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: PetscErrorCode (*MatDuplicate)(Mat,MatDuplicateOption,Mat*);
81: PetscErrorCode (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*);
82: PetscErrorCode (*MatDestroy)(Mat);
83: PetscTruth CleanUpLUSOL;
85: } Mat_LUSOL;
87: /* LUSOL input/Output Parameters (Description uses C-style indexes
88: *
89: * Input parameters Typical value
90: *
91: * luparm(0) = nout File number for printed messages. 6
92: * luparm(1) = lprint Print level. 0
93: * < 0 suppresses output.
94: * = 0 gives error messages.
95: * = 1 gives debug output from some of the
96: * other routines in LUSOL.
97: * >= 2 gives the pivot row and column and the
98: * no. of rows and columns involved at
99: * each elimination step in lu1fac.
100: * luparm(2) = maxcol lu1fac: maximum number of columns 5
101: * searched allowed in a Markowitz-type
102: * search for the next pivot element.
103: * For some of the factorization, the
104: * number of rows searched is
105: * maxrow = maxcol - 1.
106: *
107: *
108: * Output parameters
109: *
110: * luparm(9) = inform Return code from last call to any LU routine.
111: * luparm(10) = nsing No. of singularities marked in the
112: * output array w(*).
113: * luparm(11) = jsing Column index of last singularity.
114: * luparm(12) = minlen Minimum recommended value for lena.
115: * luparm(13) = maxlen ?
116: * luparm(14) = nupdat No. of updates performed by the lu8 routines.
117: * luparm(15) = nrank No. of nonempty rows of U.
118: * luparm(16) = ndens1 No. of columns remaining when the density of
119: * the matrix being factorized reached dens1.
120: * luparm(17) = ndens2 No. of columns remaining when the density of
121: * the matrix being factorized reached dens2.
122: * luparm(18) = jumin The column index associated with dumin.
123: * luparm(19) = numl0 No. of columns in initial L.
124: * luparm(20) = lenl0 Size of initial L (no. of nonzeros).
125: * luparm(21) = lenu0 Size of initial U.
126: * luparm(22) = lenl Size of current L.
127: * luparm(23) = lenu Size of current U.
128: * luparm(24) = lrow Length of row file.
129: * luparm(25) = ncp No. of compressions of LU data structures.
130: * luparm(26) = mersum lu1fac: sum of Markowitz merit counts.
131: * luparm(27) = nutri lu1fac: triangular rows in U.
132: * luparm(28) = nltri lu1fac: triangular rows in L.
133: * luparm(29) =
134: *
135: *
136: * Input parameters Typical value
137: *
138: * parmlu(0) = elmax1 Max multiplier allowed in L 10.0
139: * during factor.
140: * parmlu(1) = elmax2 Max multiplier allowed in L 10.0
141: * during updates.
142: * parmlu(2) = small Absolute tolerance for eps**0.8
143: * treating reals as zero. IBM double: 3.0d-13
144: * parmlu(3) = utol1 Absolute tol for flagging eps**0.66667
145: * small diagonals of U. IBM double: 3.7d-11
146: * parmlu(4) = utol2 Relative tol for flagging eps**0.66667
147: * small diagonals of U. IBM double: 3.7d-11
148: * parmlu(5) = uspace Factor limiting waste space in U. 3.0
149: * In lu1fac, the row or column lists
150: * are compressed if their length
151: * exceeds uspace times the length of
152: * either file after the last compression.
153: * parmlu(6) = dens1 The density at which the Markowitz 0.3
154: * strategy should search maxcol columns
155: * and no rows.
156: * parmlu(7) = dens2 the density at which the Markowitz 0.6
157: * strategy should search only 1 column
158: * or (preferably) use a dense LU for
159: * all the remaining rows and columns.
160: *
161: *
162: * Output parameters
163: *
164: * parmlu(9) = amax Maximum element in A.
165: * parmlu(10) = elmax Maximum multiplier in current L.
166: * parmlu(11) = umax Maximum element in current U.
167: * parmlu(12) = dumax Maximum diagonal in U.
168: * parmlu(13) = dumin Minimum diagonal in U.
169: * parmlu(14) =
170: * parmlu(15) =
171: * parmlu(16) =
172: * parmlu(17) =
173: * parmlu(18) =
174: * parmlu(19) = resid lu6sol: residual after solve with U or U'.
175: * ...
176: * parmlu(29) =
177: */
179: #define Factorization_Tolerance 1e-1
180: #define Factorization_Pivot_Tolerance pow(2.2204460492503131E-16, 2.0 / 3.0)
181: #define Factorization_Small_Tolerance 1e-15 /* pow(DBL_EPSILON, 0.8) */
186: PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_LUSOL_SeqAIJ(Mat A,const MatType type,MatReuse reuse,Mat *newmat)
187: {
188: /* This routine is only called to convert an unfactored PETSc-LUSOL matrix */
189: /* to its base PETSc type, so we will ignore 'MatType type'. */
191: Mat B=*newmat;
192: Mat_LUSOL *lusol=(Mat_LUSOL *)A->spptr;
195: if (reuse == MAT_INITIAL_MATRIX) {
196: MatDuplicate(A,MAT_COPY_VALUES,&B);
197: }
198: B->ops->duplicate = lusol->MatDuplicate;
199: B->ops->lufactorsymbolic = lusol->MatLUFactorSymbolic;
200: B->ops->destroy = lusol->MatDestroy;
201:
202: PetscFree(lusol);
204: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_lusol_C","",PETSC_NULL);
205: PetscObjectComposeFunction((PetscObject)B,"MatConvert_lusol_seqaij_C","",PETSC_NULL);
207: PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);
208: *newmat = B;
209: return(0);
210: }
215: PetscErrorCode MatDestroy_LUSOL(Mat A)
216: {
218: Mat_LUSOL *lusol=(Mat_LUSOL *)A->spptr;
221: if (lusol->CleanUpLUSOL) {
222: PetscFree(lusol->ip);
223: PetscFree(lusol->iq);
224: PetscFree(lusol->lenc);
225: PetscFree(lusol->lenr);
226: PetscFree(lusol->locc);
227: PetscFree(lusol->locr);
228: PetscFree(lusol->iploc);
229: PetscFree(lusol->iqloc);
230: PetscFree(lusol->ipinv);
231: PetscFree(lusol->iqinv);
232: PetscFree(lusol->mnsw);
233: PetscFree(lusol->mnsv);
234: PetscFree(lusol->indc);
235: }
237: MatConvert_LUSOL_SeqAIJ(A,MATSEQAIJ,MAT_REUSE_MATRIX,&A);
238: (*A->ops->destroy)(A);
239: return(0);
240: }
244: PetscErrorCode MatSolve_LUSOL(Mat A,Vec b,Vec x)
245: {
246: Mat_LUSOL *lusol=(Mat_LUSOL*)A->spptr;
247: double *bb,*xx;
248: int mode=5;
250: int i,m,n,nnz,status;
253: VecGetArray(x, &xx);
254: VecGetArray(b, &bb);
256: m = n = lusol->n;
257: nnz = lusol->nnz;
259: for (i = 0; i < m; i++)
260: {
261: lusol->mnsv[i] = bb[i];
262: }
264: LU6SOL(&mode, &m, &n, lusol->mnsv, xx, &nnz,
265: lusol->luparm, lusol->parmlu, lusol->data,
266: lusol->indc, lusol->indr, lusol->ip, lusol->iq,
267: lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, &status);
269: if (status != 0)
270: {
271: SETERRQ(PETSC_ERR_ARG_SIZ,"solve failed");
272: }
274: VecRestoreArray(x, &xx);
275: VecRestoreArray(b, &bb);
276: return(0);
277: }
281: PetscErrorCode MatLUFactorNumeric_LUSOL(Mat A,MatFactorInfo *info,Mat *F)
282: {
283: Mat_SeqAIJ *a;
284: Mat_LUSOL *lusol = (Mat_LUSOL*)(*F)->spptr;
286: int m, n, nz, nnz, status;
287: int i, rs, re;
288: int factorizations;
291: MatGetSize(A,&m,&n);
292: a = (Mat_SeqAIJ *)A->data;
294: if (m != lusol->n) {
295: SETERRQ(PETSC_ERR_ARG_SIZ,"factorization struct inconsistent");
296: }
298: factorizations = 0;
299: do
300: {
301: /*******************************************************************/
302: /* Check the workspace allocation. */
303: /*******************************************************************/
305: nz = a->nz;
306: nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom*nz));
307: nnz = PetscMax(nnz, 5*n);
309: if (nnz < lusol->luparm[12]){
310: nnz = (int)(lusol->luroom * lusol->luparm[12]);
311: } else if ((factorizations > 0) && (lusol->luroom < 6)){
312: lusol->luroom += 0.1;
313: }
315: nnz = PetscMax(nnz, (int)(lusol->luroom*(lusol->luparm[22] + lusol->luparm[23])));
317: if (nnz > lusol->nnz){
318: PetscFree(lusol->indc);
319: PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
320: lusol->indr = lusol->indc + nnz;
321: lusol->data = (double *)(lusol->indr + nnz);
322: lusol->nnz = nnz;
323: }
325: /*******************************************************************/
326: /* Fill in the data for the problem. (1-based Fortran style) */
327: /*******************************************************************/
329: nz = 0;
330: for (i = 0; i < n; i++)
331: {
332: rs = a->i[i];
333: re = a->i[i+1];
335: while (rs < re)
336: {
337: if (a->a[rs] != 0.0)
338: {
339: lusol->indc[nz] = i + 1;
340: lusol->indr[nz] = a->j[rs] + 1;
341: lusol->data[nz] = a->a[rs];
342: nz++;
343: }
344: rs++;
345: }
346: }
348: /*******************************************************************/
349: /* Do the factorization. */
350: /*******************************************************************/
352: LU1FAC(&m, &n, &nz, &nnz,
353: lusol->luparm, lusol->parmlu, lusol->data,
354: lusol->indc, lusol->indr, lusol->ip, lusol->iq,
355: lusol->lenc, lusol->lenr, lusol->locc, lusol->locr,
356: lusol->iploc, lusol->iqloc, lusol->ipinv,
357: lusol->iqinv, lusol->mnsw, &status);
358:
359: switch(status)
360: {
361: case 0: /* factored */
362: break;
364: case 7: /* insufficient memory */
365: break;
367: case 1:
368: case -1: /* singular */
369: SETERRQ(PETSC_ERR_LIB,"Singular matrix");
371: case 3:
372: case 4: /* error conditions */
373: SETERRQ(PETSC_ERR_LIB,"matrix error");
375: default: /* unknown condition */
376: SETERRQ(PETSC_ERR_LIB,"matrix unknown return code");
377: }
379: factorizations++;
380: } while (status == 7);
381: (*F)->assembled = PETSC_TRUE;
382: return(0);
383: }
387: PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat A, IS r, IS c,MatFactorInfo *info, Mat *F) {
388: /************************************************************************/
389: /* Input */
390: /* A - matrix to factor */
391: /* r - row permutation (ignored) */
392: /* c - column permutation (ignored) */
393: /* */
394: /* Output */
395: /* F - matrix storing the factorization; */
396: /************************************************************************/
397: Mat B;
398: Mat_LUSOL *lusol;
400: int i, m, n, nz, nnz;
403:
404: /************************************************************************/
405: /* Check the arguments. */
406: /************************************************************************/
408: MatGetSize(A, &m, &n);
409: nz = ((Mat_SeqAIJ *)A->data)->nz;
411: /************************************************************************/
412: /* Create the factorization. */
413: /************************************************************************/
415: MatCreate(A->comm,&B);
416: MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,m,n);
417: MatSetType(B,A->type_name);
418: MatSeqAIJSetPreallocation(B,0,PETSC_NULL);
420: B->ops->lufactornumeric = MatLUFactorNumeric_LUSOL;
421: B->ops->solve = MatSolve_LUSOL;
422: B->factor = FACTOR_LU;
423: lusol = (Mat_LUSOL*)(B->spptr);
425: /************************************************************************/
426: /* Initialize parameters */
427: /************************************************************************/
429: for (i = 0; i < 30; i++)
430: {
431: lusol->luparm[i] = 0;
432: lusol->parmlu[i] = 0;
433: }
435: lusol->luparm[1] = -1;
436: lusol->luparm[2] = 5;
437: lusol->luparm[7] = 1;
439: lusol->parmlu[0] = 1 / Factorization_Tolerance;
440: lusol->parmlu[1] = 1 / Factorization_Tolerance;
441: lusol->parmlu[2] = Factorization_Small_Tolerance;
442: lusol->parmlu[3] = Factorization_Pivot_Tolerance;
443: lusol->parmlu[4] = Factorization_Pivot_Tolerance;
444: lusol->parmlu[5] = 3.0;
445: lusol->parmlu[6] = 0.3;
446: lusol->parmlu[7] = 0.6;
448: /************************************************************************/
449: /* Allocate the workspace needed by LUSOL. */
450: /************************************************************************/
452: lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill);
453: nnz = PetscMax((int)(lusol->elbowroom*nz), 5*n);
454:
455: lusol->n = n;
456: lusol->nz = nz;
457: lusol->nnz = nnz;
458: lusol->luroom = 1.75;
460: PetscMalloc(sizeof(int)*n,&lusol->ip);
461: PetscMalloc(sizeof(int)*n,&lusol->iq);
462: PetscMalloc(sizeof(int)*n,&lusol->lenc);
463: PetscMalloc(sizeof(int)*n,&lusol->lenr);
464: PetscMalloc(sizeof(int)*n,&lusol->locc);
465: PetscMalloc(sizeof(int)*n,&lusol->locr);
466: PetscMalloc(sizeof(int)*n,&lusol->iploc);
467: PetscMalloc(sizeof(int)*n,&lusol->iqloc);
468: PetscMalloc(sizeof(int)*n,&lusol->ipinv);
469: PetscMalloc(sizeof(int)*n,&lusol->iqinv);
470: PetscMalloc(sizeof(double)*n,&lusol->mnsw);
471: PetscMalloc(sizeof(double)*n,&lusol->mnsv);
473: PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
474: lusol->indr = lusol->indc + nnz;
475: lusol->data = (double *)(lusol->indr + nnz);
476: lusol->CleanUpLUSOL = PETSC_TRUE;
477: *F = B;
478: return(0);
479: }
484: PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SeqAIJ_LUSOL(Mat A,const MatType type,MatReuse reuse,Mat *newmat)
485: {
487: PetscInt m, n;
488: Mat_LUSOL *lusol;
489: Mat B=*newmat;
492: MatGetSize(A, &m, &n);
493: if (m != n) {
494: SETERRQ(PETSC_ERR_ARG_SIZ,"matrix must be square");
495: }
496: if (reuse == MAT_INITIAL_MATRIX) {
497: MatDuplicate(A,MAT_COPY_VALUES,&B);
498: }
499:
500: PetscNew(Mat_LUSOL,&lusol);
501: lusol->MatDuplicate = A->ops->duplicate;
502: lusol->MatLUFactorSymbolic = A->ops->lufactorsymbolic;
503: lusol->MatDestroy = A->ops->destroy;
504: lusol->CleanUpLUSOL = PETSC_FALSE;
506: B->spptr = (void*)lusol;
507: B->ops->duplicate = MatDuplicate_LUSOL;
508: B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL;
509: B->ops->destroy = MatDestroy_LUSOL;
511: PetscInfo(0,"Using LUSOL for LU factorization and solves.\n");
512: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_lusol_C",
513: "MatConvert_SeqAIJ_LUSOL",MatConvert_SeqAIJ_LUSOL);
514: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_lusol_seqaij_C",
515: "MatConvert_LUSOL_SeqAIJ",MatConvert_LUSOL_SeqAIJ);
516: PetscObjectChangeTypeName((PetscObject)B,type);
517: *newmat = B;
518: return(0);
519: }
524: PetscErrorCode MatDuplicate_LUSOL(Mat A, MatDuplicateOption op, Mat *M) {
526: Mat_LUSOL *lu=(Mat_LUSOL *)A->spptr;
528: (*lu->MatDuplicate)(A,op,M);
529: PetscMemcpy((*M)->spptr,lu,sizeof(Mat_LUSOL));
530: return(0);
531: }
533: /*MC
534: MATLUSOL - MATLUSOL = "lusol" - A matrix type providing direct solvers (LU) for sequential matrices
535: via the external package LUSOL.
537: If LUSOL is installed (see the manual for
538: instructions on how to declare the existence of external packages),
539: a matrix type can be constructed which invokes LUSOL solvers.
540: After calling MatCreate(...,A), simply call MatSetType(A,MATLUSOL).
541: This matrix type is only supported for double precision real.
543: This matrix inherits from MATSEQAIJ. As a result, MatSeqAIJSetPreallocation is
544: supported for this matrix type. MatConvert can be called for a fast inplace conversion
545: to and from the MATSEQAIJ matrix type.
547: Options Database Keys:
548: . -mat_type lusol - sets the matrix type to "lusol" during a call to MatSetFromOptions()
550: Level: beginner
552: .seealso: PCLU
553: M*/
558: PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_LUSOL(Mat A)
559: {
563: /* Change type name before calling MatSetType to force proper construction of SeqAIJ and LUSOL types */
564: PetscObjectChangeTypeName((PetscObject)A,MATLUSOL);
565: MatSetType(A,MATSEQAIJ);
566: MatConvert_SeqAIJ_LUSOL(A,MATLUSOL,MAT_REUSE_MATRIX,&A);
567: return(0);
568: }