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 MatConvert_LUSOL_SeqAIJ(Mat A,const MatType type,MatReuse reuse,Mat *newmat)
187: {
189: Mat B=*newmat;
190: Mat_LUSOL *lusol=(Mat_LUSOL *)A->spptr;
193: if (reuse == MAT_INITIAL_MATRIX) {
194: MatDuplicate(A,MAT_COPY_VALUES,&B);
195: }
196: B->ops->duplicate = lusol->MatDuplicate;
197: B->ops->lufactorsymbolic = lusol->MatLUFactorSymbolic;
198: B->ops->destroy = lusol->MatDestroy;
199:
200: PetscFree(lusol);
202: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_lusol_C","",PETSC_NULL);
203: PetscObjectComposeFunction((PetscObject)B,"MatConvert_lusol_seqaij_C","",PETSC_NULL);
205: PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);
206: *newmat = B;
207: return(0);
208: }
213: PetscErrorCode MatDestroy_LUSOL(Mat A)
214: {
216: Mat_LUSOL *lusol=(Mat_LUSOL *)A->spptr;
219: if (lusol->CleanUpLUSOL) {
220: PetscFree(lusol->ip);
221: PetscFree(lusol->iq);
222: PetscFree(lusol->lenc);
223: PetscFree(lusol->lenr);
224: PetscFree(lusol->locc);
225: PetscFree(lusol->locr);
226: PetscFree(lusol->iploc);
227: PetscFree(lusol->iqloc);
228: PetscFree(lusol->ipinv);
229: PetscFree(lusol->iqinv);
230: PetscFree(lusol->mnsw);
231: PetscFree(lusol->mnsv);
232: PetscFree(lusol->indc);
233: }
235: MatConvert_LUSOL_SeqAIJ(A,MATSEQAIJ,MAT_REUSE_MATRIX,&A);
236: (*A->ops->destroy)(A);
237: return(0);
238: }
242: PetscErrorCode MatSolve_LUSOL(Mat A,Vec b,Vec x)
243: {
244: Mat_LUSOL *lusol=(Mat_LUSOL*)A->spptr;
245: double *bb,*xx;
246: int mode=5;
248: int i,m,n,nnz,status;
251: VecGetArray(x, &xx);
252: VecGetArray(b, &bb);
254: m = n = lusol->n;
255: nnz = lusol->nnz;
257: for (i = 0; i < m; i++)
258: {
259: lusol->mnsv[i] = bb[i];
260: }
262: LU6SOL(&mode, &m, &n, lusol->mnsv, xx, &nnz,
263: lusol->luparm, lusol->parmlu, lusol->data,
264: lusol->indc, lusol->indr, lusol->ip, lusol->iq,
265: lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, &status);
267: if (status != 0)
268: {
269: SETERRQ(PETSC_ERR_ARG_SIZ,"solve failed");
270: }
272: VecRestoreArray(x, &xx);
273: VecRestoreArray(b, &bb);
274: return(0);
275: }
279: PetscErrorCode MatLUFactorNumeric_LUSOL(Mat A,MatFactorInfo *info,Mat *F)
280: {
281: Mat_SeqAIJ *a;
282: Mat_LUSOL *lusol = (Mat_LUSOL*)(*F)->spptr;
284: int m, n, nz, nnz, status;
285: int i, rs, re;
286: int factorizations;
289: MatGetSize(A,&m,&n);
290: a = (Mat_SeqAIJ *)A->data;
292: if (m != lusol->n) {
293: SETERRQ(PETSC_ERR_ARG_SIZ,"factorization struct inconsistent");
294: }
296: factorizations = 0;
297: do
298: {
299: /*******************************************************************/
300: /* Check the workspace allocation. */
301: /*******************************************************************/
303: nz = a->nz;
304: nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom*nz));
305: nnz = PetscMax(nnz, 5*n);
307: if (nnz < lusol->luparm[12]){
308: nnz = (int)(lusol->luroom * lusol->luparm[12]);
309: } else if ((factorizations > 0) && (lusol->luroom < 6)){
310: lusol->luroom += 0.1;
311: }
313: nnz = PetscMax(nnz, (int)(lusol->luroom*(lusol->luparm[22] + lusol->luparm[23])));
315: if (nnz > lusol->nnz){
316: PetscFree(lusol->indc);
317: PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
318: lusol->indr = lusol->indc + nnz;
319: lusol->data = (double *)(lusol->indr + nnz);
320: lusol->nnz = nnz;
321: }
323: /*******************************************************************/
324: /* Fill in the data for the problem. (1-based Fortran style) */
325: /*******************************************************************/
327: nz = 0;
328: for (i = 0; i < n; i++)
329: {
330: rs = a->i[i];
331: re = a->i[i+1];
333: while (rs < re)
334: {
335: if (a->a[rs] != 0.0)
336: {
337: lusol->indc[nz] = i + 1;
338: lusol->indr[nz] = a->j[rs] + 1;
339: lusol->data[nz] = a->a[rs];
340: nz++;
341: }
342: rs++;
343: }
344: }
346: /*******************************************************************/
347: /* Do the factorization. */
348: /*******************************************************************/
350: LU1FAC(&m, &n, &nz, &nnz,
351: lusol->luparm, lusol->parmlu, lusol->data,
352: lusol->indc, lusol->indr, lusol->ip, lusol->iq,
353: lusol->lenc, lusol->lenr, lusol->locc, lusol->locr,
354: lusol->iploc, lusol->iqloc, lusol->ipinv,
355: lusol->iqinv, lusol->mnsw, &status);
356:
357: switch(status)
358: {
359: case 0: /* factored */
360: break;
362: case 7: /* insufficient memory */
363: break;
365: case 1:
366: case -1: /* singular */
367: SETERRQ(PETSC_ERR_LIB,"Singular matrix");
369: case 3:
370: case 4: /* error conditions */
371: SETERRQ(PETSC_ERR_LIB,"matrix error");
373: default: /* unknown condition */
374: SETERRQ(PETSC_ERR_LIB,"matrix unknown return code");
375: }
377: factorizations++;
378: } while (status == 7);
379: (*F)->assembled = PETSC_TRUE;
380: return(0);
381: }
385: PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat A, IS r, IS c,MatFactorInfo *info, Mat *F) {
386: /************************************************************************/
387: /* Input */
388: /* A - matrix to factor */
389: /* r - row permutation (ignored) */
390: /* c - column permutation (ignored) */
391: /* */
392: /* Output */
393: /* F - matrix storing the factorization; */
394: /************************************************************************/
395: Mat B;
396: Mat_LUSOL *lusol;
398: int i, m, n, nz, nnz;
401:
402: /************************************************************************/
403: /* Check the arguments. */
404: /************************************************************************/
406: MatGetSize(A, &m, &n);
407: nz = ((Mat_SeqAIJ *)A->data)->nz;
409: /************************************************************************/
410: /* Create the factorization. */
411: /************************************************************************/
413: MatCreate(A->comm,&B);
414: MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,m,n);
415: MatSetType(B,A->type_name);
416: MatSeqAIJSetPreallocation(B,0,PETSC_NULL);
418: B->ops->lufactornumeric = MatLUFactorNumeric_LUSOL;
419: B->ops->solve = MatSolve_LUSOL;
420: B->factor = FACTOR_LU;
421: lusol = (Mat_LUSOL*)(B->spptr);
423: /************************************************************************/
424: /* Initialize parameters */
425: /************************************************************************/
427: for (i = 0; i < 30; i++)
428: {
429: lusol->luparm[i] = 0;
430: lusol->parmlu[i] = 0;
431: }
433: lusol->luparm[1] = -1;
434: lusol->luparm[2] = 5;
435: lusol->luparm[7] = 1;
437: lusol->parmlu[0] = 1 / Factorization_Tolerance;
438: lusol->parmlu[1] = 1 / Factorization_Tolerance;
439: lusol->parmlu[2] = Factorization_Small_Tolerance;
440: lusol->parmlu[3] = Factorization_Pivot_Tolerance;
441: lusol->parmlu[4] = Factorization_Pivot_Tolerance;
442: lusol->parmlu[5] = 3.0;
443: lusol->parmlu[6] = 0.3;
444: lusol->parmlu[7] = 0.6;
446: /************************************************************************/
447: /* Allocate the workspace needed by LUSOL. */
448: /************************************************************************/
450: lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill);
451: nnz = PetscMax((int)(lusol->elbowroom*nz), 5*n);
452:
453: lusol->n = n;
454: lusol->nz = nz;
455: lusol->nnz = nnz;
456: lusol->luroom = 1.75;
458: PetscMalloc(sizeof(int)*n,&lusol->ip);
459: PetscMalloc(sizeof(int)*n,&lusol->iq);
460: PetscMalloc(sizeof(int)*n,&lusol->lenc);
461: PetscMalloc(sizeof(int)*n,&lusol->lenr);
462: PetscMalloc(sizeof(int)*n,&lusol->locc);
463: PetscMalloc(sizeof(int)*n,&lusol->locr);
464: PetscMalloc(sizeof(int)*n,&lusol->iploc);
465: PetscMalloc(sizeof(int)*n,&lusol->iqloc);
466: PetscMalloc(sizeof(int)*n,&lusol->ipinv);
467: PetscMalloc(sizeof(int)*n,&lusol->iqinv);
468: PetscMalloc(sizeof(double)*n,&lusol->mnsw);
469: PetscMalloc(sizeof(double)*n,&lusol->mnsv);
471: PetscMalloc((sizeof(double)+2*sizeof(int))*nnz,&lusol->indc);
472: lusol->indr = lusol->indc + nnz;
473: lusol->data = (double *)(lusol->indr + nnz);
474: lusol->CleanUpLUSOL = PETSC_TRUE;
475: *F = B;
476: return(0);
477: }
482: PetscErrorCode MatConvert_SeqAIJ_LUSOL(Mat A,const MatType type,MatReuse reuse,Mat *newmat)
483: {
485: PetscInt m, n;
486: Mat_LUSOL *lusol;
487: Mat B=*newmat;
490: MatGetSize(A, &m, &n);
491: if (m != n) {
492: SETERRQ(PETSC_ERR_ARG_SIZ,"matrix must be square");
493: }
494: if (reuse == MAT_INITIAL_MATRIX) {
495: MatDuplicate(A,MAT_COPY_VALUES,&B);
496: }
497:
498: PetscNew(Mat_LUSOL,&lusol);
499: lusol->MatDuplicate = A->ops->duplicate;
500: lusol->MatLUFactorSymbolic = A->ops->lufactorsymbolic;
501: lusol->MatDestroy = A->ops->destroy;
502: lusol->CleanUpLUSOL = PETSC_FALSE;
504: B->spptr = (void*)lusol;
505: B->ops->duplicate = MatDuplicate_LUSOL;
506: B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL;
507: B->ops->destroy = MatDestroy_LUSOL;
509: PetscInfo(0,"Using LUSOL for LU factorization and solves.\n");
510: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_lusol_C",
511: "MatConvert_SeqAIJ_LUSOL",MatConvert_SeqAIJ_LUSOL);
512: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_lusol_seqaij_C",
513: "MatConvert_LUSOL_SeqAIJ",MatConvert_LUSOL_SeqAIJ);
514: PetscObjectChangeTypeName((PetscObject)B,type);
515: *newmat = B;
516: return(0);
517: }
522: PetscErrorCode MatDuplicate_LUSOL(Mat A, MatDuplicateOption op, Mat *M) {
524: Mat_LUSOL *lu=(Mat_LUSOL *)A->spptr;
526: (*lu->MatDuplicate)(A,op,M);
527: PetscMemcpy((*M)->spptr,lu,sizeof(Mat_LUSOL));
528: return(0);
529: }
531: /*MC
532: MATLUSOL - MATLUSOL = "lusol" - A matrix type providing direct solvers (LU) for sequential matrices
533: via the external package LUSOL.
535: If LUSOL is installed (see the manual for
536: instructions on how to declare the existence of external packages),
537: a matrix type can be constructed which invokes LUSOL solvers.
538: After calling MatCreate(...,A), simply call MatSetType(A,MATLUSOL).
539: This matrix type is only supported for double precision real.
541: This matrix inherits from MATSEQAIJ. As a result, MatSeqAIJSetPreallocation is
542: supported for this matrix type. MatConvert can be called for a fast inplace conversion
543: to and from the MATSEQAIJ matrix type.
545: Options Database Keys:
546: . -mat_type lusol - sets the matrix type to "lusol" during a call to MatSetFromOptions()
548: Level: beginner
550: .seealso: PCLU
551: M*/
556: PetscErrorCode MatCreate_LUSOL(Mat A)
557: {
561: MatSetType(A,MATSEQAIJ);
562: MatConvert_SeqAIJ_LUSOL(A,MATLUSOL,MAT_REUSE_MATRIX,&A);
563: return(0);
564: }