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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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23
unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h
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@@ -109,6 +109,8 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, 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 = false,
@@ -145,7 +147,7 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType) {
m_impl.evalSubExprsIfNeeded(NULL);
return true;
}
@@ -158,6 +160,7 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
eigen_assert(index < dimensions().TotalSize());
Index inputIndex = 0;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
Index idx = index / m_strides[i];
index -= idx * m_strides[i];
@@ -172,6 +175,7 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
inputIndex += index;
}
} else {
EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
Index idx = index / m_strides[i];
index -= idx * m_strides[i];
@@ -205,6 +209,7 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
// local structure.
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
values[PacketSize];
EIGEN_UNROLL_LOOP
for (int i = 0; i < PacketSize; ++i) {
values[i] = coeff(index+i);
}
@@ -225,12 +230,14 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
}
EIGEN_DEVICE_FUNC typename Eigen::internal::traits<XprType>::PointerType data() const { return NULL; }
EIGEN_DEVICE_FUNC typename Storage::Type data() const { return NULL; }
/// required by sycl in order to extract the accessor
const TensorEvaluator<ArgType, Device> & impl() const { return m_impl; }
/// added for sycl in order to construct the buffer from sycl device
ReverseDimensions functor() const { return m_reverse; }
#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:
Dimensions m_dimensions;
@@ -269,7 +276,7 @@ struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return this->m_dimensions; }
@@ -285,11 +292,11 @@ struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
// This code is pilfered from TensorMorphing.h
EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
EIGEN_UNROLL_LOOP
for (int i = 0; i < PacketSize; ++i) {
this->coeffRef(index+i) = values[i];
}
}
};