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Eigen cost model part 1. This implements a basic recursive framework to estimate the cost of evaluating tensor expressions.

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This commit is contained in:
Rasmus Munk Larsen
2016-04-14 13:57:35 -07:00
parent 3551dea887
commit 235e83aba6
28 changed files with 695 additions and 185 deletions
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40
unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
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@@ -104,6 +104,10 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
typedef typename XprType::Index Index;
static const int NumDims = internal::array_size<ReverseDimensions>::value;
typedef DSizes<Index, NumDims> Dimensions;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
enum {
IsAligned = false,
@@ -135,10 +139,6 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
}
}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return m_dimensions; }
@@ -195,21 +195,33 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
PacketReturnType packet(Index index) const
{
const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+packetSize-1 < dimensions().TotalSize());
EIGEN_STATIC_ASSERT(PacketSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
// TODO(ndjaitly): write a better packing routine that uses
// local structure.
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
values[packetSize];
for (int i = 0; i < packetSize; ++i) {
values[PacketSize];
for (int i = 0; i < PacketSize; ++i) {
values[i] = coeff(index+i);
}
PacketReturnType rslt = internal::pload<PacketReturnType>(values);
return rslt;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
2 * TensorOpCost::MulCost<Index>() +
TensorOpCost::DivCost<Index>());
for (int i = 0; i < NumDims; ++i) {
if (m_reverse[i]) {
compute_cost += 2 * TensorOpCost::AddCost<Index>();
}
}
return m_impl.costPerCoeff(vectorized) +
TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
}
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
protected:
@@ -246,6 +258,7 @@ struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return this->m_dimensions; }
@@ -256,14 +269,13 @@ struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void writePacket(Index index, const PacketReturnType& x) {
const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+packetSize-1 < dimensions().TotalSize());
EIGEN_STATIC_ASSERT(PacketSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
// This code is pilfered from TensorMorphing.h
EIGEN_ALIGN_MAX CoeffReturnType values[packetSize];
EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
for (int i = 0; i < packetSize; ++i) {
for (int i = 0; i < PacketSize; ++i) {
this->coeffRef(index+i) = values[i];
}
}