,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 419 420 /* initial FreeSpace size is f*(ai[n]+1) */ 421 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space);CHKERRQ(ierr); 422 current_space = free_space; 423 ierr = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space_lvl);CHKERRQ(ierr); 424 current_space_lvl = free_space_lvl; 425 426 for (i=0; i<n; i++) { 427 nzi = 0; 428 /* copy current row into linked list */ 429 nnz = ai[r[i]+1] - ai[r[i]]; 430 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); 431 cols = aj + ai[r[i]]; 432 lnk[i] = -1; /* marker to indicate if diagonal exists */ 433 ierr = PetscIncompleteLLInit(nnz,cols,n,ic,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr); 434 nzi += nlnk; 435 436 /* make sure diagonal entry is included */ 437 if (diagonal_fill && lnk[i] == -1) { 438 fm = n; 439 while (lnk[fm] < i) fm = lnk[fm]; 440 lnk[i] = lnk[fm]; /* insert diagonal into linked list */ 441 lnk[fm] = i; 442 lnk_lvl[i] = 0; 443 nzi++; dcount++; 444 } 445 446 /* add pivot rows into the active row */ 447 nzbd = 0; 448 prow = lnk[n]; 449 while (prow < i) { 450 nnz = bdiag[prow]; 451 cols = bj_ptr[prow] + nnz + 1; 452 cols_lvl = bjlvl_ptr[prow] + nnz + 1; 453 nnz = bi[prow+1] - bi[prow] - nnz - 1; 454 455 ierr = PetscILULLAddSorted(nnz,cols,levels,cols_lvl,prow,nlnk,lnk,lnk_lvl,lnkbt,prow);CHKERRQ(ierr); 456 nzi += nlnk; 457 prow = lnk[prow]; 458 nzbd++; 459 } 460 bdiag[i] = nzbd; 461 bi[i+1] = bi[i] + nzi; 462 463 /* if free space is not available, make more free space */ 464 if (current_space->local_remaining<nzi) { 465 nnz = PetscIntMultTruncate(2,PetscIntMultTruncate(nzi,(n - i))); /* estimated and max additional space needed */ 466 ierr = PetscFreeSpaceGet(nnz,¤t_space);CHKERRQ(ierr); 467 ierr = PetscFreeSpaceGet(nnz,¤t_space_lvl);CHKERRQ(ierr); 468 reallocs++; 469 } 470 471 /* copy data into free_space and free_space_lvl, then initialize lnk */ 472 ierr = PetscIncompleteLLClean(n,n,nzi,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr); 473 474 bj_ptr[i] = current_space->array; 475 bjlvl_ptr[i] = current_space_lvl->array; 476 477 /* make sure the active row i has diagonal entry */ 478 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); 479 480 current_space->array += nzi; 481 current_space->local_used += nzi; 482 current_space->local_remaining -= nzi; 483 484 current_space_lvl->array += nzi; 485 current_space_lvl->local_used += nzi; 486 current_space_lvl->local_remaining -= nzi; 487 } 488 489 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 490 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 491 492 /* copy free_space into bj and free free_space; set bi, bj, bdiag in new datastructure; */ 493 ierr = PetscMalloc1(bi[n]+1,&bj);CHKERRQ(ierr); 494 ierr = PetscFreeSpaceContiguous_LU(&free_space,bj,n,bi,bdiag);CHKERRQ(ierr); 495 496 ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 497 ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr); 498 ierr = PetscFree2(bj_ptr,bjlvl_ptr);CHKERRQ(ierr); 499 500 #if defined(PETSC_USE_INFO) 501 { 502 PetscReal af = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]); 503 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)f,(double)af);CHKERRQ(ierr); 504 ierr = PetscInfo1(A,"Run with -[sub_]pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 505 ierr = PetscInfo1(A,"PCFactorSetFill([sub]pc,%g);\n",(double)af);CHKERRQ(ierr); 506 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 507 if (diagonal_fill) { 508 ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr); 509 } 510 } 511 #endif 512 513 /* put together the new matrix */ 514 ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 515 ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr); 516 517 b = (Mat_SeqBAIJ*)(fact)->data; 518 b->free_a = PETSC_TRUE; 519 b->free_ij = PETSC_TRUE; 520 b->singlemalloc = PETSC_FALSE; 521 522 ierr = PetscMalloc1(bs2*(bdiag[0]+1),&b->a);CHKERRQ(ierr); 523 524 b->j = bj; 525 b->i = bi; 526 b->diag = bdiag; 527 b->free_diag = PETSC_TRUE; 528 b->ilen = 0; 529 b->imax = 0; 530 b->row = isrow; 531 b->col = iscol; 532 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 533 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 534 b->icol = isicol; 535 536 ierr = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr); 537 /* In b structure: Free imax, ilen, old a, old j. 538 Allocate bdiag, solve_work, new a, new j */ 539 ierr = PetscLogObjectMemory((PetscObject)fact,(bdiag[0]+1) * (sizeof(PetscInt)+bs2*sizeof(PetscScalar)));CHKERRQ(ierr); 540 b->maxnz = b->nz = bdiag[0]+1; 541 542 fact->info.factor_mallocs = reallocs; 543 fact->info.fill_ratio_given = f; 544 fact->info.fill_ratio_needed = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]); 545 546 ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr); 547 PetscFunctionReturn(0); 548 } 549 550 /* 551 This code is virtually identical to MatILUFactorSymbolic_SeqAIJ 552 except that the data structure of Mat_SeqAIJ is slightly different. 553 Not a good example of code reuse. 554 */ 555 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_inplace(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info) 556 { 557 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b; 558 IS isicol; 559 PetscErrorCode ierr; 560 const PetscInt *r,*ic,*ai = a->i,*aj = a->j,*xi; 561 PetscInt prow,n = a->mbs,*ainew,*ajnew,jmax,*fill,nz,*im,*ajfill,*flev,*xitmp; 562 PetscInt *dloc,idx,row,m,fm,nzf,nzi,reallocate = 0,dcount = 0; 563 PetscInt incrlev,nnz,i,bs = A->rmap->bs,bs2 = a->bs2,levels,diagonal_fill,dd; 564 PetscBool col_identity,row_identity,both_identity,flg; 565 PetscReal f; 566 567 PetscFunctionBegin; 568 ierr = MatMissingDiagonal_SeqBAIJ(A,&flg,&dd);CHKERRQ(ierr); 569 if (flg) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix A is missing diagonal entry in row %D",dd); 570 571 f = info->fill; 572 levels = (PetscInt)info->levels; 573 diagonal_fill = (PetscInt)info->diagonal_fill; 574 575 ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr); 576 577 ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr); 578 ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr); 579 both_identity = (PetscBool) (row_identity && col_identity); 580 581 if (!levels && both_identity) { /* special case copy the nonzero structure */ 582 ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 583 ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr); 584 585 fact->factortype = MAT_FACTOR_ILU; 586 b = (Mat_SeqBAIJ*)fact->data; 587 b->row = isrow; 588 b->col = iscol; 589 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 590 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 591 b->icol = isicol; 592 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 593 594 ierr = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr); 595 PetscFunctionReturn(0); 596 } 597 598 /* general case perform the symbolic factorization */ 599 ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr); 600 ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr); 601 602 /* get new row pointers */ 603 ierr = PetscMalloc1(n+1,&ainew);CHKERRQ(ierr); 604 ainew[0] = 0; 605 /* don't know how many column pointers are needed so estimate */ 606 jmax = (PetscInt)(f*ai[n] + 1); 607 ierr = PetscMalloc1(jmax,&ajnew);CHKERRQ(ierr); 608 /* ajfill is level of fill for each fill entry */ 609 ierr = PetscMalloc1(jmax,&ajfill);CHKERRQ(ierr); 610 /* fill is a linked list of nonzeros in active row */ 611 ierr = PetscMalloc1(n+1,&fill);CHKERRQ(ierr); 612 /* im is level for each filled value */ 613 ierr = PetscMalloc1(n+1,&im);CHKERRQ(ierr); 614 /* dloc is location of diagonal in factor */ 615 ierr = PetscMalloc1(n+1,&dloc);CHKERRQ(ierr); 616 dloc[0] = 0; 617 for (prow=0; prow<n; prow++) { 618 619 /* copy prow into linked list */ 620 nzf = nz = ai[r[prow]+1] - ai[r[prow]]; 621 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); 622 xi = aj + ai[r[prow]]; 623 fill[n] = n; 624 fill[prow] = -1; /* marker for diagonal entry */ 625 while (nz--) { 626 fm = n; 627 idx = ic[*xi++]; 628 do { 629 m = fm; 630 fm = fill[m]; 631 } while (fm < idx); 632 fill[m] = idx; 633 fill[idx] = fm; 634 im[idx] = 0; 635 } 636 637 /* make sure diagonal entry is included */ 638 if (diagonal_fill && fill[prow] == -1) { 639 fm = n; 640 while (fill[fm] < prow) fm = fill[fm]; 641 fill[prow] = fill[fm]; /* insert diagonal into linked list */ 642 fill[fm] = prow; 643 im[prow] = 0; 644 nzf++; 645 dcount++; 646 } 647 648 nzi = 0; 649 row = fill[n]; 650 while (row < prow) { 651 incrlev = im[row] + 1; 652 nz = dloc[row]; 653 xi = ajnew + ainew[row] + nz + 1; 654 flev = ajfill + ainew[row] + nz + 1; 655 nnz = ainew[row+1] - ainew[row] - nz - 1; 656 fm = row; 657 while (nnz-- > 0) { 658 idx = *xi++; 659 if (*flev + incrlev > levels) { 660 flev++; 661 continue; 662 } 663 do { 664 m = fm; 665 fm = fill[m]; 666 } while (fm < idx); 667 if (fm != idx) { 668 im[idx] = *flev + incrlev; 669 fill[m] = idx; 670 fill[idx] = fm; 671 fm = idx; 672 nzf++; 673 } else if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev; 674 flev++; 675 } 676 row = fill[row]; 677 nzi++; 678 } 679 /* copy new filled row into permanent storage */ 680 ainew[prow+1] = ainew[prow] + nzf; 681 if (ainew[prow+1] > jmax) { 682 683 /* estimate how much additional space we will need */ 684 /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */ 685 /* just double the memory each time */ 686 PetscInt maxadd = jmax; 687 /* maxadd = (int)(((f*ai[n]+1)*(n-prow+5))/n); */ 688 if (maxadd < nzf) maxadd = (n-prow)*(nzf+1); 689 jmax += maxadd; 690 691 /* allocate a longer ajnew and ajfill */ 692 ierr = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr); 693 ierr = PetscMemcpy(xitmp,ajnew,ainew[prow]*sizeof(PetscInt));CHKERRQ(ierr); 694 ierr = PetscFree(ajnew);CHKERRQ(ierr); 695 ajnew = xitmp; 696 ierr = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr); 697 ierr = PetscMemcpy(xitmp,ajfill,ainew[prow]*sizeof(PetscInt));CHKERRQ(ierr); 698 ierr = PetscFree(ajfill);CHKERRQ(ierr); 699 ajfill = xitmp; 700 reallocate++; /* count how many reallocations are needed */ 701 } 702 xitmp = ajnew + ainew[prow]; 703 flev = ajfill + ainew[prow]; 704 dloc[prow] = nzi; 705 fm = fill[n]; 706 while (nzf--) { 707 *xitmp++ = fm; 708 *flev++ = im[fm]; 709 fm = fill[fm]; 710 } 711 /* make sure row has diagonal entry */ 712 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\ 713 try running with -pc_factor_nonzeros_along_diagonal or -pc_factor_diagonal_fill",prow); 714 } 715 ierr = PetscFree(ajfill);CHKERRQ(ierr); 716 ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr); 717 ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr); 718 ierr = PetscFree(fill);CHKERRQ(ierr); 719 ierr = PetscFree(im);CHKERRQ(ierr); 720 721 #if defined(PETSC_USE_INFO) 722 { 723 PetscReal af = ((PetscReal)ainew[n])/((PetscReal)ai[n]); 724 ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocate,(double)f,(double)af);CHKERRQ(ierr); 725 ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr); 726 ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g);\n",(double)af);CHKERRQ(ierr); 727 ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr); 728 if (diagonal_fill) { 729 ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr); 730 } 731 } 732 #endif 733 734 /* put together the new matrix */ 735 ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 736 ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr); 737 b = (Mat_SeqBAIJ*)fact->data; 738 739 b->free_a = PETSC_TRUE; 740 b->free_ij = PETSC_TRUE; 741 b->singlemalloc = PETSC_FALSE; 742 743 ierr = PetscMalloc1(bs2*ainew[n],&b->a);CHKERRQ(ierr); 744 745 b->j = ajnew; 746 b->i = ainew; 747 for (i=0; i<n; i++) dloc[i] += ainew[i]; 748 b->diag = dloc; 749 b->free_diag = PETSC_TRUE; 750 b->ilen = 0; 751 b->imax = 0; 752 b->row = isrow; 753 b->col = iscol; 754 b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE; 755 756 ierr = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr); 757 ierr = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr); 758 b->icol = isicol; 759 ierr = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr); 760 /* In b structure: Free imax, ilen, old a, old j. 761 Allocate dloc, solve_work, new a, new j */ 762 ierr = PetscLogObjectMemory((PetscObject)fact,(ainew[n]-n)*(sizeof(PetscInt))+bs2*ainew[n]*sizeof(PetscScalar));CHKERRQ(ierr); 763 b->maxnz = b->nz = ainew[n]; 764 765 fact->info.factor_mallocs = reallocate; 766 fact->info.fill_ratio_given = f; 767 fact->info.fill_ratio_needed = ((PetscReal)ainew[n])/((PetscReal)ai[prow]); 768 769 ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr); 770 PetscFunctionReturn(0); 771 } 772 773 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE(Mat A) 774 { 775 /* Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; */ 776 /* int i,*AJ=a->j,nz=a->nz; */ 777 778 PetscFunctionBegin; 779 /* Undo Column scaling */ 780 /* while (nz--) { */ 781 /* AJ[i] = AJ[i]/4; */ 782 /* } */ 783 /* This should really invoke a push/pop logic, but we don't have that yet. */ 784 A->ops->setunfactored = NULL; 785 PetscFunctionReturn(0); 786 } 787 788 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE_usj(Mat A) 789 { 790 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 791 PetscInt *AJ=a->j,nz=a->nz; 792 unsigned short *aj=(unsigned short*)AJ; 793 794 PetscFunctionBegin; 795 /* Is this really necessary? */ 796 while (nz--) { 797 AJ[nz] = (int)((unsigned int)aj[nz]); /* First extend, then convert to signed. */ 798 } 799 A->ops->setunfactored = NULL; 800 PetscFunctionReturn(0); 801 } 802 803 804