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[SYCL] This PR adds the minimum modifications to the Eigen unsupported module required to run it on devices supporting SYCL.

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* Abstracting the pointer type so that both SYCL memory and pointer can be captured.
* Converting SYCL virtual pointer to SYCL device memory in Eigen evaluator class.
* Binding SYCL placeholder accessor to command group handler by using bind method in Eigen evaluator node.
* Adding SYCL macro for controlling loop unrolling.
* Modifying the TensorDeviceSycl.h and SYCL executor method to adopt the above changes.
This commit is contained in:
Mehdi Goli
2019-06-28 10:08:23 +01:00
parent 16a56b2ddd
commit 7d08fa805a
47 changed files with 1983 additions and 951 deletions
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36
unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h
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@@ -37,7 +37,7 @@ struct traits<TensorStridingOp<Strides, XprType> > : public traits<XprType>
template<typename Strides, typename XprType>
struct eval<TensorStridingOp<Strides, XprType>, Eigen::Dense>
{
typedef const TensorStridingOp<Strides, XprType>& type;
typedef const TensorStridingOp<Strides, XprType>EIGEN_DEVICE_REF type;
};
template<typename Strides, typename XprType>
@@ -108,6 +108,8 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
typedef StorageMemory<CoeffReturnType, Device> Storage;
typedef typename Storage::Type EvaluatorPointerType;
enum {
IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
@@ -120,7 +122,7 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_impl(op.expression(), device), m_strides(op.strides())
: m_impl(op.expression(), device)
{
m_dimensions = m_impl.dimensions();
for (int i = 0; i < NumDims; ++i) {
@@ -149,9 +151,10 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
}
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType/*data*/) {
m_impl.evalSubExprsIfNeeded(NULL);
return true;
}
@@ -173,6 +176,7 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
Index inputIndices[] = {0, 0};
Index indices[] = {index, index + PacketSize - 1};
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
const Index idx0 = indices[0] / m_outputStrides[i];
const Index idx1 = indices[1] / m_outputStrides[i];
@@ -184,6 +188,7 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
inputIndices[0] += indices[0] * m_inputStrides[0];
inputIndices[1] += indices[1] * m_inputStrides[0];
} else { // RowMajor
EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
const Index idx0 = indices[0] / m_outputStrides[i];
const Index idx1 = indices[1] / m_outputStrides[i];
@@ -203,6 +208,7 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
values[0] = m_impl.coeff(inputIndices[0]);
values[PacketSize-1] = m_impl.coeff(inputIndices[1]);
EIGEN_UNROLL_LOOP
for (int i = 1; i < PacketSize-1; ++i) {
values[i] = coeff(index+i);
}
@@ -225,18 +231,20 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
}
EIGEN_DEVICE_FUNC typename Eigen::internal::traits<XprType>::PointerType data() const { return NULL; }
/// required by sycl in order to extract the accessor
const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
/// required by sycl in order to extract the accessor
Strides functor() const { return m_strides; }
EIGEN_DEVICE_FUNC typename Storage::Type data() const { return NULL; }
#ifdef EIGEN_USE_SYCL
// binding placeholder accessors to a command group handler for SYCL
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
m_impl.bind(cgh);
}
#endif
protected:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
{
Index inputIndex = 0;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
const Index idx = index / m_outputStrides[i];
inputIndex += idx * m_inputStrides[i];
@@ -244,6 +252,7 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
}
inputIndex += index * m_inputStrides[0];
} else { // RowMajor
EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
const Index idx = index / m_outputStrides[i];
inputIndex += idx * m_inputStrides[i];
@@ -258,7 +267,6 @@ struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
array<Index, NumDims> m_outputStrides;
array<Index, NumDims> m_inputStrides;
TensorEvaluator<ArgType, Device> m_impl;
const Strides m_strides;
};
// Eval as lvalue
@@ -296,11 +304,6 @@ struct TensorEvaluator<TensorStridingOp<Strides, ArgType>, Device>
return this->m_impl.coeffRef(this->srcCoeff(index));
}
/// required by sycl in order to extract the accessor
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const { return this->m_impl; }
/// required by sycl in order to extract the accessor
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Strides functor() const { return this->m_strides; }
template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void writePacket(Index index, const PacketReturnType& x)
{
@@ -310,6 +313,7 @@ struct TensorEvaluator<TensorStridingOp<Strides, ArgType>, Device>
Index inputIndices[] = {0, 0};
Index indices[] = {index, index + PacketSize - 1};
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
const Index idx0 = indices[0] / this->m_outputStrides[i];
const Index idx1 = indices[1] / this->m_outputStrides[i];
@@ -321,6 +325,7 @@ struct TensorEvaluator<TensorStridingOp<Strides, ArgType>, Device>
inputIndices[0] += indices[0] * this->m_inputStrides[0];
inputIndices[1] += indices[1] * this->m_inputStrides[0];
} else { // RowMajor
EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
const Index idx0 = indices[0] / this->m_outputStrides[i];
const Index idx1 = indices[1] / this->m_outputStrides[i];
@@ -340,6 +345,7 @@ struct TensorEvaluator<TensorStridingOp<Strides, ArgType>, Device>
internal::pstore<Scalar, PacketReturnType>(values, x);
this->m_impl.coeffRef(inputIndices[0]) = values[0];
this->m_impl.coeffRef(inputIndices[1]) = values[PacketSize-1];
EIGEN_UNROLL_LOOP
for (int i = 1; i < PacketSize-1; ++i) {
this->coeffRef(index+i) = values[i];
}