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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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49
unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
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@@ -37,7 +37,7 @@ struct traits<TensorIndexTupleOp<XprType> > : public traits<XprType>
template<typename XprType>
struct eval<TensorIndexTupleOp<XprType>, Eigen::Dense>
{
typedef const TensorIndexTupleOp<XprType>& type;
typedef const TensorIndexTupleOp<XprType>EIGEN_DEVICE_REF type;
};
template<typename XprType>
@@ -82,6 +82,8 @@ struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
static const int NumDims = internal::array_size<Dimensions>::value;
typedef StorageMemory<CoeffReturnType, Device> Storage;
typedef typename Storage::Type EvaluatorPointerType;
enum {
IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
@@ -100,7 +102,7 @@ struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
return m_impl.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;
}
@@ -118,11 +120,11 @@ struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, 1);
}
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return NULL; }
#ifdef EIGEN_USE_SYCL
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const {
return m_impl;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
m_impl.bind(cgh);
}
#endif
@@ -154,7 +156,7 @@ struct traits<TensorTupleReducerOp<ReduceOp, Dims, XprType> > : public traits<Xp
template<typename ReduceOp, typename Dims, typename XprType>
struct eval<TensorTupleReducerOp<ReduceOp, Dims, XprType>, Eigen::Dense>
{
typedef const TensorTupleReducerOp<ReduceOp, Dims, XprType>& type;
typedef const TensorTupleReducerOp<ReduceOp, Dims, XprType>EIGEN_DEVICE_REF type;
};
template<typename ReduceOp, typename Dims, typename XprType>
@@ -216,6 +218,9 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
typedef typename TensorEvaluator<const TensorIndexTupleOp<ArgType> , Device>::Dimensions InputDimensions;
static const int NumDims = internal::array_size<InputDimensions>::value;
typedef array<Index, NumDims> StrideDims;
typedef StorageMemory<CoeffReturnType, Device> Storage;
typedef typename Storage::Type EvaluatorPointerType;
typedef StorageMemory<TupleType, Device> TupleStorageMem;
enum {
IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
@@ -231,9 +236,6 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
: m_orig_impl(op.expression(), device),
m_impl(op.expression().index_tuples().reduce(op.reduce_dims(), op.reduce_op()), device),
m_return_dim(op.return_dim())
#ifdef EIGEN_USE_SYCL
,m_device(device)
#endif
{
gen_strides(m_orig_impl.dimensions(), m_strides);
if (Layout == static_cast<int>(ColMajor)) {
@@ -242,15 +244,18 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
} else {
const Index total_size = internal::array_prod(m_orig_impl.dimensions());
m_stride_mod = (m_return_dim > 0) ? m_strides[m_return_dim - 1] : total_size;
}
m_stride_div = (m_return_dim >= 0) ? m_strides[m_return_dim] : 1;
}
// If m_return_dim is not a valid index, returns 1 or this can crash on Windows.
m_stride_div = ((m_return_dim >= 0) &&
(m_return_dim < static_cast<Index>(m_strides.size())))
? m_strides[m_return_dim] : 1;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
return m_impl.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;
}
@@ -263,16 +268,13 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
return (m_return_dim < 0) ? v.first : (v.first % m_stride_mod) / m_stride_div;
}
#ifndef EIGEN_USE_SYCL
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
#else // following functions are required by sycl
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TupleType* data() const { return m_impl.data(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index return_dim() const {return m_return_dim;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const StrideDims& strides() const {return m_strides;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& stride_mod() const {return m_stride_mod;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& stride_div() const {return m_stride_div;}
const Device& device() const{return m_device;}
#endif
EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return NULL; }
#ifdef EIGEN_USE_SYCL
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
m_impl.bind(cgh);
m_orig_impl.bind(cgh);
}
#endif
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
costPerCoeff(bool vectorized) const {
@@ -312,9 +314,6 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
StrideDims m_strides;
Index m_stride_mod;
Index m_stride_div;
#ifdef EIGEN_USE_SYCL
const Device& m_device;
#endif
};
} // end namespace Eigen