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.

1 files changed, 1 insertions, 1 deletions

diff --git a/Eigen/src/Core/Random.h b/Eigen/src/Core/Random.h
index 7ac3633fe..4d6a21da4 100644
--- a/Eigen/src/Core/Random.h
+++ b/Eigen/src/Core/Random.h
@@ -41,7 +41,7 @@ struct ei_traits<Random<MatrixType> >
     ColsAtCompileTime = ei_traits<MatrixType>::ColsAtCompileTime,
     MaxRowsAtCompileTime = ei_traits<MatrixType>::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = ei_traits<MatrixType>::MaxColsAtCompileTime,
-    Flags = ei_traits<MatrixType>::Flags | EvalBeforeNestingBit,
+    Flags = (ei_traits<MatrixType>::Flags | EvalBeforeNestingBit) & ~VectorizableBit,
     CoeffReadCost = 2 * NumTraits<Scalar>::MulCost // FIXME: arbitrary value
   };
 };