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fully vectorize DiagonalProduct

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(it used to be partially vectorized and that had been lost in the big changes from the previous commit)
This commit is contained in:
Benoit Jacob 2009-06-29 04:01:31 +02:00
parent 6809f7b1cd
commit 2de9b7f537
3 changed files with 61 additions and 24 deletions
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38
Eigen/src/Core/DiagonalProduct.h
View File

@ -26,8 +26,8 @@
#ifndef EIGEN_DIAGONALPRODUCT_H
#define EIGEN_DIAGONALPRODUCT_H
template<typename MatrixType, typename DiagonalType, int Order>
struct ei_traits<DiagonalProduct<MatrixType, DiagonalType, Order> >
template<typename MatrixType, typename DiagonalType, int ProductOrder>
struct ei_traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
{
typedef typename MatrixType::Scalar Scalar;
enum {
@ -35,14 +35,15 @@ struct ei_traits<DiagonalProduct<MatrixType, DiagonalType, Order> >
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
Flags = (unsigned int)(MatrixType::Flags) & HereditaryBits,
Flags = (HereditaryBits & (unsigned int)(MatrixType::Flags))
| (PacketAccessBit & (unsigned int)(MatrixType::Flags) & (unsigned int)(DiagonalType::DiagonalVectorType::Flags)),
CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
};
};
template<typename MatrixType, typename DiagonalType, int Order>
template<typename MatrixType, typename DiagonalType, int ProductOrder>
class DiagonalProduct : ei_no_assignment_operator,
public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, Order> >
public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
{
public:
@ -51,7 +52,7 @@ class DiagonalProduct : ei_no_assignment_operator,
inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
: m_matrix(matrix), m_diagonal(diagonal)
{
ei_assert(diagonal.diagonal().size() == (Order == DiagonalOnTheLeft ? matrix.rows() : matrix.cols()));
ei_assert(diagonal.diagonal().size() == (ProductOrder == DiagonalOnTheLeft ? matrix.rows() : matrix.cols()));
}
inline int rows() const { return m_matrix.rows(); }
@ -59,7 +60,30 @@ class DiagonalProduct : ei_no_assignment_operator,
const Scalar coeff(int row, int col) const
{
return m_diagonal.diagonal().coeff(Order == DiagonalOnTheLeft ? row : col) * m_matrix.coeff(row, col);
return m_diagonal.diagonal().coeff(ProductOrder == DiagonalOnTheLeft ? row : col) * m_matrix.coeff(row, col);
}
template<int LoadMode>
EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
{
enum {
StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor,
InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
DiagonalVectorPacketLoadMode = (LoadMode == Aligned && ((InnerSize%16) == 0)) ? Aligned : Unaligned
};
const int indexInDiagonalVector = ProductOrder == DiagonalOnTheLeft ? row : col;
if((int(StorageOrder) == RowMajor && int(ProductOrder) == DiagonalOnTheLeft)
||(int(StorageOrder) == ColMajor && int(ProductOrder) == DiagonalOnTheRight))
{
return ei_pmul(m_matrix.template packet<LoadMode>(row, col),
ei_pset1(m_diagonal.diagonal().coeff(indexInDiagonalVector)));
}
else
{
return ei_pmul(m_matrix.template packet<LoadMode>(row, col),
m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(indexInDiagonalVector));
}
}
protected:

2
Eigen/src/Core/util/ForwardDeclarations.h
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@ -53,7 +53,7 @@ template<typename Lhs, typename Rhs, int ProductMode> class Product;
template<typename Derived> class DiagonalBase;
template<typename _DiagonalVectorType> class DiagonalWrapper;
template<typename _Scalar, int _Size> class DiagonalMatrix;
template<typename MatrixType, typename DiagonalType, int Order> class DiagonalProduct;
template<typename MatrixType, typename DiagonalType, int ProductOrder> class DiagonalProduct;
template<typename MatrixType, int Index> class Diagonal;
template<typename MatrixType, int PacketAccess = AsRequested> class Map;

45
test/diagonalmatrices.cpp
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@ -23,7 +23,7 @@
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "main.h"
using namespace std;
template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
@ -34,7 +34,7 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
int rows = m.rows();
int cols = m.cols();
@ -46,20 +46,7 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
rv2 = RowVectorType::Random(cols);
LeftDiagonalMatrix ldm1(v1), ldm2(v2);
RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
int i = ei_random<int>(0, rows-1);
int j = ei_random<int>(0, cols-1);
VERIFY_IS_APPROX( ((ldm1 * m1)(i,j)) , ldm1.diagonal()(i) * m1(i,j) );
VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j)) , ldm1.diagonal()(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * rdm1)(i,j)) , rdm1.diagonal()(j) * m1(i,j) );
VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j)) , v1(i) * m1(i,j) );
VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j)) , rv1(j) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j)) , (v1+v2)(i) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j)) , (v1+v2)(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * m1(i,j) );
VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * (m1+m2)(i,j) );
SquareMatrixType sq_m1 (v1.asDiagonal());
VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
sq_m1 = v1.asDiagonal();
@ -77,6 +64,32 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
sq_m1.transpose() = ldm1;
VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
int i = ei_random<int>(0, rows-1);
int j = ei_random<int>(0, cols-1);
VERIFY_IS_APPROX( ((ldm1 * m1)(i,j)) , ldm1.diagonal()(i) * m1(i,j) );
VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j)) , ldm1.diagonal()(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * rdm1)(i,j)) , rdm1.diagonal()(j) * m1(i,j) );
VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j)) , v1(i) * m1(i,j) );
VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j)) , rv1(j) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j)) , (v1+v2)(i) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j)) , (v1+v2)(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * m1(i,j) );
VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * (m1+m2)(i,j) );
BigMatrix big;
big.setZero(2*rows, 2*cols);
big.block(i,j,rows,cols) = m1;
big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols);
VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 );
big.block(i,j,rows,cols) = m1;
big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
}
void test_diagonalmatrices()