Actual source code: superlu.c

petsc-master 2017-06-21
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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>

 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 that defines the SuperLU factored 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: /*
 59:     Utility function
 60: */
 61: static PetscErrorCode MatFactorInfo_SuperLU(Mat A,PetscViewer viewer)
 62: {
 63:   Mat_SuperLU       *lu= (Mat_SuperLU*)A->data;
 64:   PetscErrorCode    ierr;
 65:   superlu_options_t options;

 68:   options = lu->options;

 70:   PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");
 71:   PetscViewerASCIIPrintf(viewer,"  Equil: %s\n",(options.Equil != NO) ? "YES" : "NO");
 72:   PetscViewerASCIIPrintf(viewer,"  ColPerm: %D\n",options.ColPerm);
 73:   PetscViewerASCIIPrintf(viewer,"  IterRefine: %D\n",options.IterRefine);
 74:   PetscViewerASCIIPrintf(viewer,"  SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES" : "NO");
 75:   PetscViewerASCIIPrintf(viewer,"  DiagPivotThresh: %g\n",options.DiagPivotThresh);
 76:   PetscViewerASCIIPrintf(viewer,"  PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES" : "NO");
 77:   PetscViewerASCIIPrintf(viewer,"  ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES" : "NO");
 78:   PetscViewerASCIIPrintf(viewer,"  RowPerm: %D\n",options.RowPerm);
 79:   PetscViewerASCIIPrintf(viewer,"  ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES" : "NO");
 80:   PetscViewerASCIIPrintf(viewer,"  PrintStat: %s\n",(options.PrintStat != NO) ? "YES" : "NO");
 81:   PetscViewerASCIIPrintf(viewer,"  lwork: %D\n",lu->lwork);
 82:   if (A->factortype == MAT_FACTOR_ILU) {
 83:     PetscViewerASCIIPrintf(viewer,"  ILU_DropTol: %g\n",options.ILU_DropTol);
 84:     PetscViewerASCIIPrintf(viewer,"  ILU_FillTol: %g\n",options.ILU_FillTol);
 85:     PetscViewerASCIIPrintf(viewer,"  ILU_FillFactor: %g\n",options.ILU_FillFactor);
 86:     PetscViewerASCIIPrintf(viewer,"  ILU_DropRule: %D\n",options.ILU_DropRule);
 87:     PetscViewerASCIIPrintf(viewer,"  ILU_Norm: %D\n",options.ILU_Norm);
 88:     PetscViewerASCIIPrintf(viewer,"  ILU_MILU: %D\n",options.ILU_MILU);
 89:   }
 90:   return(0);
 91: }

 93: PetscErrorCode MatSolve_SuperLU_Private(Mat A,Vec b,Vec x)
 94: {
 95:   Mat_SuperLU       *lu = (Mat_SuperLU*)A->data;
 96:   const PetscScalar *barray;
 97:   PetscScalar       *xarray;
 98:   PetscErrorCode    ierr;
 99:   PetscInt          info,i,n;
100:   PetscReal         ferr,berr;
101:   static PetscBool  cite = PETSC_FALSE;

104:   if (lu->lwork == -1) return(0);
105:   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);

107:   VecGetLocalSize(x,&n);
108:   lu->B.ncol = 1;   /* Set the number of right-hand side */
109:   if (lu->options.Equil && !lu->rhs_dup) {
110:     /* superlu overwrites b when Equil is used, thus create rhs_dup to keep user's b unchanged */
111:     PetscMalloc1(n,&lu->rhs_dup);
112:   }
113:   if (lu->options.Equil) {
114:     /* Copy b into rsh_dup */
115:     VecGetArrayRead(b,&barray);
116:     PetscMemcpy(lu->rhs_dup,barray,n*sizeof(PetscScalar));
117:     VecRestoreArrayRead(b,&barray);
118:     barray = lu->rhs_dup;
119:   } else {
120:     VecGetArrayRead(b,&barray);
121:   }
122:   VecGetArray(x,&xarray);

124: #if defined(PETSC_USE_COMPLEX)
125: #if defined(PETSC_USE_REAL_SINGLE)
126:   ((DNformat*)lu->B.Store)->nzval = (singlecomplex*)barray;
127:   ((DNformat*)lu->X.Store)->nzval = (singlecomplex*)xarray;
128: #else
129:   ((DNformat*)lu->B.Store)->nzval = (doublecomplex*)barray;
130:   ((DNformat*)lu->X.Store)->nzval = (doublecomplex*)xarray;
131: #endif
132: #else
133:   ((DNformat*)lu->B.Store)->nzval = (void*)barray;
134:   ((DNformat*)lu->X.Store)->nzval = xarray;
135: #endif

137:   lu->options.Fact = FACTORED; /* Indicate the factored form of A is supplied. */
138:   if (A->factortype == MAT_FACTOR_LU) {
139: #if defined(PETSC_USE_COMPLEX)
140: #if defined(PETSC_USE_REAL_SINGLE)
141:     PetscStackCall("SuperLU:cgssvx",cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
142:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
143:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
144: #else
145:     PetscStackCall("SuperLU:zgssvx",zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
146:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
147:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
148: #endif
149: #else
150: #if defined(PETSC_USE_REAL_SINGLE)
151:     PetscStackCall("SuperLU:sgssvx",sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
152:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
153:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
154: #else
155:     PetscStackCall("SuperLU:dgssvx",dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
156:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
157:                                      &lu->Glu,&lu->mem_usage, &lu->stat, &info));
158: #endif
159: #endif
160:   } else if (A->factortype == MAT_FACTOR_ILU) {
161: #if defined(PETSC_USE_COMPLEX)
162: #if defined(PETSC_USE_REAL_SINGLE)
163:     PetscStackCall("SuperLU:cgsisx",cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
164:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
165:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
166: #else
167:     PetscStackCall("SuperLU:zgsisx",zgsisx(&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,
169:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
170: #endif
171: #else
172: #if defined(PETSC_USE_REAL_SINGLE)
173:     PetscStackCall("SuperLU:sgsisx",sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
174:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
175:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
176: #else
177:     PetscStackCall("SuperLU:dgsisx",dgsisx(&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,
179:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &info));
180: #endif
181: #endif
182:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
183:   if (!lu->options.Equil) {
184:     VecRestoreArrayRead(b,&barray);
185:   }
186:   VecRestoreArray(x,&xarray);

188:   if (!info || info == lu->A.ncol+1) {
189:     if (lu->options.IterRefine) {
190:       PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n");
191:       PetscPrintf(PETSC_COMM_SELF,"  %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR");
192:       for (i = 0; i < 1; ++i) {
193:         PetscPrintf(PETSC_COMM_SELF,"  %8d%8d%16e%16e\n", i+1, lu->stat.RefineSteps, ferr, berr);
194:       }
195:     }
196:   } else if (info > 0) {
197:     if (lu->lwork == -1) {
198:       PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %D bytes\n", info - lu->A.ncol);
199:     } else {
200:       PetscPrintf(PETSC_COMM_SELF,"  Warning: gssvx() returns info %D\n",info);
201:     }
202:   } 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);

204:   if (lu->options.PrintStat) {
205:     PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n");
206:     PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat));
207:   }
208:   return(0);
209: }

211: PetscErrorCode MatSolve_SuperLU(Mat A,Vec b,Vec x)
212: {
213:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->data;

217:   if (A->factorerrortype) {
218:     PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");
219:     VecSetInf(x);
220:     return(0);
221:   }

223:   lu->options.Trans = TRANS;
224:   MatSolve_SuperLU_Private(A,b,x);
225:   return(0);
226: }

228: PetscErrorCode MatSolveTranspose_SuperLU(Mat A,Vec b,Vec x)
229: {
230:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->data;

234:   if (A->factorerrortype) {
235:     PetscInfo(A,"MatSolve is called with singular matrix factor, skip\n");
236:     VecSetInf(x);
237:     return(0);
238:   }

240:   lu->options.Trans = NOTRANS;
241:   MatSolve_SuperLU_Private(A,b,x);
242:   return(0);
243: }

245: static PetscErrorCode MatLUFactorNumeric_SuperLU(Mat F,Mat A,const MatFactorInfo *info)
246: {
247:   Mat_SuperLU    *lu = (Mat_SuperLU*)F->data;
248:   Mat_SeqAIJ     *aa;
250:   PetscInt       sinfo;
251:   PetscReal      ferr, berr;
252:   NCformat       *Ustore;
253:   SCformat       *Lstore;

256:   if (lu->flg == SAME_NONZERO_PATTERN) { /* successing numerical factorization */
257:     lu->options.Fact = SamePattern;
258:     /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */
259:     Destroy_SuperMatrix_Store(&lu->A);
260:     if (lu->options.Equil) {
261:       MatCopy_SeqAIJ(A,lu->A_dup,SAME_NONZERO_PATTERN);
262:     }
263:     if (lu->lwork >= 0) {
264:       PetscStackCall("SuperLU:Destroy_SuperNode_Matrix",Destroy_SuperNode_Matrix(&lu->L));
265:       PetscStackCall("SuperLU:Destroy_CompCol_Matrix",Destroy_CompCol_Matrix(&lu->U));
266:       lu->options.Fact = SamePattern;
267:     }
268:   }

270:   /* Create the SuperMatrix for lu->A=A^T:
271:        Since SuperLU likes column-oriented matrices,we pass it the transpose,
272:        and then solve A^T X = B in MatSolve(). */
273:   if (lu->options.Equil) {
274:     aa = (Mat_SeqAIJ*)(lu->A_dup)->data;
275:   } else {
276:     aa = (Mat_SeqAIJ*)(A)->data;
277:   }
278: #if defined(PETSC_USE_COMPLEX)
279: #if defined(PETSC_USE_REAL_SINGLE)
280:   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));
281: #else
282:   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));
283: #endif
284: #else
285: #if defined(PETSC_USE_REAL_SINGLE)
286:   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));
287: #else
288:   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));
289: #endif
290: #endif

292:   /* Numerical factorization */
293:   lu->B.ncol = 0;  /* Indicate not to solve the system */
294:   if (F->factortype == MAT_FACTOR_LU) {
295: #if defined(PETSC_USE_COMPLEX)
296: #if defined(PETSC_USE_REAL_SINGLE)
297:     PetscStackCall("SuperLU:cgssvx",cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
298:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
299:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
300: #else
301:     PetscStackCall("SuperLU:zgssvx",zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
302:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
303:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
304: #endif
305: #else
306: #if defined(PETSC_USE_REAL_SINGLE)
307:     PetscStackCall("SuperLU:sgssvx",sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
308:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
309:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
310: #else
311:     PetscStackCall("SuperLU:dgssvx",dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
312:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
313:                                      &lu->Glu,&lu->mem_usage, &lu->stat, &sinfo));
314: #endif
315: #endif
316:   } else if (F->factortype == MAT_FACTOR_ILU) {
317:     /* Compute the incomplete factorization, condition number and pivot growth */
318: #if defined(PETSC_USE_COMPLEX)
319: #if defined(PETSC_USE_REAL_SINGLE)
320:     PetscStackCall("SuperLU:cgsisx",cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r,lu->etree, lu->equed, lu->R, lu->C,
321:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
322:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
323: #else
324:     PetscStackCall("SuperLU:zgsisx",zgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r,lu->etree, lu->equed, lu->R, lu->C,
325:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
326:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
327: #endif
328: #else
329: #if defined(PETSC_USE_REAL_SINGLE)
330:     PetscStackCall("SuperLU:sgsisx",sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
331:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
332:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
333: #else
334:     PetscStackCall("SuperLU:dgsisx",dgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
335:                                      &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond,
336:                                      &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
337: #endif
338: #endif
339:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
340:   if (!sinfo || sinfo == lu->A.ncol+1) {
341:     if (lu->options.PivotGrowth) {
342:       PetscPrintf(PETSC_COMM_SELF,"  Recip. pivot growth = %e\n", lu->rpg);
343:     }
344:     if (lu->options.ConditionNumber) {
345:       PetscPrintf(PETSC_COMM_SELF,"  Recip. condition number = %e\n", lu->rcond);
346:     }
347:   } else if (sinfo > 0) {
348:     if (A->erroriffailure) {
349:       SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot in row %D",sinfo);
350:     } else {
351:       if (sinfo <= lu->A.ncol) {
352:         if (lu->options.ILU_FillTol == 0.0) {
353:           F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
354:         }
355:         PetscInfo2(F,"Number of zero pivots %D, ILU_FillTol %g\n",sinfo,lu->options.ILU_FillTol);
356:       } else if (sinfo == lu->A.ncol + 1) {
357:         /* 
358:          U is nonsingular, but RCOND is less than machine
359:                        precision, meaning that the matrix is singular to
360:                        working precision. Nevertheless, the solution and
361:                        error bounds are computed because there are a number
362:                        of situations where the computed solution can be more
363:                        accurate than the value of RCOND would suggest.
364:          */
365:         PetscInfo1(F,"Matrix factor U is nonsingular, but is singular to working precision. The solution is computed. info %D",sinfo);
366:       } else { /* sinfo > lu->A.ncol + 1 */
367:         F->factorerrortype = MAT_FACTOR_OUTMEMORY;
368:         PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);
369:       }
370:     }
371:   } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", sinfo,-sinfo);

373:   if (lu->options.PrintStat) {
374:     PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n");
375:     PetscStackCall("SuperLU:StatPrint",StatPrint(&lu->stat));
376:     Lstore = (SCformat*) lu->L.Store;
377:     Ustore = (NCformat*) lu->U.Store;
378:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor L = %D\n", Lstore->nnz);
379:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor U = %D\n", Ustore->nnz);
380:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in L+U = %D\n", Lstore->nnz + Ustore->nnz - lu->A.ncol);
381:     PetscPrintf(PETSC_COMM_SELF,"  L\\U MB %.3f\ttotal MB needed %.3f\n",
382:                          lu->mem_usage.for_lu/1e6, lu->mem_usage.total_needed/1e6);
383:   }

385:   lu->flg                = SAME_NONZERO_PATTERN;
386:   F->ops->solve          = MatSolve_SuperLU;
387:   F->ops->solvetranspose = MatSolveTranspose_SuperLU;
388:   F->ops->matsolve       = NULL;
389:   return(0);
390: }

392: static PetscErrorCode MatDestroy_SuperLU(Mat A)
393: {
395:   Mat_SuperLU    *lu=(Mat_SuperLU*)A->data;

398:   if (lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */
399:     PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->A));
400:     PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->B));
401:     PetscStackCall("SuperLU:Destroy_SuperMatrix_Store",Destroy_SuperMatrix_Store(&lu->X));
402:     PetscStackCall("SuperLU:StatFree",StatFree(&lu->stat));
403:     if (lu->lwork >= 0) {
404:       PetscStackCall("SuperLU:Destroy_SuperNode_Matrix",Destroy_SuperNode_Matrix(&lu->L));
405:       PetscStackCall("SuperLU:Destroy_CompCol_Matrix",Destroy_CompCol_Matrix(&lu->U));
406:     }
407:   }
408:   PetscFree(lu->etree);
409:   PetscFree(lu->perm_r);
410:   PetscFree(lu->perm_c);
411:   PetscFree(lu->R);
412:   PetscFree(lu->C);
413:   PetscFree(lu->rhs_dup);
414:   MatDestroy(&lu->A_dup);
415:   PetscFree(A->data);

417:   /* clear composed functions */
418:   PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);
419:   PetscObjectComposeFunction((PetscObject)A,"MatSuperluSetILUDropTol_C",NULL);
420:   return(0);
421: }

423: static PetscErrorCode MatView_SuperLU(Mat A,PetscViewer viewer)
424: {
425:   PetscErrorCode    ierr;
426:   PetscBool         iascii;
427:   PetscViewerFormat format;

430:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
431:   if (iascii) {
432:     PetscViewerGetFormat(viewer,&format);
433:     if (format == PETSC_VIEWER_ASCII_INFO) {
434:       MatFactorInfo_SuperLU(A,viewer);
435:     }
436:   }
437:   return(0);
438: }

440: PetscErrorCode MatMatSolve_SuperLU(Mat A,Mat B,Mat X)
441: {
442:   Mat_SuperLU    *lu = (Mat_SuperLU*)A->data;
443:   PetscBool      flg;

447:   PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
448:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix");
449:   PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);
450:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix");
451:   lu->options.Trans = TRANS;
452:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatMatSolve_SuperLU() is not implemented yet");
453:   return(0);
454: }

456: /*
457:    Note the r permutation is ignored
458: */
459: static PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info)
460: {
461:   Mat_SuperLU *lu = (Mat_SuperLU*)(F->data);

464:   lu->flg                 = DIFFERENT_NONZERO_PATTERN;
465:   lu->CleanUpSuperLU      = PETSC_TRUE;
466:   F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU;
467:   return(0);
468: }

470: static PetscErrorCode MatSuperluSetILUDropTol_SuperLU(Mat F,PetscReal dtol)
471: {
472:   Mat_SuperLU *lu= (Mat_SuperLU*)F->data;

475:   lu->options.ILU_DropTol = dtol;
476:   return(0);
477: }

479: /*@
480:   MatSuperluSetILUDropTol - Set SuperLU ILU drop tolerance
481:    Logically Collective on Mat

483:    Input Parameters:
484: +  F - the factored matrix obtained by calling MatGetFactor() from PETSc-SuperLU interface
485: -  dtol - drop tolerance

487:   Options Database:
488: .   -mat_superlu_ilu_droptol <dtol>

490:    Level: beginner

492:    References:
493: .      SuperLU Users' Guide

495: .seealso: MatGetFactor()
496: @*/
497: PetscErrorCode MatSuperluSetILUDropTol(Mat F,PetscReal dtol)
498: {

504:   PetscTryMethod(F,"MatSuperluSetILUDropTol_C",(Mat,PetscReal),(F,dtol));
505:   return(0);
506: }

508: PetscErrorCode MatFactorGetSolverPackage_seqaij_superlu(Mat A,const MatSolverPackage *type)
509: {
511:   *type = MATSOLVERSUPERLU;
512:   return(0);
513: }

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

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

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

523:   Options Database Keys:
524: + -mat_superlu_equil <FALSE>            - Equil (None)
525: . -mat_superlu_colperm <COLAMD>         - (choose one of) NATURAL MMD_ATA MMD_AT_PLUS_A COLAMD
526: . -mat_superlu_iterrefine <NOREFINE>    - (choose one of) NOREFINE SINGLE DOUBLE EXTRA
527: . -mat_superlu_symmetricmode: <FALSE>   - SymmetricMode (None)
528: . -mat_superlu_diagpivotthresh <1>      - DiagPivotThresh (None)
529: . -mat_superlu_pivotgrowth <FALSE>      - PivotGrowth (None)
530: . -mat_superlu_conditionnumber <FALSE>  - ConditionNumber (None)
531: . -mat_superlu_rowperm <NOROWPERM>      - (choose one of) NOROWPERM LargeDiag
532: . -mat_superlu_replacetinypivot <FALSE> - ReplaceTinyPivot (None)
533: . -mat_superlu_printstat <FALSE>        - PrintStat (None)
534: . -mat_superlu_lwork <0>                - size of work array in bytes used by factorization (None)
535: . -mat_superlu_ilu_droptol <0>          - ILU_DropTol (None)
536: . -mat_superlu_ilu_filltol <0>          - ILU_FillTol (None)
537: . -mat_superlu_ilu_fillfactor <0>       - ILU_FillFactor (None)
538: . -mat_superlu_ilu_droprull <0>         - ILU_DropRule (None)
539: . -mat_superlu_ilu_norm <0>             - ILU_Norm (None)
540: - -mat_superlu_ilu_milu <0>             - ILU_MILU (None)

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

544:    Level: beginner

546: .seealso: PCLU, PCILU, MATSOLVERSUPERLU_DIST, MATSOLVERMUMPS, PCFactorSetMatSolverPackage(), MatSolverPackage
547: M*/

549: static PetscErrorCode MatGetFactor_seqaij_superlu(Mat A,MatFactorType ftype,Mat *F)
550: {
551:   Mat            B;
552:   Mat_SuperLU    *lu;
554:   PetscInt       indx,m=A->rmap->n,n=A->cmap->n;
555:   PetscBool      flg,set;
556:   PetscReal      real_input;
557:   const char     *colperm[]   ={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */
558:   const char     *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"};
559:   const char     *rowperm[]   ={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */

562:   MatCreate(PetscObjectComm((PetscObject)A),&B);
563:   MatSetSizes(B,A->rmap->n,A->cmap->n,PETSC_DETERMINE,PETSC_DETERMINE);
564:   PetscStrallocpy("superlu",&((PetscObject)B)->type_name);
565:   MatSetUp(B);
566:   if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU) {
567:     B->ops->lufactorsymbolic  = MatLUFactorSymbolic_SuperLU;
568:     B->ops->ilufactorsymbolic = MatLUFactorSymbolic_SuperLU;
569:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");

571:   PetscFree(B->solvertype);
572:   PetscStrallocpy(MATSOLVERSUPERLU,&B->solvertype);

574:   B->ops->getinfo     = MatGetInfo_External;
575:   B->ops->destroy     = MatDestroy_SuperLU;
576:   B->ops->view        = MatView_SuperLU;
577:   B->factortype       = ftype;
578:   B->assembled        = PETSC_TRUE;           /* required by -ksp_view */
579:   B->preallocated     = PETSC_TRUE;

581:   PetscNewLog(B,&lu);

583:   if (ftype == MAT_FACTOR_LU) {
584:     set_default_options(&lu->options);
585:     /* Comments from SuperLU_4.0/SRC/dgssvx.c:
586:       "Whether or not the system will be equilibrated depends on the
587:        scaling of the matrix A, but if equilibration is used, A is
588:        overwritten by diag(R)*A*diag(C) and B by diag(R)*B
589:        (if options->Trans=NOTRANS) or diag(C)*B (if options->Trans = TRANS or CONJ)."
590:      We set 'options.Equil = NO' as default because additional space is needed for it.
591:     */
592:     lu->options.Equil = NO;
593:   } else if (ftype == MAT_FACTOR_ILU) {
594:     /* Set the default input options of ilu: */
595:     PetscStackCall("SuperLU:ilu_set_default_options",ilu_set_default_options(&lu->options));
596:   }
597:   lu->options.PrintStat = NO;

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

603:   PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU Options","Mat");
604:   PetscOptionsBool("-mat_superlu_equil","Equil","None",(PetscBool)lu->options.Equil,(PetscBool*)&lu->options.Equil,NULL);
605:   PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);
606:   if (flg) lu->options.ColPerm = (colperm_t)indx;
607:   PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);
608:   if (flg) lu->options.IterRefine = (IterRefine_t)indx;
609:   PetscOptionsBool("-mat_superlu_symmetricmode","SymmetricMode","None",(PetscBool)lu->options.SymmetricMode,&flg,&set);
610:   if (set && flg) lu->options.SymmetricMode = YES;
611:   PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&real_input,&flg);
612:   if (flg) lu->options.DiagPivotThresh = (double) real_input;
613:   PetscOptionsBool("-mat_superlu_pivotgrowth","PivotGrowth","None",(PetscBool)lu->options.PivotGrowth,&flg,&set);
614:   if (set && flg) lu->options.PivotGrowth = YES;
615:   PetscOptionsBool("-mat_superlu_conditionnumber","ConditionNumber","None",(PetscBool)lu->options.ConditionNumber,&flg,&set);
616:   if (set && flg) lu->options.ConditionNumber = YES;
617:   PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[lu->options.RowPerm],&indx,&flg);
618:   if (flg) lu->options.RowPerm = (rowperm_t)indx;
619:   PetscOptionsBool("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",(PetscBool)lu->options.ReplaceTinyPivot,&flg,&set);
620:   if (set && flg) lu->options.ReplaceTinyPivot = YES;
621:   PetscOptionsBool("-mat_superlu_printstat","PrintStat","None",(PetscBool)lu->options.PrintStat,&flg,&set);
622:   if (set && flg) lu->options.PrintStat = YES;
623:   PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,NULL);
624:   if (lu->lwork > 0) {
625:     /* lwork is in bytes, hence PetscMalloc() is used here, not PetscMalloc1()*/
626:     PetscMalloc(lu->lwork,&lu->work);
627:   } else if (lu->lwork != 0 && lu->lwork != -1) {
628:     PetscPrintf(PETSC_COMM_SELF,"   Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork);
629:     lu->lwork = 0;
630:   }
631:   /* ilu options */
632:   PetscOptionsReal("-mat_superlu_ilu_droptol","ILU_DropTol","None",lu->options.ILU_DropTol,&real_input,&flg);
633:   if (flg) lu->options.ILU_DropTol = (double) real_input;
634:   PetscOptionsReal("-mat_superlu_ilu_filltol","ILU_FillTol","None",lu->options.ILU_FillTol,&real_input,&flg);
635:   if (flg) lu->options.ILU_FillTol = (double) real_input;
636:   PetscOptionsReal("-mat_superlu_ilu_fillfactor","ILU_FillFactor","None",lu->options.ILU_FillFactor,&real_input,&flg);
637:   if (flg) lu->options.ILU_FillFactor = (double) real_input;
638:   PetscOptionsInt("-mat_superlu_ilu_droprull","ILU_DropRule","None",lu->options.ILU_DropRule,&lu->options.ILU_DropRule,NULL);
639:   PetscOptionsInt("-mat_superlu_ilu_norm","ILU_Norm","None",lu->options.ILU_Norm,&indx,&flg);
640:   if (flg) lu->options.ILU_Norm = (norm_t)indx;
641:   PetscOptionsInt("-mat_superlu_ilu_milu","ILU_MILU","None",lu->options.ILU_MILU,&indx,&flg);
642:   if (flg) lu->options.ILU_MILU = (milu_t)indx;
643:   PetscOptionsEnd();
644:   if (lu->options.Equil == YES) {
645:     /* superlu overwrites input matrix and rhs when Equil is used, thus create A_dup to keep user's A unchanged */
646:     MatDuplicate_SeqAIJ(A,MAT_COPY_VALUES,&lu->A_dup);
647:   }

649:   /* Allocate spaces (notice sizes are for the transpose) */
650:   PetscMalloc1(m,&lu->etree);
651:   PetscMalloc1(n,&lu->perm_r);
652:   PetscMalloc1(m,&lu->perm_c);
653:   PetscMalloc1(n,&lu->R);
654:   PetscMalloc1(m,&lu->C);

656:   /* create rhs and solution x without allocate space for .Store */
657: #if defined(PETSC_USE_COMPLEX)
658: #if defined(PETSC_USE_REAL_SINGLE)
659:   PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
660:   PetscStackCall("SuperLU:cCreate_Dense_Matrix(",cCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
661: #else
662:   PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
663:   PetscStackCall("SuperLU:zCreate_Dense_Matrix",zCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
664: #endif
665: #else
666: #if defined(PETSC_USE_REAL_SINGLE)
667:   PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
668:   PetscStackCall("SuperLU:sCreate_Dense_Matrix",sCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
669: #else
670:   PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
671:   PetscStackCall("SuperLU:dCreate_Dense_Matrix",dCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
672: #endif
673: #endif

675:   PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_seqaij_superlu);
676:   PetscObjectComposeFunction((PetscObject)B,"MatSuperluSetILUDropTol_C",MatSuperluSetILUDropTol_SuperLU);
677:   B->data  = lu;

679:   *F       = B;
680:   return(0);
681: }

683: PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_SuperLU(void)
684: {

688:   MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ,       MAT_FACTOR_LU,MatGetFactor_seqaij_superlu);
689:   MatSolverPackageRegister(MATSOLVERSUPERLU,MATSEQAIJ,       MAT_FACTOR_ILU,MatGetFactor_seqaij_superlu);
690:   return(0);
691: }