Actual source code: superlu.c
1: /*
2: This file implements a subclass of the SeqAIJ matrix class that uses
3: the SuperLU sparse solver.
4: */
6: /*
7: Defines the data structure for the base matrix type (SeqAIJ)
8: */
9: #include <../src/mat/impls/aij/seq/aij.h>
11: /*
12: SuperLU include files
13: */
14: EXTERN_C_BEGIN
15: #if defined(PETSC_USE_COMPLEX)
16: #if defined(PETSC_USE_REAL_SINGLE)
17: #include <slu_cdefs.h>
18: #else
19: #include <slu_zdefs.h>
20: #endif
21: #else
22: #if defined(PETSC_USE_REAL_SINGLE)
23: #include <slu_sdefs.h>
24: #else
25: #include <slu_ddefs.h>
26: #endif
27: #endif
28: #include <slu_util.h>
29: EXTERN_C_END
31: /*
32: This is the data that defines the SuperLU factored matrix type
33: */
34: typedef struct {
35: SuperMatrix A, L, U, B, X;
36: superlu_options_t options;
37: PetscInt *perm_c; /* column permutation vector */
38: PetscInt *perm_r; /* row permutations from partial pivoting */
39: PetscInt *etree;
40: PetscReal *R, *C;
41: char equed[1];
42: PetscInt lwork;
43: void *work;
44: PetscReal rpg, rcond;
45: mem_usage_t mem_usage;
46: MatStructure flg;
47: SuperLUStat_t stat;
48: Mat A_dup;
49: PetscScalar *rhs_dup;
50: GlobalLU_t Glu;
51: PetscBool needconversion;
53: /* Flag to clean up (non-global) SuperLU objects during Destroy */
54: PetscBool CleanUpSuperLU;
55: } Mat_SuperLU;
57: /*
58: Utility function
59: */
60: static PetscErrorCode MatView_Info_SuperLU(Mat A, PetscViewer viewer)
61: {
62: Mat_SuperLU *lu = (Mat_SuperLU *)A->data;
63: superlu_options_t options;
65: PetscFunctionBegin;
66: options = lu->options;
68: PetscCall(PetscViewerASCIIPrintf(viewer, "SuperLU run parameters:\n"));
69: PetscCall(PetscViewerASCIIPrintf(viewer, " Equil: %s\n", (options.Equil != NO) ? "YES" : "NO"));
70: PetscCall(PetscViewerASCIIPrintf(viewer, " ColPerm: %" PetscInt_FMT "\n", options.ColPerm));
71: PetscCall(PetscViewerASCIIPrintf(viewer, " IterRefine: %" PetscInt_FMT "\n", options.IterRefine));
72: PetscCall(PetscViewerASCIIPrintf(viewer, " SymmetricMode: %s\n", (options.SymmetricMode != NO) ? "YES" : "NO"));
73: PetscCall(PetscViewerASCIIPrintf(viewer, " DiagPivotThresh: %g\n", options.DiagPivotThresh));
74: PetscCall(PetscViewerASCIIPrintf(viewer, " PivotGrowth: %s\n", (options.PivotGrowth != NO) ? "YES" : "NO"));
75: PetscCall(PetscViewerASCIIPrintf(viewer, " ConditionNumber: %s\n", (options.ConditionNumber != NO) ? "YES" : "NO"));
76: PetscCall(PetscViewerASCIIPrintf(viewer, " RowPerm: %" PetscInt_FMT "\n", options.RowPerm));
77: PetscCall(PetscViewerASCIIPrintf(viewer, " ReplaceTinyPivot: %s\n", (options.ReplaceTinyPivot != NO) ? "YES" : "NO"));
78: PetscCall(PetscViewerASCIIPrintf(viewer, " PrintStat: %s\n", (options.PrintStat != NO) ? "YES" : "NO"));
79: PetscCall(PetscViewerASCIIPrintf(viewer, " lwork: %" PetscInt_FMT "\n", lu->lwork));
80: if (A->factortype == MAT_FACTOR_ILU) {
81: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_DropTol: %g\n", options.ILU_DropTol));
82: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_FillTol: %g\n", options.ILU_FillTol));
83: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_FillFactor: %g\n", options.ILU_FillFactor));
84: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_DropRule: %" PetscInt_FMT "\n", options.ILU_DropRule));
85: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_Norm: %" PetscInt_FMT "\n", options.ILU_Norm));
86: PetscCall(PetscViewerASCIIPrintf(viewer, " ILU_MILU: %" PetscInt_FMT "\n", options.ILU_MILU));
87: }
88: PetscFunctionReturn(PETSC_SUCCESS);
89: }
91: static PetscErrorCode MatSolve_SuperLU_Private(Mat A, Vec b, Vec x)
92: {
93: Mat_SuperLU *lu = (Mat_SuperLU *)A->data;
94: const PetscScalar *barray;
95: PetscScalar *xarray;
96: PetscInt info, i, n;
97: PetscReal ferr, berr;
98: static PetscBool cite = PETSC_FALSE;
100: PetscFunctionBegin;
101: if (lu->lwork == -1) PetscFunctionReturn(PETSC_SUCCESS);
102: PetscCall(PetscCitationsRegister("@article{superlu99,\n author = {James W. Demmel and Stanley C. Eisenstat and\n John R. Gilbert and Xiaoye S. Li and Joseph W. H. Liu},\n title = {A supernodal approach to sparse partial "
103: "pivoting},\n journal = {SIAM J. Matrix Analysis and Applications},\n year = {1999},\n volume = {20},\n number = {3},\n pages = {720-755}\n}\n",
104: &cite));
106: PetscCall(VecGetLocalSize(x, &n));
107: lu->B.ncol = 1; /* Set the number of right-hand side */
108: if (lu->options.Equil && !lu->rhs_dup) {
109: /* superlu overwrites b when Equil is used, thus create rhs_dup to keep user's b unchanged */
110: PetscCall(PetscMalloc1(n, &lu->rhs_dup));
111: }
112: if (lu->options.Equil) {
113: /* Copy b into rsh_dup */
114: PetscCall(VecGetArrayRead(b, &barray));
115: PetscCall(PetscArraycpy(lu->rhs_dup, barray, n));
116: PetscCall(VecRestoreArrayRead(b, &barray));
117: barray = lu->rhs_dup;
118: } else {
119: PetscCall(VecGetArrayRead(b, &barray));
120: }
121: PetscCall(VecGetArray(x, &xarray));
123: #if defined(PETSC_USE_COMPLEX)
124: #if defined(PETSC_USE_REAL_SINGLE)
125: ((DNformat *)lu->B.Store)->nzval = (singlecomplex *)barray;
126: ((DNformat *)lu->X.Store)->nzval = (singlecomplex *)xarray;
127: #else
128: ((DNformat *)lu->B.Store)->nzval = (doublecomplex *)barray;
129: ((DNformat *)lu->X.Store)->nzval = (doublecomplex *)xarray;
130: #endif
131: #else
132: ((DNformat *)lu->B.Store)->nzval = (void *)barray;
133: ((DNformat *)lu->X.Store)->nzval = xarray;
134: #endif
136: lu->options.Fact = FACTORED; /* Indicate the factored form of A is supplied. */
137: if (A->factortype == MAT_FACTOR_LU) {
138: #if defined(PETSC_USE_COMPLEX)
139: #if defined(PETSC_USE_REAL_SINGLE)
140: PetscStackCallExternalVoid("SuperLU:cgssvx", cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
141: #else
142: PetscStackCallExternalVoid("SuperLU:zgssvx", zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
143: #endif
144: #else
145: #if defined(PETSC_USE_REAL_SINGLE)
146: PetscStackCallExternalVoid("SuperLU:sgssvx", sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
147: #else
148: PetscStackCallExternalVoid("SuperLU:dgssvx", dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
149: #endif
150: #endif
151: } else if (A->factortype == MAT_FACTOR_ILU) {
152: #if defined(PETSC_USE_COMPLEX)
153: #if defined(PETSC_USE_REAL_SINGLE)
154: PetscStackCallExternalVoid("SuperLU:cgsisx", cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
155: #else
156: PetscStackCallExternalVoid("SuperLU:zgsisx", zgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
157: #endif
158: #else
159: #if defined(PETSC_USE_REAL_SINGLE)
160: PetscStackCallExternalVoid("SuperLU:sgsisx", sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
161: #else
162: PetscStackCallExternalVoid("SuperLU:dgsisx", dgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &info));
163: #endif
164: #endif
165: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
166: if (!lu->options.Equil) PetscCall(VecRestoreArrayRead(b, &barray));
167: PetscCall(VecRestoreArray(x, &xarray));
169: if (!info || info == lu->A.ncol + 1) {
170: if (lu->options.IterRefine) {
171: PetscCall(PetscPrintf(PETSC_COMM_SELF, "Iterative Refinement:\n"));
172: PetscCall(PetscPrintf(PETSC_COMM_SELF, " %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR"));
173: for (i = 0; i < 1; ++i) PetscCall(PetscPrintf(PETSC_COMM_SELF, " %8d%8d%16e%16e\n", i + 1, lu->stat.RefineSteps, ferr, berr));
174: }
175: } else if (info > 0) {
176: if (lu->lwork == -1) {
177: PetscCall(PetscPrintf(PETSC_COMM_SELF, " ** Estimated memory: %" PetscInt_FMT " bytes\n", info - lu->A.ncol));
178: } else {
179: PetscCall(PetscPrintf(PETSC_COMM_SELF, " Warning: gssvx() returns info %" PetscInt_FMT "\n", info));
180: }
181: } else PetscCheck(info >= 0, PETSC_COMM_SELF, PETSC_ERR_LIB, "info = %" PetscInt_FMT ", the %" PetscInt_FMT "-th argument in gssvx() had an illegal value", info, -info);
183: if (lu->options.PrintStat) {
184: PetscCall(PetscPrintf(PETSC_COMM_SELF, "MatSolve__SuperLU():\n"));
185: PetscStackCallExternalVoid("SuperLU:StatPrint", StatPrint(&lu->stat));
186: }
187: PetscFunctionReturn(PETSC_SUCCESS);
188: }
190: static PetscErrorCode MatSolve_SuperLU(Mat A, Vec b, Vec x)
191: {
192: Mat_SuperLU *lu = (Mat_SuperLU *)A->data;
193: trans_t oldOption;
195: PetscFunctionBegin;
196: PetscCall(VecFlag(x, A->factorerrortype));
197: if (A->factorerrortype) {
198: PetscCall(PetscInfo(A, "MatSolve is called with singular matrix factor, skip\n"));
199: PetscFunctionReturn(PETSC_SUCCESS);
200: }
202: oldOption = lu->options.Trans;
203: lu->options.Trans = TRANS;
204: PetscCall(MatSolve_SuperLU_Private(A, b, x));
205: lu->options.Trans = oldOption;
206: PetscFunctionReturn(PETSC_SUCCESS);
207: }
209: static PetscErrorCode MatSolveTranspose_SuperLU(Mat A, Vec b, Vec x)
210: {
211: Mat_SuperLU *lu = (Mat_SuperLU *)A->data;
212: trans_t oldOption;
214: PetscFunctionBegin;
215: PetscCall(VecFlag(x, A->factorerrortype));
216: if (A->factorerrortype) {
217: PetscCall(PetscInfo(A, "MatSolve is called with singular matrix factor, skip\n"));
218: PetscFunctionReturn(PETSC_SUCCESS);
219: }
221: oldOption = lu->options.Trans;
222: lu->options.Trans = NOTRANS;
223: PetscCall(MatSolve_SuperLU_Private(A, b, x));
224: lu->options.Trans = oldOption;
225: PetscFunctionReturn(PETSC_SUCCESS);
226: }
228: static PetscErrorCode MatLUFactorNumeric_SuperLU(Mat F, Mat A, const MatFactorInfo *info)
229: {
230: Mat_SuperLU *lu = (Mat_SuperLU *)F->data;
231: Mat_SeqAIJ *aa;
232: PetscInt sinfo;
233: PetscReal ferr, berr;
234: NCformat *Ustore;
235: SCformat *Lstore;
237: PetscFunctionBegin;
238: if (lu->flg == SAME_NONZERO_PATTERN) { /* successive numerical factorization */
239: lu->options.Fact = SamePattern;
240: /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */
241: Destroy_SuperMatrix_Store(&lu->A);
242: if (lu->A_dup) PetscCall(MatCopy_SeqAIJ(A, lu->A_dup, SAME_NONZERO_PATTERN));
244: if (lu->lwork >= 0) {
245: PetscStackCallExternalVoid("SuperLU:Destroy_SuperNode_Matrix", Destroy_SuperNode_Matrix(&lu->L));
246: PetscStackCallExternalVoid("SuperLU:Destroy_CompCol_Matrix", Destroy_CompCol_Matrix(&lu->U));
247: lu->options.Fact = SamePattern;
248: }
249: }
251: /* Create the SuperMatrix for lu->A=A^T:
252: Since SuperLU likes column-oriented matrices,we pass it the transpose,
253: and then solve A^T X = B in MatSolve(). */
254: if (lu->A_dup) {
255: aa = (Mat_SeqAIJ *)lu->A_dup->data;
256: } else {
257: aa = (Mat_SeqAIJ *)A->data;
258: }
259: #if defined(PETSC_USE_COMPLEX)
260: #if defined(PETSC_USE_REAL_SINGLE)
261: PetscStackCallExternalVoid("SuperLU:cCreate_CompCol_Matrix", cCreate_CompCol_Matrix(&lu->A, A->cmap->n, A->rmap->n, aa->nz, (singlecomplex *)aa->a, aa->j, aa->i, SLU_NC, SLU_C, SLU_GE));
262: #else
263: PetscStackCallExternalVoid("SuperLU:zCreate_CompCol_Matrix", zCreate_CompCol_Matrix(&lu->A, A->cmap->n, A->rmap->n, aa->nz, (doublecomplex *)aa->a, aa->j, aa->i, SLU_NC, SLU_Z, SLU_GE));
264: #endif
265: #else
266: #if defined(PETSC_USE_REAL_SINGLE)
267: PetscStackCallExternalVoid("SuperLU:sCreate_CompCol_Matrix", sCreate_CompCol_Matrix(&lu->A, A->cmap->n, A->rmap->n, aa->nz, aa->a, aa->j, aa->i, SLU_NC, SLU_S, SLU_GE));
268: #else
269: PetscStackCallExternalVoid("SuperLU:dCreate_CompCol_Matrix", dCreate_CompCol_Matrix(&lu->A, A->cmap->n, A->rmap->n, aa->nz, aa->a, aa->j, aa->i, SLU_NC, SLU_D, SLU_GE));
270: #endif
271: #endif
273: /* Numerical factorization */
274: lu->B.ncol = 0; /* Indicate not to solve the system */
275: if (F->factortype == MAT_FACTOR_LU) {
276: #if defined(PETSC_USE_COMPLEX)
277: #if defined(PETSC_USE_REAL_SINGLE)
278: PetscStackCallExternalVoid("SuperLU:cgssvx", cgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
279: #else
280: PetscStackCallExternalVoid("SuperLU:zgssvx", zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
281: #endif
282: #else
283: #if defined(PETSC_USE_REAL_SINGLE)
284: PetscStackCallExternalVoid("SuperLU:sgssvx", sgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
285: #else
286: PetscStackCallExternalVoid("SuperLU:dgssvx", dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
287: #endif
288: #endif
289: } else if (F->factortype == MAT_FACTOR_ILU) {
290: /* Compute the incomplete factorization, condition number and pivot growth */
291: #if defined(PETSC_USE_COMPLEX)
292: #if defined(PETSC_USE_REAL_SINGLE)
293: PetscStackCallExternalVoid("SuperLU:cgsisx", cgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
294: #else
295: PetscStackCallExternalVoid("SuperLU:zgsisx", zgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
296: #endif
297: #else
298: #if defined(PETSC_USE_REAL_SINGLE)
299: PetscStackCallExternalVoid("SuperLU:sgsisx", sgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
300: #else
301: PetscStackCallExternalVoid("SuperLU:dgsisx", dgsisx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C, &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &lu->Glu, &lu->mem_usage, &lu->stat, &sinfo));
302: #endif
303: #endif
304: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
305: if (!sinfo || sinfo == lu->A.ncol + 1) {
306: if (lu->options.PivotGrowth) PetscCall(PetscPrintf(PETSC_COMM_SELF, " Recip. pivot growth = %e\n", lu->rpg));
307: if (lu->options.ConditionNumber) PetscCall(PetscPrintf(PETSC_COMM_SELF, " Recip. condition number = %e\n", lu->rcond));
308: } else if (sinfo > 0) {
309: if (A->erroriffailure) {
310: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_MAT_LU_ZRPVT, "Zero pivot in row %" PetscInt_FMT, sinfo);
311: } else {
312: if (sinfo <= lu->A.ncol) {
313: if (lu->options.ILU_FillTol == 0.0) F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
314: PetscCall(PetscInfo(F, "Number of zero pivots %" PetscInt_FMT ", ILU_FillTol %g\n", sinfo, lu->options.ILU_FillTol));
315: } else if (sinfo == lu->A.ncol + 1) {
316: /*
317: U is nonsingular, but RCOND is less than machine
318: precision, meaning that the matrix is singular to
319: working precision. Nevertheless, the solution and
320: error bounds are computed because there are a number
321: of situations where the computed solution can be more
322: accurate than the value of RCOND would suggest.
323: */
324: PetscCall(PetscInfo(F, "Matrix factor U is nonsingular, but is singular to working precision. The solution is computed. info %" PetscInt_FMT "\n", sinfo));
325: } else { /* sinfo > lu->A.ncol + 1 */
326: F->factorerrortype = MAT_FACTOR_OUTMEMORY;
327: PetscCall(PetscInfo(F, "Number of bytes allocated when memory allocation fails %" PetscInt_FMT "\n", sinfo));
328: }
329: }
330: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "info = %" PetscInt_FMT ", the %" PetscInt_FMT "-th argument in gssvx() had an illegal value", sinfo, -sinfo);
332: if (lu->options.PrintStat) {
333: PetscCall(PetscPrintf(PETSC_COMM_SELF, "MatLUFactorNumeric_SuperLU():\n"));
334: PetscStackCallExternalVoid("SuperLU:StatPrint", StatPrint(&lu->stat));
335: Lstore = (SCformat *)lu->L.Store;
336: Ustore = (NCformat *)lu->U.Store;
337: PetscCall(PetscPrintf(PETSC_COMM_SELF, " No of nonzeros in factor L = %" PetscInt_FMT "\n", Lstore->nnz));
338: PetscCall(PetscPrintf(PETSC_COMM_SELF, " No of nonzeros in factor U = %" PetscInt_FMT "\n", Ustore->nnz));
339: PetscCall(PetscPrintf(PETSC_COMM_SELF, " No of nonzeros in L+U = %" PetscInt_FMT "\n", Lstore->nnz + Ustore->nnz - lu->A.ncol));
340: PetscCall(PetscPrintf(PETSC_COMM_SELF, " L\\U MB %.3f\ttotal MB needed %.3f\n", lu->mem_usage.for_lu / 1e6, lu->mem_usage.total_needed / 1e6));
341: }
343: lu->flg = SAME_NONZERO_PATTERN;
344: F->ops->solve = MatSolve_SuperLU;
345: F->ops->solvetranspose = MatSolveTranspose_SuperLU;
346: F->ops->matsolve = NULL;
347: PetscFunctionReturn(PETSC_SUCCESS);
348: }
350: static PetscErrorCode MatDestroy_SuperLU(Mat A)
351: {
352: Mat_SuperLU *lu = (Mat_SuperLU *)A->data;
354: PetscFunctionBegin;
355: if (lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */
356: PetscStackCallExternalVoid("SuperLU:Destroy_SuperMatrix_Store", Destroy_SuperMatrix_Store(&lu->A));
357: if (lu->lwork >= 0) {
358: PetscStackCallExternalVoid("SuperLU:Destroy_SuperNode_Matrix", Destroy_SuperNode_Matrix(&lu->L));
359: PetscStackCallExternalVoid("SuperLU:Destroy_CompCol_Matrix", Destroy_CompCol_Matrix(&lu->U));
360: }
361: }
362: PetscStackCallExternalVoid("SuperLU:Destroy_SuperMatrix_Store", Destroy_SuperMatrix_Store(&lu->B));
363: PetscStackCallExternalVoid("SuperLU:Destroy_SuperMatrix_Store", Destroy_SuperMatrix_Store(&lu->X));
364: PetscStackCallExternalVoid("SuperLU:StatFree", StatFree(&lu->stat));
365: PetscCall(PetscFree(lu->etree));
366: PetscCall(PetscFree(lu->perm_r));
367: PetscCall(PetscFree(lu->perm_c));
368: PetscCall(PetscFree(lu->R));
369: PetscCall(PetscFree(lu->C));
370: PetscCall(PetscFree(lu->rhs_dup));
371: PetscCall(MatDestroy(&lu->A_dup));
372: PetscCall(PetscFree(A->data));
374: /* clear composed functions */
375: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatFactorGetSolverType_C", NULL));
376: PetscCall(PetscObjectComposeFunction((PetscObject)A, "MatSuperluSetILUDropTol_C", NULL));
377: PetscFunctionReturn(PETSC_SUCCESS);
378: }
380: static PetscErrorCode MatView_SuperLU(Mat A, PetscViewer viewer)
381: {
382: PetscBool iascii;
383: PetscViewerFormat format;
385: PetscFunctionBegin;
386: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
387: if (iascii) {
388: PetscCall(PetscViewerGetFormat(viewer, &format));
389: if (format == PETSC_VIEWER_ASCII_INFO) PetscCall(MatView_Info_SuperLU(A, viewer));
390: }
391: PetscFunctionReturn(PETSC_SUCCESS);
392: }
394: static PetscErrorCode MatLUFactorSymbolic_SuperLU(Mat F, Mat A, IS r, IS c, const MatFactorInfo *info)
395: {
396: Mat_SuperLU *lu = (Mat_SuperLU *)F->data;
397: PetscInt indx;
398: PetscBool flg, set;
399: PetscReal real_input;
400: const char *colperm[] = {"NATURAL", "MMD_ATA", "MMD_AT_PLUS_A", "COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */
401: const char *iterrefine[] = {"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"};
402: const char *rowperm[] = {"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */
404: PetscFunctionBegin;
405: /* Set options to F */
406: PetscOptionsBegin(PetscObjectComm((PetscObject)F), ((PetscObject)F)->prefix, "SuperLU Options", "Mat");
407: PetscCall(PetscOptionsBool("-mat_superlu_equil", "Equil", "None", (PetscBool)lu->options.Equil, (PetscBool *)&lu->options.Equil, NULL));
408: PetscCall(PetscOptionsEList("-mat_superlu_colperm", "ColPerm", "None", colperm, 4, colperm[3], &indx, &flg));
409: if (flg) lu->options.ColPerm = (colperm_t)indx;
410: PetscCall(PetscOptionsEList("-mat_superlu_iterrefine", "IterRefine", "None", iterrefine, 4, iterrefine[0], &indx, &flg));
411: if (flg) lu->options.IterRefine = (IterRefine_t)indx;
412: PetscCall(PetscOptionsBool("-mat_superlu_symmetricmode", "SymmetricMode", "None", (PetscBool)lu->options.SymmetricMode, &flg, &set));
413: if (set && flg) lu->options.SymmetricMode = YES;
414: PetscCall(PetscOptionsReal("-mat_superlu_diagpivotthresh", "DiagPivotThresh", "None", lu->options.DiagPivotThresh, &real_input, &flg));
415: if (flg) lu->options.DiagPivotThresh = (double)real_input;
416: PetscCall(PetscOptionsBool("-mat_superlu_pivotgrowth", "PivotGrowth", "None", (PetscBool)lu->options.PivotGrowth, &flg, &set));
417: if (set && flg) lu->options.PivotGrowth = YES;
418: PetscCall(PetscOptionsBool("-mat_superlu_conditionnumber", "ConditionNumber", "None", (PetscBool)lu->options.ConditionNumber, &flg, &set));
419: if (set && flg) lu->options.ConditionNumber = YES;
420: PetscCall(PetscOptionsEList("-mat_superlu_rowperm", "rowperm", "None", rowperm, 2, rowperm[lu->options.RowPerm], &indx, &flg));
421: if (flg) lu->options.RowPerm = (rowperm_t)indx;
422: PetscCall(PetscOptionsBool("-mat_superlu_replacetinypivot", "ReplaceTinyPivot", "None", (PetscBool)lu->options.ReplaceTinyPivot, &flg, &set));
423: if (set && flg) lu->options.ReplaceTinyPivot = YES;
424: PetscCall(PetscOptionsBool("-mat_superlu_printstat", "PrintStat", "None", (PetscBool)lu->options.PrintStat, &flg, &set));
425: if (set && flg) lu->options.PrintStat = YES;
426: PetscCall(PetscOptionsInt("-mat_superlu_lwork", "size of work array in bytes used by factorization", "None", lu->lwork, &lu->lwork, NULL));
427: if (lu->lwork > 0) {
428: /* lwork is in bytes, hence PetscMalloc() is used here, not PetscMalloc1()*/
429: PetscCall(PetscMalloc(lu->lwork, &lu->work));
430: } else if (lu->lwork != 0 && lu->lwork != -1) {
431: PetscCall(PetscPrintf(PETSC_COMM_SELF, " Warning: lwork %" PetscInt_FMT " is not supported by SUPERLU. The default lwork=0 is used.\n", lu->lwork));
432: lu->lwork = 0;
433: }
434: /* ilu options */
435: PetscCall(PetscOptionsReal("-mat_superlu_ilu_droptol", "ILU_DropTol", "None", lu->options.ILU_DropTol, &real_input, &flg));
436: if (flg) lu->options.ILU_DropTol = (double)real_input;
437: PetscCall(PetscOptionsReal("-mat_superlu_ilu_filltol", "ILU_FillTol", "None", lu->options.ILU_FillTol, &real_input, &flg));
438: if (flg) lu->options.ILU_FillTol = (double)real_input;
439: PetscCall(PetscOptionsReal("-mat_superlu_ilu_fillfactor", "ILU_FillFactor", "None", lu->options.ILU_FillFactor, &real_input, &flg));
440: if (flg) lu->options.ILU_FillFactor = (double)real_input;
441: PetscCall(PetscOptionsInt("-mat_superlu_ilu_droprull", "ILU_DropRule", "None", lu->options.ILU_DropRule, &lu->options.ILU_DropRule, NULL));
442: PetscCall(PetscOptionsInt("-mat_superlu_ilu_norm", "ILU_Norm", "None", lu->options.ILU_Norm, &indx, &flg));
443: if (flg) lu->options.ILU_Norm = (norm_t)indx;
444: PetscCall(PetscOptionsInt("-mat_superlu_ilu_milu", "ILU_MILU", "None", lu->options.ILU_MILU, &indx, &flg));
445: if (flg) lu->options.ILU_MILU = (milu_t)indx;
446: PetscOptionsEnd();
448: lu->flg = DIFFERENT_NONZERO_PATTERN;
449: lu->CleanUpSuperLU = PETSC_TRUE;
450: F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU;
452: /* if we are here, the nonzero pattern has changed unless the user explicitly called MatLUFactorSymbolic */
453: PetscCall(MatDestroy(&lu->A_dup));
454: if (lu->needconversion) PetscCall(MatConvert(A, MATSEQAIJ, MAT_INITIAL_MATRIX, &lu->A_dup));
455: if (lu->options.Equil == YES && !lu->A_dup) { /* superlu overwrites input matrix and rhs when Equil is used, thus create A_dup to keep user's A unchanged */
456: PetscCall(MatDuplicate_SeqAIJ(A, MAT_COPY_VALUES, &lu->A_dup));
457: }
458: PetscFunctionReturn(PETSC_SUCCESS);
459: }
461: static PetscErrorCode MatSuperluSetILUDropTol_SuperLU(Mat F, PetscReal dtol)
462: {
463: Mat_SuperLU *lu = (Mat_SuperLU *)F->data;
465: PetscFunctionBegin;
466: lu->options.ILU_DropTol = dtol;
467: PetscFunctionReturn(PETSC_SUCCESS);
468: }
470: /*@
471: MatSuperluSetILUDropTol - Set SuperLU <https://portal.nersc.gov/project/sparse/superlu/superlu_ug.pdf> ILU drop tolerance
473: Logically Collective
475: Input Parameters:
476: + F - the factored matrix obtained by calling `MatGetFactor()`
477: - dtol - drop tolerance
479: Options Database Key:
480: . -mat_superlu_ilu_droptol <dtol> - the drop tolerance
482: Level: beginner
484: .seealso: [](ch_matrices), `Mat`, `MatGetFactor()`, `MATSOLVERSUPERLU`
485: @*/
486: PetscErrorCode MatSuperluSetILUDropTol(Mat F, PetscReal dtol)
487: {
488: PetscFunctionBegin;
491: PetscTryMethod(F, "MatSuperluSetILUDropTol_C", (Mat, PetscReal), (F, dtol));
492: PetscFunctionReturn(PETSC_SUCCESS);
493: }
495: static PetscErrorCode MatFactorGetSolverType_seqaij_superlu(Mat A, MatSolverType *type)
496: {
497: PetscFunctionBegin;
498: *type = MATSOLVERSUPERLU;
499: PetscFunctionReturn(PETSC_SUCCESS);
500: }
502: /*MC
503: MATSOLVERSUPERLU = "superlu" - A solver package providing solvers LU and ILU for sequential matrices
504: via the external package SuperLU <https://portal.nersc.gov/project/sparse/superlu/superlu_ug.pdf>
506: Use `./configure --download-superlu` to have PETSc installed with SuperLU
508: Use `-pc_type lu` `-pc_factor_mat_solver_type superlu` to use this direct solver
510: Options Database Keys:
511: + -mat_superlu_equil <FALSE> - Equil (None)
512: . -mat_superlu_colperm <COLAMD> - (choose one of) `NATURAL`, `MMD_ATA MMD_AT_PLUS_A`, `COLAMD`
513: . -mat_superlu_iterrefine <NOREFINE> - (choose one of) `NOREFINE`, `SINGLE`, `DOUBLE`, `EXTRA`
514: . -mat_superlu_symmetricmode: <FALSE> - SymmetricMode (None)
515: . -mat_superlu_diagpivotthresh <1> - DiagPivotThresh (None)
516: . -mat_superlu_pivotgrowth <FALSE> - PivotGrowth (None)
517: . -mat_superlu_conditionnumber <FALSE> - ConditionNumber (None)
518: . -mat_superlu_rowperm <NOROWPERM> - (choose one of) `NOROWPERM`, `LargeDiag`
519: . -mat_superlu_replacetinypivot <FALSE> - ReplaceTinyPivot (None)
520: . -mat_superlu_printstat <FALSE> - PrintStat (None)
521: . -mat_superlu_lwork <0> - size of work array in bytes used by factorization (None)
522: . -mat_superlu_ilu_droptol <0> - ILU_DropTol (None)
523: . -mat_superlu_ilu_filltol <0> - ILU_FillTol (None)
524: . -mat_superlu_ilu_fillfactor <0> - ILU_FillFactor (None)
525: . -mat_superlu_ilu_droprull <0> - ILU_DropRule (None)
526: . -mat_superlu_ilu_norm <0> - ILU_Norm (None)
527: - -mat_superlu_ilu_milu <0> - ILU_MILU (None)
529: Level: beginner
531: Notes:
532: Do not confuse this with `MATSOLVERSUPERLU_DIST` which is for parallel sparse solves
534: Cannot use ordering provided by PETSc, provides its own.
536: .seealso: [](ch_matrices), `Mat`, `PCLU`, `PCILU`, `MATSOLVERSUPERLU_DIST`, `MATSOLVERMUMPS`, `PCFactorSetMatSolverType()`, `MatSolverType`
537: M*/
539: static PetscErrorCode MatGetFactor_seqaij_superlu(Mat A, MatFactorType ftype, Mat *F)
540: {
541: Mat B;
542: Mat_SuperLU *lu;
543: PetscInt m = A->rmap->n, n = A->cmap->n;
545: PetscFunctionBegin;
546: PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
547: PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, PETSC_DETERMINE, PETSC_DETERMINE));
548: PetscCall(PetscStrallocpy("superlu", &((PetscObject)B)->type_name));
549: PetscCall(MatSetUp(B));
550: B->trivialsymbolic = PETSC_TRUE;
551: if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU) {
552: B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
553: B->ops->ilufactorsymbolic = MatLUFactorSymbolic_SuperLU;
554: } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Factor type not supported");
556: PetscCall(PetscFree(B->solvertype));
557: PetscCall(PetscStrallocpy(MATSOLVERSUPERLU, &B->solvertype));
559: B->ops->getinfo = MatGetInfo_External;
560: B->ops->destroy = MatDestroy_SuperLU;
561: B->ops->view = MatView_SuperLU;
562: B->factortype = ftype;
563: B->assembled = PETSC_TRUE; /* required by -ksp_view */
564: B->preallocated = PETSC_TRUE;
566: PetscCall(PetscNew(&lu));
568: if (ftype == MAT_FACTOR_LU) {
569: set_default_options(&lu->options);
570: /* Comments from SuperLU_4.0/SRC/dgssvx.c:
571: "Whether or not the system will be equilibrated depends on the
572: scaling of the matrix A, but if equilibration is used, A is
573: overwritten by diag(R)*A*diag(C) and B by diag(R)*B
574: (if options->Trans=NOTRANS) or diag(C)*B (if options->Trans = TRANS or CONJ)."
575: We set 'options.Equil = NO' as default because additional space is needed for it.
576: */
577: lu->options.Equil = NO;
578: } else if (ftype == MAT_FACTOR_ILU) {
579: /* Set the default input options of ilu: */
580: PetscStackCallExternalVoid("SuperLU:ilu_set_default_options", ilu_set_default_options(&lu->options));
581: }
582: lu->options.PrintStat = NO;
584: /* Initialize the statistics variables. */
585: PetscStackCallExternalVoid("SuperLU:StatInit", StatInit(&lu->stat));
586: lu->lwork = 0; /* allocate space internally by system malloc */
588: /* Allocate spaces (notice sizes are for the transpose) */
589: PetscCall(PetscMalloc1(m, &lu->etree));
590: PetscCall(PetscMalloc1(n, &lu->perm_r));
591: PetscCall(PetscMalloc1(m, &lu->perm_c));
592: PetscCall(PetscMalloc1(n, &lu->R));
593: PetscCall(PetscMalloc1(m, &lu->C));
595: /* create rhs and solution x without allocate space for .Store */
596: #if defined(PETSC_USE_COMPLEX)
597: #if defined(PETSC_USE_REAL_SINGLE)
598: PetscStackCallExternalVoid("SuperLU:cCreate_Dense_Matrix(", cCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
599: PetscStackCallExternalVoid("SuperLU:cCreate_Dense_Matrix(", cCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_C, SLU_GE));
600: #else
601: PetscStackCallExternalVoid("SuperLU:zCreate_Dense_Matrix", zCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
602: PetscStackCallExternalVoid("SuperLU:zCreate_Dense_Matrix", zCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_Z, SLU_GE));
603: #endif
604: #else
605: #if defined(PETSC_USE_REAL_SINGLE)
606: PetscStackCallExternalVoid("SuperLU:sCreate_Dense_Matrix", sCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
607: PetscStackCallExternalVoid("SuperLU:sCreate_Dense_Matrix", sCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_S, SLU_GE));
608: #else
609: PetscStackCallExternalVoid("SuperLU:dCreate_Dense_Matrix", dCreate_Dense_Matrix(&lu->B, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
610: PetscStackCallExternalVoid("SuperLU:dCreate_Dense_Matrix", dCreate_Dense_Matrix(&lu->X, m, 1, NULL, m, SLU_DN, SLU_D, SLU_GE));
611: #endif
612: #endif
614: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatFactorGetSolverType_C", MatFactorGetSolverType_seqaij_superlu));
615: PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSuperluSetILUDropTol_C", MatSuperluSetILUDropTol_SuperLU));
616: B->data = lu;
618: *F = B;
619: PetscFunctionReturn(PETSC_SUCCESS);
620: }
622: static PetscErrorCode MatGetFactor_seqsell_superlu(Mat A, MatFactorType ftype, Mat *F)
623: {
624: Mat_SuperLU *lu;
626: PetscFunctionBegin;
627: PetscCall(MatGetFactor_seqaij_superlu(A, ftype, F));
628: lu = (Mat_SuperLU *)((*F)->data);
629: lu->needconversion = PETSC_TRUE;
630: PetscFunctionReturn(PETSC_SUCCESS);
631: }
633: PETSC_INTERN PetscErrorCode MatSolverTypeRegister_SuperLU(void)
634: {
635: PetscFunctionBegin;
636: PetscCall(MatSolverTypeRegister(MATSOLVERSUPERLU, MATSEQAIJ, MAT_FACTOR_LU, MatGetFactor_seqaij_superlu));
637: PetscCall(MatSolverTypeRegister(MATSOLVERSUPERLU, MATSEQAIJ, MAT_FACTOR_ILU, MatGetFactor_seqaij_superlu));
638: PetscCall(MatSolverTypeRegister(MATSOLVERSUPERLU, MATSEQSELL, MAT_FACTOR_LU, MatGetFactor_seqsell_superlu));
639: PetscCall(MatSolverTypeRegister(MATSOLVERSUPERLU, MATSEQSELL, MAT_FACTOR_ILU, MatGetFactor_seqsell_superlu));
640: PetscFunctionReturn(PETSC_SUCCESS);
641: }