devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Assign.h: add LinearTraversal (non-vectorized index-based traversal)

Browse Source 
Rename some constants to make names match more closely what they mean.
This commit is contained in:
Benoit Jacob
2009-11-18 11:57:07 -05:00
parent 9f21e2aab7
commit 94c706d04f
6 changed files with 176 additions and 115 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
Eigen/src/Core/Redux.h
View File

@@ -54,16 +54,16 @@ private:
public:
enum {
Vectorization = int(MayLinearVectorize) ? int(LinearVectorization)
: int(MaySliceVectorize) ? int(SliceVectorization)
: int(NoVectorization)
Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
: int(MaySliceVectorize) ? int(SliceVectorizedTraversal)
: int(DefaultTraversal)
};
private:
enum {
Cost = Derived::SizeAtCompileTime * Derived::CoeffReadCost
+ (Derived::SizeAtCompileTime-1) * NumTraits<typename Derived::Scalar>::AddCost,
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (int(Vectorization) == int(NoVectorization) ? 1 : int(PacketSize))
UnrollingLimit = EIGEN_UNROLLING_LIMIT * (int(Traversal) == int(DefaultTraversal) ? 1 : int(PacketSize))
};
public:
@@ -171,13 +171,13 @@ struct ei_redux_vec_unroller<Func, Derived, Start, 1>
***************************************************************************/
template<typename Func, typename Derived,
int Vectorization = ei_redux_traits<Func, Derived>::Vectorization,
int Traversal = ei_redux_traits<Func, Derived>::Traversal,
int Unrolling = ei_redux_traits<Func, Derived>::Unrolling
>
struct ei_redux_impl;
template<typename Func, typename Derived>
struct ei_redux_impl<Func, Derived, NoVectorization, NoUnrolling>
struct ei_redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
static Scalar run(const Derived& mat, const Func& func)
@@ -195,12 +195,12 @@ struct ei_redux_impl<Func, Derived, NoVectorization, NoUnrolling>
};
template<typename Func, typename Derived>
struct ei_redux_impl<Func,Derived, NoVectorization, CompleteUnrolling>
struct ei_redux_impl<Func,Derived, DefaultTraversal, CompleteUnrolling>
: public ei_redux_novec_unroller<Func,Derived, 0, Derived::SizeAtCompileTime>
{};
template<typename Func, typename Derived>
struct ei_redux_impl<Func, Derived, LinearVectorization, NoUnrolling>
struct ei_redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename ei_packet_traits<Scalar>::type PacketScalar;
@@ -246,7 +246,7 @@ struct ei_redux_impl<Func, Derived, LinearVectorization, NoUnrolling>
};
template<typename Func, typename Derived>
struct ei_redux_impl<Func, Derived, SliceVectorization, NoUnrolling>
struct ei_redux_impl<Func, Derived, SliceVectorizedTraversal, NoUnrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename ei_packet_traits<Scalar>::type PacketScalar;
@@ -277,7 +277,7 @@ struct ei_redux_impl<Func, Derived, SliceVectorization, NoUnrolling>
else // too small to vectorize anything.
// since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize.
{
res = ei_redux_impl<Func, Derived, NoVectorization, NoUnrolling>::run(mat, func);
res = ei_redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>::run(mat, func);
}
return res;
@@ -285,20 +285,20 @@ struct ei_redux_impl<Func, Derived, SliceVectorization, NoUnrolling>
};
template<typename Func, typename Derived>
struct ei_redux_impl<Func, Derived, LinearVectorization, CompleteUnrolling>
struct ei_redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
{
typedef typename Derived::Scalar Scalar;
typedef typename ei_packet_traits<Scalar>::type PacketScalar;
enum {
PacketSize = ei_packet_traits<Scalar>::size,
Size = Derived::SizeAtCompileTime,
VectorizationSize = (Size / PacketSize) * PacketSize
VectorizedSize = (Size / PacketSize) * PacketSize
};
EIGEN_STRONG_INLINE static Scalar run(const Derived& mat, const Func& func)
{
Scalar res = func.predux(ei_redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
if (VectorizationSize != Size)
res = func(res,ei_redux_novec_unroller<Func, Derived, VectorizationSize, Size-VectorizationSize>::run(mat,func));
if (VectorizedSize != Size)
res = func(res,ei_redux_novec_unroller<Func, Derived, VectorizedSize, Size-VectorizedSize>::run(mat,func));
return res;
}
};