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diff --git a/src/EigenUnsupported/src/Skyline/SkylineInplaceLU.h b/src/EigenUnsupported/src/Skyline/SkylineInplaceLU.h
deleted file mode 100644
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--- a/src/EigenUnsupported/src/Skyline/SkylineInplaceLU.h
+++ /dev/null
@@ -1,352 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Guillaume Saupin <guillaume.saupin@cea.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SKYLINEINPLACELU_H
-#define EIGEN_SKYLINEINPLACELU_H
-
-namespace Eigen { 
-
-/** \ingroup Skyline_Module
- *
- * \class SkylineInplaceLU
- *
- * \brief Inplace LU decomposition of a skyline matrix and associated features
- *
- * \param MatrixType the type of the matrix of which we are computing the LU factorization
- *
- */
-template<typename MatrixType>
-class SkylineInplaceLU {
-protected:
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::Index Index;
-    
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-
-public:
-
-    /** Creates a LU object and compute the respective factorization of \a matrix using
-     * flags \a flags. */
-    SkylineInplaceLU(MatrixType& matrix, int flags = 0)
-    : /*m_matrix(matrix.rows(), matrix.cols()),*/ m_flags(flags), m_status(0), m_lu(matrix) {
-        m_precision = RealScalar(0.1) * Eigen::dummy_precision<RealScalar > ();
-        m_lu.IsRowMajor ? computeRowMajor() : compute();
-    }
-
-    /** Sets the relative threshold value used to prune zero coefficients during the decomposition.
-     *
-     * Setting a value greater than zero speeds up computation, and yields to an incomplete
-     * factorization with fewer non zero coefficients. Such approximate factors are especially
-     * useful to initialize an iterative solver.
-     *
-     * Note that the exact meaning of this parameter might depends on the actual
-     * backend. Moreover, not all backends support this feature.
-     *
-     * \sa precision() */
-    void setPrecision(RealScalar v) {
-        m_precision = v;
-    }
-
-    /** \returns the current precision.
-     *
-     * \sa setPrecision() */
-    RealScalar precision() const {
-        return m_precision;
-    }
-
-    /** Sets the flags. Possible values are:
-     *  - CompleteFactorization
-     *  - IncompleteFactorization
-     *  - MemoryEfficient
-     *  - one of the ordering methods
-     *  - etc...
-     *
-     * \sa flags() */
-    void setFlags(int f) {
-        m_flags = f;
-    }
-
-    /** \returns the current flags */
-    int flags() const {
-        return m_flags;
-    }
-
-    void setOrderingMethod(int m) {
-        m_flags = m;
-    }
-
-    int orderingMethod() const {
-        return m_flags;
-    }
-
-    /** Computes/re-computes the LU factorization */
-    void compute();
-    void computeRowMajor();
-
-    /** \returns the lower triangular matrix L */
-    //inline const MatrixType& matrixL() const { return m_matrixL; }
-
-    /** \returns the upper triangular matrix U */
-    //inline const MatrixType& matrixU() const { return m_matrixU; }
-
-    template<typename BDerived, typename XDerived>
-    bool solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>* x,
-            const int transposed = 0) const;
-
-    /** \returns true if the factorization succeeded */
-    inline bool succeeded(void) const {
-        return m_succeeded;
-    }
-
-protected:
-    RealScalar m_precision;
-    int m_flags;
-    mutable int m_status;
-    bool m_succeeded;
-    MatrixType& m_lu;
-};
-
-/** Computes / recomputes the in place LU decomposition of the SkylineInplaceLU.
- * using the default algorithm.
- */
-template<typename MatrixType>
-//template<typename _Scalar>
-void SkylineInplaceLU<MatrixType>::compute() {
-    const size_t rows = m_lu.rows();
-    const size_t cols = m_lu.cols();
-
-    eigen_assert(rows == cols && "We do not (yet) support rectangular LU.");
-    eigen_assert(!m_lu.IsRowMajor && "LU decomposition does not work with rowMajor Storage");
-
-    for (Index row = 0; row < rows; row++) {
-        const double pivot = m_lu.coeffDiag(row);
-
-        //Lower matrix Columns update
-        const Index& col = row;
-        for (typename MatrixType::InnerLowerIterator lIt(m_lu, col); lIt; ++lIt) {
-            lIt.valueRef() /= pivot;
-        }
-
-        //Upper matrix update -> contiguous memory access
-        typename MatrixType::InnerLowerIterator lIt(m_lu, col);
-        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
-            typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
-            typename MatrixType::InnerUpperIterator uIt(m_lu, rrow);
-            const double coef = lIt.value();
-
-            uItPivot += (rrow - row - 1);
-
-            //update upper part  -> contiguous memory access
-            for (++uItPivot; uIt && uItPivot;) {
-                uIt.valueRef() -= uItPivot.value() * coef;
-
-                ++uIt;
-                ++uItPivot;
-            }
-            ++lIt;
-        }
-
-        //Upper matrix update -> non contiguous memory access
-        typename MatrixType::InnerLowerIterator lIt3(m_lu, col);
-        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
-            typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
-            const double coef = lIt3.value();
-
-            //update lower part ->  non contiguous memory access
-            for (Index i = 0; i < rrow - row - 1; i++) {
-                m_lu.coeffRefLower(rrow, row + i + 1) -= uItPivot.value() * coef;
-                ++uItPivot;
-            }
-            ++lIt3;
-        }
-        //update diag -> contiguous
-        typename MatrixType::InnerLowerIterator lIt2(m_lu, col);
-        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
-
-            typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
-            typename MatrixType::InnerUpperIterator uIt(m_lu, rrow);
-            const double coef = lIt2.value();
-
-            uItPivot += (rrow - row - 1);
-            m_lu.coeffRefDiag(rrow) -= uItPivot.value() * coef;
-            ++lIt2;
-        }
-    }
-}
-
-template<typename MatrixType>
-void SkylineInplaceLU<MatrixType>::computeRowMajor() {
-    const size_t rows = m_lu.rows();
-    const size_t cols = m_lu.cols();
-
-    eigen_assert(rows == cols && "We do not (yet) support rectangular LU.");
-    eigen_assert(m_lu.IsRowMajor && "You're trying to apply rowMajor decomposition on a ColMajor matrix !");
-
-    for (Index row = 0; row < rows; row++) {
-        typename MatrixType::InnerLowerIterator llIt(m_lu, row);
-
-
-        for (Index col = llIt.col(); col < row; col++) {
-            if (m_lu.coeffExistLower(row, col)) {
-                const double diag = m_lu.coeffDiag(col);
-
-                typename MatrixType::InnerLowerIterator lIt(m_lu, row);
-                typename MatrixType::InnerUpperIterator uIt(m_lu, col);
-
-
-                const Index offset = lIt.col() - uIt.row();
-
-
-                Index stop = offset > 0 ? col - lIt.col() : col - uIt.row();
-
-                //#define VECTORIZE
-#ifdef VECTORIZE
-                Map<VectorXd > rowVal(lIt.valuePtr() + (offset > 0 ? 0 : -offset), stop);
-                Map<VectorXd > colVal(uIt.valuePtr() + (offset > 0 ? offset : 0), stop);
-
-
-                Scalar newCoeff = m_lu.coeffLower(row, col) - rowVal.dot(colVal);
-#else
-                if (offset > 0) //Skip zero value of lIt
-                    uIt += offset;
-                else //Skip zero values of uIt
-                    lIt += -offset;
-                Scalar newCoeff = m_lu.coeffLower(row, col);
-
-                for (Index k = 0; k < stop; ++k) {
-                    const Scalar tmp = newCoeff;
-                    newCoeff = tmp - lIt.value() * uIt.value();
-                    ++lIt;
-                    ++uIt;
-                }
-#endif
-
-                m_lu.coeffRefLower(row, col) = newCoeff / diag;
-            }
-        }
-
-        //Upper matrix update
-        const Index col = row;
-        typename MatrixType::InnerUpperIterator uuIt(m_lu, col);
-        for (Index rrow = uuIt.row(); rrow < col; rrow++) {
-
-            typename MatrixType::InnerLowerIterator lIt(m_lu, rrow);
-            typename MatrixType::InnerUpperIterator uIt(m_lu, col);
-            const Index offset = lIt.col() - uIt.row();
-
-            Index stop = offset > 0 ? rrow - lIt.col() : rrow - uIt.row();
-
-#ifdef VECTORIZE
-            Map<VectorXd > rowVal(lIt.valuePtr() + (offset > 0 ? 0 : -offset), stop);
-            Map<VectorXd > colVal(uIt.valuePtr() + (offset > 0 ? offset : 0), stop);
-
-            Scalar newCoeff = m_lu.coeffUpper(rrow, col) - rowVal.dot(colVal);
-#else
-            if (offset > 0) //Skip zero value of lIt
-                uIt += offset;
-            else //Skip zero values of uIt
-                lIt += -offset;
-            Scalar newCoeff = m_lu.coeffUpper(rrow, col);
-            for (Index k = 0; k < stop; ++k) {
-                const Scalar tmp = newCoeff;
-                newCoeff = tmp - lIt.value() * uIt.value();
-
-                ++lIt;
-                ++uIt;
-            }
-#endif
-            m_lu.coeffRefUpper(rrow, col) = newCoeff;
-        }
-
-
-        //Diag matrix update
-        typename MatrixType::InnerLowerIterator lIt(m_lu, row);
-        typename MatrixType::InnerUpperIterator uIt(m_lu, row);
-
-        const Index offset = lIt.col() - uIt.row();
-
-
-        Index stop = offset > 0 ? lIt.size() : uIt.size();
-#ifdef VECTORIZE
-        Map<VectorXd > rowVal(lIt.valuePtr() + (offset > 0 ? 0 : -offset), stop);
-        Map<VectorXd > colVal(uIt.valuePtr() + (offset > 0 ? offset : 0), stop);
-        Scalar newCoeff = m_lu.coeffDiag(row) - rowVal.dot(colVal);
-#else
-        if (offset > 0) //Skip zero value of lIt
-            uIt += offset;
-        else //Skip zero values of uIt
-            lIt += -offset;
-        Scalar newCoeff = m_lu.coeffDiag(row);
-        for (Index k = 0; k < stop; ++k) {
-            const Scalar tmp = newCoeff;
-            newCoeff = tmp - lIt.value() * uIt.value();
-            ++lIt;
-            ++uIt;
-        }
-#endif
-        m_lu.coeffRefDiag(row) = newCoeff;
-    }
-}
-
-/** Computes *x = U^-1 L^-1 b
- *
- * If \a transpose is set to SvTranspose or SvAdjoint, the solution
- * of the transposed/adjoint system is computed instead.
- *
- * Not all backends implement the solution of the transposed or
- * adjoint system.
- */
-template<typename MatrixType>
-template<typename BDerived, typename XDerived>
-bool SkylineInplaceLU<MatrixType>::solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>* x, const int transposed) const {
-    const size_t rows = m_lu.rows();
-    const size_t cols = m_lu.cols();
-
-
-    for (Index row = 0; row < rows; row++) {
-        x->coeffRef(row) = b.coeff(row);
-        Scalar newVal = x->coeff(row);
-        typename MatrixType::InnerLowerIterator lIt(m_lu, row);
-
-        Index col = lIt.col();
-        while (lIt.col() < row) {
-
-            newVal -= x->coeff(col++) * lIt.value();
-            ++lIt;
-        }
-
-        x->coeffRef(row) = newVal;
-    }
-
-
-    for (Index col = rows - 1; col > 0; col--) {
-        x->coeffRef(col) = x->coeff(col) / m_lu.coeffDiag(col);
-
-        const Scalar x_col = x->coeff(col);
-
-        typename MatrixType::InnerUpperIterator uIt(m_lu, col);
-        uIt += uIt.size()-1;
-
-
-        while (uIt) {
-            x->coeffRef(uIt.row()) -= x_col * uIt.value();
-            //TODO : introduce --operator
-            uIt += -1;
-        }
-
-
-    }
-    x->coeffRef(0) = x->coeff(0) / m_lu.coeffDiag(0);
-
-    return true;
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_SKYLINEINPLACELU_H