Actual source code: umfpack.c
2: /*
3: Provides an interface to the UMFPACKv4.3 sparse solver
4: */
6: #include src/mat/impls/aij/seq/aij.h
9: #include "umfpack.h"
12: typedef struct {
13: void *Symbolic, *Numeric;
14: double Info[UMFPACK_INFO], Control[UMFPACK_CONTROL],*W;
15: int *Wi,*ai,*aj,*perm_c;
16: PetscScalar *av;
17: MatStructure flg;
18: PetscTruth PetscMatOdering;
20: /* A few function pointers for inheritance */
21: PetscErrorCode (*MatDuplicate)(Mat,MatDuplicateOption,Mat*);
22: PetscErrorCode (*MatView)(Mat,PetscViewer);
23: PetscErrorCode (*MatAssemblyEnd)(Mat,MatAssemblyType);
24: PetscErrorCode (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*);
25: PetscErrorCode (*MatDestroy)(Mat);
26:
27: /* Flag to clean up UMFPACK objects during Destroy */
28: PetscTruth CleanUpUMFPACK;
29: } Mat_UMFPACK;
31: EXTERN PetscErrorCode MatDuplicate_UMFPACK(Mat,MatDuplicateOption,Mat*);
36: PetscErrorCode MatConvert_UMFPACK_SeqAIJ(Mat A,const MatType type,Mat *newmat)
37: {
38: /* This routine is only called to convert an unfactored PETSc-UMFPACK matrix */
39: /* to its base PETSc type, so we will ignore 'MatType type'. */
41: Mat B=*newmat;
42: Mat_UMFPACK *lu=(Mat_UMFPACK*)A->spptr;
45: if (B != A) {
46: MatDuplicate(A,MAT_COPY_VALUES,&B);
47: }
48: /* Reset the original function pointers */
49: B->ops->duplicate = lu->MatDuplicate;
50: B->ops->view = lu->MatView;
51: B->ops->assemblyend = lu->MatAssemblyEnd;
52: B->ops->lufactorsymbolic = lu->MatLUFactorSymbolic;
53: B->ops->destroy = lu->MatDestroy;
54:
55: PetscFree(lu);
57: PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_umfpack_C","",PETSC_NULL);
58: PetscObjectComposeFunction((PetscObject)B,"MatConvert_umfpack_seqaij_C","",PETSC_NULL);
60: PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);
61: *newmat = B;
62: return(0);
63: }
68: PetscErrorCode MatDestroy_UMFPACK(Mat A)
69: {
71: Mat_UMFPACK *lu=(Mat_UMFPACK*)A->spptr;
74: if (lu->CleanUpUMFPACK) {
75: umfpack_di_free_symbolic(&lu->Symbolic);
76: umfpack_di_free_numeric(&lu->Numeric);
77: PetscFree(lu->Wi);
78: PetscFree(lu->W);
79: if (lu->PetscMatOdering) {
80: PetscFree(lu->perm_c);
81: }
82: }
83: MatConvert_UMFPACK_SeqAIJ(A,MATSEQAIJ,&A);
84: (*A->ops->destroy)(A);
85: return(0);
86: }
90: PetscErrorCode MatSolve_UMFPACK(Mat A,Vec b,Vec x)
91: {
92: Mat_UMFPACK *lu = (Mat_UMFPACK*)A->spptr;
93: PetscScalar *av=lu->av,*ba,*xa;
95: int *ai=lu->ai,*aj=lu->aj,status;
96:
98: /* solve Ax = b by umfpack_di_wsolve */
99: /* ----------------------------------*/
100: VecGetArray(b,&ba);
101: VecGetArray(x,&xa);
103: status = umfpack_di_wsolve(UMFPACK_At,ai,aj,av,xa,ba,lu->Numeric,lu->Control,lu->Info,lu->Wi,lu->W);
104: umfpack_di_report_info(lu->Control, lu->Info);
105: if (status < 0){
106: umfpack_di_report_status(lu->Control, status);
107: SETERRQ(PETSC_ERR_LIB,"umfpack_di_wsolve failed");
108: }
109:
110: VecRestoreArray(b,&ba);
111: VecRestoreArray(x,&xa);
113: return(0);
114: }
118: PetscErrorCode MatLUFactorNumeric_UMFPACK(Mat A,Mat *F)
119: {
120: Mat_UMFPACK *lu=(Mat_UMFPACK*)(*F)->spptr;
122: int *ai=lu->ai,*aj=lu->aj,m=A->m,status;
123: PetscScalar *av=lu->av;
126: /* numeric factorization of A' */
127: /* ----------------------------*/
128: if (lu->flg == SAME_NONZERO_PATTERN && lu->Numeric){
129: umfpack_di_free_numeric(&lu->Numeric);
130: }
131: status = umfpack_di_numeric (ai,aj,av,lu->Symbolic,&lu->Numeric,lu->Control,lu->Info);
132: if (status < 0) SETERRQ(PETSC_ERR_LIB,"umfpack_di_numeric failed");
133: /* report numeric factorization of A' when Control[PRL] > 3 */
134: (void) umfpack_di_report_numeric (lu->Numeric, lu->Control);
136: if (lu->flg == DIFFERENT_NONZERO_PATTERN){ /* first numeric factorization */
137: /* allocate working space to be used by Solve */
138: PetscMalloc(m * sizeof(int), &lu->Wi);
139: PetscMalloc(5*m * sizeof(double), &lu->W);
140: }
141: lu->flg = SAME_NONZERO_PATTERN;
142: lu->CleanUpUMFPACK = PETSC_TRUE;
143: return(0);
144: }
146: /*
147: Note the r permutation is ignored
148: */
151: PetscErrorCode MatLUFactorSymbolic_UMFPACK(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F)
152: {
153: Mat B;
154: Mat_SeqAIJ *mat=(Mat_SeqAIJ*)A->data;
155: Mat_UMFPACK *lu;
157: int m=A->m,n=A->n,*ai=mat->i,*aj=mat->j,status,*ra,idx;
158: PetscScalar *av=mat->a;
159: const char *strategy[]={"AUTO","UNSYMMETRIC","SYMMETRIC","2BY2"},
160: *scale[]={"NONE","SUM","MAX"};
161: PetscTruth flg;
162:
164: /* Create the factorization matrix F */
165: MatCreate(A->comm,PETSC_DECIDE,PETSC_DECIDE,m,n,&B);
166: MatSetType(B,A->type_name);
167: MatSeqAIJSetPreallocation(B,0,PETSC_NULL);
168:
169: B->ops->lufactornumeric = MatLUFactorNumeric_UMFPACK;
170: B->ops->solve = MatSolve_UMFPACK;
171: B->factor = FACTOR_LU;
172: B->assembled = PETSC_TRUE; /* required by -ksp_view */
174: lu = (Mat_UMFPACK*)(B->spptr);
175:
176: /* initializations */
177: /* ------------------------------------------------*/
178: /* get the default control parameters */
179: umfpack_di_defaults (lu->Control);
180: lu->perm_c = PETSC_NULL; /* use defaul UMFPACK col permutation */
181: lu->Control[UMFPACK_IRSTEP] = 0; /* max num of iterative refinement steps to attempt */
183: PetscOptionsBegin(A->comm,A->prefix,"UMFPACK Options","Mat");
184: /* Control parameters used by reporting routiones */
185: PetscOptionsReal("-mat_umfpack_prl","Control[UMFPACK_PRL]","None",lu->Control[UMFPACK_PRL],&lu->Control[UMFPACK_PRL],PETSC_NULL);
187: /* Control parameters for symbolic factorization */
188: PetscOptionsEList("-mat_umfpack_strategy","ordering and pivoting strategy","None",strategy,4,strategy[0],&idx,&flg);
189: if (flg) {
190: switch (idx){
191: case 0: lu->Control[UMFPACK_STRATEGY] = UMFPACK_STRATEGY_AUTO; break;
192: case 1: lu->Control[UMFPACK_STRATEGY] = UMFPACK_STRATEGY_UNSYMMETRIC; break;
193: case 2: lu->Control[UMFPACK_STRATEGY] = UMFPACK_STRATEGY_SYMMETRIC; break;
194: case 3: lu->Control[UMFPACK_STRATEGY] = UMFPACK_STRATEGY_2BY2; break;
195: }
196: }
197: PetscOptionsReal("-mat_umfpack_dense_col","Control[UMFPACK_DENSE_COL]","None",lu->Control[UMFPACK_DENSE_COL],&lu->Control[UMFPACK_DENSE_COL],PETSC_NULL);
198: PetscOptionsReal("-mat_umfpack_dense_row","Control[UMFPACK_DENSE_ROW]","None",lu->Control[UMFPACK_DENSE_ROW],&lu->Control[UMFPACK_DENSE_ROW],PETSC_NULL);
199: PetscOptionsReal("-mat_umfpack_amd_dense","Control[UMFPACK_AMD_DENSE]","None",lu->Control[UMFPACK_AMD_DENSE],&lu->Control[UMFPACK_AMD_DENSE],PETSC_NULL);
200: PetscOptionsReal("-mat_umfpack_block_size","Control[UMFPACK_BLOCK_SIZE]","None",lu->Control[UMFPACK_BLOCK_SIZE],&lu->Control[UMFPACK_BLOCK_SIZE],PETSC_NULL);
201: PetscOptionsReal("-mat_umfpack_2by2_tolerance","Control[UMFPACK_2BY2_TOLERANCE]","None",lu->Control[UMFPACK_2BY2_TOLERANCE],&lu->Control[UMFPACK_2BY2_TOLERANCE],PETSC_NULL);
202: PetscOptionsReal("-mat_umfpack_fixq","Control[UMFPACK_FIXQ]","None",lu->Control[UMFPACK_FIXQ],&lu->Control[UMFPACK_FIXQ],PETSC_NULL);
203: PetscOptionsReal("-mat_umfpack_aggressive","Control[UMFPACK_AGGRESSIVE]","None",lu->Control[UMFPACK_AGGRESSIVE],&lu->Control[UMFPACK_AGGRESSIVE],PETSC_NULL);
205: /* Control parameters used by numeric factorization */
206: PetscOptionsReal("-mat_umfpack_pivot_tolerance","Control[UMFPACK_PIVOT_TOLERANCE]","None",lu->Control[UMFPACK_PIVOT_TOLERANCE],&lu->Control[UMFPACK_PIVOT_TOLERANCE],PETSC_NULL);
207: PetscOptionsReal("-mat_umfpack_sym_pivot_tolerance","Control[UMFPACK_SYM_PIVOT_TOLERANCE]","None",lu->Control[UMFPACK_SYM_PIVOT_TOLERANCE],&lu->Control[UMFPACK_SYM_PIVOT_TOLERANCE],PETSC_NULL);
208: PetscOptionsEList("-mat_umfpack_scale","Control[UMFPACK_SCALE]","None",scale,3,scale[0],&idx,&flg);
209: if (flg) {
210: switch (idx){
211: case 0: lu->Control[UMFPACK_SCALE] = UMFPACK_SCALE_NONE; break;
212: case 1: lu->Control[UMFPACK_SCALE] = UMFPACK_SCALE_SUM; break;
213: case 2: lu->Control[UMFPACK_SCALE] = UMFPACK_SCALE_MAX; break;
214: }
215: }
216: PetscOptionsReal("-mat_umfpack_alloc_init","Control[UMFPACK_ALLOC_INIT]","None",lu->Control[UMFPACK_ALLOC_INIT],&lu->Control[UMFPACK_ALLOC_INIT],PETSC_NULL);
217: PetscOptionsReal("-mat_umfpack_front_alloc_init","Control[UMFPACK_FRONT_ALLOC_INIT]","None",lu->Control[UMFPACK_FRONT_ALLOC_INIT],&lu->Control[UMFPACK_ALLOC_INIT],PETSC_NULL);
218: PetscOptionsReal("-mat_umfpack_droptol","Control[UMFPACK_DROPTOL]","None",lu->Control[UMFPACK_DROPTOL],&lu->Control[UMFPACK_DROPTOL],PETSC_NULL);
220: /* Control parameters used by solve */
221: PetscOptionsReal("-mat_umfpack_irstep","Control[UMFPACK_IRSTEP]","None",lu->Control[UMFPACK_IRSTEP],&lu->Control[UMFPACK_IRSTEP],PETSC_NULL);
222:
223: /* use Petsc mat ordering (note: size is for the transpose, and PETSc r = Umfpack perm_c) */
224: PetscOptionsHasName(PETSC_NULL,"-pc_lu_mat_ordering_type",&lu->PetscMatOdering);
225: if (lu->PetscMatOdering) {
226: ISGetIndices(r,&ra);
227: PetscMalloc(A->m*sizeof(int),&lu->perm_c);
228: PetscMemcpy(lu->perm_c,ra,A->m*sizeof(int));
229: ISRestoreIndices(r,&ra);
230: }
231: PetscOptionsEnd();
233: /* print the control parameters */
234: if( lu->Control[UMFPACK_PRL] > 1 ) umfpack_di_report_control (lu->Control);
236: /* symbolic factorization of A' */
237: /* ---------------------------------------------------------------------- */
238: if (lu->PetscMatOdering) { /* use Petsc row ordering */
239: status = umfpack_di_qsymbolic(n,m,ai,aj,av,lu->perm_c,&lu->Symbolic,lu->Control,lu->Info);
240: } else { /* use Umfpack col ordering */
241: status = umfpack_di_symbolic(n,m,ai,aj,av,&lu->Symbolic,lu->Control,lu->Info);
242: }
243: if (status < 0){
244: umfpack_di_report_info(lu->Control, lu->Info);
245: umfpack_di_report_status(lu->Control, status);
246: SETERRQ(PETSC_ERR_LIB,"umfpack_di_symbolic failed");
247: }
248: /* report sumbolic factorization of A' when Control[PRL] > 3 */
249: (void) umfpack_di_report_symbolic(lu->Symbolic, lu->Control);
251: lu->flg = DIFFERENT_NONZERO_PATTERN;
252: lu->ai = ai;
253: lu->aj = aj;
254: lu->av = av;
255: lu->CleanUpUMFPACK = PETSC_TRUE;
256: *F = B;
257: return(0);
258: }
262: PetscErrorCode MatAssemblyEnd_UMFPACK(Mat A,MatAssemblyType mode)
263: {
265: Mat_UMFPACK *lu=(Mat_UMFPACK*)(A->spptr);
268: (*lu->MatAssemblyEnd)(A,mode);
269: lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic;
270: A->ops->lufactorsymbolic = MatLUFactorSymbolic_UMFPACK;
271: return(0);
272: }
274: /* used by -ksp_view */
277: PetscErrorCode MatFactorInfo_UMFPACK(Mat A,PetscViewer viewer)
278: {
279: Mat_UMFPACK *lu= (Mat_UMFPACK*)A->spptr;
283: /* check if matrix is UMFPACK type */
284: if (A->ops->solve != MatSolve_UMFPACK) return(0);
286: PetscViewerASCIIPrintf(viewer,"UMFPACK run parameters:\n");
287: /* Control parameters used by reporting routiones */
288: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_PRL]: %g\n",lu->Control[UMFPACK_PRL]);
290: /* Control parameters used by symbolic factorization */
291: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_STRATEGY]: %g\n",lu->Control[UMFPACK_STRATEGY]);
292: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_DENSE_COL]: %g\n",lu->Control[UMFPACK_DENSE_COL]);
293: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_DENSE_ROW]: %g\n",lu->Control[UMFPACK_DENSE_ROW]);
294: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_AMD_DENSE]: %g\n",lu->Control[UMFPACK_AMD_DENSE]);
295: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_BLOCK_SIZE]: %g\n",lu->Control[UMFPACK_BLOCK_SIZE]);
296: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_2BY2_TOLERANCE]: %g\n",lu->Control[UMFPACK_2BY2_TOLERANCE]);
297: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_FIXQ]: %g\n",lu->Control[UMFPACK_FIXQ]);
298: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_AGGRESSIVE]: %g\n",lu->Control[UMFPACK_AGGRESSIVE]);
300: /* Control parameters used by numeric factorization */
301: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_PIVOT_TOLERANCE]: %g\n",lu->Control[UMFPACK_PIVOT_TOLERANCE]);
302: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_SYM_PIVOT_TOLERANCE]: %g\n",lu->Control[UMFPACK_SYM_PIVOT_TOLERANCE]);
303: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_SCALE]: %g\n",lu->Control[UMFPACK_SCALE]);
304: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_ALLOC_INIT]: %g\n",lu->Control[UMFPACK_ALLOC_INIT]);
305: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_DROPTOL]: %g\n",lu->Control[UMFPACK_DROPTOL]);
307: /* Control parameters used by solve */
308: PetscViewerASCIIPrintf(viewer," Control[UMFPACK_IRSTEP]: %g\n",lu->Control[UMFPACK_IRSTEP]);
310: /* mat ordering */
311: if(!lu->PetscMatOdering) PetscViewerASCIIPrintf(viewer," UMFPACK default matrix ordering is used (not the PETSc matrix ordering) \n");
313: return(0);
314: }
318: PetscErrorCode MatView_UMFPACK(Mat A,PetscViewer viewer)
319: {
321: PetscTruth iascii;
322: PetscViewerFormat format;
323: Mat_UMFPACK *lu=(Mat_UMFPACK*)(A->spptr);
326: (*lu->MatView)(A,viewer);
328: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
329: if (iascii) {
330: PetscViewerGetFormat(viewer,&format);
331: if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
332: MatFactorInfo_UMFPACK(A,viewer);
333: }
334: }
335: return(0);
336: }
341: PetscErrorCode MatConvert_SeqAIJ_UMFPACK(Mat A,const MatType type,Mat *newmat)
342: {
343: /* This routine is only called to convert to MATUMFPACK */
344: /* from MATSEQAIJ, so we will ignore 'MatType type'. */
346: Mat B=*newmat;
347: Mat_UMFPACK *lu;
350: if (B != A) {
351: MatDuplicate(A,MAT_COPY_VALUES,&B);
352: }
354: PetscNew(Mat_UMFPACK,&lu);
355: lu->MatDuplicate = A->ops->duplicate;
356: lu->MatView = A->ops->view;
357: lu->MatAssemblyEnd = A->ops->assemblyend;
358: lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic;
359: lu->MatDestroy = A->ops->destroy;
360: lu->CleanUpUMFPACK = PETSC_FALSE;
362: B->spptr = (void*)lu;
363: B->ops->duplicate = MatDuplicate_UMFPACK;
364: B->ops->view = MatView_UMFPACK;
365: B->ops->assemblyend = MatAssemblyEnd_UMFPACK;
366: B->ops->lufactorsymbolic = MatLUFactorSymbolic_UMFPACK;
367: B->ops->destroy = MatDestroy_UMFPACK;
369: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_umfpack_C",
370: "MatConvert_SeqAIJ_UMFPACK",MatConvert_SeqAIJ_UMFPACK);
371: PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_umfpack_seqaij_C",
372: "MatConvert_UMFPACK_SeqAIJ",MatConvert_UMFPACK_SeqAIJ);
373: PetscLogInfo(0,"Using UMFPACK for SeqAIJ LU factorization and solves.");
374: PetscObjectChangeTypeName((PetscObject)B,MATUMFPACK);
375: *newmat = B;
376: return(0);
377: }
382: PetscErrorCode MatDuplicate_UMFPACK(Mat A, MatDuplicateOption op, Mat *M)
383: {
385: Mat_UMFPACK *lu=(Mat_UMFPACK*)A->spptr;
388: (*lu->MatDuplicate)(A,op,M);
389: PetscMemcpy((*M)->spptr,lu,sizeof(Mat_UMFPACK));
390: return(0);
391: }
393: /*MC
394: MATUMFPACK - MATUMFPACK = "umfpack" - A matrix type providing direct solvers (LU) for sequential matrices
395: via the external package UMFPACK.
397: If UMFPACK is installed (see the manual for
398: instructions on how to declare the existence of external packages),
399: a matrix type can be constructed which invokes UMFPACK solvers.
400: After calling MatCreate(...,A), simply call MatSetType(A,UMFPACK).
401: This matrix type is only supported for double precision real.
403: This matrix inherits from MATSEQAIJ. As a result, MatSeqAIJSetPreallocation is
404: supported for this matrix type. One can also call MatConvert for an inplace conversion to or from
405: the MATSEQAIJ type without data copy.
407: Consult UMFPACK documentation for more information about the Control parameters
408: which correspond to the options database keys below.
410: Options Database Keys:
411: + -mat_type umfpack - sets the matrix type to "umfpack" during a call to MatSetFromOptions()
412: . -mat_umfpack_prl - UMFPACK print level: Control[UMFPACK_PRL]
413: . -mat_umfpack_dense_col <alpha_c> - UMFPACK dense column threshold: Control[UMFPACK_DENSE_COL]
414: . -mat_umfpack_block_size <bs> - UMFPACK block size for BLAS-Level 3 calls: Control[UMFPACK_BLOCK_SIZE]
415: . -mat_umfpack_pivot_tolerance <delta> - UMFPACK partial pivot tolerance: Control[UMFPACK_PIVOT_TOLERANCE]
416: . -mat_umfpack_alloc_init <delta> - UMFPACK factorized matrix allocation modifier: Control[UMFPACK_ALLOC_INIT]
417: - -mat_umfpack_irstep <maxit> - UMFPACK maximum number of iterative refinement steps: Control[UMFPACK_IRSTEP]
419: Level: beginner
421: .seealso: PCLU
422: M*/
427: PetscErrorCode MatCreate_UMFPACK(Mat A)
428: {
432: /* Change type name before calling MatSetType to force proper construction of SeqAIJ and UMFPACK types */
433: PetscObjectChangeTypeName((PetscObject)A,MATUMFPACK);
434: MatSetType(A,MATSEQAIJ);
435: MatConvert_SeqAIJ_UMFPACK(A,MATUMFPACK,&A);
436: return(0);
437: }