diff --git a/Eigen/SparseCore b/Eigen/SparseCore
index 9a7d11124..3d355a90e 100644
--- a/Eigen/SparseCore
+++ b/Eigen/SparseCore
@@ -44,6 +44,7 @@ struct Sparse {};
 #include "src/SparseCore/SparseCwiseUnaryOp.h"
 #include "src/SparseCore/SparseCwiseBinaryOp.h"
 #include "src/SparseCore/SparseDot.h"
+#include "src/SparseCore/SparsePermutation.h"
 #include "src/SparseCore/SparseAssign.h"
 #include "src/SparseCore/SparseRedux.h"
 #include "src/SparseCore/SparseFuzzy.h"
diff --git a/Eigen/src/SparseCore/SparsePermutation.h b/Eigen/src/SparseCore/SparsePermutation.h
new file mode 100644
index 000000000..1fe2f404a
--- /dev/null
+++ b/Eigen/src/SparseCore/SparsePermutation.h
@@ -0,0 +1,160 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// Eigen is free software; you can redistribute it and/or
+// modify it under the terms of the GNU Lesser General Public
+// License as published by the Free Software Foundation; either
+// version 3 of the License, or (at your option) any later version.
+//
+// Alternatively, you can redistribute it and/or
+// modify it under the terms of the GNU General Public License as
+// published by the Free Software Foundation; either version 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
+// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+
+#ifndef EIGEN_SPARSE_PERMUTATION_H
+#define EIGEN_SPARSE_PERMUTATION_H
+
+// This file implements sparse * permutation products
+
+namespace internal {
+
+template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
+struct traits<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
+{
+  typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
+  typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
+  typedef typename MatrixTypeNestedCleaned::Index Index;
+  enum {
+    SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
+    MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
+  };
+
+  typedef typename internal::conditional<MoveOuter,
+        SparseMatrix<Scalar,SrcStorageOrder,Index>,
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> >::type ReturnType;
+};
+
+template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
+struct permut_sparsematrix_product_retval
+ : public ReturnByValue<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
+{
+    typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
+    typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
+    typedef typename MatrixTypeNestedCleaned::Index Index;
+
+    enum {
+      SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
+      MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
+    };
+
+    permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
+      : m_permutation(perm), m_matrix(matrix)
+    {}
+
+    inline int rows() const { return m_matrix.rows(); }
+    inline int cols() const { return m_matrix.cols(); }
+
+    template<typename Dest> inline void evalTo(Dest& dst) const
+    {
+      if(MoveOuter)
+      {
+        SparseMatrix<Scalar,SrcStorageOrder,Index> tmp(m_matrix.rows(), m_matrix.cols());
+        VectorXi sizes(m_matrix.outerSize());
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+        {
+          Index jp = m_permutation.indices().coeff(j);
+          sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = m_matrix.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).size();
+        }
+        tmp.reserve(sizes);
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+        {
+          Index jp = m_permutation.indices().coeff(j);
+          Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
+          Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,jsrc); it; ++it)
+            tmp.insertByOuterInner(jdst,it.index()) = it.value();
+        }
+        dst = tmp;
+      }
+      else
+      {
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> tmp(m_matrix.rows(), m_matrix.cols());
+        VectorXi sizes(tmp.outerSize());
+        sizes.setZero();
+        PermutationMatrix<Dynamic,Dynamic,Index> perm;
+        if((Side==OnTheLeft) ^ Transposed)
+          perm = m_permutation;
+        else
+          perm = m_permutation.transpose();
+
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
+            sizes[perm.indices().coeff(it.index())]++;
+        tmp.reserve(sizes);
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
+            tmp.insertByOuterInner(perm.indices().coeff(it.index()),j) = it.value();
+        dst = tmp;
+      }
+    }
+
+  protected:
+    const PermutationType& m_permutation;
+    typename MatrixType::Nested m_matrix;
+};
+
+}
+
+
+
+/** \returns the matrix with the permutation applied to the columns
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>
+operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>(perm, matrix.derived());
+}
+
+/** \returns the matrix with the permutation applied to the rows
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>
+operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>(perm, matrix.derived());
+}
+
+
+
+/** \returns the matrix with the inverse permutation applied to the columns.
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>
+operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived());
+}
+
+/** \returns the matrix with the inverse permutation applied to the rows.
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>
+operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived());
+}
+
+
+#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
diff --git a/test/sparse_permutations.cpp b/test/sparse_permutations.cpp
index 522e78f67..4d22e358e 100644
--- a/test/sparse_permutations.cpp
+++ b/test/sparse_permutations.cpp
@@ -59,6 +59,26 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
   randomPermutationVector(pi, cols);
   p.indices() = pi;
 
+  res = mat*p;
+  res_d = mat_d*p;
+  VERIFY(res.isApprox(res_d) && "mat*p");
+
+  res = p*mat;
+  res_d = p*mat_d;
+  VERIFY(res.isApprox(res_d) && "p*mat");
+
+  res = mat*p.inverse();
+  res_d = mat*p.inverse();
+  VERIFY(res.isApprox(res_d) && "mat*inv(p)");
+
+  res = p.inverse()*mat;
+  res_d = p.inverse()*mat_d;
+  VERIFY(res.isApprox(res_d) && "inv(p)*mat");
+
+  res = mat.twistedBy(p);
+  res_d = (p * mat_d) * p.inverse();
+  VERIFY(res.isApprox(res_d) && "p*mat*inv(p)");
+
   
   res = mat.template selfadjointView<Upper>().twistedBy(p_null);
   res_d = up_sym_d;
@@ -76,6 +96,41 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
   res = lo.template selfadjointView<Lower>().twistedBy(p_null);
   res_d = lo_sym_d;
   VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
+
+
+  res = mat.template selfadjointView<Upper>();
+  res_d = up_sym_d;
+  VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
+
+  res = mat.template selfadjointView<Lower>();
+  res_d = lo_sym_d;
+  VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
+
+  res = up.template selfadjointView<Upper>();
+  res_d = up_sym_d;
+  VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
+
+  res = lo.template selfadjointView<Lower>();
+  res_d = lo_sym_d;
+  VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
+
+
+  res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>();
+  res_d = up_sym_d.template triangularView<Upper>();
+  VERIFY(res.isApprox(res_d) && "full selfadjoint upper to upper");
+
+  res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>();
+  res_d = up_sym_d.template triangularView<Lower>();
+  VERIFY(res.isApprox(res_d) && "full selfadjoint upper to lower");
+
+  res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>();
+  res_d = lo_sym_d.template triangularView<Upper>();
+  VERIFY(res.isApprox(res_d) && "full selfadjoint lower to upper");
+
+  res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>();
+  res_d = lo_sym_d.template triangularView<Lower>();
+  VERIFY(res.isApprox(res_d) && "full selfadjoint lower to lower");
+
   
   
   res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>().twistedBy(p);