/* Provides an interface to the LUSOL package of .... */ #include <../src/mat/impls/aij/seq/aij.h> #if defined(PETSC_HAVE_FORTRAN_UNDERSCORE) #define LU1FAC lu1fac_ #define LU6SOL lu6sol_ #define M1PAGE m1page_ #define M5SETX m5setx_ #define M6RDEL m6rdel_ #elif !defined(PETSC_HAVE_FORTRAN_CAPS) #define LU1FAC lu1fac #define LU6SOL lu6sol #define M1PAGE m1page #define M5SETX m5setx #define M6RDEL m6rdel #endif /* Dummy symbols that the MINOS files mi25bfac.f and mi15blas.f may require */ PETSC_EXTERN void M1PAGE() { ; } PETSC_EXTERN void M5SETX() { ; } PETSC_EXTERN void M6RDEL() { ; } 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); 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); extern PetscErrorCode MatDuplicate_LUSOL(Mat, MatDuplicateOption, Mat *); typedef struct { double *data; int *indc; int *indr; int *ip; int *iq; int *lenc; int *lenr; int *locc; int *locr; int *iploc; int *iqloc; int *ipinv; int *iqinv; double *mnsw; double *mnsv; double elbowroom; double luroom; /* Extra space allocated when factor fails */ double parmlu[30]; /* Input/output to LUSOL */ int n; /* Number of rows/columns in matrix */ int nz; /* Number of nonzeros */ int nnz; /* Number of nonzeros allocated for factors */ int luparm[30]; /* Input/output to LUSOL */ PetscBool CleanUpLUSOL; } Mat_LUSOL; /* LUSOL input/Output Parameters (Description uses C-style indexes * * Input parameters Typical value * * luparm(0) = nout File number for printed messages. 6 * luparm(1) = lprint Print level. 0 * < 0 suppresses output. * = 0 gives error messages. * = 1 gives debug output from some of the * other routines in LUSOL. * >= 2 gives the pivot row and column and the * no. of rows and columns involved at * each elimination step in lu1fac. * luparm(2) = maxcol lu1fac: maximum number of columns 5 * searched allowed in a Markowitz-type * search for the next pivot element. * For some of the factorization, the * number of rows searched is * maxrow = maxcol - 1. * * * Output parameters: * * luparm(9) = inform Return code from last call to any LU routine. * luparm(10) = nsing No. of singularities marked in the * output array w(*). * luparm(11) = jsing Column index of last singularity. * luparm(12) = minlen Minimum recommended value for lena. * luparm(13) = maxlen ? * luparm(14) = nupdat No. of updates performed by the lu8 routines. * luparm(15) = nrank No. of nonempty rows of U. * luparm(16) = ndens1 No. of columns remaining when the density of * the matrix being factorized reached dens1. * luparm(17) = ndens2 No. of columns remaining when the density of * the matrix being factorized reached dens2. * luparm(18) = jumin The column index associated with dumin. * luparm(19) = numl0 No. of columns in initial L. * luparm(20) = lenl0 Size of initial L (no. of nonzeros). * luparm(21) = lenu0 Size of initial U. * luparm(22) = lenl Size of current L. * luparm(23) = lenu Size of current U. * luparm(24) = lrow Length of row file. * luparm(25) = ncp No. of compressions of LU data structures. * luparm(26) = mersum lu1fac: sum of Markowitz merit counts. * luparm(27) = nutri lu1fac: triangular rows in U. * luparm(28) = nltri lu1fac: triangular rows in L. * luparm(29) = * * * Input parameters Typical value * * parmlu(0) = elmax1 Max multiplier allowed in L 10.0 * during factor. * parmlu(1) = elmax2 Max multiplier allowed in L 10.0 * during updates. * parmlu(2) = small Absolute tolerance for eps**0.8 * treating reals as zero. IBM double: 3.0d-13 * parmlu(3) = utol1 Absolute tol for flagging eps**0.66667 * small diagonals of U. IBM double: 3.7d-11 * parmlu(4) = utol2 Relative tol for flagging eps**0.66667 * small diagonals of U. IBM double: 3.7d-11 * parmlu(5) = uspace Factor limiting waste space in U. 3.0 * In lu1fac, the row or column lists * are compressed if their length * exceeds uspace times the length of * either file after the last compression. * parmlu(6) = dens1 The density at which the Markowitz 0.3 * strategy should search maxcol columns * and no rows. * parmlu(7) = dens2 the density at which the Markowitz 0.6 * strategy should search only 1 column * or (preferably) use a dense LU for * all the remaining rows and columns. * * * Output parameters: * * parmlu(9) = amax Maximum element in A. * parmlu(10) = elmax Maximum multiplier in current L. * parmlu(11) = umax Maximum element in current U. * parmlu(12) = dumax Maximum diagonal in U. * parmlu(13) = dumin Minimum diagonal in U. * parmlu(14) = * parmlu(15) = * parmlu(16) = * parmlu(17) = * parmlu(18) = * parmlu(19) = resid lu6sol: residual after solve with U or U'. * ... * parmlu(29) = */ #define Factorization_Tolerance 1e-1 #define Factorization_Pivot_Tolerance pow(2.2204460492503131E-16, 2.0 / 3.0) #define Factorization_Small_Tolerance 1e-15 /* pow(DBL_EPSILON, 0.8) */ static PetscErrorCode MatDestroy_LUSOL(Mat A) { Mat_LUSOL *lusol = (Mat_LUSOL *)A->spptr; PetscFunctionBegin; if (lusol && lusol->CleanUpLUSOL) { PetscCall(PetscFree(lusol->ip)); PetscCall(PetscFree(lusol->iq)); PetscCall(PetscFree(lusol->lenc)); PetscCall(PetscFree(lusol->lenr)); PetscCall(PetscFree(lusol->locc)); PetscCall(PetscFree(lusol->locr)); PetscCall(PetscFree(lusol->iploc)); PetscCall(PetscFree(lusol->iqloc)); PetscCall(PetscFree(lusol->ipinv)); PetscCall(PetscFree(lusol->iqinv)); PetscCall(PetscFree(lusol->mnsw)); PetscCall(PetscFree(lusol->mnsv)); PetscCall(PetscFree3(lusol->data, lusol->indc, lusol->indr)); } PetscCall(PetscFree(A->spptr)); PetscCall(MatDestroy_SeqAIJ(A)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatSolve_LUSOL(Mat A, Vec b, Vec x) { Mat_LUSOL *lusol = (Mat_LUSOL *)A->spptr; double *xx; const double *bb; int mode = 5; int i, m, n, nnz, status; PetscFunctionBegin; PetscCall(VecGetArray(x, &xx)); PetscCall(VecGetArrayRead(b, &bb)); m = n = lusol->n; nnz = lusol->nnz; for (i = 0; i < m; i++) lusol->mnsv[i] = bb[i]; 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); PetscCheck(!status, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "solve failed, error code %d", status); PetscCall(VecRestoreArray(x, &xx)); PetscCall(VecRestoreArrayRead(b, &bb)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatLUFactorNumeric_LUSOL(Mat F, Mat A, const MatFactorInfo *info) { Mat_SeqAIJ *a; Mat_LUSOL *lusol = (Mat_LUSOL *)F->spptr; int m, n, nz, nnz, status; int i, rs, re; int factorizations; PetscFunctionBegin; PetscCall(MatGetSize(A, &m, &n)); a = (Mat_SeqAIJ *)A->data; PetscCheck(m == lusol->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "factorization struct inconsistent"); factorizations = 0; do { /*******************************************************************/ /* Check the workspace allocation. */ /*******************************************************************/ nz = a->nz; nnz = PetscMax(lusol->nnz, (int)(lusol->elbowroom * nz)); nnz = PetscMax(nnz, 5 * n); if (nnz < lusol->luparm[12]) { nnz = (int)(lusol->luroom * lusol->luparm[12]); } else if ((factorizations > 0) && (lusol->luroom < 6)) { lusol->luroom += 0.1; } nnz = PetscMax(nnz, (int)(lusol->luroom * (lusol->luparm[22] + lusol->luparm[23]))); if (nnz > lusol->nnz) { PetscCall(PetscFree3(lusol->data, lusol->indc, lusol->indr)); PetscCall(PetscMalloc3(nnz, &lusol->data, nnz, &lusol->indc, nnz, &lusol->indr)); lusol->nnz = nnz; } /*******************************************************************/ /* Fill in the data for the problem. (1-based Fortran style) */ /*******************************************************************/ nz = 0; for (i = 0; i < n; i++) { rs = a->i[i]; re = a->i[i + 1]; while (rs < re) { if (a->a[rs] != 0.0) { lusol->indc[nz] = i + 1; lusol->indr[nz] = a->j[rs] + 1; lusol->data[nz] = a->a[rs]; nz++; } rs++; } } /*******************************************************************/ /* Do the factorization. */ /*******************************************************************/ 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); switch (status) { case 0: /* factored */ break; case 7: /* insufficient memory */ break; case 1: case -1: /* singular */ SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "Singular matrix"); case 3: case 4: /* error conditions */ SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "matrix error"); default: /* unknown condition */ SETERRQ(PETSC_COMM_SELF, PETSC_ERR_LIB, "matrix unknown return code"); } factorizations++; } while (status == 7); F->ops->solve = MatSolve_LUSOL; F->assembled = PETSC_TRUE; F->preallocated = PETSC_TRUE; PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatLUFactorSymbolic_LUSOL(Mat F, Mat A, IS r, IS c, const MatFactorInfo *info) { /************************************************************************/ /* Input */ /* A - matrix to factor */ /* r - row permutation (ignored) */ /* c - column permutation (ignored) */ /* */ /* Output */ /* F - matrix storing the factorization; */ /************************************************************************/ Mat_LUSOL *lusol; int i, m, n, nz, nnz; PetscFunctionBegin; /************************************************************************/ /* Check the arguments. */ /************************************************************************/ PetscCall(MatGetSize(A, &m, &n)); nz = ((Mat_SeqAIJ *)A->data)->nz; /************************************************************************/ /* Create the factorization. */ /************************************************************************/ F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL; lusol = (Mat_LUSOL *)F->spptr; /************************************************************************/ /* Initialize parameters */ /************************************************************************/ for (i = 0; i < 30; i++) { lusol->luparm[i] = 0; lusol->parmlu[i] = 0; } lusol->luparm[1] = -1; lusol->luparm[2] = 5; lusol->luparm[7] = 1; lusol->parmlu[0] = 1 / Factorization_Tolerance; lusol->parmlu[1] = 1 / Factorization_Tolerance; lusol->parmlu[2] = Factorization_Small_Tolerance; lusol->parmlu[3] = Factorization_Pivot_Tolerance; lusol->parmlu[4] = Factorization_Pivot_Tolerance; lusol->parmlu[5] = 3.0; lusol->parmlu[6] = 0.3; lusol->parmlu[7] = 0.6; /************************************************************************/ /* Allocate the workspace needed by LUSOL. */ /************************************************************************/ lusol->elbowroom = PetscMax(lusol->elbowroom, info->fill); nnz = PetscMax((int)(lusol->elbowroom * nz), 5 * n); lusol->n = n; lusol->nz = nz; lusol->nnz = nnz; lusol->luroom = 1.75; PetscCall(PetscMalloc(sizeof(int) * n, &lusol->ip)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iq)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->lenc)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->lenr)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->locc)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->locr)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iploc)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iqloc)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->ipinv)); PetscCall(PetscMalloc(sizeof(int) * n, &lusol->iqinv)); PetscCall(PetscMalloc(sizeof(double) * n, &lusol->mnsw)); PetscCall(PetscMalloc(sizeof(double) * n, &lusol->mnsv)); PetscCall(PetscMalloc3(nnz, &lusol->data, nnz, &lusol->indc, nnz, &lusol->indr)); lusol->CleanUpLUSOL = PETSC_TRUE; F->ops->lufactornumeric = MatLUFactorNumeric_LUSOL; PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode MatFactorGetSolverType_seqaij_lusol(Mat A, MatSolverType *type) { PetscFunctionBegin; *type = MATSOLVERLUSOL; PetscFunctionReturn(PETSC_SUCCESS); } PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat A, MatFactorType ftype, Mat *F) { Mat B; Mat_LUSOL *lusol; int m, n; PetscFunctionBegin; PetscCall(MatGetSize(A, &m, &n)); PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); PetscCall(MatSetSizes(B, PETSC_DECIDE, PETSC_DECIDE, m, n)); PetscCall(MatSetType(B, ((PetscObject)A)->type_name)); PetscCall(MatSeqAIJSetPreallocation(B, 0, NULL)); PetscCall(PetscNew(&lusol)); B->spptr = lusol; B->trivialsymbolic = PETSC_TRUE; B->ops->lufactorsymbolic = MatLUFactorSymbolic_LUSOL; B->ops->destroy = MatDestroy_LUSOL; PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatFactorGetSolverType_C", MatFactorGetSolverType_seqaij_lusol)); B->factortype = MAT_FACTOR_LU; PetscCall(PetscFree(B->solvertype)); PetscCall(PetscStrallocpy(MATSOLVERLUSOL, &B->solvertype)); PetscFunctionReturn(PETSC_SUCCESS); } PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_Lusol(void) { PetscFunctionBegin; PetscCall(MatSolverTypeRegister(MATSOLVERLUSOL, MATSEQAIJ, MAT_FACTOR_LU, MatGetFactor_seqaij_lusol)); PetscFunctionReturn(PETSC_SUCCESS); } /*MC MATSOLVERLUSOL - "lusol" - Provides direct solvers, LU, for sequential matrices via the external package LUSOL. Works with `MATSEQAIJ` matrices Level: beginner .seealso: [](ch_matrices), `Mat`, `PCLU`, `PCFactorSetMatSolverType()`, `MatSolverType` M*/