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* more cleaning in Product

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* make Matrix2f (and similar) vectorized using linear path
* fix a couple of warnings and compilation issues with ICC and gcc 3.3/3.4
  (cannot get Transform compiles with gcc 3.3/3.4, see the FIXME)
This commit is contained in:
Gael Guennebaud 2008-06-19 23:00:51 +00:00
parent 82c3cea1d5
commit fb4a151982
7 changed files with 112 additions and 136 deletions
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24
Eigen/src/Core/Assign.h
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@ -351,23 +351,25 @@ struct ei_assign_impl<Derived1, Derived2, LinearVectorization, CompleteUnrolling
{
inline static void run(Derived1 &dst, const Derived2 &src)
{
const int size = Derived1::SizeAtCompileTime;
const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
const int alignedSize = (size/packetSize)*packetSize;
const bool rowMajor = Derived1::Flags&RowMajorBit;
const int innerSize = rowMajor ? Derived1::ColsAtCompileTime : Derived1::RowsAtCompileTime;
const int outerSize = rowMajor ? Derived1::RowsAtCompileTime : Derived1::ColsAtCompileTime;
int index = 0;
enum {
size = Derived1::SizeAtCompileTime,
packetSize = ei_packet_traits<typename Derived1::Scalar>::size,
alignedSize = (int(size)/int(packetSize))*int(packetSize),
rowMajor = int(Derived1::Flags)&RowMajorBit,
innerSize = int(rowMajor) ? int(Derived1::ColsAtCompileTime) : int(Derived1::RowsAtCompileTime),
outerSize = int(rowMajor) ? int(Derived1::RowsAtCompileTime) : int(Derived1::ColsAtCompileTime)
};
// do the vectorizable part of the assignment
ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
// now we must do the rest without vectorization.
const int k = alignedSize/innerSize;
const int i = alignedSize%innerSize;
enum {
k = int(alignedSize)/int(innerSize),
i = int(alignedSize)%int(innerSize)
};
// do the remainder of the current row or col
ei_assign_novec_InnerUnrolling<Derived1, Derived2, i, innerSize>::run(dst, src, k);
ei_assign_novec_InnerUnrolling<Derived1, Derived2, i, int(k)<int(outerSize) ? int(innerSize) : 0>::run(dst, src, k);
// do the remaining rows or cols
for(int j = k+1; j < outerSize; j++)

4
Eigen/src/Core/DiagonalCoeffs.h
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@ -101,8 +101,8 @@ template<typename MatrixType> class DiagonalCoeffs
*
* \sa class DiagonalCoeffs */
template<typename Derived>
DiagonalCoeffs<Derived>
inline MatrixBase<Derived>::diagonal()
inline DiagonalCoeffs<Derived>
MatrixBase<Derived>::diagonal()
{
return DiagonalCoeffs<Derived>(derived());
}

75
Eigen/src/Core/Product.h
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@ -201,14 +201,21 @@ template<typename LhsNested, typename RhsNested, int ProductMode> class Product
ei_assert(lhs.cols() == rhs.rows());
}
/** \internal */
template<typename DestDerived>
void _cacheFriendlyEval(DestDerived& res) const;
/** \internal */
/** \internal
* compute \a res += \c *this using the cache friendly product.
*/
template<typename DestDerived>
void _cacheFriendlyEvalAndAdd(DestDerived& res) const;
/** \internal
* \returns whether it is worth it to use the cache friendly product.
*/
inline bool _useCacheFriendlyProduct() const {
return _rows()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& _cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& m_lhs.cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD;
}
private:
inline int _rows() const { return m_lhs.rows(); }
@ -229,7 +236,7 @@ template<typename LhsNested, typename RhsNested, int ProductMode> class Product
return res;
}
template<typename Lhs_, typename Rhs_, int EvalMode_, typename DestDerived_, bool DirectAccess_>
template<typename Lhs_, typename Rhs_, int ProductMode_, typename DestDerived_, bool DirectAccess_>
friend struct ei_cache_friendly_selector;
protected:
@ -419,7 +426,10 @@ template<typename Lhs,typename Rhs>
inline Derived&
MatrixBase<Derived>::operator+=(const Flagged<Product<Lhs,Rhs,CacheFriendlyProduct>, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>& other)
{
if (other._expression()._useCacheFriendlyProduct())
other._expression()._cacheFriendlyEvalAndAdd(const_cast_derived());
else
lazyAssign(derived() + other._expression());
return derived();
}
@ -427,7 +437,15 @@ template<typename Derived>
template<typename Lhs, typename Rhs>
inline Derived& MatrixBase<Derived>::lazyAssign(const Product<Lhs,Rhs,CacheFriendlyProduct>& product)
{
product._cacheFriendlyEval(derived());
if (product._useCacheFriendlyProduct())
{
setZero();
product._cacheFriendlyEvalAndAdd(derived());
}
else
{
lazyAssign<Product<Lhs,Rhs,CacheFriendlyProduct> >(product);
}
return derived();
}
@ -472,43 +490,9 @@ template<typename T> struct ei_product_copy_lhs
>::ret type;
};
template<typename Lhs, typename Rhs, int EvalMode>
template<typename Lhs, typename Rhs, int ProductMode>
template<typename DestDerived>
inline void Product<Lhs,Rhs,EvalMode>::_cacheFriendlyEval(DestDerived& res) const
{
if ( _rows()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& _cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& m_lhs.cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
)
{
res.setZero();
typedef typename ei_product_copy_lhs<_LhsNested>::type LhsCopy;
typedef typename ei_unref<LhsCopy>::type _LhsCopy;
typedef typename ei_product_copy_rhs<_RhsNested>::type RhsCopy;
typedef typename ei_unref<RhsCopy>::type _RhsCopy;
LhsCopy lhs(m_lhs);
RhsCopy rhs(m_rhs);
ei_cache_friendly_product<Scalar>(
_rows(), _cols(), lhs.cols(),
_LhsCopy::Flags&RowMajorBit, &(lhs.const_cast_derived().coeffRef(0,0)), lhs.stride(),
_RhsCopy::Flags&RowMajorBit, &(rhs.const_cast_derived().coeffRef(0,0)), rhs.stride(),
Flags&RowMajorBit, &(res.coeffRef(0,0)), res.stride()
);
}
else
{
res = Product<_LhsNested,_RhsNested,NormalProduct>(m_lhs, m_rhs).lazy();
}
}
template<typename Lhs, typename Rhs, int EvalMode>
template<typename DestDerived>
inline void Product<Lhs,Rhs,EvalMode>::_cacheFriendlyEvalAndAdd(DestDerived& res) const
{
if ( _rows()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& _cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
&& m_lhs.cols()>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
)
inline void Product<Lhs,Rhs,ProductMode>::_cacheFriendlyEvalAndAdd(DestDerived& res) const
{
typedef typename ei_product_copy_lhs<_LhsNested>::type LhsCopy;
typedef typename ei_unref<LhsCopy>::type _LhsCopy;
@ -523,10 +507,5 @@ inline void Product<Lhs,Rhs,EvalMode>::_cacheFriendlyEvalAndAdd(DestDerived& res
Flags&RowMajorBit, &(res.coeffRef(0,0)), res.stride()
);
}
else
{
res += Product<_LhsNested,_RhsNested,NormalProduct>(m_lhs, m_rhs).lazy();
}
}
#endif // EIGEN_PRODUCT_H

16
Eigen/src/Core/Redux.h
View File

@ -101,8 +101,8 @@ MatrixBase<Derived>::redux(const BinaryOp& func) const
* \sa trace()
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
inline MatrixBase<Derived>::sum() const
inline typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::sum() const
{
return this->redux(Eigen::ei_scalar_sum_op<Scalar>());
}
@ -114,8 +114,8 @@ inline MatrixBase<Derived>::sum() const
* \sa diagonal(), sum()
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
inline MatrixBase<Derived>::trace() const
inline typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::trace() const
{
return diagonal().sum();
}
@ -123,8 +123,8 @@ inline MatrixBase<Derived>::trace() const
/** \returns the minimum of all coefficients of *this
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
inline MatrixBase<Derived>::minCoeff() const
inline typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::minCoeff() const
{
return this->redux(Eigen::ei_scalar_min_op<Scalar>());
}
@ -132,8 +132,8 @@ inline MatrixBase<Derived>::minCoeff() const
/** \returns the maximum of all coefficients of *this
*/
template<typename Derived>
typename ei_traits<Derived>::Scalar
inline MatrixBase<Derived>::maxCoeff() const
inline typename ei_traits<Derived>::Scalar
MatrixBase<Derived>::maxCoeff() const
{
return this->redux(Eigen::ei_scalar_max_op<Scalar>());
}

4
Eigen/src/Core/util/Meta.h
View File

@ -156,10 +156,10 @@ class ei_corrected_matrix_flags
? SuggestedFlags&RowMajorBit
: Cols > 1 ? RowMajorBit : 0,
is_big = MaxRows == Dynamic || MaxCols == Dynamic,
inner_size = row_major_bit ? Cols : Rows,
linear_size = Cols * Rows,
packet_access_bit
= ei_packet_traits<Scalar>::size > 1
&& (is_big || inner_size%ei_packet_traits<Scalar>::size==0)
&& (is_big || linear_size%ei_packet_traits<Scalar>::size==0)
? PacketAccessBit : 0
};

4
Eigen/src/Geometry/Cross.h
View File

@ -28,8 +28,8 @@
/** \returns the cross product of \c *this and \a other */
template<typename Derived>
template<typename OtherDerived>
typename ei_eval<Derived>::type
inline MatrixBase<Derived>::cross(const MatrixBase<OtherDerived>& other) const
inline typename ei_eval<Derived>::type
MatrixBase<Derived>::cross(const MatrixBase<OtherDerived>& other) const
{
// Note that there is no need for an expression here since the compiler
// optimize such a small temporary very well (even within a complex expression)

91
Eigen/src/Geometry/Transform.h
View File

@ -62,6 +62,47 @@ protected:
int OtherCols=Other::ColsAtCompileTime>
struct ei_transform_product_impl;
// FIXME these specializations of ei_transform_product_impl does not work with gcc 3.3 and 3.4 because
// Dim depends on a template parameter. Replacing Dim by 3 (for the 3D case) works.
// note that these specializations have to be defined here,
// otherwise some compilers (at least ICC and NVCC) complain about
// the use of Dim in the specialization parameters.
template<typename Other>
struct ei_transform_product_impl<Other,Dim+1,Dim+1>
{
typedef typename Transform<Scalar,Dim>::MatrixType MatrixType;
typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return tr.matrix() * other; }
};
template<typename Other>
struct ei_transform_product_impl<Other,Dim+1,1>
{
typedef typename Transform<Scalar,Dim>::MatrixType MatrixType;
typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return tr.matrix() * other; }
};
template<typename Other>
struct ei_transform_product_impl<Other,Dim,1>
{
typedef typename Transform<Scalar,Dim>::AffineMatrixRef MatrixType;
typedef const CwiseUnaryOp<
ei_scalar_multiple_op<Scalar>,
NestByValue<CwiseBinaryOp<
ei_scalar_sum_op<Scalar>,
NestByValue<typename ProductReturnType<NestByValue<MatrixType>,Other>::Type >,
NestByValue<typename Transform<Scalar,Dim>::VectorRef> > >
> ResultType;
// FIXME shall we offer an optimized version when the last row is know to be 0,0...,0,1 ?
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return ((tr.affine().nestByValue() * other).nestByValue() + tr.translation().nestByValue()).nestByValue()
* (Scalar(1) / ( (tr.matrix().template block<1,Dim>(Dim,0) * other).coeff(0) + tr.matrix().coeff(Dim,Dim))); }
};
public:
/** Default constructor without initialization of the coefficients. */
@ -103,13 +144,7 @@ public:
inline VectorRef translation() { return m_matrix.template block<Dim,1>(0,Dim); }
template<typename OtherDerived>
struct TransformProductReturnType
{
typedef typename ei_transform_product_impl<OtherDerived>::ResultType Type;
};
template<typename OtherDerived>
const typename TransformProductReturnType<OtherDerived>::Type
const typename ei_transform_product_impl<OtherDerived>::ResultType
operator * (const MatrixBase<OtherDerived> &other) const;
/** Contatenates two transformations */
@ -192,7 +227,7 @@ QMatrix Transform<Scalar,Dim>::toQMatrix(void) const
template<typename Scalar, int Dim>
template<typename OtherDerived>
const typename Transform<Scalar,Dim>::template TransformProductReturnType<OtherDerived>::Type
const typename Transform<Scalar,Dim>::template ei_transform_product_impl<OtherDerived>::ResultType
Transform<Scalar,Dim>::operator*(const MatrixBase<OtherDerived> &other) const
{
return ei_transform_product_impl<OtherDerived>::run(*this,other.derived());
@ -373,44 +408,4 @@ Transform<Scalar,Dim>::fromPositionOrientationScale(const MatrixBase<PositionDer
return *this;
}
//----------
template<typename Scalar, int Dim>
template<typename Other>
struct Transform<Scalar,Dim>::ei_transform_product_impl<Other,Dim+1,Dim+1>
{
typedef typename Transform<Scalar,Dim>::MatrixType MatrixType;
typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return tr.matrix() * other; }
};
template<typename Scalar, int Dim>
template<typename Other>
struct Transform<Scalar,Dim>::ei_transform_product_impl<Other,Dim+1,1>
{
typedef typename Transform<Scalar,Dim>::MatrixType MatrixType;
typedef typename ProductReturnType<MatrixType,Other>::Type ResultType;
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return tr.matrix() * other; }
};
template<typename Scalar, int Dim>
template<typename Other>
struct Transform<Scalar,Dim>::ei_transform_product_impl<Other,Dim,1>
{
typedef typename Transform<Scalar,Dim>::AffineMatrixRef MatrixType;
typedef const CwiseUnaryOp<
ei_scalar_multiple_op<Scalar>,
NestByValue<CwiseBinaryOp<
ei_scalar_sum_op<Scalar>,
NestByValue<typename ProductReturnType<NestByValue<MatrixType>,Other>::Type >,
NestByValue<typename Transform<Scalar,Dim>::VectorRef> > >
> ResultType;
// FIXME shall we offer an optimized version when the last row is know to be 0,0...,0,1 ?
static ResultType run(const Transform<Scalar,Dim>& tr, const Other& other)
{ return ((tr.affine().nestByValue() * other).nestByValue() + tr.translation().nestByValue()).nestByValue()
* (Scalar(1) / ( (tr.matrix().template block<1,Dim>(Dim,0) * other).coeff(0) + tr.matrix().coeff(Dim,Dim))); }
};
#endif // EIGEN_TRANSFORM_H