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*/