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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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25
unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
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@@ -119,6 +119,8 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
typedef StorageMemory<CoeffReturnType, Device> Storage;
typedef typename Storage::Type EvaluatorPointerType;
enum {
IsAligned = false,
PacketAccess = TensorEvaluator<LeftArgType, Device>::PacketAccess & TensorEvaluator<RightArgType, Device>::PacketAccess,
@@ -181,7 +183,7 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
// TODO(phli): Add short-circuit memcpy evaluation if underlying data are linear?
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType)
{
m_leftImpl.evalSubExprsIfNeeded(NULL);
m_rightImpl.evalSubExprsIfNeeded(NULL);
@@ -219,11 +221,13 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
Index left_index;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
left_index = subs[0];
EIGEN_UNROLL_LOOP
for (int i = 1; i < NumDims; ++i) {
left_index += (subs[i] % left_dims[i]) * m_leftStrides[i];
}
} else {
left_index = subs[NumDims - 1];
EIGEN_UNROLL_LOOP
for (int i = NumDims - 2; i >= 0; --i) {
left_index += (subs[i] % left_dims[i]) * m_leftStrides[i];
}
@@ -235,11 +239,13 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
Index right_index;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
right_index = subs[0];
EIGEN_UNROLL_LOOP
for (int i = 1; i < NumDims; ++i) {
right_index += (subs[i] % right_dims[i]) * m_rightStrides[i];
}
} else {
right_index = subs[NumDims - 1];
EIGEN_UNROLL_LOOP
for (int i = NumDims - 2; i >= 0; --i) {
right_index += (subs[i] % right_dims[i]) * m_rightStrides[i];
}
@@ -257,6 +263,7 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
eigen_assert(index + packetSize - 1 < dimensions().TotalSize());
EIGEN_ALIGN_MAX CoeffReturnType values[packetSize];
EIGEN_UNROLL_LOOP
for (int i = 0; i < packetSize; ++i) {
values[i] = coeff(index+i);
}
@@ -279,13 +286,15 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
TensorOpCost(0, 0, compute_cost);
}
EIGEN_DEVICE_FUNC typename Eigen::internal::traits<XprType>::PointerType data() const { return NULL; }
/// required by sycl in order to extract the accessor
const TensorEvaluator<LeftArgType, Device>& left_impl() const { return m_leftImpl; }
/// required by sycl in order to extract the accessor
const TensorEvaluator<RightArgType, Device>& right_impl() const { return m_rightImpl; }
/// required by sycl in order to extract the accessor
const Axis& axis() const { return m_axis; }
EIGEN_DEVICE_FUNC EvaluatorPointerType 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_leftImpl.bind(cgh);
m_rightImpl.bind(cgh);
}
#endif
protected:
Dimensions m_dimensions;