1 2 /* -------------------------------------------------------------------- 3 4 This file implements a subclass of the SeqAIJ matrix class that uses 5 the SuperLU sparse solver. 6 */ 7 8 /* 9 Defines the data structure for the base matrix type (SeqAIJ) 10 */ 11 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 12 13 /* 14 SuperLU include files 15 */ 16 EXTERN_C_BEGIN 17 #if defined(PETSC_USE_COMPLEX) 18 #if defined(PETSC_USE_REAL_SINGLE) 19 #include <slu_cdefs.h> 20 #else 21 #include <slu_zdefs.h> 22 #endif 23 #else 24 #if defined(PETSC_USE_REAL_SINGLE) 25 #include <slu_sdefs.h> 26 #else 27 #include <slu_ddefs.h> 28 #endif 29 #endif 30 #include <slu_util.h> 31 EXTERN_C_END 32 33 /* 34 This is the data we are "ADDING" to the SeqAIJ matrix type to get the SuperLU matrix type 35 */ 36 typedef struct { 37 SuperMatrix A,L,U,B,X; 38 superlu_options_t options; 39 PetscInt *perm_c; /* column permutation vector */ 40 PetscInt *perm_r; /* row permutations from partial pivoting */ 41 PetscInt *etree; 42 PetscReal *R, *C; 43 char equed[1]; 44 PetscInt lwork; 45 void *work; 46 PetscReal rpg, rcond; 47 mem_usage_t mem_usage; 48 MatStructure flg; 49 SuperLUStat_t stat; 50 Mat A_dup; 51 PetscScalar *rhs_dup; 52 GlobalLU_t Glu; 53 54 /* Flag to clean up (non-global) SuperLU objects during Destroy */ 55 PetscBool CleanUpSuperLU; 56 } Mat_SuperLU; 57 58 extern PetscErrorCode MatFactorInfo_SuperLU(Mat,PetscViewer); 59 extern PetscErrorCode MatLUFactorNumeric_SuperLU(Mat,Mat,const MatFactorInfo*); 60 extern PetscErrorCode MatDestroy_SuperLU(Mat); 61 extern PetscErrorCode MatView_SuperLU(Mat,PetscViewer); 62 extern PetscErrorCode MatAssemblyEnd_SuperLU(Mat,MatAssemblyType); 63 extern PetscErrorCode MatSolve_SuperLU(Mat,Vec,Vec); 64 extern PetscErrorCode MatMatSolve_SuperLU(Mat,Mat,Mat); 65 extern PetscErrorCode MatSolveTranspose_SuperLU(Mat,Vec,Vec); 66 extern PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat,Mat,IS,IS,const MatFactorInfo*); 67 extern PetscErrorCode MatDuplicate_SuperLU(Mat, MatDuplicateOption, Mat*); 68 69 /* 70 Utility function 71 */ 72 #undef __FUNCT__ 73 #define __FUNCT__ "MatFactorInfo_SuperLU" 74 PetscErrorCode MatFactorInfo_SuperLU(Mat A,PetscViewer viewer) 75 { 76 Mat_SuperLU *lu= (Mat_SuperLU*)A->spptr; 77 PetscErrorCode ierr; 78 superlu_options_t options; 79 80 PetscFunctionBegin; 81 /* check if matrix is superlu_dist type */ 82 if (A->ops->solve != MatSolve_SuperLU) PetscFunctionReturn(0); 83 84 options = lu->options; 85 86 ierr = PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");CHKERRQ(ierr); 87 ierr = PetscViewerASCIIPrintf(viewer," Equil: %s\n",(options.Equil != NO) ? "YES" : "NO");CHKERRQ(ierr); 88 ierr = PetscViewerASCIIPrintf(viewer," ColPerm: %D\n",options.ColPerm);CHKERRQ(ierr); 89 ierr = PetscViewerASCIIPrintf(viewer," IterRefine: %D\n",options.IterRefine);CHKERRQ(ierr); 90 ierr = PetscViewerASCIIPrintf(viewer," SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES" : "NO");CHKERRQ(ierr); 91 ierr = PetscViewerASCIIPrintf(viewer," DiagPivotThresh: %g\n",options.DiagPivotThresh);CHKERRQ(ierr); 92 ierr = PetscViewerASCIIPrintf(viewer," PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES" : "NO");CHKERRQ(ierr); 93 ierr = PetscViewerASCIIPrintf(viewer," ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES" : "NO");CHKERRQ(ierr); 94 ierr = PetscViewerASCIIPrintf(viewer," RowPerm: %D\n",options.RowPerm);CHKERRQ(ierr); 95 ierr = PetscViewerASCIIPrintf(viewer," ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES" : "NO");CHKERRQ(ierr); 96 ierr = PetscViewerASCIIPrintf(viewer," PrintStat: %s\n",(options.PrintStat != NO) ? "YES" : "NO");CHKERRQ(ierr); 97 ierr = PetscViewerASCIIPrintf(viewer," lwork: %D\n",lu->lwork);CHKERRQ(ierr); 98 if (A->factortype == MAT_FACTOR_ILU) { 99 ierr = PetscViewerASCIIPrintf(viewer," ILU_DropTol: %g\n",options.ILU_DropTol);CHKERRQ(ierr); 100 ierr = PetscViewerASCIIPrintf(viewer," ILU_FillTol: %g\n",options.ILU_FillTol);CHKERRQ(ierr); 101 ierr = PetscViewerASCIIPrintf(viewer," ILU_FillFactor: %g\n",options.ILU_FillFactor);CHKERRQ(ierr); 102 ierr = PetscViewerASCIIPrintf(viewer," ILU_DropRule: %D\n",options.ILU_DropRule);CHKERRQ(ierr); 103 ierr = PetscViewerASCIIPrintf(viewer," ILU_Norm: %D\n",options.ILU_Norm);CHKERRQ(ierr); 104 ierr = PetscViewerASCIIPrintf(viewer," ILU_MILU: %D\n",options.ILU_MILU);CHKERRQ(ierr); 105 } 106 PetscFunctionReturn(0); 107 } 108 109 /* 110 These are the methods provided to REPLACE the corresponding methods of the 111 SeqAIJ matrix class. Other methods of SeqAIJ are not replaced 112 */ 113 #undef __FUNCT__ 114 #define __FUNCT__ "MatLUFactorNumeric_SuperLU" 115 PetscErrorCode MatLUFactorNumeric_SuperLU(Mat F,Mat A,const MatFactorInfo *info) 116 { 117 Mat_SuperLU *lu = (Mat_SuperLU*)F->spptr; 118 Mat_SeqAIJ *aa; 119 PetscErrorCode ierr; 120 PetscInt sinfo; 121 PetscReal ferr, berr; 122 NCformat *Ustore; 123 SCformat *Lstore; 124 125 PetscFunctionBegin; 126 if (lu->flg == SAME_NONZERO_PATTERN) { /* successing numerical factorization */ 127 lu->options.Fact = SamePattern; 128 /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */ 129 Destroy_SuperMatrix_Store(&lu->A); 130 if (lu->options.Equil) { 131 ierr = MatCopy_SeqAIJ(A,lu->A_dup,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 132 } 133 if (lu->lwork >= 0) { 134 PetscStackCall("SuperLU:Destroy_SuperNode_Matrix",Destroy_SuperNode_Matrix(&lu->L)); 135 PetscStackCall("SuperLU:Destroy_CompCol_Matrix",Destroy_CompCol_Matrix(&lu->U)); 136 lu->options.Fact = SamePattern; 137 } 138 } 139 140 /* Create the SuperMatrix for lu->A=A^T: 141 Since SuperLU likes column-oriented matrices,we pass it the transpose, 142 and then solve A^T X = B in MatSolve(). */ 143 if (lu->options.Equil) { 144 aa = (Mat_SeqAIJ*)(lu->A_dup)->data; 145 } else { 146 aa = (Mat_SeqAIJ*)(A)->data; 147 } 148 #if defined(PETSC_USE_COMPLEX) 149 #if defined(PETSC_USE_REAL_SINGLE) 150 PetscStackCall("SuperLU:cCreate_CompCol_Matrix",cCreate_CompCol_Matrix(&lu->A,A->cmap->n,A->rmap->n,aa->nz,(singlecomplex*)aa->a,aa->j,aa->i,SLU_NC,SLU_C,SLU_GE)); 151 #else 152 PetscStackCall("SuperLU:zCreate_CompCol_Matrix",zCreate_CompCol_Matrix(&lu->A,A->cmap->n,A->rmap->n,aa->nz,(doublecomplex*)aa->a,aa->j,aa->i,SLU_NC,SLU_Z,SLU_GE)); 153 #endif 154 #else 155 #if defined(PETSC_USE_REAL_SINGLE) 156 PetscStackCall("SuperLU:sCreate_CompCol_Matrix",sCreate_CompCol_Matrix(&lu->A,A->cmap->n,A->rmap->n,aa->nz,aa->a,aa->j,aa->i,SLU_NC,SLU_S,SLU_GE)); 157 #else 158 PetscStackCall("SuperLU:dCreate_CompCol_Matrix",dCreate_CompCol_Matrix(&lu->A,A->cmap->n,A->rmap->n,aa->nz,aa->a,aa->j,aa->i,SLU_NC,SLU_D,SLU_GE)); 159 #endif 160 #endif 161 162 /* Numerical factorization */ 163 lu->B.ncol = 0; /* Indicate not to solve the system */ 164 if (F->factortype == MAT_FACTOR_LU) { 165 #if defined(PETSC_USE_COMPLEX) 166 #if defined(PETSC_USE_REAL_SINGLE) 167 PetscStackCall("SuperLU:cgssvx",cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 168 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 169 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 170 #else 171 PetscStackCall("SuperLU:zgssvx",zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 172 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 173 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 174 #endif 175 #else 176 #if defined(PETSC_USE_REAL_SINGLE) 177 PetscStackCall("SuperLU:sgssvx",sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 178 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 179 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 180 #else 181 PetscStackCall("SuperLU:dgssvx",dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 182 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 183 &lu->Glu,&lu->mem_usage, &lu->stat, &sinfo)); 184 #endif 185 #endif 186 } else if (F->factortype == MAT_FACTOR_ILU) { 187 /* Compute the incomplete factorization, condition number and pivot growth */ 188 #if defined(PETSC_USE_COMPLEX) 189 #if defined(PETSC_USE_REAL_SINGLE) 190 PetscStackCall("SuperLU:cgsisx",cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r,lu->etree, lu->equed, lu->R, lu->C, 191 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 192 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 193 #else 194 PetscStackCall("SuperLU:zgsisx",zgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r,lu->etree, lu->equed, lu->R, lu->C, 195 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 196 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 197 #endif 198 #else 199 #if defined(PETSC_USE_REAL_SINGLE) 200 PetscStackCall("SuperLU:sgsisx",sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 201 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 202 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 203 #else 204 PetscStackCall("SuperLU:dgsisx",dgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 205 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 206 &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo)); 207 #endif 208 #endif 209 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported"); 210 if (!sinfo || sinfo == lu->A.ncol+1) { 211 if (lu->options.PivotGrowth) { 212 ierr = PetscPrintf(PETSC_COMM_SELF," Recip. pivot growth = %e\n", lu->rpg);CHKERRQ(ierr); 213 } 214 if (lu->options.ConditionNumber) { 215 ierr = PetscPrintf(PETSC_COMM_SELF," Recip. condition number = %e\n", lu->rcond);CHKERRQ(ierr); 216 } 217 } else if (sinfo > 0) { 218 if (A->erroriffailure) { 219 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot in row %D",sinfo); 220 } else { 221 if (sinfo <= lu->A.ncol) { 222 if (lu->options.ILU_FillTol == 0.0) { 223 F->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 224 } 225 ierr = PetscInfo2(F,"Number of zero pivots %D, ILU_FillTol %g\n",sinfo,lu->options.ILU_FillTol);CHKERRQ(ierr); 226 } else if (sinfo == lu->A.ncol + 1) { 227 /* 228 U is nonsingular, but RCOND is less than machine 229 precision, meaning that the matrix is singular to 230 working precision. Nevertheless, the solution and 231 error bounds are computed because there are a number 232 of situations where the computed solution can be more 233 accurate than the value of RCOND would suggest. 234 */ 235 ierr = PetscInfo1(F,"Matrix factor U is nonsingular, but is singular to working precision. The solution is computed. info %D",sinfo);CHKERRQ(ierr); 236 } else { /* sinfo > lu->A.ncol + 1 */ 237 F->errortype = MAT_FACTOR_OUTMEMORY; 238 ierr = PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);CHKERRQ(ierr); 239 } 240 } 241 } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", sinfo,-sinfo); 242 243 if (lu->options.PrintStat) { 244 ierr = PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n");CHKERRQ(ierr); 245 PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat)); 246 Lstore = (SCformat*) lu->L.Store; 247 Ustore = (NCformat*) lu->U.Store; 248 ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in factor L = %D\n", Lstore->nnz); 249 ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in factor U = %D\n", Ustore->nnz); 250 ierr = PetscPrintf(PETSC_COMM_SELF," No of nonzeros in L+U = %D\n", Lstore->nnz + Ustore->nnz - lu->A.ncol); 251 ierr = PetscPrintf(PETSC_COMM_SELF," L\\U MB %.3f\ttotal MB needed %.3f\n", 252 lu->mem_usage.for_lu/1e6, lu->mem_usage.total_needed/1e6); 253 } 254 255 lu->flg = SAME_NONZERO_PATTERN; 256 F->ops->solve = MatSolve_SuperLU; 257 F->ops->solvetranspose = MatSolveTranspose_SuperLU; 258 F->ops->matsolve = NULL; 259 PetscFunctionReturn(0); 260 } 261 262 #undef __FUNCT__ 263 #define __FUNCT__ "MatGetDiagonal_SuperLU" 264 PetscErrorCode MatGetDiagonal_SuperLU(Mat A,Vec v) 265 { 266 PetscFunctionBegin; 267 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Mat type: SuperLU factor"); 268 PetscFunctionReturn(0); 269 } 270 271 #undef __FUNCT__ 272 #define __FUNCT__ "MatDestroy_SuperLU" 273 PetscErrorCode MatDestroy_SuperLU(Mat A) 274 { 275 PetscErrorCode ierr; 276 Mat_SuperLU *lu=(Mat_SuperLU*)A->spptr; 277 278 PetscFunctionBegin; 279 if (lu && lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */ 280 PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->A)); 281 PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->B)); 282 PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->X)); 283 PetscStackCall("SuperLU:StatFree",StatFree(&lu->stat)); 284 if (lu->lwork >= 0) { 285 PetscStackCall("SuperLU:Destroy_SuperNode_Matrix",Destroy_SuperNode_Matrix(&lu->L)); 286 PetscStackCall("SuperLU:Destroy_CompCol_Matrix",Destroy_CompCol_Matrix(&lu->U)); 287 } 288 } 289 if (lu) { 290 ierr = PetscFree(lu->etree);CHKERRQ(ierr); 291 ierr = PetscFree(lu->perm_r);CHKERRQ(ierr); 292 ierr = PetscFree(lu->perm_c);CHKERRQ(ierr); 293 ierr = PetscFree(lu->R);CHKERRQ(ierr); 294 ierr = PetscFree(lu->C);CHKERRQ(ierr); 295 ierr = PetscFree(lu->rhs_dup);CHKERRQ(ierr); 296 ierr = MatDestroy(&lu->A_dup);CHKERRQ(ierr); 297 } 298 ierr = PetscFree(A->spptr);CHKERRQ(ierr); 299 300 /* clear composed functions */ 301 ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr); 302 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSuperluSetILUDropTol_C",NULL);CHKERRQ(ierr); 303 304 ierr = MatDestroy_SeqAIJ(A);CHKERRQ(ierr); 305 PetscFunctionReturn(0); 306 } 307 308 #undef __FUNCT__ 309 #define __FUNCT__ "MatView_SuperLU" 310 PetscErrorCode MatView_SuperLU(Mat A,PetscViewer viewer) 311 { 312 PetscErrorCode ierr; 313 PetscBool iascii; 314 PetscViewerFormat format; 315 316 PetscFunctionBegin; 317 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 318 if (iascii) { 319 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 320 if (format == PETSC_VIEWER_ASCII_INFO) { 321 ierr = MatFactorInfo_SuperLU(A,viewer);CHKERRQ(ierr); 322 } 323 } 324 PetscFunctionReturn(0); 325 } 326 327 328 #undef __FUNCT__ 329 #define __FUNCT__ "MatSolve_SuperLU_Private" 330 PetscErrorCode MatSolve_SuperLU_Private(Mat A,Vec b,Vec x) 331 { 332 Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; 333 const PetscScalar *barray; 334 PetscScalar *xarray; 335 PetscErrorCode ierr; 336 PetscInt info,i,n; 337 PetscReal ferr,berr; 338 static PetscBool cite = PETSC_FALSE; 339 340 PetscFunctionBegin; 341 if (lu->lwork == -1) PetscFunctionReturn(0); 342 ierr = PetscCitationsRegister("@article{superlu99,\n author = {James W. Demmel and Stanley C. Eisenstat and\n John R. Gilbert and Xiaoye S. Li and Joseph W. H. Liu},\n title = {A supernodal approach to sparse partial pivoting},\n journal = {SIAM J. Matrix Analysis and Applications},\n year = {1999},\n volume = {20},\n number = {3},\n pages = {720-755}\n}\n",&cite);CHKERRQ(ierr); 343 344 ierr = VecGetLocalSize(x,&n);CHKERRQ(ierr); 345 lu->B.ncol = 1; /* Set the number of right-hand side */ 346 if (lu->options.Equil && !lu->rhs_dup) { 347 /* superlu overwrites b when Equil is used, thus create rhs_dup to keep user's b unchanged */ 348 ierr = PetscMalloc1(n,&lu->rhs_dup);CHKERRQ(ierr); 349 } 350 if (lu->options.Equil) { 351 /* Copy b into rsh_dup */ 352 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 353 ierr = PetscMemcpy(lu->rhs_dup,barray,n*sizeof(PetscScalar));CHKERRQ(ierr); 354 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 355 barray = lu->rhs_dup; 356 } else { 357 ierr = VecGetArrayRead(b,&barray);CHKERRQ(ierr); 358 } 359 ierr = VecGetArray(x,&xarray);CHKERRQ(ierr); 360 361 #if defined(PETSC_USE_COMPLEX) 362 #if defined(PETSC_USE_REAL_SINGLE) 363 ((DNformat*)lu->B.Store)->nzval = (singlecomplex*)barray; 364 ((DNformat*)lu->X.Store)->nzval = (singlecomplex*)xarray; 365 #else 366 ((DNformat*)lu->B.Store)->nzval = (doublecomplex*)barray; 367 ((DNformat*)lu->X.Store)->nzval = (doublecomplex*)xarray; 368 #endif 369 #else 370 ((DNformat*)lu->B.Store)->nzval = (void*)barray; 371 ((DNformat*)lu->X.Store)->nzval = xarray; 372 #endif 373 374 lu->options.Fact = FACTORED; /* Indicate the factored form of A is supplied. */ 375 if (A->factortype == MAT_FACTOR_LU) { 376 #if defined(PETSC_USE_COMPLEX) 377 #if defined(PETSC_USE_REAL_SINGLE) 378 PetscStackCall("SuperLU:cgssvx",cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 379 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 380 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 381 #else 382 PetscStackCall("SuperLU:zgssvx",zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 383 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 384 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 385 #endif 386 #else 387 #if defined(PETSC_USE_REAL_SINGLE) 388 PetscStackCall("SuperLU:sgssvx",sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 389 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 390 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 391 #else 392 PetscStackCall("SuperLU:dgssvx",dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 393 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, 394 &lu->Glu,&lu->mem_usage, &lu->stat, &info)); 395 #endif 396 #endif 397 } else if (A->factortype == MAT_FACTOR_ILU) { 398 #if defined(PETSC_USE_COMPLEX) 399 #if defined(PETSC_USE_REAL_SINGLE) 400 PetscStackCall("SuperLU:cgsisx",cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 401 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 402 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 403 #else 404 PetscStackCall("SuperLU:zgsisx",zgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 405 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 406 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 407 #endif 408 #else 409 #if defined(PETSC_USE_REAL_SINGLE) 410 PetscStackCall("SuperLU:sgsisx",sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 411 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 412 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 413 #else 414 PetscStackCall("SuperLU:dgsisx",dgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, 415 &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, 416 &lu->Glu, &lu->mem_usage, &lu->stat, &info)); 417 #endif 418 #endif 419 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported"); 420 if (!lu->options.Equil) { 421 ierr = VecRestoreArrayRead(b,&barray);CHKERRQ(ierr); 422 } 423 ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr); 424 425 if (!info || info == lu->A.ncol+1) { 426 if (lu->options.IterRefine) { 427 ierr = PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n"); 428 ierr = PetscPrintf(PETSC_COMM_SELF," %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR"); 429 for (i = 0; i < 1; ++i) { 430 ierr = PetscPrintf(PETSC_COMM_SELF," %8d%8d%16e%16e\n", i+1, lu->stat.RefineSteps, ferr, berr); 431 } 432 } 433 } else if (info > 0) { 434 if (lu->lwork == -1) { 435 ierr = PetscPrintf(PETSC_COMM_SELF," ** Estimated memory: %D bytes\n", info - lu->A.ncol); 436 } else { 437 ierr = PetscPrintf(PETSC_COMM_SELF," Warning: gssvx() returns info %D\n",info); 438 } 439 } else if (info < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", info,-info); 440 441 if (lu->options.PrintStat) { 442 ierr = PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n"); 443 PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat)); 444 } 445 PetscFunctionReturn(0); 446 } 447 448 #undef __FUNCT__ 449 #define __FUNCT__ "MatSolve_SuperLU" 450 PetscErrorCode MatSolve_SuperLU(Mat A,Vec b,Vec x) 451 { 452 Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; 453 PetscErrorCode ierr; 454 455 PetscFunctionBegin; 456 if (A->errortype) { 457 ierr = PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");CHKERRQ(ierr); 458 ierr = VecSetInf(x);CHKERRQ(ierr); 459 PetscFunctionReturn(0); 460 } 461 462 lu->options.Trans = TRANS; 463 ierr = MatSolve_SuperLU_Private(A,b,x);CHKERRQ(ierr); 464 PetscFunctionReturn(0); 465 } 466 467 #undef __FUNCT__ 468 #define __FUNCT__ "MatSolveTranspose_SuperLU" 469 PetscErrorCode MatSolveTranspose_SuperLU(Mat A,Vec b,Vec x) 470 { 471 Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; 472 PetscErrorCode ierr; 473 474 PetscFunctionBegin; 475 if (A->errortype) { 476 ierr = PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");CHKERRQ(ierr); 477 ierr = VecSetInf(x);CHKERRQ(ierr); 478 PetscFunctionReturn(0); 479 } 480 481 lu->options.Trans = NOTRANS; 482 ierr = MatSolve_SuperLU_Private(A,b,x);CHKERRQ(ierr); 483 PetscFunctionReturn(0); 484 } 485 486 #undef __FUNCT__ 487 #define __FUNCT__ "MatMatSolve_SuperLU" 488 PetscErrorCode MatMatSolve_SuperLU(Mat A,Mat B,Mat X) 489 { 490 Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr; 491 PetscBool flg; 492 PetscErrorCode ierr; 493 494 PetscFunctionBegin; 495 ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 496 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 497 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 498 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 499 lu->options.Trans = TRANS; 500 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatMatSolve_SuperLU() is not implemented yet"); 501 PetscFunctionReturn(0); 502 } 503 504 /* 505 Note the r permutation is ignored 506 */ 507 #undef __FUNCT__ 508 #define __FUNCT__ "MatLUFactorSymbolic_SuperLU" 509 PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) 510 { 511 Mat_SuperLU *lu = (Mat_SuperLU*)(F->spptr); 512 513 PetscFunctionBegin; 514 lu->flg = DIFFERENT_NONZERO_PATTERN; 515 lu->CleanUpSuperLU = PETSC_TRUE; 516 F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU; 517 PetscFunctionReturn(0); 518 } 519 520 #undef __FUNCT__ 521 #define __FUNCT__ "MatSuperluSetILUDropTol_SuperLU" 522 static PetscErrorCode MatSuperluSetILUDropTol_SuperLU(Mat F,PetscReal dtol) 523 { 524 Mat_SuperLU *lu= (Mat_SuperLU*)F->spptr; 525 526 PetscFunctionBegin; 527 lu->options.ILU_DropTol = dtol; 528 PetscFunctionReturn(0); 529 } 530 531 #undef __FUNCT__ 532 #define __FUNCT__ "MatSuperluSetILUDropTol" 533 /*@ 534 MatSuperluSetILUDropTol - Set SuperLU ILU drop tolerance 535 Logically Collective on Mat 536 537 Input Parameters: 538 + F - the factored matrix obtained by calling MatGetFactor() from PETSc-SuperLU interface 539 - dtol - drop tolerance 540 541 Options Database: 542 . -mat_superlu_ilu_droptol <dtol> 543 544 Level: beginner 545 546 References: 547 . SuperLU Users' Guide 548 549 .seealso: MatGetFactor() 550 @*/ 551 PetscErrorCode MatSuperluSetILUDropTol(Mat F,PetscReal dtol) 552 { 553 PetscErrorCode ierr; 554 555 PetscFunctionBegin; 556 PetscValidHeaderSpecific(F,MAT_CLASSID,1); 557 PetscValidLogicalCollectiveReal(F,dtol,2); 558 ierr = PetscTryMethod(F,"MatSuperluSetILUDropTol_C",(Mat,PetscReal),(F,dtol));CHKERRQ(ierr); 559 PetscFunctionReturn(0); 560 } 561 562 #undef __FUNCT__ 563 #define __FUNCT__ "MatFactorGetSolverPackage_seqaij_superlu" 564 PetscErrorCode MatFactorGetSolverPackage_seqaij_superlu(Mat A,const MatSolverPackage *type) 565 { 566 PetscFunctionBegin; 567 *type = MATSOLVERSUPERLU; 568 PetscFunctionReturn(0); 569 } 570 571 572 /*MC 573 MATSOLVERSUPERLU = "superlu" - A solver package providing solvers LU and ILU for sequential matrices 574 via the external package SuperLU. 575 576 Use ./configure --download-superlu to have PETSc installed with SuperLU 577 578 Use -pc_type lu -pc_factor_mat_solver_package superlu to us this direct solver 579 580 Options Database Keys: 581 + -mat_superlu_equil <FALSE> - Equil (None) 582 . -mat_superlu_colperm <COLAMD> - (choose one of) NATURAL MMD_ATA MMD_AT_PLUS_A COLAMD 583 . -mat_superlu_iterrefine <NOREFINE> - (choose one of) NOREFINE SINGLE DOUBLE EXTRA 584 . -mat_superlu_symmetricmode: <FALSE> - SymmetricMode (None) 585 . -mat_superlu_diagpivotthresh <1> - DiagPivotThresh (None) 586 . -mat_superlu_pivotgrowth <FALSE> - PivotGrowth (None) 587 . -mat_superlu_conditionnumber <FALSE> - ConditionNumber (None) 588 . -mat_superlu_rowperm <NOROWPERM> - (choose one of) NOROWPERM LargeDiag 589 . -mat_superlu_replacetinypivot <FALSE> - ReplaceTinyPivot (None) 590 . -mat_superlu_printstat <FALSE> - PrintStat (None) 591 . -mat_superlu_lwork <0> - size of work array in bytes used by factorization (None) 592 . -mat_superlu_ilu_droptol <0> - ILU_DropTol (None) 593 . -mat_superlu_ilu_filltol <0> - ILU_FillTol (None) 594 . -mat_superlu_ilu_fillfactor <0> - ILU_FillFactor (None) 595 . -mat_superlu_ilu_droprull <0> - ILU_DropRule (None) 596 . -mat_superlu_ilu_norm <0> - ILU_Norm (None) 597 - -mat_superlu_ilu_milu <0> - ILU_MILU (None) 598 599 Notes: Do not confuse this with MATSOLVERSUPERLU_DIST which is for parallel sparse solves 600 601 Level: beginner 602 603 .seealso: PCLU, PCILU, MATSOLVERSUPERLU_DIST, MATSOLVERMUMPS, PCFactorSetMatSolverPackage(), MatSolverPackage 604 M*/ 605 606 #undef __FUNCT__ 607 #define __FUNCT__ "MatGetFactor_seqaij_superlu" 608 static PetscErrorCode MatGetFactor_seqaij_superlu(Mat A,MatFactorType ftype,Mat *F) 609 { 610 Mat B; 611 Mat_SuperLU *lu; 612 PetscErrorCode ierr; 613 PetscInt indx,m=A->rmap->n,n=A->cmap->n; 614 PetscBool flg,set; 615 PetscReal real_input; 616 const char *colperm[] ={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */ 617 const char *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"}; 618 const char *rowperm[] ={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */ 619 620 PetscFunctionBegin; 621 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 622 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 623 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 624 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 625 626 if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU) { 627 B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU; 628 B->ops->ilufactorsymbolic = MatLUFactorSymbolic_SuperLU; 629 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported"); 630 631 B->ops->destroy = MatDestroy_SuperLU; 632 B->ops->view = MatView_SuperLU; 633 B->ops->getdiagonal = MatGetDiagonal_SuperLU; 634 B->factortype = ftype; 635 B->assembled = PETSC_TRUE; /* required by -ksp_view */ 636 B->preallocated = PETSC_TRUE; 637 638 ierr = PetscNewLog(B,&lu);CHKERRQ(ierr); 639 640 if (ftype == MAT_FACTOR_LU) { 641 set_default_options(&lu->options); 642 /* Comments from SuperLU_4.0/SRC/dgssvx.c: 643 "Whether or not the system will be equilibrated depends on the 644 scaling of the matrix A, but if equilibration is used, A is 645 overwritten by diag(R)*A*diag(C) and B by diag(R)*B 646 (if options->Trans=NOTRANS) or diag(C)*B (if options->Trans = TRANS or CONJ)." 647 We set 'options.Equil = NO' as default because additional space is needed for it. 648 */ 649 lu->options.Equil = NO; 650 } else if (ftype == MAT_FACTOR_ILU) { 651 /* Set the default input options of ilu: */ 652 PetscStackCall("SuperLU:ilu_set_default_options",ilu_set_default_options(&lu->options)); 653 } 654 lu->options.PrintStat = NO; 655 656 /* Initialize the statistics variables. */ 657 PetscStackCall("SuperLU:StatInit",StatInit(&lu->stat)); 658 lu->lwork = 0; /* allocate space internally by system malloc */ 659 660 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU Options","Mat");CHKERRQ(ierr); 661 ierr = PetscOptionsBool("-mat_superlu_equil","Equil","None",(PetscBool)lu->options.Equil,(PetscBool*)&lu->options.Equil,NULL);CHKERRQ(ierr); 662 ierr = PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);CHKERRQ(ierr); 663 if (flg) lu->options.ColPerm = (colperm_t)indx; 664 ierr = PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);CHKERRQ(ierr); 665 if (flg) lu->options.IterRefine = (IterRefine_t)indx; 666 ierr = PetscOptionsBool("-mat_superlu_symmetricmode","SymmetricMode","None",(PetscBool)lu->options.SymmetricMode,&flg,&set);CHKERRQ(ierr); 667 if (set && flg) lu->options.SymmetricMode = YES; 668 ierr = PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&real_input,&flg);CHKERRQ(ierr); 669 if (flg) lu->options.DiagPivotThresh = (double) real_input; 670 ierr = PetscOptionsBool("-mat_superlu_pivotgrowth","PivotGrowth","None",(PetscBool)lu->options.PivotGrowth,&flg,&set);CHKERRQ(ierr); 671 if (set && flg) lu->options.PivotGrowth = YES; 672 ierr = PetscOptionsBool("-mat_superlu_conditionnumber","ConditionNumber","None",(PetscBool)lu->options.ConditionNumber,&flg,&set);CHKERRQ(ierr); 673 if (set && flg) lu->options.ConditionNumber = YES; 674 ierr = PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[lu->options.RowPerm],&indx,&flg);CHKERRQ(ierr); 675 if (flg) lu->options.RowPerm = (rowperm_t)indx; 676 ierr = PetscOptionsBool("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",(PetscBool)lu->options.ReplaceTinyPivot,&flg,&set);CHKERRQ(ierr); 677 if (set && flg) lu->options.ReplaceTinyPivot = YES; 678 ierr = PetscOptionsBool("-mat_superlu_printstat","PrintStat","None",(PetscBool)lu->options.PrintStat,&flg,&set);CHKERRQ(ierr); 679 if (set && flg) lu->options.PrintStat = YES; 680 ierr = PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,NULL);CHKERRQ(ierr); 681 if (lu->lwork > 0) { 682 /* lwork is in bytes, hence PetscMalloc() is used here, not PetscMalloc1()*/ 683 ierr = PetscMalloc(lu->lwork,&lu->work);CHKERRQ(ierr); 684 } else if (lu->lwork != 0 && lu->lwork != -1) { 685 ierr = PetscPrintf(PETSC_COMM_SELF," Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork); 686 lu->lwork = 0; 687 } 688 /* ilu options */ 689 ierr = PetscOptionsReal("-mat_superlu_ilu_droptol","ILU_DropTol","None",lu->options.ILU_DropTol,&real_input,&flg);CHKERRQ(ierr); 690 if (flg) lu->options.ILU_DropTol = (double) real_input; 691 ierr = PetscOptionsReal("-mat_superlu_ilu_filltol","ILU_FillTol","None",lu->options.ILU_FillTol,&real_input,&flg);CHKERRQ(ierr); 692 if (flg) lu->options.ILU_FillTol = (double) real_input; 693 ierr = PetscOptionsReal("-mat_superlu_ilu_fillfactor","ILU_FillFactor","None",lu->options.ILU_FillFactor,&real_input,&flg);CHKERRQ(ierr); 694 if (flg) lu->options.ILU_FillFactor = (double) real_input; 695 ierr = PetscOptionsInt("-mat_superlu_ilu_droprull","ILU_DropRule","None",lu->options.ILU_DropRule,&lu->options.ILU_DropRule,NULL);CHKERRQ(ierr); 696 ierr = PetscOptionsInt("-mat_superlu_ilu_norm","ILU_Norm","None",lu->options.ILU_Norm,&indx,&flg);CHKERRQ(ierr); 697 if (flg) lu->options.ILU_Norm = (norm_t)indx; 698 ierr = PetscOptionsInt("-mat_superlu_ilu_milu","ILU_MILU","None",lu->options.ILU_MILU,&indx,&flg);CHKERRQ(ierr); 699 if (flg) lu->options.ILU_MILU = (milu_t)indx; 700 PetscOptionsEnd(); 701 if (lu->options.Equil == YES) { 702 /* superlu overwrites input matrix and rhs when Equil is used, thus create A_dup to keep user's A unchanged */ 703 ierr = MatDuplicate_SeqAIJ(A,MAT_COPY_VALUES,&lu->A_dup);CHKERRQ(ierr); 704 } 705 706 /* Allocate spaces (notice sizes are for the transpose) */ 707 ierr = PetscMalloc1(m,&lu->etree);CHKERRQ(ierr); 708 ierr = PetscMalloc1(n,&lu->perm_r);CHKERRQ(ierr); 709 ierr = PetscMalloc1(m,&lu->perm_c);CHKERRQ(ierr); 710 ierr = PetscMalloc1(n,&lu->R);CHKERRQ(ierr); 711 ierr = PetscMalloc1(m,&lu->C);CHKERRQ(ierr); 712 713 /* create rhs and solution x without allocate space for .Store */ 714 #if defined(PETSC_USE_COMPLEX) 715 #if defined(PETSC_USE_REAL_SINGLE) 716 PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE)); 717 PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE)); 718 #else 719 PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE)); 720 PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE)); 721 #endif 722 #else 723 #if defined(PETSC_USE_REAL_SINGLE) 724 PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE)); 725 PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE)); 726 #else 727 PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE)); 728 PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE)); 729 #endif 730 #endif 731 732 ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_seqaij_superlu);CHKERRQ(ierr); 733 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSuperluSetILUDropTol_C",MatSuperluSetILUDropTol_SuperLU);CHKERRQ(ierr); 734 B->spptr = lu; 735 736 *F = B; 737 PetscFunctionReturn(0); 738 } 739 740 #undef __FUNCT__ 741 #define __FUNCT__ "MatSolverPackageRegister_SuperLU" 742 PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_SuperLU(void) 743 { 744 PetscErrorCode ierr; 745 746 PetscFunctionBegin; 747 ierr = MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ, MAT_FACTOR_LU,MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 748 ierr = MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ, MAT_FACTOR_ILU,MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 749 PetscFunctionReturn(0); 750 } 751