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Optimize the product of a householder-sequence with the identity, and optimize the evaluation of a HouseholderSequence to a dense matrix using faster blocked product.
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@ -11,7 +11,7 @@ set(CTEST_DROP_METHOD "http")
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set(CTEST_DROP_SITE "manao.inria.fr")
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set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
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set(CTEST_DROP_SITE_CDASH TRUE)
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set(CTEST_PROJECT_SUBPROJECTS
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Official
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Unsupported
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)
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#set(CTEST_PROJECT_SUBPROJECTS
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#Official
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#Unsupported
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#)
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@ -295,6 +295,14 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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for(Index k = 0; k<cols()-vecs ; ++k)
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dst.col(k).tail(rows()-k-1).setZero();
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}
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else if(m_length>BlockSize)
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{
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dst.setIdentity(rows(), rows());
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if(m_reverse)
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applyThisOnTheLeft(dst,workspace,true);
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else
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applyThisOnTheLeft(dst,workspace,true);
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}
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else
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{
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dst.setIdentity(rows(), rows());
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@ -332,24 +340,27 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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}
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/** \internal */
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template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
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template<typename Dest> inline void applyThisOnTheLeft(Dest& dst, bool inputIsIdentity = false) const
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{
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Matrix<Scalar,1,Dest::ColsAtCompileTime,RowMajor,1,Dest::MaxColsAtCompileTime> workspace;
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applyThisOnTheLeft(dst, workspace);
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applyThisOnTheLeft(dst, workspace, inputIsIdentity);
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}
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/** \internal */
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template<typename Dest, typename Workspace>
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inline void applyThisOnTheLeft(Dest& dst, Workspace& workspace) const
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inline void applyThisOnTheLeft(Dest& dst, Workspace& workspace, bool inputIsIdentity = false) const
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{
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const Index BlockSize = 48;
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if(inputIsIdentity && m_reverse)
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inputIsIdentity = false;
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// if the entries are large enough, then apply the reflectors by block
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if(m_length>=BlockSize && dst.cols()>1)
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{
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for(Index i = 0; i < m_length; i+=BlockSize)
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// Make sure we have at least 2 useful blocks, otherwise it is point-less:
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Index blockSize = m_length<2*BlockSize ? (m_length+1)/2 : BlockSize;
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for(Index i = 0; i < m_length; i+=blockSize)
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{
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Index end = m_reverse ? (std::min)(m_length,i+BlockSize) : m_length-i;
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Index k = m_reverse ? i : (std::max)(Index(0),end-BlockSize);
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Index end = m_reverse ? (std::min)(m_length,i+blockSize) : m_length-i;
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Index k = m_reverse ? i : (std::max)(Index(0),end-blockSize);
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Index bs = end-k;
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Index start = k + m_shift;
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@ -359,7 +370,14 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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Side==OnTheRight ? bs : m_vectors.rows()-start,
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Side==OnTheRight ? m_vectors.cols()-start : bs);
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typename internal::conditional<Side==OnTheRight, Transpose<SubVectorsType>, SubVectorsType&>::type sub_vecs(sub_vecs1);
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Block<Dest,Dynamic,Dynamic> sub_dst(dst,dst.rows()-rows()+m_shift+k,0, rows()-m_shift-k,dst.cols());
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Index dstStart = dst.rows()-rows()+m_shift+k;
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Index dstRows = rows()-m_shift-k;
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Block<Dest,Dynamic,Dynamic> sub_dst(dst,
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dstStart,
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inputIsIdentity ? dstStart : 0,
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dstRows,
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inputIsIdentity ? dstRows : dst.cols());
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apply_block_householder_on_the_left(sub_dst, sub_vecs, m_coeffs.segment(k, bs), !m_reverse);
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}
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}
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@ -369,7 +387,8 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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for(Index k = 0; k < m_length; ++k)
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{
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Index actual_k = m_reverse ? k : m_length-k-1;
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dst.bottomRows(rows()-m_shift-actual_k)
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Index dstStart = rows()-m_shift-actual_k;
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dst.bottomRightCorner(dstStart, inputIsIdentity ? dstStart : dst.cols())
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.applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data());
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}
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}
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@ -387,7 +406,7 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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{
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typename internal::matrix_type_times_scalar_type<Scalar, OtherDerived>::Type
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res(other.template cast<typename internal::matrix_type_times_scalar_type<Scalar,OtherDerived>::ResultScalar>());
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applyThisOnTheLeft(res);
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applyThisOnTheLeft(res, internal::is_identity<OtherDerived>::value && res.rows()==res.cols());
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return res;
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}
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@ -461,6 +480,7 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
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bool m_reverse;
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Index m_length;
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Index m_shift;
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enum { BlockSize = 48 };
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};
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/** \brief Computes the product of a matrix with a Householder sequence.
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@ -129,7 +129,7 @@ void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci)
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template<typename A, typename B, typename C>
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EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c)
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{
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c.noalias() += a * b;
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c.noalias() += a * b;
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}
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int main(int argc, char ** argv)
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