blob: 7b2c8dca38f1ac941819e1d5f1b50ba91f63c4bf [file] [log] [blame]
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011-2018 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_PARTIALREDUX_H
#define EIGEN_PARTIALREDUX_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
/***************************************************************************
*
* This file provides evaluators for partial reductions.
* There are two modes:
*
* - scalar path: simply calls the respective function on the column or row.
* -> nothing special here, all the tricky part is handled by the return
* types of VectorwiseOp's members. They embed the functor calling the
* respective DenseBase's member function.
*
* - vectorized path: implements a packet-wise reductions followed by
* some (optional) processing of the outcome, e.g., division by n for mean.
*
* For the vectorized path let's observe that the packet-size and outer-unrolling
* are both decided by the assignment logic. So all we have to do is to decide
* on the inner unrolling.
*
* For the unrolling, we can reuse "internal::redux_vec_unroller" from Redux.h,
* but be need to be careful to specify correct increment.
*
***************************************************************************/
/* logic deciding a strategy for unrolling of vectorized paths */
template <typename Func, typename Evaluator>
struct packetwise_redux_traits {
enum {
OuterSize = int(Evaluator::IsRowMajor) ? Evaluator::RowsAtCompileTime : Evaluator::ColsAtCompileTime,
Cost = OuterSize == Dynamic ? HugeCost
: OuterSize * Evaluator::CoeffReadCost + (OuterSize - 1) * functor_traits<Func>::Cost,
Unrolling = Cost <= EIGEN_UNROLLING_LIMIT ? CompleteUnrolling : NoUnrolling
};
};
/* Value to be returned when size==0 , by default let's return 0 */
template <typename PacketType, typename Func>
EIGEN_DEVICE_FUNC PacketType packetwise_redux_empty_value(const Func&) {
const typename unpacket_traits<PacketType>::type zero(0);
return pset1<PacketType>(zero);
}
/* For products the default is 1 */
template <typename PacketType, typename Scalar>
EIGEN_DEVICE_FUNC PacketType packetwise_redux_empty_value(const scalar_product_op<Scalar, Scalar>&) {
return pset1<PacketType>(Scalar(1));
}
/* Perform the actual reduction */
template <typename Func, typename Evaluator, int Unrolling = packetwise_redux_traits<Func, Evaluator>::Unrolling>
struct packetwise_redux_impl;
/* Perform the actual reduction with unrolling */
template <typename Func, typename Evaluator>
struct packetwise_redux_impl<Func, Evaluator, CompleteUnrolling> {
typedef redux_novec_unroller<Func, Evaluator, 0, Evaluator::SizeAtCompileTime> Base;
typedef typename Evaluator::Scalar Scalar;
template <typename PacketType>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func& func, Index /*size*/) {
return redux_vec_unroller<Func, Evaluator, 0,
packetwise_redux_traits<Func, Evaluator>::OuterSize>::template run<PacketType>(eval,
func);
}
};
/* Add a specialization of redux_vec_unroller for size==0 at compiletime.
* This specialization is not required for general reductions, which is
* why it is defined here.
*/
template <typename Func, typename Evaluator, Index Start>
struct redux_vec_unroller<Func, Evaluator, Start, 0> {
template <typename PacketType>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator&, const Func& f) {
return packetwise_redux_empty_value<PacketType>(f);
}
};
/* Perform the actual reduction for dynamic sizes */
template <typename Func, typename Evaluator>
struct packetwise_redux_impl<Func, Evaluator, NoUnrolling> {
typedef typename Evaluator::Scalar Scalar;
typedef typename redux_traits<Func, Evaluator>::PacketType PacketScalar;
template <typename PacketType>
EIGEN_DEVICE_FUNC static PacketType run(const Evaluator& eval, const Func& func, Index size) {
if (size == 0) return packetwise_redux_empty_value<PacketType>(func);
const Index size4 = (size - 1) & (~3);
PacketType p = eval.template packetByOuterInner<Unaligned, PacketType>(0, 0);
Index i = 1;
// This loop is optimized for instruction pipelining:
// - each iteration generates two independent instructions
// - thanks to branch prediction and out-of-order execution we have independent instructions across loops
for (; i < size4; i += 4)
p = func.packetOp(
p, func.packetOp(func.packetOp(eval.template packetByOuterInner<Unaligned, PacketType>(i + 0, 0),
eval.template packetByOuterInner<Unaligned, PacketType>(i + 1, 0)),
func.packetOp(eval.template packetByOuterInner<Unaligned, PacketType>(i + 2, 0),
eval.template packetByOuterInner<Unaligned, PacketType>(i + 3, 0))));
for (; i < size; ++i) p = func.packetOp(p, eval.template packetByOuterInner<Unaligned, PacketType>(i, 0));
return p;
}
};
template <typename ArgType, typename MemberOp, int Direction>
struct evaluator<PartialReduxExpr<ArgType, MemberOp, Direction> >
: evaluator_base<PartialReduxExpr<ArgType, MemberOp, Direction> > {
typedef PartialReduxExpr<ArgType, MemberOp, Direction> XprType;
typedef typename internal::nested_eval<ArgType, 1>::type ArgTypeNested;
typedef add_const_on_value_type_t<ArgTypeNested> ConstArgTypeNested;
typedef internal::remove_all_t<ArgTypeNested> ArgTypeNestedCleaned;
typedef typename ArgType::Scalar InputScalar;
typedef typename XprType::Scalar Scalar;
enum {
TraversalSize = Direction == int(Vertical) ? int(ArgType::RowsAtCompileTime) : int(ArgType::ColsAtCompileTime)
};
typedef typename MemberOp::template Cost<int(TraversalSize)> CostOpType;
enum {
CoeffReadCost = TraversalSize == Dynamic ? HugeCost
: TraversalSize == 0
? 1
: int(TraversalSize) * int(evaluator<ArgType>::CoeffReadCost) + int(CostOpType::value),
ArgFlags_ = evaluator<ArgType>::Flags,
Vectorizable_ = bool(int(ArgFlags_) & PacketAccessBit) && bool(MemberOp::Vectorizable) &&
(Direction == int(Vertical) ? bool(ArgFlags_ & RowMajorBit) : (ArgFlags_ & RowMajorBit) == 0) &&
(TraversalSize != 0),
Flags = (traits<XprType>::Flags & RowMajorBit) | (evaluator<ArgType>::Flags & (HereditaryBits & (~RowMajorBit))) |
(Vectorizable_ ? PacketAccessBit : 0) | LinearAccessBit,
Alignment = 0 // FIXME this will need to be improved once PartialReduxExpr is vectorized
};
EIGEN_DEVICE_FUNC explicit evaluator(const XprType xpr) : m_arg(xpr.nestedExpression()), m_functor(xpr.functor()) {
EIGEN_INTERNAL_CHECK_COST_VALUE(TraversalSize == Dynamic ? HugeCost
: (TraversalSize == 0 ? 1 : int(CostOpType::value)));
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const {
return coeff(Direction == Vertical ? j : i);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index index) const {
return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index i, Index j) const {
return packet<LoadMode, PacketType>(Direction == Vertical ? j : i);
}
template <int LoadMode, typename PacketType>
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC PacketType packet(Index idx) const {
enum { PacketSize = internal::unpacket_traits<PacketType>::size };
typedef Block<const ArgTypeNestedCleaned, Direction == Vertical ? int(ArgType::RowsAtCompileTime) : int(PacketSize),
Direction == Vertical ? int(PacketSize) : int(ArgType::ColsAtCompileTime), true /* InnerPanel */>
PanelType;
PanelType panel(m_arg, Direction == Vertical ? 0 : idx, Direction == Vertical ? idx : 0,
Direction == Vertical ? m_arg.rows() : Index(PacketSize),
Direction == Vertical ? Index(PacketSize) : m_arg.cols());
// FIXME
// See bug 1612, currently if PacketSize==1 (i.e. complex<double> with 128bits registers) then the storage-order of
// panel get reversed and methods like packetByOuterInner do not make sense anymore in this context. So let's just
// by pass "vectorization" in this case:
if (PacketSize == 1) return internal::pset1<PacketType>(coeff(idx));
typedef typename internal::redux_evaluator<PanelType> PanelEvaluator;
PanelEvaluator panel_eval(panel);
typedef typename MemberOp::BinaryOp BinaryOp;
PacketType p = internal::packetwise_redux_impl<BinaryOp, PanelEvaluator>::template run<PacketType>(
panel_eval, m_functor.binaryFunc(), m_arg.outerSize());
return p;
}
protected:
ConstArgTypeNested m_arg;
const MemberOp m_functor;
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_PARTIALREDUX_H