Actual source code: superlu.c

petsc-3.7.4 2016-10-02
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  2: /*  --------------------------------------------------------------------

  4:      This file implements a subclass of the SeqAIJ matrix class that uses
  5:      the SuperLU sparse solver.
  6: */

  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*/

 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

 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;

 54:   /* Flag to clean up (non-global) SuperLU objects during Destroy */
 55:   PetscBool CleanUpSuperLU;
 56: } Mat_SuperLU;

 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*);

 69: /*
 70:     Utility function
 71: */
 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;

 81:   /* check if matrix is superlu_dist type */
 82:   if (A->ops->solve != MatSolve_SuperLU) return(0);

 84:   options = lu->options;

 86:   PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");
 87:   PetscViewerASCIIPrintf(viewer,"  Equil: %s\n",(options.Equil != NO) ? "YES" : "NO");
 88:   PetscViewerASCIIPrintf(viewer,"  ColPerm: %D\n",options.ColPerm);
 89:   PetscViewerASCIIPrintf(viewer,"  IterRefine: %D\n",options.IterRefine);
 90:   PetscViewerASCIIPrintf(viewer,"  SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES" : "NO");
 91:   PetscViewerASCIIPrintf(viewer,"  DiagPivotThresh: %g\n",options.DiagPivotThresh);
 92:   PetscViewerASCIIPrintf(viewer,"  PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES" : "NO");
 93:   PetscViewerASCIIPrintf(viewer,"  ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES" : "NO");
 94:   PetscViewerASCIIPrintf(viewer,"  RowPerm: %D\n",options.RowPerm);
 95:   PetscViewerASCIIPrintf(viewer,"  ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES" : "NO");
 96:   PetscViewerASCIIPrintf(viewer,"  PrintStat: %s\n",(options.PrintStat != NO) ? "YES" : "NO");
 97:   PetscViewerASCIIPrintf(viewer,"  lwork: %D\n",lu->lwork);
 98:   if (A->factortype == MAT_FACTOR_ILU) {
 99:     PetscViewerASCIIPrintf(viewer,"  ILU_DropTol: %g\n",options.ILU_DropTol);
100:     PetscViewerASCIIPrintf(viewer,"  ILU_FillTol: %g\n",options.ILU_FillTol);
101:     PetscViewerASCIIPrintf(viewer,"  ILU_FillFactor: %g\n",options.ILU_FillFactor);
102:     PetscViewerASCIIPrintf(viewer,"  ILU_DropRule: %D\n",options.ILU_DropRule);
103:     PetscViewerASCIIPrintf(viewer,"  ILU_Norm: %D\n",options.ILU_Norm);
104:     PetscViewerASCIIPrintf(viewer,"  ILU_MILU: %D\n",options.ILU_MILU);
105:   }
106:   return(0);
107: }

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: */
115: PetscErrorCode MatLUFactorNumeric_SuperLU(Mat F,Mat A,const MatFactorInfo *info)
116: {
117:   Mat_SuperLU    *lu = (Mat_SuperLU*)F->spptr;
118:   Mat_SeqAIJ     *aa;
120:   PetscInt       sinfo;
121:   PetscReal      ferr, berr;
122:   NCformat       *Ustore;
123:   SCformat       *Lstore;

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:       MatCopy_SeqAIJ(A,lu->A_dup,SAME_NONZERO_PATTERN);
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:   }

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

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:       PetscPrintf(PETSC_COMM_SELF,"  Recip. pivot growth = %e\n", lu->rpg);
213:     }
214:     if (lu->options.ConditionNumber) {
215:       PetscPrintf(PETSC_COMM_SELF,"  Recip. condition number = %e\n", lu->rcond);
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:         PetscInfo2(F,"Number of zero pivots %D, ILU_FillTol %g\n",sinfo,lu->options.ILU_FillTol);
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:         PetscInfo1(F,"Matrix factor U is nonsingular, but is singular to working precision. The solution is computed. info %D",sinfo);
236:       } else { /* sinfo > lu->A.ncol + 1 */
237:         F->errortype = MAT_FACTOR_OUTMEMORY;
238:         PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);
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);

243:   if (lu->options.PrintStat) {
244:     PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n");
245:     PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat));
246:     Lstore = (SCformat*) lu->L.Store;
247:     Ustore = (NCformat*) lu->U.Store;
248:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor L = %D\n", Lstore->nnz);
249:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor U = %D\n", Ustore->nnz);
250:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in L+U = %D\n", Lstore->nnz + Ustore->nnz - lu->A.ncol);
251:     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:   }

255:   lu->flg                = SAME_NONZERO_PATTERN;
256:   F->ops->solve          = MatSolve_SuperLU;
257:   F->ops->solvetranspose = MatSolveTranspose_SuperLU;
258:   F->ops->matsolve       = NULL;
259:   return(0);
260: }

264: PetscErrorCode MatGetDiagonal_SuperLU(Mat A,Vec v)
265: {
267:   SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Mat type: SuperLU factor");
268:   return(0);
269: }

273: PetscErrorCode MatDestroy_SuperLU(Mat A)
274: {
276:   Mat_SuperLU    *lu=(Mat_SuperLU*)A->spptr;

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:     PetscFree(lu->etree);
291:     PetscFree(lu->perm_r);
292:     PetscFree(lu->perm_c);
293:     PetscFree(lu->R);
294:     PetscFree(lu->C);
295:     PetscFree(lu->rhs_dup);
296:     MatDestroy(&lu->A_dup);
297:   }
298:   PetscFree(A->spptr);

300:   /* clear composed functions */
301:   PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);
302:   PetscObjectComposeFunction((PetscObject)A,"MatSuperluSetILUDropTol_C",NULL);

304:   MatDestroy_SeqAIJ(A);
305:   return(0);
306: }

310: PetscErrorCode MatView_SuperLU(Mat A,PetscViewer viewer)
311: {
312:   PetscErrorCode    ierr;
313:   PetscBool         iascii;
314:   PetscViewerFormat format;

317:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
318:   if (iascii) {
319:     PetscViewerGetFormat(viewer,&format);
320:     if (format == PETSC_VIEWER_ASCII_INFO) {
321:       MatFactorInfo_SuperLU(A,viewer);
322:     }
323:   }
324:   return(0);
325: }


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;

341:   if (lu->lwork == -1) return(0);
342:   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);

344:   VecGetLocalSize(x,&n);
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:     PetscMalloc1(n,&lu->rhs_dup);
349:   }
350:   if (lu->options.Equil) {
351:     /* Copy b into rsh_dup */
352:     VecGetArrayRead(b,&barray);
353:     PetscMemcpy(lu->rhs_dup,barray,n*sizeof(PetscScalar));
354:     VecRestoreArrayRead(b,&barray);
355:     barray = lu->rhs_dup;
356:   } else {
357:     VecGetArrayRead(b,&barray);
358:   }
359:   VecGetArray(x,&xarray);

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

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:     VecRestoreArrayRead(b,&barray);
422:   }
423:   VecRestoreArray(x,&xarray);

425:   if (!info || info == lu->A.ncol+1) {
426:     if (lu->options.IterRefine) {
427:       PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n");
428:       PetscPrintf(PETSC_COMM_SELF,"  %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR");
429:       for (i = 0; i < 1; ++i) {
430:         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:       PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %D bytes\n", info - lu->A.ncol);
436:     } else {
437:       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);

441:   if (lu->options.PrintStat) {
442:     PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n");
443:     PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat));
444:   }
445:   return(0);
446: }

450: PetscErrorCode MatSolve_SuperLU(Mat A,Vec b,Vec x)
451: {
452:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->spptr;

456:   if (A->errortype) {
457:     PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");
458:     VecSetInf(x);
459:     return(0);
460:   }

462:   lu->options.Trans = TRANS;
463:   MatSolve_SuperLU_Private(A,b,x);
464:   return(0);
465: }

469: PetscErrorCode MatSolveTranspose_SuperLU(Mat A,Vec b,Vec x)
470: {
471:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->spptr;

475:   if (A->errortype) {
476:     PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");
477:     VecSetInf(x);
478:     return(0);
479:   }

481:   lu->options.Trans = NOTRANS;
482:   MatSolve_SuperLU_Private(A,b,x);
483:   return(0);
484: }

488: PetscErrorCode MatMatSolve_SuperLU(Mat A,Mat B,Mat X)
489: {
490:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->spptr;
491:   PetscBool      flg;

495:   PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
496:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
497:   PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
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:   return(0);
502: }

504: /*
505:    Note the r permutation is ignored
506: */
509: PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
510: {
511:   Mat_SuperLU *lu = (Mat_SuperLU*)(F->spptr);

514:   lu->flg                 = DIFFERENT_NONZERO_PATTERN;
515:   lu->CleanUpSuperLU      = PETSC_TRUE;
516:   F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU;
517:   return(0);
518: }

522: static PetscErrorCode MatSuperluSetILUDropTol_SuperLU(Mat F,PetscReal dtol)
523: {
524:   Mat_SuperLU *lu= (Mat_SuperLU*)F->spptr;

527:   lu->options.ILU_DropTol = dtol;
528:   return(0);
529: }

533: /*@
534:   MatSuperluSetILUDropTol - Set SuperLU ILU drop tolerance
535:    Logically Collective on Mat

537:    Input Parameters:
538: +  F - the factored matrix obtained by calling MatGetFactor() from PETSc-SuperLU interface
539: -  dtol - drop tolerance

541:   Options Database:
542: .   -mat_superlu_ilu_droptol <dtol>

544:    Level: beginner

546:    References:
547: .      SuperLU Users' Guide

549: .seealso: MatGetFactor()
550: @*/
551: PetscErrorCode MatSuperluSetILUDropTol(Mat F,PetscReal dtol)
552: {

558:   PetscTryMethod(F,"MatSuperluSetILUDropTol_C",(Mat,PetscReal),(F,dtol));
559:   return(0);
560: }

564: PetscErrorCode MatFactorGetSolverPackage_seqaij_superlu(Mat A,const MatSolverPackage *type)
565: {
567:   *type = MATSOLVERSUPERLU;
568:   return(0);
569: }


572: /*MC
573:   MATSOLVERSUPERLU = "superlu" - A solver package providing solvers LU and ILU for sequential matrices
574:   via the external package SuperLU.

576:   Use ./configure --download-superlu to have PETSc installed with SuperLU

578:   Use -pc_type lu -pc_factor_mat_solver_package superlu to us this direct solver

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)

599:    Notes: Do not confuse this with MATSOLVERSUPERLU_DIST which is for parallel sparse solves

601:    Level: beginner

603: .seealso: PCLU, PCILU, MATSOLVERSUPERLU_DIST, MATSOLVERMUMPS, PCFactorSetMatSolverPackage(), MatSolverPackage
604: M*/

608: static PetscErrorCode MatGetFactor_seqaij_superlu(Mat A,MatFactorType ftype,Mat *F)
609: {
610:   Mat            B;
611:   Mat_SuperLU    *lu;
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 */

621:   MatCreate(PetscObjectComm((PetscObject)A),&B);
622:   MatSetSizes(B,A->rmap->n,A->cmap->n,PETSC_DETERMINE,PETSC_DETERMINE);
623:   MatSetType(B,((PetscObject)A)->type_name);
624:   MatSeqAIJSetPreallocation(B,0,NULL);

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");

631:   PetscFree(B->solvertype);
632:   PetscStrallocpy(MATSOLVERSUPERLU,&B->solvertype);

634:   B->ops->destroy     = MatDestroy_SuperLU;
635:   B->ops->view        = MatView_SuperLU;
636:   B->ops->getdiagonal = MatGetDiagonal_SuperLU;
637:   B->factortype       = ftype;
638:   B->assembled        = PETSC_TRUE;           /* required by -ksp_view */
639:   B->preallocated     = PETSC_TRUE;

641:   PetscNewLog(B,&lu);

643:   if (ftype == MAT_FACTOR_LU) {
644:     set_default_options(&lu->options);
645:     /* Comments from SuperLU_4.0/SRC/dgssvx.c:
646:       "Whether or not the system will be equilibrated depends on the
647:        scaling of the matrix A, but if equilibration is used, A is
648:        overwritten by diag(R)*A*diag(C) and B by diag(R)*B
649:        (if options->Trans=NOTRANS) or diag(C)*B (if options->Trans = TRANS or CONJ)."
650:      We set 'options.Equil = NO' as default because additional space is needed for it.
651:     */
652:     lu->options.Equil = NO;
653:   } else if (ftype == MAT_FACTOR_ILU) {
654:     /* Set the default input options of ilu: */
655:     PetscStackCall("SuperLU:ilu_set_default_options",ilu_set_default_options(&lu->options));
656:   }
657:   lu->options.PrintStat = NO;

659:   /* Initialize the statistics variables. */
660:   PetscStackCall("SuperLU:StatInit",StatInit(&lu->stat));
661:   lu->lwork = 0;   /* allocate space internally by system malloc */

663:   PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU Options","Mat");
664:   PetscOptionsBool("-mat_superlu_equil","Equil","None",(PetscBool)lu->options.Equil,(PetscBool*)&lu->options.Equil,NULL);
665:   PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);
666:   if (flg) lu->options.ColPerm = (colperm_t)indx;
667:   PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);
668:   if (flg) lu->options.IterRefine = (IterRefine_t)indx;
669:   PetscOptionsBool("-mat_superlu_symmetricmode","SymmetricMode","None",(PetscBool)lu->options.SymmetricMode,&flg,&set);
670:   if (set && flg) lu->options.SymmetricMode = YES;
671:   PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&real_input,&flg);
672:   if (flg) lu->options.DiagPivotThresh = (double) real_input;
673:   PetscOptionsBool("-mat_superlu_pivotgrowth","PivotGrowth","None",(PetscBool)lu->options.PivotGrowth,&flg,&set);
674:   if (set && flg) lu->options.PivotGrowth = YES;
675:   PetscOptionsBool("-mat_superlu_conditionnumber","ConditionNumber","None",(PetscBool)lu->options.ConditionNumber,&flg,&set);
676:   if (set && flg) lu->options.ConditionNumber = YES;
677:   PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[lu->options.RowPerm],&indx,&flg);
678:   if (flg) lu->options.RowPerm = (rowperm_t)indx;
679:   PetscOptionsBool("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",(PetscBool)lu->options.ReplaceTinyPivot,&flg,&set);
680:   if (set && flg) lu->options.ReplaceTinyPivot = YES;
681:   PetscOptionsBool("-mat_superlu_printstat","PrintStat","None",(PetscBool)lu->options.PrintStat,&flg,&set);
682:   if (set && flg) lu->options.PrintStat = YES;
683:   PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,NULL);
684:   if (lu->lwork > 0) {
685:     /* lwork is in bytes, hence PetscMalloc() is used here, not PetscMalloc1()*/
686:     PetscMalloc(lu->lwork,&lu->work);
687:   } else if (lu->lwork != 0 && lu->lwork != -1) {
688:     PetscPrintf(PETSC_COMM_SELF,"   Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork);
689:     lu->lwork = 0;
690:   }
691:   /* ilu options */
692:   PetscOptionsReal("-mat_superlu_ilu_droptol","ILU_DropTol","None",lu->options.ILU_DropTol,&real_input,&flg);
693:   if (flg) lu->options.ILU_DropTol = (double) real_input;
694:   PetscOptionsReal("-mat_superlu_ilu_filltol","ILU_FillTol","None",lu->options.ILU_FillTol,&real_input,&flg);
695:   if (flg) lu->options.ILU_FillTol = (double) real_input;
696:   PetscOptionsReal("-mat_superlu_ilu_fillfactor","ILU_FillFactor","None",lu->options.ILU_FillFactor,&real_input,&flg);
697:   if (flg) lu->options.ILU_FillFactor = (double) real_input;
698:   PetscOptionsInt("-mat_superlu_ilu_droprull","ILU_DropRule","None",lu->options.ILU_DropRule,&lu->options.ILU_DropRule,NULL);
699:   PetscOptionsInt("-mat_superlu_ilu_norm","ILU_Norm","None",lu->options.ILU_Norm,&indx,&flg);
700:   if (flg) lu->options.ILU_Norm = (norm_t)indx;
701:   PetscOptionsInt("-mat_superlu_ilu_milu","ILU_MILU","None",lu->options.ILU_MILU,&indx,&flg);
702:   if (flg) lu->options.ILU_MILU = (milu_t)indx;
703:   PetscOptionsEnd();
704:   if (lu->options.Equil == YES) {
705:     /* superlu overwrites input matrix and rhs when Equil is used, thus create A_dup to keep user's A unchanged */
706:     MatDuplicate_SeqAIJ(A,MAT_COPY_VALUES,&lu->A_dup);
707:   }

709:   /* Allocate spaces (notice sizes are for the transpose) */
710:   PetscMalloc1(m,&lu->etree);
711:   PetscMalloc1(n,&lu->perm_r);
712:   PetscMalloc1(m,&lu->perm_c);
713:   PetscMalloc1(n,&lu->R);
714:   PetscMalloc1(m,&lu->C);

716:   /* create rhs and solution x without allocate space for .Store */
717: #if defined(PETSC_USE_COMPLEX)
718: #if defined(PETSC_USE_REAL_SINGLE)
719:   PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
720:   PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
721: #else
722:   PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
723:   PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
724: #endif
725: #else
726: #if defined(PETSC_USE_REAL_SINGLE)
727:   PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
728:   PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
729: #else
730:   PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
731:   PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
732: #endif
733: #endif

735:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_seqaij_superlu);
736:   PetscObjectComposeFunction((PetscObject)B,"MatSuperluSetILUDropTol_C",MatSuperluSetILUDropTol_SuperLU);
737:   B->spptr = lu;

739:   *F       = B;
740:   return(0);
741: }

745: PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_SuperLU(void)
746: {

750:   MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ,       MAT_FACTOR_LU,MatGetFactor_seqaij_superlu);
751:   MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ,       MAT_FACTOR_ILU,MatGetFactor_seqaij_superlu);
752:   return(0);
753: }