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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
#define EIGEN_GENERAL_MATRIX_MATRIX_H
#ifndef EIGEN_EXTERN_INSTANTIATIONS
/* Specialization for a row-major destination matrix => simple transposition of the product */
template<
typename Scalar,
int LhsStorageOrder, bool ConjugateLhs,
int RhsStorageOrder, bool ConjugateRhs>
struct ei_general_matrix_matrix_product<Scalar,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,RowMajor>
{
static EIGEN_STRONG_INLINE void run(
int rows, int cols, int depth,
const Scalar* lhs, int lhsStride,
const Scalar* rhs, int rhsStride,
Scalar* res, int resStride,
Scalar alpha)
{
// transpose the product such that the result is column major
ei_general_matrix_matrix_product<Scalar,
RhsStorageOrder==RowMajor ? ColMajor : RowMajor,
ConjugateRhs,
LhsStorageOrder==RowMajor ? ColMajor : RowMajor,
ConjugateLhs,
ColMajor>
::run(cols,rows,depth,rhs,rhsStride,lhs,lhsStride,res,resStride,alpha);
}
};
/* Specialization for a col-major destination matrix
* => Blocking algorithm following Goto's paper */
template<
typename Scalar,
int LhsStorageOrder, bool ConjugateLhs,
int RhsStorageOrder, bool ConjugateRhs>
struct ei_general_matrix_matrix_product<Scalar,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor>
{
static void run(int rows, int cols, int depth,
const Scalar* _lhs, int lhsStride,
const Scalar* _rhs, int rhsStride,
Scalar* res, int resStride,
Scalar alpha)
{
ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
ei_const_blas_data_mapper<Scalar, RhsStorageOrder> rhs(_rhs,rhsStride);
if (ConjugateRhs)
alpha = ei_conj(alpha);
typedef typename ei_packet_traits<Scalar>::type PacketType;
typedef ei_product_blocking_traits<Scalar> Blocking;
int kc = std::min<int>(Blocking::Max_kc,depth); // cache block size along the K direction
int mc = std::min<int>(Blocking::Max_mc,rows); // cache block size along the M direction
Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
Scalar* allocatedBlockB = ei_aligned_stack_new(Scalar, sizeB);
Scalar* blockB = allocatedBlockB + kc*Blocking::PacketSize*Blocking::nr;
// For each horizontal panel of the rhs, and corresponding panel of the lhs...
// (==GEMM_VAR1)
for(int k2=0; k2<depth; k2+=kc)
{
const int actual_kc = std::min(k2+kc,depth)-k2;
// OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
// => Pack rhs's panel into a sequential chunk of memory (L2 caching)
// Note that this panel will be read as many times as the number of blocks in the lhs's
// vertical panel which is, in practice, a very low number.
ei_gemm_pack_rhs<Scalar, Blocking::nr, RhsStorageOrder>()(blockB, &rhs(k2,0), rhsStride, alpha, actual_kc, cols);
// For each mc x kc block of the lhs's vertical panel...
// (==GEPP_VAR1)
for(int i2=0; i2<rows; i2+=mc)
{
const int actual_mc = std::min(i2+mc,rows)-i2;
// We pack the lhs's block into a sequential chunk of memory (L1 caching)
// Note that this block will be read a very high number of times, which is equal to the number of
// micro vertical panel of the large rhs's panel (e.g., cols/4 times).
ei_gemm_pack_lhs<Scalar, Blocking::mr, LhsStorageOrder>()(blockA, &lhs(i2,k2), lhsStride, actual_kc, actual_mc);
// Everything is packed, we can now call the block * panel kernel:
ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> >()
(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols);
// sgemm_kernel(actual_mc, cols, actual_kc, alpha, blockA, allocatedBlockB, res+i2, resStride);
}
}
ei_aligned_stack_delete(Scalar, blockA, kc*mc);
ei_aligned_stack_delete(Scalar, allocatedBlockB, sizeB);
}
};
#endif // EIGEN_EXTERN_INSTANTIATIONS
/*********************************************************************************
* Specialization of GeneralProduct<> for "large" GEMM, i.e.,
* implementation of the high level wrapper to ei_general_matrix_matrix_product
**********************************************************************************/
template<typename Lhs, typename Rhs>
struct ei_traits<GeneralProduct<Lhs,Rhs,GemmProduct> >
: ei_traits<ProductBase<GeneralProduct<Lhs,Rhs,GemmProduct>, Lhs, Rhs> >
{};
template<typename Scalar, typename Gemm, typename Lhs, typename Rhs, typename Dest>
struct ei_gemm_functor
{
ei_gemm_functor(const Lhs& lhs, const Rhs& rhs, Dest& dest, Scalar actualAlpha)
: m_lhs(lhs), m_rhs(rhs), m_dest(dest), m_actualAlpha(actualAlpha)
{}
void operator() (int col, int cols, int row=0, int rows=-1) const
{
if(rows==-1)
rows = m_lhs.rows();
Gemm::run(rows, cols, m_lhs.cols(),
(const Scalar*)&(m_lhs.const_cast_derived().coeffRef(row,0)), m_lhs.stride(),
(const Scalar*)&(m_rhs.const_cast_derived().coeffRef(0,col)), m_rhs.stride(),
(Scalar*)&(m_dest.coeffRef(row,col)), m_dest.stride(),
m_actualAlpha);
}
protected:
const Lhs& m_lhs;
const Rhs& m_rhs;
mutable Dest& m_dest;
Scalar m_actualAlpha;
};
template<typename Lhs, typename Rhs>
class GeneralProduct<Lhs, Rhs, GemmProduct>
: public ProductBase<GeneralProduct<Lhs,Rhs,GemmProduct>, Lhs, Rhs>
{
public:
EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
{
EIGEN_STATIC_ASSERT((ei_is_same_type<typename Lhs::Scalar, typename Rhs::Scalar>::ret),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
}
template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
{
ei_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
* RhsBlasTraits::extractScalarFactor(m_rhs);
typedef ei_gemm_functor<
Scalar,
ei_general_matrix_matrix_product<
Scalar,
(_ActualLhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate),
(_ActualRhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate),
(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor>,
_ActualLhsType,
_ActualRhsType,
Dest> Functor;
ei_run_parallel_2d<true>(Functor(lhs, rhs, dst, actualAlpha), this->cols(), this->rows());
}
};
#endif // EIGEN_GENERAL_MATRIX_MATRIX_H
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