Actual source code: lusol.c
2: /*
3: Provides an interface to the LUSOL package of ....
5: */
6: #include <../src/mat/impls/aij/seq/aij.h>
8: #if defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
9: #define LU1FAC lu1fac_
10: #define LU6SOL lu6sol_
11: #define M1PAGE m1page_
12: #define M5SETX m5setx_
13: #define M6RDEL m6rdel_
14: #elif !defined(PETSC_HAVE_FORTRAN_CAPS)
15: #define LU1FAC lu1fac
16: #define LU6SOL lu6sol
17: #define M1PAGE m1page
18: #define M5SETX m5setx
19: #define M6RDEL m6rdel
20: #endif
22: /*
23: Dummy symbols that the MINOS files mi25bfac.f and mi15blas.f may require
24: */
25: PETSC_EXTERN void M1PAGE()
26: {
27: ;
28: }
29: PETSC_EXTERN void M5SETX()
30: {
31: ;
32: }
34: PETSC_EXTERN void M6RDEL()
35: {
36: ;
37: }
39: PETSC_EXTERN void LU1FAC(int *m, int *n, int *nnz, int *size, int *luparm, double *parmlu, double *data, int *indc, int *indr, int *rowperm, int *colperm, int *collen, int *rowlen, int *colstart, int *rowstart, int *rploc, int *cploc, int *rpinv, int *cpinv, double *w, int *inform);
41: PETSC_EXTERN void LU6SOL(int *mode, int *m, int *n, double *rhs, double *x, int *size, int *luparm, double *parmlu, double *data, int *indc, int *indr, int *rowperm, int *colperm, int *collen, int *rowlen, int *colstart, int *rowstart, int *inform);
43: extern PetscErrorCode MatDuplicate_LUSOL(Mat, MatDuplicateOption, Mat *);
45: typedef struct {
46: double *data;
47: int *indc;
48: int *indr;
50: int *ip;
51: int *iq;
52: int *lenc;
53: int *lenr;
54: int *locc;
55: int *locr;
56: int *iploc;
57: int *iqloc;
58: int *ipinv;
59: int *iqinv;
60: double *mnsw;
61: double *mnsv;
63: double elbowroom;
64: double luroom; /* Extra space allocated when factor fails */
65: double parmlu[30]; /* Input/output to LUSOL */
67: int n; /* Number of rows/columns in matrix */
68: int nz; /* Number of nonzeros */
69: int nnz; /* Number of nonzeros allocated for factors */
70: int luparm[30]; /* Input/output to LUSOL */
72: PetscBool CleanUpLUSOL;
74: } Mat_LUSOL;
76: /* LUSOL input/Output Parameters (Description uses C-style indexes
77: *
78: * Input parameters Typical value
79: *
80: * luparm(0) = nout File number for printed messages. 6
81: * luparm(1) = lprint Print level. 0
82: * < 0 suppresses output.
83: * = 0 gives error messages.
84: * = 1 gives debug output from some of the
85: * other routines in LUSOL.
86: * >= 2 gives the pivot row and column and the
87: * no. of rows and columns involved at
88: * each elimination step in lu1fac.
89: * luparm(2) = maxcol lu1fac: maximum number of columns 5
90: * searched allowed in a Markowitz-type
91: * search for the next pivot element.
92: * For some of the factorization, the
93: * number of rows searched is
94: * maxrow = maxcol - 1.
95: *
96: *
97: * Output parameters:
98: *
99: * luparm(9) = inform Return code from last call to any LU routine.
100: * luparm(10) = nsing No. of singularities marked in the
101: * output array w(*).
102: * luparm(11) = jsing Column index of last singularity.
103: * luparm(12) = minlen Minimum recommended value for lena.
104: * luparm(13) = maxlen ?
105: * luparm(14) = nupdat No. of updates performed by the lu8 routines.
106: * luparm(15) = nrank No. of nonempty rows of U.
107: * luparm(16) = ndens1 No. of columns remaining when the density of
108: * the matrix being factorized reached dens1.
109: * luparm(17) = ndens2 No. of columns remaining when the density of
110: * the matrix being factorized reached dens2.
111: * luparm(18) = jumin The column index associated with dumin.
112: * luparm(19) = numl0 No. of columns in initial L.
113: * luparm(20) = lenl0 Size of initial L (no. of nonzeros).
114: * luparm(21) = lenu0 Size of initial U.
115: * luparm(22) = lenl Size of current L.
116: * luparm(23) = lenu Size of current U.
117: * luparm(24) = lrow Length of row file.
118: * luparm(25) = ncp No. of compressions of LU data structures.
119: * luparm(26) = mersum lu1fac: sum of Markowitz merit counts.
120: * luparm(27) = nutri lu1fac: triangular rows in U.
121: * luparm(28) = nltri lu1fac: triangular rows in L.
122: * luparm(29) =
123: *
124: *
125: * Input parameters Typical value
126: *
127: * parmlu(0) = elmax1 Max multiplier allowed in L 10.0
128: * during factor.
129: * parmlu(1) = elmax2 Max multiplier allowed in L 10.0
130: * during updates.
131: * parmlu(2) = small Absolute tolerance for eps**0.8
132: * treating reals as zero. IBM double: 3.0d-13
133: * parmlu(3) = utol1 Absolute tol for flagging eps**0.66667
134: * small diagonals of U. IBM double: 3.7d-11
135: * parmlu(4) = utol2 Relative tol for flagging eps**0.66667
136: * small diagonals of U. IBM double: 3.7d-11
137: * parmlu(5) = uspace Factor limiting waste space in U. 3.0
138: * In lu1fac, the row or column lists
139: * are compressed if their length
140: * exceeds uspace times the length of
141: * either file after the last compression.
142: * parmlu(6) = dens1 The density at which the Markowitz 0.3
143: * strategy should search maxcol columns
144: * and no rows.
145: * parmlu(7) = dens2 the density at which the Markowitz 0.6
146: * strategy should search only 1 column
147: * or (preferably) use a dense LU for
148: * all the remaining rows and columns.
149: *
150: *
151: * Output parameters:
152: *
153: * parmlu(9) = amax Maximum element in A.
154: * parmlu(10) = elmax Maximum multiplier in current L.
155: * parmlu(11) = umax Maximum element in current U.
156: * parmlu(12) = dumax Maximum diagonal in U.
157: * parmlu(13) = dumin Minimum diagonal in U.
158: * parmlu(14) =
159: * parmlu(15) =
160: * parmlu(16) =
161: * parmlu(17) =
162: * parmlu(18) =
163: * parmlu(19) = resid lu6sol: residual after solve with U or U'.
164: * ...
165: * parmlu(29) =
166: */
168: #define Factorization_Tolerance 1e-1
169: #define Factorization_Pivot_Tolerance pow(2.2204460492503131E-16, 2.0 / 3.0)
170: #define Factorization_Small_Tolerance 1e-15 /* pow(DBL_EPSILON, 0.8) */
172: PetscErrorCode MatDestroy_LUSOL(Mat A)
173: {
174: Mat_LUSOL *lusol = (Mat_LUSOL *)A->spptr;
176: PetscFunctionBegin;
177: if (lusol && lusol->CleanUpLUSOL) {
178: PetscCall(PetscFree(lusol->ip));
179: PetscCall(PetscFree(lusol->iq));
180: PetscCall(PetscFree(lusol->lenc));
181: PetscCall(PetscFree(lusol->lenr));
182: PetscCall(PetscFree(lusol->locc));
183: PetscCall(PetscFree(lusol->locr));
184: PetscCall(PetscFree(lusol->iploc));
185: PetscCall(PetscFree(lusol->iqloc));
186: PetscCall(PetscFree(lusol->ipinv));
187: PetscCall(PetscFree(lusol->iqinv));
188: PetscCall(PetscFree(lusol->mnsw));
189: PetscCall(PetscFree(lusol->mnsv));
190: PetscCall(PetscFree3(lusol->data, lusol->indc, lusol->indr));
191: }
192: PetscCall(PetscFree(A->spptr));
193: PetscCall(MatDestroy_SeqAIJ(A));
194: PetscFunctionReturn(PETSC_SUCCESS);
195: }
197: PetscErrorCode MatSolve_LUSOL(Mat A, Vec b, Vec x)
198: {
199: Mat_LUSOL *lusol = (Mat_LUSOL *)A->spptr;
200: double *xx;
201: const double *bb;
202: int mode = 5;
203: int i, m, n, nnz, status;
205: PetscFunctionBegin;
206: PetscCall(VecGetArray(x, &xx));
207: PetscCall(VecGetArrayRead(b, &bb));
209: m = n = lusol->n;
210: nnz = lusol->nnz;
212: for (i = 0; i < m; i++) lusol->mnsv[i] = bb[i];
214: LU6SOL(&mode, &m, &n, lusol->mnsv, xx, &nnz, lusol->luparm, lusol->parmlu, lusol->data, lusol->indc, lusol->indr, lusol->ip, lusol->iq, lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, &status);
216: PetscCheck(!status, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "solve failed, error code %d", status);
218: PetscCall(VecRestoreArray(x, &xx));
219: PetscCall(VecRestoreArrayRead(b, &bb));
220: PetscFunctionReturn(PETSC_SUCCESS);
221: }
223: PetscErrorCode MatLUFactorNumeric_LUSOL(Mat F, Mat A, const MatFactorInfo *info)
224: {
225: Mat_SeqAIJ *a;
226: Mat_LUSOL *lusol = (Mat_LUSOL *)F->spptr;
227: int m, n, nz, nnz, status;
228: int i, rs, re;
229: int factorizations;
231: PetscFunctionBegin;
232: PetscCall(MatGetSize(A, &m, &n));
233: a = (Mat_SeqAIJ *)A->data;
235: PetscCheck(m == lusol->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "factorization struct inconsistent");
237: factorizations = 0;
238: do {
239: /*******************************************************************/
240: /* Check the workspace allocation. */
241: /*******************************************************************/
243: nz = a->nz;
244: nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom * nz));
245: nnz = PetscMax(nnz, 5 * n);
247: if (nnz < lusol->luparm[12]) {
248: nnz = (int)(lusol->luroom * lusol->luparm[12]);
249: } else if ((factorizations > 0) && (lusol->luroom < 6)) {
250: lusol->luroom += 0.1;
251: }
253: nnz = PetscMax(nnz, (int)(lusol->luroom * (lusol->luparm[22] + lusol->luparm[23])));
255: if (nnz > lusol->nnz) {
256: PetscCall(PetscFree3(lusol->data, lusol->indc, lusol->indr));
257: PetscCall(PetscMalloc3(nnz, &lusol->data, nnz, &lusol->indc, nnz, &lusol->indr));
258: lusol->nnz = nnz;
259: }
261: /*******************************************************************/
262: /* Fill in the data for the problem. (1-based Fortran style) */
263: /*******************************************************************/
265: nz = 0;
266: for (i = 0; i < n; i++) {
267: rs = a->i[i];
268: re = a->i[i + 1];
270: while (rs < re) {
271: if (a->a[rs] != 0.0) {
272: lusol->indc[nz] = i + 1;
273: lusol->indr[nz] = a->j[rs] + 1;
274: lusol->data[nz] = a->a[rs];
275: nz++;
276: }
277: rs++;
278: }
279: }
281: /*******************************************************************/
282: /* Do the factorization. */
283: /*******************************************************************/
285: LU1FAC(&m, &n, &nz, &nnz, lusol->luparm, lusol->parmlu, lusol->data, lusol->indc, lusol->indr, lusol->ip, lusol->iq, lusol->lenc, lusol->lenr, lusol->locc, lusol->locr, lusol->iploc, lusol->iqloc, lusol->ipinv, lusol->iqinv, lusol->mnsw, &status);
287: switch (status) {
288: case 0: /* factored */
289: break;
291: case 7: /* insufficient memory */
292: break;
294: case 1:
295: case -1: /* singular */
296: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "Singular matrix");
298: case 3:
299: case 4: /* error conditions */
300: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "matrix error");
302: default: /* unknown condition */
303: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "matrix unknown return code");
304: }
306: factorizations++;
307: } while (status == 7);
308: F->ops->solve = MatSolve_LUSOL;
309: F->assembled = PETSC_TRUE;
310: F->preallocated = PETSC_TRUE;
311: PetscFunctionReturn(PETSC_SUCCESS);
312: }
314: PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat F, Mat A, IS r, IS c, const MatFactorInfo *info)
315: {
316: /************************************************************************/
317: /* Input */
318: /* A - matrix to factor */
319: /* r - row permutation (ignored) */
320: /* c - column permutation (ignored) */
321: /* */
322: /* Output */
323: /* F - matrix storing the factorization; */
324: /************************************************************************/
325: Mat_LUSOL *lusol;
326: int i, m, n, nz, nnz;
328: PetscFunctionBegin;
329: /************************************************************************/
330: /* Check the arguments. */
331: /************************************************************************/
333: PetscCall(MatGetSize(A, &m, &n));
334: nz = ((Mat_SeqAIJ *)A->data)->nz;
336: /************************************************************************/
337: /* Create the factorization. */
338: /************************************************************************/
340: F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL;
341: lusol = (Mat_LUSOL *)(F->spptr);
343: /************************************************************************/
344: /* Initialize parameters */
345: /************************************************************************/
347: for (i = 0; i < 30; i++) {
348: lusol->luparm[i] = 0;
349: lusol->parmlu[i] = 0;
350: }
352: lusol->luparm[1] = -1;
353: lusol->luparm[2] = 5;
354: lusol->luparm[7] = 1;
356: lusol->parmlu[0] = 1 / Factorization_Tolerance;
357: lusol->parmlu[1] = 1 / Factorization_Tolerance;
358: lusol->parmlu[2] = Factorization_Small_Tolerance;
359: lusol->parmlu[3] = Factorization_Pivot_Tolerance;
360: lusol->parmlu[4] = Factorization_Pivot_Tolerance;
361: lusol->parmlu[5] = 3.0;
362: lusol->parmlu[6] = 0.3;
363: lusol->parmlu[7] = 0.6;
365: /************************************************************************/
366: /* Allocate the workspace needed by LUSOL. */
367: /************************************************************************/
369: lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill);
370: nnz = PetscMax((int)(lusol->elbowroom * nz), 5 * n);
372: lusol->n = n;
373: lusol->nz = nz;
374: lusol->nnz = nnz;
375: lusol->luroom = 1.75;
377: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->ip));
378: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iq));
379: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->lenc));
380: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->lenr));
381: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->locc));
382: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->locr));
383: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iploc));
384: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iqloc));
385: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->ipinv));
386: PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iqinv));
387: PetscCall(PetscMalloc(sizeof(double) * n, &lusol->mnsw));
388: PetscCall(PetscMalloc(sizeof(double) * n, &lusol->mnsv));
389: PetscCall(PetscMalloc3(nnz, &lusol->data, nnz, &lusol->indc, nnz, &lusol->indr));
391: lusol->CleanUpLUSOL = PETSC_TRUE;
392: F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL;
393: PetscFunctionReturn(PETSC_SUCCESS);
394: }
396: PetscErrorCode MatFactorGetSolverType_seqaij_lusol(Mat A, MatSolverType *type)
397: {
398: PetscFunctionBegin;
399: *type = MATSOLVERLUSOL;
400: PetscFunctionReturn(PETSC_SUCCESS);
401: }
403: PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat A, MatFactorType ftype, Mat *F)
404: {
405: Mat B;
406: Mat_LUSOL *lusol;
407: int m, n;
409: PetscFunctionBegin;
410: PetscCall(MatGetSize(A, &m, &n));
411: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
412: PetscCall(MatSetSizes(B, PETSC_DECIDE, PETSC_DECIDE, m, n));
413: PetscCall(MatSetType(B, ((PetscObject)A)->type_name));
414: PetscCall(MatSeqAIJSetPreallocation(B, 0, NULL));
416: PetscCall(PetscNew(&lusol));
417: B->spptr = lusol;
419: B->trivialsymbolic = PETSC_TRUE;
420: B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL;
421: B->ops->destroy = MatDestroy_LUSOL;
423: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatFactorGetSolverType_C", MatFactorGetSolverType_seqaij_lusol));
425: B->factortype = MAT_FACTOR_LU;
426: PetscCall(PetscFree(B->solvertype));
427: PetscCall(PetscStrallocpy(MATSOLVERLUSOL, &B->solvertype));
429: PetscFunctionReturn(PETSC_SUCCESS);
430: }
432: PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_Lusol(void)
433: {
434: PetscFunctionBegin;
435: PetscCall(MatSolverTypeRegister(MATSOLVERLUSOL, MATSEQAIJ, MAT_FACTOR_LU, MatGetFactor_seqaij_lusol));
436: PetscFunctionReturn(PETSC_SUCCESS);
437: }
439: /*MC
440: MATSOLVERLUSOL - "lusol" - Provides direct solvers, LU, for sequential matrices
441: via the external package LUSOL.
443: Works with `MATSEQAIJ` matrices
445: Level: beginner
447: .seealso: [](ch_matrices), `Mat`, `PCLU`, `PCFactorSetMatSolverType()`, `MatSolverType`
448: M*/