Actual source code: lusol.c

  1: #define PETSCMAT_DLL

  3: /* 
  4:         Provides an interface to the LUSOL package of ....

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

  9: #if defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
 10: #define LU1FAC   lu1fac_
 11: #define LU6SOL   lu6sol_
 12: #define M1PAGE   m1page_
 13: #define M5SETX   m5setx_
 14: #define M6RDEL   m6rdel_
 15: #elif !defined(PETSC_HAVE_FORTRAN_CAPS)
 16: #define LU1FAC   lu1fac
 17: #define LU6SOL   lu6sol
 18: #define M1PAGE   m1page
 19: #define M5SETX   m5setx
 20: #define M6RDEL   m6rdel
 21: #endif

 24: /*
 25:     Dummy symbols that the MINOS files mi25bfac.f and mi15blas.f may require
 26: */
 27: void PETSC_STDCALL M1PAGE() {
 28:   ;
 29: }
 30: void PETSC_STDCALL M5SETX() {
 31:   ;
 32: }

 34: void PETSC_STDCALL M6RDEL() {
 35:   ;
 36: }

 39:                         double *parmlu, double *data, int *indc, int *indr,
 40:                         int *rowperm, int *colperm, int *collen, int *rowlen,
 41:                         int *colstart, int *rowstart, int *rploc, int *cploc,
 42:                         int *rpinv, int *cpinv, double *w, int *inform);

 45:                         int *size, int *luparm, double *parmlu, double *data,
 46:                         int *indc, int *indr, int *rowperm, int *colperm,
 47:                         int *collen, int *rowlen, int *colstart, int *rowstart,
 48:                         int *inform);

 51: EXTERN PetscErrorCode MatDuplicate_LUSOL(Mat,MatDuplicateOption,Mat*);

 53: typedef struct  {
 54:   double *data;
 55:   int *indc;
 56:   int *indr;

 58:   int *ip;
 59:   int *iq;
 60:   int *lenc;
 61:   int *lenr;
 62:   int *locc;
 63:   int *locr;
 64:   int *iploc;
 65:   int *iqloc;
 66:   int *ipinv;
 67:   int *iqinv;
 68:   double *mnsw;
 69:   double *mnsv;

 71:   double elbowroom;
 72:   double luroom;                /* Extra space allocated when factor fails   */
 73:   double parmlu[30];                /* Input/output to LUSOL                     */

 75:   int n;                        /* Number of rows/columns in matrix          */
 76:   int nz;                        /* Number of nonzeros                        */
 77:   int nnz;                        /* Number of nonzeros allocated for factors  */
 78:   int luparm[30];                /* Input/output to LUSOL                     */

 80:   PetscTruth CleanUpLUSOL;

 82: } Mat_LUSOL;

 84: /*  LUSOL input/Output Parameters (Description uses C-style indexes
 85:  *
 86:  *  Input parameters                                        Typical value
 87:  *
 88:  *  luparm(0) = nout     File number for printed messages.         6
 89:  *  luparm(1) = lprint   Print level.                              0
 90:  *                    < 0 suppresses output.
 91:  *                    = 0 gives error messages.
 92:  *                    = 1 gives debug output from some of the
 93:  *                        other routines in LUSOL.
 94:  *                   >= 2 gives the pivot row and column and the
 95:  *                        no. of rows and columns involved at
 96:  *                        each elimination step in lu1fac.
 97:  *  luparm(2) = maxcol   lu1fac: maximum number of columns         5
 98:  *                        searched allowed in a Markowitz-type
 99:  *                        search for the next pivot element.
100:  *                        For some of the factorization, the
101:  *                        number of rows searched is
102:  *                        maxrow = maxcol - 1.
103:  *
104:  *
105:  *  Output parameters
106:  *
107:  *  luparm(9) = inform   Return code from last call to any LU routine.
108:  *  luparm(10) = nsing    No. of singularities marked in the
109:  *                        output array w(*).
110:  *  luparm(11) = jsing    Column index of last singularity.
111:  *  luparm(12) = minlen   Minimum recommended value for  lena.
112:  *  luparm(13) = maxlen   ?
113:  *  luparm(14) = nupdat   No. of updates performed by the lu8 routines.
114:  *  luparm(15) = nrank    No. of nonempty rows of U.
115:  *  luparm(16) = ndens1   No. of columns remaining when the density of
116:  *                        the matrix being factorized reached dens1.
117:  *  luparm(17) = ndens2   No. of columns remaining when the density of
118:  *                        the matrix being factorized reached dens2.
119:  *  luparm(18) = jumin    The column index associated with dumin.
120:  *  luparm(19) = numl0    No. of columns in initial  L.
121:  *  luparm(20) = lenl0    Size of initial  L  (no. of nonzeros).
122:  *  luparm(21) = lenu0    Size of initial  U.
123:  *  luparm(22) = lenl     Size of current  L.
124:  *  luparm(23) = lenu     Size of current  U.
125:  *  luparm(24) = lrow     Length of row file.
126:  *  luparm(25) = ncp      No. of compressions of LU data structures.
127:  *  luparm(26) = mersum   lu1fac: sum of Markowitz merit counts.
128:  *  luparm(27) = nutri    lu1fac: triangular rows in U.
129:  *  luparm(28) = nltri    lu1fac: triangular rows in L.
130:  *  luparm(29) =
131:  *
132:  *
133:  *  Input parameters                                        Typical value
134:  *
135:  *  parmlu(0) = elmax1   Max multiplier allowed in  L           10.0
136:  *                        during factor.
137:  *  parmlu(1) = elmax2   Max multiplier allowed in  L           10.0
138:  *                        during updates.
139:  *  parmlu(2) = small    Absolute tolerance for             eps**0.8
140:  *                        treating reals as zero.     IBM double: 3.0d-13
141:  *  parmlu(3) = utol1    Absolute tol for flagging          eps**0.66667
142:  *                        small diagonals of U.       IBM double: 3.7d-11
143:  *  parmlu(4) = utol2    Relative tol for flagging          eps**0.66667
144:  *                        small diagonals of U.       IBM double: 3.7d-11
145:  *  parmlu(5) = uspace   Factor limiting waste space in  U.      3.0
146:  *                        In lu1fac, the row or column lists
147:  *                        are compressed if their length
148:  *                        exceeds uspace times the length of
149:  *                        either file after the last compression.
150:  *  parmlu(6) = dens1    The density at which the Markowitz      0.3
151:  *                        strategy should search maxcol columns
152:  *                        and no rows.
153:  *  parmlu(7) = dens2    the density at which the Markowitz      0.6
154:  *                        strategy should search only 1 column
155:  *                        or (preferably) use a dense LU for
156:  *                        all the remaining rows and columns.
157:  *
158:  *
159:  *  Output parameters
160:  *
161:  *  parmlu(9) = amax     Maximum element in  A.
162:  *  parmlu(10) = elmax    Maximum multiplier in current  L.
163:  *  parmlu(11) = umax     Maximum element in current  U.
164:  *  parmlu(12) = dumax    Maximum diagonal in  U.
165:  *  parmlu(13) = dumin    Minimum diagonal in  U.
166:  *  parmlu(14) =
167:  *  parmlu(15) =
168:  *  parmlu(16) =
169:  *  parmlu(17) =
170:  *  parmlu(18) =
171:  *  parmlu(19) = resid    lu6sol: residual after solve with U or U'.
172:  *  ...
173:  *  parmlu(29) =
174:  */

176: #define Factorization_Tolerance       1e-1
177: #define Factorization_Pivot_Tolerance pow(2.2204460492503131E-16, 2.0 / 3.0) 
178: #define Factorization_Small_Tolerance 1e-15 /* pow(DBL_EPSILON, 0.8) */

182: PetscErrorCode MatDestroy_LUSOL(Mat A)
183: {
185:   Mat_LUSOL      *lusol=(Mat_LUSOL *)A->spptr;

188:   if (lusol->CleanUpLUSOL) {
189:     PetscFree(lusol->ip);
190:     PetscFree(lusol->iq);
191:     PetscFree(lusol->lenc);
192:     PetscFree(lusol->lenr);
193:     PetscFree(lusol->locc);
194:     PetscFree(lusol->locr);
195:     PetscFree(lusol->iploc);
196:     PetscFree(lusol->iqloc);
197:     PetscFree(lusol->ipinv);
198:     PetscFree(lusol->iqinv);
199:     PetscFree(lusol->mnsw);
200:     PetscFree(lusol->mnsv);
201:     PetscFree(lusol->indc);
202:   }
203:   MatDestroy_SeqAIJ(A);
204:   return(0);
205: }

209: PetscErrorCode MatSolve_LUSOL(Mat A,Vec b,Vec x)
210: {
211:   Mat_LUSOL      *lusol=(Mat_LUSOL*)A->spptr;
212:   double         *bb,*xx;
213:   int            mode=5;
215:   int            i,m,n,nnz,status;

218:   VecGetArray(x, &xx);
219:   VecGetArray(b, &bb);

221:   m = n = lusol->n;
222:   nnz = lusol->nnz;

224:   for (i = 0; i < m; i++)
225:     {
226:       lusol->mnsv[i] = bb[i];
227:     }

229:   LU6SOL(&mode, &m, &n, lusol->mnsv, xx, &nnz,
230:          lusol->luparm, lusol->parmlu, lusol->data,
231:          lusol->indc, lusol->indr, lusol->ip, lusol->iq,
232:          lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, &status);

234:   if (status != 0) SETERRQ1(PETSC_ERR_ARG_SIZ,"solve failed, error code %d",status);

236:   VecRestoreArray(x, &xx);
237:   VecRestoreArray(b, &bb);
238:   return(0);
239: }

243: PetscErrorCode MatLUFactorNumeric_LUSOL(Mat F,Mat A,const MatFactorInfo *info)
244: {
245:   Mat_SeqAIJ     *a;
246:   Mat_LUSOL      *lusol = (Mat_LUSOL*)F->spptr;
248:   int            m, n, nz, nnz, status;
249:   int            i, rs, re;
250:   int            factorizations;

253:   MatGetSize(A,&m,&n);
254:   a = (Mat_SeqAIJ *)A->data;

256:   if (m != lusol->n) SETERRQ(PETSC_ERR_ARG_SIZ,"factorization struct inconsistent");

258:   factorizations = 0;
259:   do
260:     {
261:       /*******************************************************************/
262:       /* Check the workspace allocation.                                 */
263:       /*******************************************************************/

265:       nz = a->nz;
266:       nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom*nz));
267:       nnz = PetscMax(nnz, 5*n);

269:       if (nnz < lusol->luparm[12]){
270:         nnz = (int)(lusol->luroom * lusol->luparm[12]);
271:       } else if ((factorizations > 0) && (lusol->luroom < 6)){
272:         lusol->luroom += 0.1;
273:       }

275:       nnz = PetscMax(nnz, (int)(lusol->luroom*(lusol->luparm[22] + lusol->luparm[23])));

277:       if (nnz > lusol->nnz){
278:         PetscFree(lusol->indc);
279:         PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
280:         lusol->indr = lusol->indc + nnz;
281:         lusol->data = (double *)(lusol->indr + nnz);
282:         lusol->nnz  = nnz;
283:       }

285:       /*******************************************************************/
286:       /* Fill in the data for the problem.      (1-based Fortran style)  */
287:       /*******************************************************************/

289:       nz = 0;
290:       for (i = 0; i < n; i++)
291:         {
292:           rs = a->i[i];
293:           re = a->i[i+1];

295:           while (rs < re)
296:             {
297:               if (a->a[rs] != 0.0)
298:                 {
299:                   lusol->indc[nz] = i + 1;
300:                   lusol->indr[nz] = a->j[rs] + 1;
301:                   lusol->data[nz] = a->a[rs];
302:                   nz++;
303:                 }
304:               rs++;
305:             }
306:         }

308:       /*******************************************************************/
309:       /* Do the factorization.                                           */
310:       /*******************************************************************/

312:       LU1FAC(&m, &n, &nz, &nnz,
313:              lusol->luparm, lusol->parmlu, lusol->data,
314:              lusol->indc, lusol->indr, lusol->ip, lusol->iq,
315:              lusol->lenc, lusol->lenr, lusol->locc, lusol->locr,
316:              lusol->iploc, lusol->iqloc, lusol->ipinv,
317:              lusol->iqinv, lusol->mnsw, &status);
318: 
319:       switch(status)
320:         {
321:         case 0:                /* factored */
322:           break;

324:         case 7:                /* insufficient memory */
325:           break;

327:         case 1:
328:         case -1:                /* singular */
329:           SETERRQ(PETSC_ERR_LIB,"Singular matrix");

331:         case 3:
332:         case 4:                /* error conditions */
333:           SETERRQ(PETSC_ERR_LIB,"matrix error");

335:         default:                /* unknown condition */
336:           SETERRQ(PETSC_ERR_LIB,"matrix unknown return code");
337:         }

339:       factorizations++;
340:     } while (status == 7);
341:   F->ops->solve   = MatSolve_LUSOL;
342:   F->assembled    = PETSC_TRUE;
343:   F->preallocated = PETSC_TRUE;
344:   return(0);
345: }

349: PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat F,Mat A, IS r, IS c,const MatFactorInfo *info)
350: {
351:   /************************************************************************/
352:   /* Input                                                                */
353:   /*     A  - matrix to factor                                            */
354:   /*     r  - row permutation (ignored)                                   */
355:   /*     c  - column permutation (ignored)                                */
356:   /*                                                                      */
357:   /* Output                                                               */
358:   /*     F  - matrix storing the factorization;                           */
359:   /************************************************************************/
360:   Mat_LUSOL      *lusol;
362:   int            i, m, n, nz, nnz;

365: 
366:   /************************************************************************/
367:   /* Check the arguments.                                                 */
368:   /************************************************************************/

370:   MatGetSize(A, &m, &n);
371:   nz = ((Mat_SeqAIJ *)A->data)->nz;

373:   /************************************************************************/
374:   /* Create the factorization.                                            */
375:   /************************************************************************/

377:   F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL;
378:   lusol                   = (Mat_LUSOL*)(F->spptr);

380:   /************************************************************************/
381:   /* Initialize parameters                                                */
382:   /************************************************************************/

384:   for (i = 0; i < 30; i++)
385:     {
386:       lusol->luparm[i] = 0;
387:       lusol->parmlu[i] = 0;
388:     }

390:   lusol->luparm[1] = -1;
391:   lusol->luparm[2] = 5;
392:   lusol->luparm[7] = 1;

394:   lusol->parmlu[0] = 1 / Factorization_Tolerance;
395:   lusol->parmlu[1] = 1 / Factorization_Tolerance;
396:   lusol->parmlu[2] = Factorization_Small_Tolerance;
397:   lusol->parmlu[3] = Factorization_Pivot_Tolerance;
398:   lusol->parmlu[4] = Factorization_Pivot_Tolerance;
399:   lusol->parmlu[5] = 3.0;
400:   lusol->parmlu[6] = 0.3;
401:   lusol->parmlu[7] = 0.6;

403:   /************************************************************************/
404:   /* Allocate the workspace needed by LUSOL.                              */
405:   /************************************************************************/

407:   lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill);
408:   nnz = PetscMax((int)(lusol->elbowroom*nz), 5*n);
409: 
410:   lusol->n = n;
411:   lusol->nz = nz;
412:   lusol->nnz = nnz;
413:   lusol->luroom = 1.75;

415:   PetscMalloc(sizeof(int)*n,&lusol->ip);
416:   PetscMalloc(sizeof(int)*n,&lusol->iq);
417:   PetscMalloc(sizeof(int)*n,&lusol->lenc);
418:   PetscMalloc(sizeof(int)*n,&lusol->lenr);
419:   PetscMalloc(sizeof(int)*n,&lusol->locc);
420:   PetscMalloc(sizeof(int)*n,&lusol->locr);
421:   PetscMalloc(sizeof(int)*n,&lusol->iploc);
422:   PetscMalloc(sizeof(int)*n,&lusol->iqloc);
423:   PetscMalloc(sizeof(int)*n,&lusol->ipinv);
424:   PetscMalloc(sizeof(int)*n,&lusol->iqinv);
425:   PetscMalloc(sizeof(double)*n,&lusol->mnsw);
426:   PetscMalloc(sizeof(double)*n,&lusol->mnsv);

428:   PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
429:   lusol->indr = lusol->indc + nnz;
430:   lusol->data = (double *)(lusol->indr + nnz);
431:   lusol->CleanUpLUSOL = PETSC_TRUE;
432:   F->ops->lufactornumeric  = MatLUFactorNumeric_LUSOL;
433:   return(0);
434: }

439: PetscErrorCode MatFactorGetSolverPackage_seqaij_lusol(Mat A,const MatSolverPackage *type)
440: {
442:   *type = MAT_SOLVER_LUSOL;
443:   return(0);
444: }

449: PetscErrorCode MatGetFactor_seqaij_lusol(Mat A,MatFactorType ftype,Mat *F)
450: {
451:   Mat            B;
452:   Mat_LUSOL      *lusol;
454:   int            m, n;

457:   MatGetSize(A, &m, &n);
458:   MatCreate(((PetscObject)A)->comm,&B);
459:   MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,m,n);
460:   MatSetType(B,((PetscObject)A)->type_name);
461:   MatSeqAIJSetPreallocation(B,0,PETSC_NULL);

463:   PetscNewLog(B,Mat_LUSOL,&lusol);
464:   B->spptr                 = lusol;

466:   B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL;
467:   B->ops->destroy          = MatDestroy_LUSOL;
468:   PetscObjectComposeFunctionDynamic((PetscObject)B,"MatFactorGetSolverPackage_C","MatFactorGetSolverPackage_seqaij_lusol",MatFactorGetSolverPackage_seqaij_lusol);
469:   B->factor                = MAT_FACTOR_LU;
470:   return(0);
471: }

473: /*MC
474:   MAT_SOLVER_LUSOL - "lusol" - Provides direct solvers (LU) for sequential matrices 
475:                          via the external package LUSOL.

477:   If LUSOL is installed (see the manual for
478:   instructions on how to declare the existence of external packages),

480:   Works with MATSEQAIJ matrices

482:    Level: beginner

484: .seealso: PCLU, PCFactorSetMatSolverPackage(), MatSolverPackage

486: M*/