Added initial experimental support for explicit vectorization.

Currently only the following platform/operations are supported:
 - SSE2 compatible architecture
 - compiler compatible with intel's SSE2 intrinsics
 - float, double and int data types
 - fixed size matrices with a storage major dimension multiple of 4 (or 2 for double)
 - scalar-matrix product, component wise: +,-,*,min,max
 - matrix-matrix product only if the left matrix is vectorizable and column major
   or the right matrix is vectorizable and row major, e.g.:
   a.transpose() * b is not vectorized with the default column major storage.
To use it you must define EIGEN_VECTORIZE and EIGEN_INTEL_PLATFORM.

Eigen/src/Core/Transpose.h

@@ -77,6 +77,16 @@ template<typename MatrixType> class Transpose
       return m_matrix.coeff(col, row);
     }
 
+    PacketScalar _packetCoeff(int row, int col) const
+    {
+      return m_matrix.packetCoeff(col, row);
+    }
+
+    void _writePacketCoeff(int row, int col, const PacketScalar& x)
+    {
+      m_matrix.const_cast_derived().writePacketCoeff(col, row, x);
+    }
+
   protected:
     const typename MatrixType::XprCopy m_matrix;
 };