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Diffstat (limited to 'Eigen/src/PARDISOSupport/PARDISOSupport.h')
| -rw-r--r-- | Eigen/src/PARDISOSupport/PARDISOSupport.h | 427 |
1 files changed, 427 insertions, 0 deletions
diff --git a/Eigen/src/PARDISOSupport/PARDISOSupport.h b/Eigen/src/PARDISOSupport/PARDISOSupport.h new file mode 100644 index 000000000..d0d50c8f8 --- /dev/null +++ b/Eigen/src/PARDISOSupport/PARDISOSupport.h @@ -0,0 +1,427 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL PARDISO + ******************************************************************************** +*/ + +#ifndef EIGEN_PARDISOSUPPORT_H +#define EIGEN_PARDISOSUPPORT_H + +template<typename _MatrixType> +class PardisoLU; +template<typename _MatrixType> +class PardisoLLT; +template<typename _MatrixType> +class PardisoLDLT; + +namespace internal +{ + template<typename Index> + struct pardiso_run_selector + { + static Index run(_MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a, + Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x) + { + Index error = 0; + ::pardiso(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error); + return error; + } + }; + template<> + struct pardiso_run_selector<long long int> + { + typedef long long int Index; + static Index run(_MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a, + Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x) + { + Index error = 0; + ::pardiso_64(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error); + return error; + } + }; + + template<class Pardiso> + struct pardiso_traits; + + template<typename _MatrixType> + struct pardiso_traits< PardisoLU<_MatrixType> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template<typename _MatrixType> + struct pardiso_traits< PardisoLLT<_MatrixType> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template<typename _MatrixType> + struct pardiso_traits< PardisoLDLT<_MatrixType> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + +} + +template<class Derived> +class PardisoImpl +{ + public: + typedef typename internal::pardiso_traits<Derived>::MatrixType MatrixType; + typedef typename internal::pardiso_traits<Derived>::Scalar Scalar; + typedef typename internal::pardiso_traits<Derived>::RealScalar RealScalar; + typedef typename internal::pardiso_traits<Derived>::Index Index; + typedef Matrix<Scalar,Dynamic,1> VectorType; + typedef Matrix<Index, 1, MatrixType::ColsAtCompileTime> IntRowVectorType; + typedef Matrix<Index, MatrixType::RowsAtCompileTime, 1> IntColVectorType; + enum { + ScalarIsComplex = NumTraits<Scalar>::IsComplex + }; + + PardisoImpl(int flags) : m_flags(flags) + { + eigen_assert((sizeof(Index) >= sizeof(_INTEGER_t) && sizeof(Index) <= 8) && "Non-supported index type"); + memset(m_iparm, 0, sizeof(m_iparm)); + m_msglvl = 0; /* No output */ + m_initialized = false; + } + + ~PardisoImpl() + { + pardisoRelease(); + } + + inline Index cols() const { return m_matrix.cols(); } + inline Index rows() const { return m_matrix.rows(); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_initialized && "Decomposition is not initialized."); + return m_info; + } + + int orderingMethod() const + { + return m_flags&OrderingMask; + } + + Derived& compute(const MatrixType& matrix); + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template<typename Rhs> + inline const internal::solve_retval<PardisoImpl, Rhs> + solve(const MatrixBase<Rhs>& b, const int transposed = SvNoTrans) const + { + eigen_assert(m_initialized && "SimplicialCholesky is not initialized."); + eigen_assert(rows()==b.rows() + && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval<PardisoImpl, Rhs>(*this, b.derived(), transposed); + } + + Derived& derived() + { + return *static_cast<Derived*>(this); + } + const Derived& derived() const + { + return *static_cast<const Derived*>(this); + } + + template<typename BDerived, typename XDerived> + bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x, const int transposed = SvNoTrans) const; + + protected: + void pardisoRelease() + { + if(m_initialized) // Factorization ran at least once + { + internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, -1, m_matrix.rows(), NULL, NULL, NULL, m_perm.data(), 0, + m_iparm, m_msglvl, NULL, NULL); + memset(m_iparm, 0, sizeof(m_iparm)); + } + } + protected: + // cached data to reduce reallocation, etc. + + ComputationInfo m_info; + bool m_symmetric, m_initialized, m_succeeded; + int m_flags; + Index m_type, m_msglvl; + mutable void *m_pt[64]; + mutable Index m_iparm[64]; + mutable SparseMatrix<Scalar, RowMajor> m_matrix; + mutable IntColVectorType m_perm; +}; + +template<class Derived> +Derived& PardisoImpl<Derived>::compute(const MatrixType& a) +{ + Index n = a.rows(), i; + eigen_assert(a.rows() == a.cols()); + + pardisoRelease(); + memset(m_pt, 0, sizeof(m_pt)); + m_initialized = true; + + m_symmetric = abs(m_type) < 10; + + switch (orderingMethod()) + { + case MinimumDegree_AT_PLUS_A : m_iparm[1] = 0; break; + case NaturalOrdering : m_iparm[5] = 1; break; + case Metis : m_iparm[1] = 3; break; + default: + //std::cerr << "Eigen: ordering method \"" << Base::orderingMethod() << "\" not supported by the PARDISO backend\n"; + m_iparm[1] = 0; + }; + + m_iparm[0] = 1; /* No solver default */ + /* Numbers of processors, value of OMP_NUM_THREADS */ + m_iparm[2] = 1; + m_iparm[3] = 0; /* No iterative-direct algorithm */ + m_iparm[4] = 0; /* No user fill-in reducing permutation */ + m_iparm[5] = 0; /* Write solution into x */ + m_iparm[6] = 0; /* Not in use */ + m_iparm[7] = 2; /* Max numbers of iterative refinement steps */ + m_iparm[8] = 0; /* Not in use */ + m_iparm[9] = 13; /* Perturb the pivot elements with 1E-13 */ + m_iparm[10] = m_symmetric ? 0 : 1; /* Use nonsymmetric permutation and scaling MPS */ + m_iparm[11] = 0; /* Not in use */ + m_iparm[12] = m_symmetric ? 0 : 1; /* Maximum weighted matching algorithm is switched-off (default for symmetric). Try m_iparm[12] = 1 in case of inappropriate accuracy */ + m_iparm[13] = 0; /* Output: Number of perturbed pivots */ + m_iparm[14] = 0; /* Not in use */ + m_iparm[15] = 0; /* Not in use */ + m_iparm[16] = 0; /* Not in use */ + m_iparm[17] = -1; /* Output: Number of nonzeros in the factor LU */ + m_iparm[18] = -1; /* Output: Mflops for LU factorization */ + m_iparm[19] = 0; /* Output: Numbers of CG Iterations */ + m_iparm[20] = 0; /* 1x1 pivoting */ + m_iparm[26] = 0; /* No matrix checker */ + m_iparm[27] = (sizeof(RealScalar) == 4) ? 1 : 0; + m_iparm[34] = 0; /* Fortran indexing */ + m_iparm[59] = 1; /* Automatic switch between In-Core and Out-of-Core modes */ + + m_perm.resize(n); + if(orderingMethod() == NaturalOrdering) + { + for(Index i = 0; i < n; i++) + m_perm[i] = i; + } + + m_matrix = a; + + /* Convert to Fortran-style indexing */ + for(i = 0; i <= m_matrix.rows(); ++i) + ++m_matrix._outerIndexPtr()[i]; + for(i = 0; i < m_matrix.nonZeros(); ++i) + ++m_matrix._innerIndexPtr()[i]; + + Index error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 12, n, + m_matrix._valuePtr(), m_matrix._outerIndexPtr(), m_matrix._innerIndexPtr(), + m_perm.data(), 0, m_iparm, m_msglvl, NULL, NULL); + + switch(error) + { + case 0: + m_succeeded = true; + m_info = Success; + return derived(); + case -4: + case -7: + m_info = NumericalIssue; + break; + default: + m_info = InvalidInput; + } + m_succeeded = false; + return derived(); +} + +template<class Base> +template<typename BDerived,typename XDerived> +bool PardisoImpl<Base>::_solve(const MatrixBase<BDerived> &b, + MatrixBase<XDerived>& x, const int transposed) const +{ + if(m_iparm[0] == 0) // Factorization was not computed + return false; + + Index n = m_matrix.rows(); + Index nrhs = b.cols(); + eigen_assert(n==b.rows()); + eigen_assert(((MatrixBase<BDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major right hand sides are not supported"); + eigen_assert(((MatrixBase<XDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major matrices of unknowns are not supported"); + eigen_assert(((nrhs == 1) || b.outerStride() == b.rows())); + + x.derived().resizeLike(b); + + switch (transposed) { + case SvNoTrans : m_iparm[11] = 0 ; break; + case SvTranspose : m_iparm[11] = 2 ; break; + case SvAdjoint : m_iparm[11] = 1 ; break; + default: + //std::cerr << "Eigen: transposition option \"" << transposed << "\" not supported by the PARDISO backend\n"; + m_iparm[11] = 0; + } + + Index error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 33, n, + m_matrix._valuePtr(), m_matrix._outerIndexPtr(), m_matrix._innerIndexPtr(), + m_perm.data(), nrhs, m_iparm, m_msglvl, const_cast<Scalar*>(&b(0, 0)), &x(0, 0)); + + return error==0; +} + + +template<typename MatrixType> +class PardisoLU : public PardisoImpl< PardisoLU<MatrixType> > +{ + protected: + typedef PardisoImpl< PardisoLU<MatrixType> > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + using Base::m_type; + + public: + + using Base::compute; + using Base::solve; + + PardisoLU(int flags = Metis) + : Base(flags) + { + m_type = Base::ScalarIsComplex ? 13 : 11; + } + + PardisoLU(const MatrixType& matrix, int flags = Metis) + : Base(flags) + { + m_type = Base::ScalarIsComplex ? 13 : 11; + compute(matrix); + } +}; + +template<typename MatrixType> +class PardisoLLT : public PardisoImpl< PardisoLLT<MatrixType> > +{ + protected: + typedef PardisoImpl< PardisoLLT<MatrixType> > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + using Base::m_type; + + public: + + using Base::compute; + using Base::solve; + + PardisoLLT(int flags = Metis) + : Base(flags) + { + m_type = Base::ScalarIsComplex ? 4 : 2; + } + + PardisoLLT(const MatrixType& matrix, int flags = Metis) + : Base(flags) + { + m_type = Base::ScalarIsComplex ? 4 : 2; + compute(matrix); + } +}; + +template<typename MatrixType> +class PardisoLDLT : public PardisoImpl< PardisoLDLT<MatrixType> > +{ + protected: + typedef PardisoImpl< PardisoLDLT<MatrixType> > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + using Base::m_type; + + public: + + using Base::compute; + using Base::solve; + + PardisoLDLT(int flags = Metis) + : Base(flags) + { + m_type = Base::ScalarIsComplex ? -4 : -2; + } + + PardisoLDLT(const MatrixType& matrix, int flags = Metis, bool hermitian = true) + : Base(flags) + { + compute(matrix, hermitian); + } + + void compute(const MatrixType& matrix, bool hermitian = true) + { + m_type = Base::ScalarIsComplex ? (hermitian ? -4 : 6) : -2; + Base::compute(matrix); + } + +}; + +namespace internal { + +template<typename _Derived, typename Rhs> +struct solve_retval<PardisoImpl<_Derived>, Rhs> + : solve_retval_base<PardisoImpl<_Derived>, Rhs> +{ + typedef PardisoImpl<_Derived> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + solve_retval(const PardisoImpl<_Derived>& dec, const Rhs& rhs, const int transposed) + : Base(dec, rhs), m_transposed(transposed) {} + + template<typename Dest> void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst,m_transposed); + } + + int m_transposed; +}; + +} + +#endif // EIGEN_PARDISOSUPPORT_H |