Actual source code: superlu.c

  2: /* 
  3:         Provides an interface to the SuperLU 3.0 sparse solver
  4: */

 6:  #include src/mat/impls/aij/seq/aij.h

  9: #if defined(PETSC_USE_COMPLEX)
 10: #include "zsp_defs.h"
 11: #else
 12: #include "dsp_defs.h"
 13: #endif  
 14: #include "util.h"

 17: typedef struct {
 18:   SuperMatrix       A,L,U,B,X;
 19:   superlu_options_t options;
 20:   int               *perm_c; /* column permutation vector */
 21:   int               *perm_r; /* row permutations from partial pivoting */
 22:   int               *etree;
 23:   double            *R, *C;
 24:   char              equed[1];
 25:   int               lwork;
 26:   void              *work;
 27:   double            rpg, rcond;
 28:   mem_usage_t       mem_usage;
 29:   MatStructure      flg;

 31:   /* A few function pointers for inheritance */
 32:   PetscErrorCode (*MatDuplicate)(Mat,MatDuplicateOption,Mat*);
 33:   PetscErrorCode (*MatView)(Mat,PetscViewer);
 34:   PetscErrorCode (*MatAssemblyEnd)(Mat,MatAssemblyType);
 35:   PetscErrorCode (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*);
 36:   PetscErrorCode (*MatDestroy)(Mat);

 38:   /* Flag to clean up (non-global) SuperLU objects during Destroy */
 39:   PetscTruth CleanUpSuperLU;
 40: } Mat_SuperLU;


 43: EXTERN PetscErrorCode MatFactorInfo_SuperLU(Mat,PetscViewer);
 44: EXTERN PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat,IS,IS,MatFactorInfo*,Mat*);

 47: EXTERN PetscErrorCode MatConvert_SuperLU_SeqAIJ(Mat,const MatType,Mat*);
 48: EXTERN PetscErrorCode MatConvert_SeqAIJ_SuperLU(Mat,const MatType,Mat*);

 53: PetscErrorCode MatDestroy_SuperLU(Mat A)
 54: {
 56:   Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr;

 59:   if (lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */
 60:     Destroy_SuperMatrix_Store(&lu->A);
 61:     Destroy_SuperMatrix_Store(&lu->B);
 62:     Destroy_SuperMatrix_Store(&lu->X);

 64:     PetscFree(lu->etree);
 65:     PetscFree(lu->perm_r);
 66:     PetscFree(lu->perm_c);
 67:     PetscFree(lu->R);
 68:     PetscFree(lu->C);
 69:     if ( lu->lwork >= 0 ) {
 70:       Destroy_SuperNode_Matrix(&lu->L);
 71:       Destroy_CompCol_Matrix(&lu->U);
 72:     }
 73:   }
 74:   MatConvert_SuperLU_SeqAIJ(A,MATSEQAIJ,&A);
 75:   (*A->ops->destroy)(A);
 76:   return(0);
 77: }

 81: PetscErrorCode MatView_SuperLU(Mat A,PetscViewer viewer)
 82: {
 84:   PetscTruth        iascii;
 85:   PetscViewerFormat format;
 86:   Mat_SuperLU       *lu=(Mat_SuperLU*)(A->spptr);

 89:   (*lu->MatView)(A,viewer);

 91:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
 92:   if (iascii) {
 93:     PetscViewerGetFormat(viewer,&format);
 94:     if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
 95:       MatFactorInfo_SuperLU(A,viewer);
 96:     }
 97:   }
 98:   return(0);
 99: }

103: PetscErrorCode MatAssemblyEnd_SuperLU(Mat A,MatAssemblyType mode) {
105:   Mat_SuperLU *lu=(Mat_SuperLU*)(A->spptr);

108:   (*lu->MatAssemblyEnd)(A,mode);

110:   lu->MatLUFactorSymbolic  = A->ops->lufactorsymbolic;
111:   A->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
112:   return(0);
113: }

115: /* This function was written for SuperLU 2.0 by Matthew Knepley. Not tested for SuperLU 3.0! */
116: #ifdef SuperLU2
117:  #include src/mat/impls/dense/seq/dense.h
120: PetscErrorCode MatCreateNull_SuperLU(Mat A,Mat *nullMat)
121: {
122:   Mat_SuperLU   *lu = (Mat_SuperLU*)A->spptr;
123:   int           numRows = A->m,numCols = A->n;
124:   SCformat      *Lstore;
125:   int           numNullCols,size;
126:   SuperLUStat_t stat;
127: #if defined(PETSC_USE_COMPLEX)
128:   doublecomplex *nullVals,*workVals;
129: #else
130:   PetscScalar   *nullVals,*workVals;
131: #endif
132:   int           row,newRow,col,newCol,block,b;

136:   if (!A->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Unfactored matrix");
137:   numNullCols = numCols - numRows;
138:   if (numNullCols < 0) SETERRQ(PETSC_ERR_ARG_WRONG,"Function only applies to underdetermined problems");
139:   /* Create the null matrix using MATSEQDENSE explicitly */
140:   MatCreate(A->comm,numRows,numNullCols,numRows,numNullCols,nullMat);
141:   MatSetType(*nullMat,MATSEQDENSE);
142:   MatSeqDenseSetPreallocation(*nullMat,PETSC_NULL);
143:   if (!numNullCols) {
144:     MatAssemblyBegin(*nullMat,MAT_FINAL_ASSEMBLY);
145:     MatAssemblyEnd(*nullMat,MAT_FINAL_ASSEMBLY);
146:     return(0);
147:   }
148: #if defined(PETSC_USE_COMPLEX)
149:   nullVals = (doublecomplex*)((Mat_SeqDense*)(*nullMat)->data)->v;
150: #else
151:   nullVals = ((Mat_SeqDense*)(*nullMat)->data)->v;
152: #endif
153:   /* Copy in the columns */
154:   Lstore = (SCformat*)lu->L.Store;
155:   for(block = 0; block <= Lstore->nsuper; block++) {
156:     newRow = Lstore->sup_to_col[block];
157:     size   = Lstore->sup_to_col[block+1] - Lstore->sup_to_col[block];
158:     for(col = Lstore->rowind_colptr[newRow]; col < Lstore->rowind_colptr[newRow+1]; col++) {
159:       newCol = Lstore->rowind[col];
160:       if (newCol >= numRows) {
161:         for(b = 0; b < size; b++)
162: #if defined(PETSC_USE_COMPLEX)
163:           nullVals[(newCol-numRows)*numRows+newRow+b] = ((doublecomplex*)Lstore->nzval)[Lstore->nzval_colptr[newRow+b]+col];
164: #else
165:           nullVals[(newCol-numRows)*numRows+newRow+b] = ((double*)Lstore->nzval)[Lstore->nzval_colptr[newRow+b]+col];
166: #endif
167:       }
168:     }
169:   }
170:   /* Permute rhs to form P^T_c B */
171:   PetscMalloc(numRows*sizeof(double),&workVals);
172:   for(b = 0; b < numNullCols; b++) {
173:     for(row = 0; row < numRows; row++) workVals[lu->perm_c[row]] = nullVals[b*numRows+row];
174:     for(row = 0; row < numRows; row++) nullVals[b*numRows+row]   = workVals[row];
175:   }
176:   /* Backward solve the upper triangle A x = b */
177:   for(b = 0; b < numNullCols; b++) {
178: #if defined(PETSC_USE_COMPLEX)
179:     sp_ztrsv("L","T","U",&lu->L,&lu->U,&nullVals[b*numRows],&stat,&ierr);
180: #else
181:     sp_dtrsv("L","T","U",&lu->L,&lu->U,&nullVals[b*numRows],&stat,&ierr);
182: #endif
183:     if (ierr < 0)
184:       SETERRQ1(PETSC_ERR_ARG_WRONG,"The argument %D was invalid",-ierr);
185:   }
186:   PetscFree(workVals);

188:   MatAssemblyBegin(*nullMat,MAT_FINAL_ASSEMBLY);
189:   MatAssemblyEnd(*nullMat,MAT_FINAL_ASSEMBLY);
190:   return(0);
191: }
192: #endif

196: PetscErrorCode MatSolve_SuperLU(Mat A,Vec b,Vec x)
197: {
198:   Mat_SuperLU   *lu = (Mat_SuperLU*)A->spptr;
199:   PetscScalar   *barray,*xarray;
201:   int           info,i;
202:   SuperLUStat_t stat;
203:   double        ferr,berr;

206:   if ( lu->lwork == -1 ) {
207:     return(0);
208:   }
209:   lu->B.ncol = 1;   /* Set the number of right-hand side */
210:   VecGetArray(b,&barray);
211:   VecGetArray(x,&xarray);

213: #if defined(PETSC_USE_COMPLEX)
214:   ((DNformat*)lu->B.Store)->nzval = (doublecomplex*)barray;
215:   ((DNformat*)lu->X.Store)->nzval = (doublecomplex*)xarray;
216: #else
217:   ((DNformat*)lu->B.Store)->nzval = barray;
218:   ((DNformat*)lu->X.Store)->nzval = xarray;
219: #endif

221:   /* Initialize the statistics variables. */
222:   StatInit(&stat);

224:   lu->options.Fact  = FACTORED; /* Indicate the factored form of A is supplied. */
225:   lu->options.Trans = TRANS;
226: #if defined(PETSC_USE_COMPLEX)
227:   zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
228:            &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
229:            &lu->mem_usage, &stat, &info);
230: #else
231:   dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
232:            &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
233:            &lu->mem_usage, &stat, &info);
234: #endif   
235:   VecRestoreArray(b,&barray);
236:   VecRestoreArray(x,&xarray);

238:   if ( !info || info == lu->A.ncol+1 ) {
239:     if ( lu->options.IterRefine ) {
240:       PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n");
241:       PetscPrintf(PETSC_COMM_SELF,"  %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR");
242:       for (i = 0; i < 1; ++i)
243:         PetscPrintf(PETSC_COMM_SELF,"  %8d%8d%16e%16e\n", i+1, stat.RefineSteps, ferr, berr);
244:     }
245:   } else if ( info > 0 ){
246:     if ( lu->lwork == -1 ) {
247:       PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %D bytes\n", info - lu->A.ncol);
248:     } else {
249:       PetscPrintf(PETSC_COMM_SELF,"  Warning: gssvx() returns info %D\n",info);
250:     }
251:   } else if (info < 0){
252:     SETERRQ2(PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", info,-info);
253:   }

255:   if ( lu->options.PrintStat ) {
256:     PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n");
257:     StatPrint(&stat);
258:   }
259:   StatFree(&stat);
260:   return(0);
261: }

265: PetscErrorCode MatLUFactorNumeric_SuperLU(Mat A,Mat *F)
266: {
267:   Mat_SeqAIJ    *aa = (Mat_SeqAIJ*)(A)->data;
268:   Mat_SuperLU   *lu = (Mat_SuperLU*)(*F)->spptr;
270:   int           info;
271:   SuperLUStat_t stat;
272:   double        ferr, berr;
273:   NCformat      *Ustore;
274:   SCformat      *Lstore;
275: 
277:   if (lu->flg == SAME_NONZERO_PATTERN){ /* successing numerical factorization */
278:     lu->options.Fact = SamePattern;
279:     /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */
280:     Destroy_SuperMatrix_Store(&lu->A);
281:     if ( lu->lwork >= 0 ) {
282:       Destroy_SuperNode_Matrix(&lu->L);
283:       Destroy_CompCol_Matrix(&lu->U);
284:       lu->options.Fact = SamePattern;
285:     }
286:   }

288:   /* Create the SuperMatrix for lu->A=A^T:
289:        Since SuperLU likes column-oriented matrices,we pass it the transpose,
290:        and then solve A^T X = B in MatSolve(). */
291: #if defined(PETSC_USE_COMPLEX)
292:   zCreate_CompCol_Matrix(&lu->A,A->n,A->m,aa->nz,(doublecomplex*)aa->a,aa->j,aa->i,
293:                            SLU_NC,SLU_Z,SLU_GE);
294: #else
295:   dCreate_CompCol_Matrix(&lu->A,A->n,A->m,aa->nz,aa->a,aa->j,aa->i,
296:                            SLU_NC,SLU_D,SLU_GE);
297: #endif
298: 
299:   /* Initialize the statistics variables. */
300:   StatInit(&stat);

302:   /* Numerical factorization */
303:   lu->B.ncol = 0;  /* Indicate not to solve the system */
304: #if defined(PETSC_USE_COMPLEX)
305:    zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
306:            &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
307:            &lu->mem_usage, &stat, &info);
308: #else
309:   dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
310:            &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
311:            &lu->mem_usage, &stat, &info);
312: #endif
313:   if ( !info || info == lu->A.ncol+1 ) {
314:     if ( lu->options.PivotGrowth )
315:       PetscPrintf(PETSC_COMM_SELF,"  Recip. pivot growth = %e\n", lu->rpg);
316:     if ( lu->options.ConditionNumber )
317:       PetscPrintf(PETSC_COMM_SELF,"  Recip. condition number = %e\n", lu->rcond);
318:   } else if ( info > 0 ){
319:     if ( lu->lwork == -1 ) {
320:       PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %D bytes\n", info - lu->A.ncol);
321:     } else {
322:       PetscPrintf(PETSC_COMM_SELF,"  Warning: gssvx() returns info %D\n",info);
323:     }
324:   } else { /* info < 0 */
325:     SETERRQ2(PETSC_ERR_LIB, "info = %D, the %D-th argument in gssvx() had an illegal value", info,-info);
326:   }

328:   if ( lu->options.PrintStat ) {
329:     PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n");
330:     StatPrint(&stat);
331:     Lstore = (SCformat *) lu->L.Store;
332:     Ustore = (NCformat *) lu->U.Store;
333:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor L = %D\n", Lstore->nnz);
334:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor U = %D\n", Ustore->nnz);
335:     PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in L+U = %D\n", Lstore->nnz + Ustore->nnz - lu->A.ncol);
336:     PetscPrintf(PETSC_COMM_SELF,"  L\\U MB %.3f\ttotal MB needed %.3f\texpansions %D\n",
337:                lu->mem_usage.for_lu/1e6, lu->mem_usage.total_needed/1e6,
338:                lu->mem_usage.expansions);
339:   }
340:   StatFree(&stat);

342:   lu->flg = SAME_NONZERO_PATTERN;
343:   return(0);
344: }

346: /*
347:    Note the r permutation is ignored
348: */
351: PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F)
352: {
353:   Mat          B;
354:   Mat_SuperLU  *lu;
356:   int          m=A->m,n=A->n,indx;
357:   PetscTruth   flg;
358:   const char   *colperm[]={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */
359:   const char   *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"};
360:   const char   *rowperm[]={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */

363: 
364:   MatCreate(A->comm,A->m,A->n,PETSC_DETERMINE,PETSC_DETERMINE,&B);
365:   MatSetType(B,A->type_name);
366:   MatSeqAIJSetPreallocation(B,0,PETSC_NULL);

368:   B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU;
369:   B->ops->solve           = MatSolve_SuperLU;
370:   B->factor               = FACTOR_LU;
371:   B->assembled            = PETSC_TRUE;  /* required by -ksp_view */
372: 
373:   lu = (Mat_SuperLU*)(B->spptr);

375:   /* Set SuperLU options */
376:     /* the default values for options argument:
377:         options.Fact = DOFACT;
378:         options.Equil = YES;
379:             options.ColPerm = COLAMD;
380:         options.DiagPivotThresh = 1.0;
381:             options.Trans = NOTRANS;
382:             options.IterRefine = NOREFINE;
383:             options.SymmetricMode = NO;
384:             options.PivotGrowth = NO;
385:             options.ConditionNumber = NO;
386:             options.PrintStat = YES;
387:     */
388:   set_default_options(&lu->options);
389:   /* equilibration causes error in solve(), thus not supported here. See dgssvx.c for possible reason. */
390:   lu->options.Equil = NO;
391:   lu->options.PrintStat = NO;
392:   lu->lwork = 0;   /* allocate space internally by system malloc */

394:   PetscOptionsBegin(A->comm,A->prefix,"SuperLU Options","Mat");
395:   /* 
396:   PetscOptionsLogical("-mat_superlu_equil","Equil","None",PETSC_FALSE,&flg,0);
397:   if (flg) lu->options.Equil = YES; -- not supported by the interface !!!
398:   */
399:   PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);
400:   if (flg) {lu->options.ColPerm = (colperm_t)indx;}
401:   PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);
402:   if (flg) { lu->options.IterRefine = (IterRefine_t)indx;}
403:   PetscOptionsLogical("-mat_superlu_symmetricmode","SymmetricMode","None",PETSC_FALSE,&flg,0);
404:   if (flg) lu->options.SymmetricMode = YES;
405:   PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&lu->options.DiagPivotThresh,PETSC_NULL);
406:   PetscOptionsLogical("-mat_superlu_pivotgrowth","PivotGrowth","None",PETSC_FALSE,&flg,0);
407:   if (flg) lu->options.PivotGrowth = YES;
408:   PetscOptionsLogical("-mat_superlu_conditionnumber","ConditionNumber","None",PETSC_FALSE,&flg,0);
409:   if (flg) lu->options.ConditionNumber = YES;
410:   PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[0],&indx,&flg);
411:   if (flg) {lu->options.RowPerm = (rowperm_t)indx;}
412:   PetscOptionsLogical("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",PETSC_FALSE,&flg,0);
413:   if (flg) lu->options.ReplaceTinyPivot = YES;
414:   PetscOptionsLogical("-mat_superlu_printstat","PrintStat","None",PETSC_FALSE,&flg,0);
415:   if (flg) lu->options.PrintStat = YES;
416:   PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,PETSC_NULL);
417:   if (lu->lwork > 0 ){
418:     PetscMalloc(lu->lwork,&lu->work);
419:   } else if (lu->lwork != 0 && lu->lwork != -1){
420:     PetscPrintf(PETSC_COMM_SELF,"   Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork);
421:     lu->lwork = 0;
422:   }
423:   PetscOptionsEnd();

425: #ifdef SUPERLU2
426:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatCreateNull","MatCreateNull_SuperLU",
427:                                     (void(*)(void))MatCreateNull_SuperLU);
428: #endif

430:   /* Allocate spaces (notice sizes are for the transpose) */
431:   PetscMalloc(m*sizeof(int),&lu->etree);
432:   PetscMalloc(n*sizeof(int),&lu->perm_r);
433:   PetscMalloc(m*sizeof(int),&lu->perm_c);
434:   PetscMalloc(n*sizeof(int),&lu->R);
435:   PetscMalloc(m*sizeof(int),&lu->C);
436: 
437:   /* create rhs and solution x without allocate space for .Store */
438: #if defined(PETSC_USE_COMPLEX)
439:   zCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
440:   zCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
441: #else
442:   dCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
443:   dCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
444: #endif

446:   lu->flg            = DIFFERENT_NONZERO_PATTERN;
447:   lu->CleanUpSuperLU = PETSC_TRUE;

449:   *F = B;
450:   PetscLogObjectMemory(B,(A->m+A->n)*sizeof(int)+sizeof(Mat_SuperLU));
451:   return(0);
452: }

454: /* used by -ksp_view */
457: PetscErrorCode MatFactorInfo_SuperLU(Mat A,PetscViewer viewer)
458: {
459:   Mat_SuperLU       *lu= (Mat_SuperLU*)A->spptr;
460:   int               ierr;
461:   superlu_options_t options;

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

467:   options = lu->options;
468:   PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");
469:   PetscViewerASCIIPrintf(viewer,"  Equil: %s\n",(options.Equil != NO) ? "YES": "NO");
470:   PetscViewerASCIIPrintf(viewer,"  ColPerm: %D\n",options.ColPerm);
471:   PetscViewerASCIIPrintf(viewer,"  IterRefine: %D\n",options.IterRefine);
472:   PetscViewerASCIIPrintf(viewer,"  SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES": "NO");
473:   PetscViewerASCIIPrintf(viewer,"  DiagPivotThresh: %g\n",options.DiagPivotThresh);
474:   PetscViewerASCIIPrintf(viewer,"  PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES": "NO");
475:   PetscViewerASCIIPrintf(viewer,"  ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES": "NO");
476:   PetscViewerASCIIPrintf(viewer,"  RowPerm: %D\n",options.RowPerm);
477:   PetscViewerASCIIPrintf(viewer,"  ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES": "NO");
478:   PetscViewerASCIIPrintf(viewer,"  PrintStat: %s\n",(options.PrintStat != NO) ? "YES": "NO");
479:   PetscViewerASCIIPrintf(viewer,"  lwork: %D\n",lu->lwork);

481:   return(0);
482: }

486: PetscErrorCode MatDuplicate_SuperLU(Mat A, MatDuplicateOption op, Mat *M) {
487:   int         ierr;
488:   Mat_SuperLU *lu=(Mat_SuperLU *)A->spptr;

491:   (*lu->MatDuplicate)(A,op,M);
492:   PetscMemcpy((*M)->spptr,lu,sizeof(Mat_SuperLU));
493:   return(0);
494: }

499: PetscErrorCode MatConvert_SuperLU_SeqAIJ(Mat A,const MatType type,Mat *newmat)
500: {
501:   /* This routine is only called to convert an unfactored PETSc-SuperLU matrix */
502:   /* to its base PETSc type, so we will ignore 'MatType type'. */
503:   int                  ierr;
504:   Mat                  B=*newmat;
505:   Mat_SuperLU   *lu=(Mat_SuperLU *)A->spptr;

508:   if (B != A) {
509:     MatDuplicate(A,MAT_COPY_VALUES,&B);
510:   }
511:   /* Reset the original function pointers */
512:   B->ops->duplicate        = lu->MatDuplicate;
513:   B->ops->view             = lu->MatView;
514:   B->ops->assemblyend      = lu->MatAssemblyEnd;
515:   B->ops->lufactorsymbolic = lu->MatLUFactorSymbolic;
516:   B->ops->destroy          = lu->MatDestroy;
517:   /* lu is only a function pointer stash unless we've factored the matrix, which we haven't! */
518:   PetscFree(lu);

520:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_superlu_C","",PETSC_NULL);
521:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_superlu_seqaij_C","",PETSC_NULL);

523:   PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);
524:   *newmat = B;
525:   return(0);
526: }

532: PetscErrorCode MatConvert_SeqAIJ_SuperLU(Mat A,const MatType type,Mat *newmat)
533: {
534:   /* This routine is only called to convert to MATSUPERLU */
535:   /* from MATSEQAIJ, so we will ignore 'MatType type'. */
536:   int         ierr;
537:   Mat         B=*newmat;
538:   Mat_SuperLU *lu;

541:   if (B != A) {
542:     MatDuplicate(A,MAT_COPY_VALUES,&B);
543:   }

545:   PetscNew(Mat_SuperLU,&lu);
546:   lu->MatDuplicate         = A->ops->duplicate;
547:   lu->MatView              = A->ops->view;
548:   lu->MatAssemblyEnd       = A->ops->assemblyend;
549:   lu->MatLUFactorSymbolic  = A->ops->lufactorsymbolic;
550:   lu->MatDestroy           = A->ops->destroy;
551:   lu->CleanUpSuperLU       = PETSC_FALSE;

553:   B->spptr                 = (void*)lu;
554:   B->ops->duplicate        = MatDuplicate_SuperLU;
555:   B->ops->view             = MatView_SuperLU;
556:   B->ops->assemblyend      = MatAssemblyEnd_SuperLU;
557:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
558:   B->ops->choleskyfactorsymbolic = 0;
559:   B->ops->destroy          = MatDestroy_SuperLU;

561:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_superlu_C",
562:                                            "MatConvert_SeqAIJ_SuperLU",MatConvert_SeqAIJ_SuperLU);
563:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_seqaij_C",
564:                                            "MatConvert_SuperLU_SeqAIJ",MatConvert_SuperLU_SeqAIJ);
565:   PetscLogInfo(0,"Using SuperLU for SeqAIJ LU factorization and solves.");
566:   PetscObjectChangeTypeName((PetscObject)B,MATSUPERLU);
567:   *newmat = B;
568:   return(0);
569: }

572: /*MC
573:   MATSUPERLU - MATSUPERLU = "superlu" - A matrix type providing direct solvers (LU) for sequential matrices 
574:   via the external package SuperLU.

576:   If SuperLU is installed (see the manual for
577:   instructions on how to declare the existence of external packages),
578:   a matrix type can be constructed which invokes SuperLU solvers.
579:   After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU).
580:   This matrix type is only supported for double precision real.

582:   This matrix inherits from MATSEQAIJ.  As a result, MatSeqAIJSetPreallocation is 
583:   supported for this matrix type.  One can also call MatConvert for an inplace conversion to or from 
584:   the MATSEQAIJ type without data copy.

586:   Options Database Keys:
587: + -mat_type superlu - sets the matrix type to "superlu" during a call to MatSetFromOptions()
588: - -mat_superlu_ordering <0,1,2,3> - 0: natural ordering, 
589:                                     1: MMD applied to A'*A, 
590:                                     2: MMD applied to A'+A, 
591:                                     3: COLAMD, approximate minimum degree column ordering

593:    Level: beginner

595: .seealso: PCLU
596: M*/

601: PetscErrorCode MatCreate_SuperLU(Mat A)
602: {

606:   /* Change type name before calling MatSetType to force proper construction of SeqAIJ and SUPERLU types */
607:   PetscObjectChangeTypeName((PetscObject)A,MATSUPERLU);
608:   MatSetType(A,MATSEQAIJ);
609:   MatConvert_SeqAIJ_SuperLU(A,MATSUPERLU,&A);
610:   return(0);
611: }