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Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorSyclFunctors.h')
| -rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorSyclFunctors.h | 248 |
1 files changed, 0 insertions, 248 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorSyclFunctors.h b/unsupported/Eigen/CXX11/src/Tensor/TensorSyclFunctors.h deleted file mode 100644 index a447c3f88..000000000 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorSyclFunctors.h +++ /dev/null @@ -1,248 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Mehdi Goli Codeplay Software Ltd. -// Ralph Potter Codeplay Software Ltd. -// Luke Iwanski Codeplay Software Ltd. -// Contact: eigen@codeplay.com -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -// General include header of SYCL target for Tensor Module -#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCLFUNCTORS_H -#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCLFUNCTORS_H - -namespace Eigen { -namespace TensorSycl { -namespace internal { - - template<typename CoeffReturnType, typename OP, typename OutputAccessor, typename InputAccessor, typename LocalAccessor> struct GenericKernelReducer{ - OP op; - OutputAccessor aOut; - ptrdiff_t out_offset; - InputAccessor aI; - LocalAccessor scratch; - size_t length, local; - GenericKernelReducer(OP op_, OutputAccessor aOut_, ptrdiff_t out_offset_, InputAccessor aI_, LocalAccessor scratch_, size_t length_, size_t local_) - : op(op_), aOut(aOut_), out_offset(out_offset_), aI(aI_), scratch(scratch_), length(length_), local(local_){} - void operator()(cl::sycl::nd_item<1> itemID) { - size_t globalid = itemID.get_global(0); - size_t localid = itemID.get_local(0); - /* All threads collectively read from global memory into local. - * The barrier ensures all threads' IO is resolved before - * execution continues (strictly speaking, all threads within - * a single work-group - there is no co-ordination between - * work-groups, only work-items). */ - if (globalid < length) { - scratch[localid] = aI[globalid]; - } - itemID.barrier(cl::sycl::access::fence_space::local_space); - - /* Apply the reduction operation between the current local - * id and the one on the other half of the vector. */ - if (globalid < length) { - auto min = (length < local) ? length : local; - for (size_t offset = min / 2; offset > 0; offset /= 2) { - if (localid < offset) { - auto accum = op.initialize(); - op.reduce(scratch[localid], &accum); - op.reduce(scratch[localid + offset], &accum); - op.finalize(accum); - scratch[localid]=accum; - //scratch[localid] += scratch[localid + offset]; - } - itemID.barrier(cl::sycl::access::fence_space::local_space); - } - /* The final result will be stored in local id 0. */ - if (localid == 0) { - aI[itemID.get_group(0)] = scratch[localid]; - if((length<=local) && globalid ==0){ - auto aOutPtr = ConvertToActualTypeSycl(CoeffReturnType, aOut); - aOutPtr[0 + ConvertToActualSyclOffset(CoeffReturnType, out_offset)]=scratch[0]; - } - } - } - } - - }; - -/// ReductionFunctor -template < typename HostExpr, typename FunctorExpr, typename Tuple_of_Acc, typename Dims, typename Op, typename Index> class ReductionFunctor { - public: - typedef typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr; - typedef cl::sycl::accessor<uint8_t, 1, cl::sycl::access::mode::write, cl::sycl::access::target::global_buffer> write_accessor; - ReductionFunctor(write_accessor output_accessor_, ptrdiff_t out_offset_, FunctorExpr functors_, Tuple_of_Acc tuple_of_accessors_,Dims dims_, Op functor_, Index range_, Index) - :output_accessor(output_accessor_), out_offset(out_offset_), functors(functors_), tuple_of_accessors(tuple_of_accessors_), dims(dims_), functor(functor_), range(range_) {} - void operator()(cl::sycl::nd_item<1> itemID) { - - typedef typename ConvertToDeviceExpression<const HostExpr>::Type DevExpr; - auto device_expr = createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors); - /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour - /// the first behaviour is when it is used as a root to launch the sub-kernel. The second one is when it is treated as a leafnode to pass the - /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here. - const auto device_self_expr= Eigen::TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, functor); - /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is - /// the device_evaluator is detectable and recognisable on the device. - typedef Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice> DeviceSelf; - auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice>(device_self_expr, Eigen::SyclKernelDevice()); - auto output_accessor_ptr =ConvertToActualTypeSycl(typename DeviceSelf::CoeffReturnType, output_accessor); - /// const cast added as a naive solution to solve the qualifier drop error - auto globalid=static_cast<Index>(itemID.get_global_linear_id()); - if (globalid< range) { - typename DeviceSelf::CoeffReturnType accum = functor.initialize(); - Eigen::internal::GenericDimReducer<DeviceSelf::NumReducedDims-1, DeviceSelf, Op>::reduce(device_self_evaluator, device_self_evaluator.firstInput(static_cast<typename DevExpr::Index>(globalid)),const_cast<Op&>(functor), &accum); - functor.finalize(accum); - output_accessor_ptr[globalid + ConvertToActualSyclOffset(typename DeviceSelf::CoeffReturnType, out_offset)]= accum; - } - } - private: - write_accessor output_accessor; - ptrdiff_t out_offset; - FunctorExpr functors; - Tuple_of_Acc tuple_of_accessors; - Dims dims; - Op functor; - Index range; -}; - -template < typename HostExpr, typename FunctorExpr, typename Tuple_of_Acc, typename Dims, typename Index> -class ReductionFunctor<HostExpr, FunctorExpr, Tuple_of_Acc, Dims, Eigen::internal::MeanReducer<typename HostExpr::CoeffReturnType>, Index> { - public: - typedef typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr; - typedef cl::sycl::accessor<uint8_t, 1, cl::sycl::access::mode::write, cl::sycl::access::target::global_buffer> write_accessor; - typedef Eigen::internal::SumReducer<typename HostExpr::CoeffReturnType> Op; - ReductionFunctor(write_accessor output_accessor_, ptrdiff_t out_offset_, FunctorExpr functors_, Tuple_of_Acc tuple_of_accessors_,Dims dims_, - Eigen::internal::MeanReducer<typename HostExpr::CoeffReturnType>, Index range_, Index num_values_to_reduce_) - :output_accessor(output_accessor_), out_offset(out_offset_), functors(functors_), tuple_of_accessors(tuple_of_accessors_), dims(dims_), functor(Op()), range(range_), num_values_to_reduce(num_values_to_reduce_) {} - void operator()(cl::sycl::nd_item<1> itemID) { - - typedef typename ConvertToDeviceExpression<const HostExpr>::Type DevExpr; - auto device_expr = createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors); - /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour - /// the first behaviour is when it is used as a root to launch the sub-kernel. The second one is when it is treated as a leafnode to pass the - /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here. - const auto device_self_expr= Eigen::TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, functor); - /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is - /// the device_evaluator is detectable and recognisable on the device. - typedef Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice> DeviceSelf; - auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice>(device_self_expr, Eigen::SyclKernelDevice()); - auto output_accessor_ptr =ConvertToActualTypeSycl(typename DeviceSelf::CoeffReturnType, output_accessor); - /// const cast added as a naive solution to solve the qualifier drop error - auto globalid=static_cast<Index>(itemID.get_global_linear_id()); - if (globalid< range) { - typename DeviceSelf::CoeffReturnType accum = functor.initialize(); - Eigen::internal::GenericDimReducer<DeviceSelf::NumReducedDims-1, DeviceSelf, Op>::reduce(device_self_evaluator, device_self_evaluator.firstInput(static_cast<typename DevExpr::Index>(globalid)),const_cast<Op&>(functor), &accum); - functor.finalize(accum); - output_accessor_ptr[globalid+ ConvertToActualSyclOffset(typename DeviceSelf::CoeffReturnType, out_offset)]= accum/num_values_to_reduce; - } - } - private: - write_accessor output_accessor; - ptrdiff_t out_offset; - FunctorExpr functors; - Tuple_of_Acc tuple_of_accessors; - Dims dims; - Op functor; - Index range; - Index num_values_to_reduce; -}; - -template<typename CoeffReturnType ,typename OutAccessor, typename HostExpr, typename FunctorExpr, typename Op, typename Dims, typename Index, typename TupleType> -class FullReductionKernelFunctor{ -public: - typedef typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr; - OutAccessor tmp_global_accessor; - Index rng , remaining, red_factor; - Op op; - Dims dims; - FunctorExpr functors; - TupleType tuple_of_accessors; - - FullReductionKernelFunctor(OutAccessor acc, Index rng_, Index remaining_, Index red_factor_, Op op_, Dims dims_, FunctorExpr functors_, TupleType t_acc) - :tmp_global_accessor(acc), rng(rng_), remaining(remaining_), red_factor(red_factor_),op(op_), dims(dims_), functors(functors_), tuple_of_accessors(t_acc){} - - void operator()(cl::sycl::nd_item<1> itemID) { - - typedef typename TensorSycl::internal::ConvertToDeviceExpression<const HostExpr>::Type DevExpr; - auto device_expr = TensorSycl::internal::createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors); - /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour - /// the first behaviour is when it is used as a root to launch the sub-kernel. The second one is when it is treated as a leafnode to pass the - /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here. - const auto device_self_expr= Eigen::TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, op); - /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is - /// the device_evaluator is detectable and recognisable on the device. - auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice>(device_self_expr, Eigen::SyclKernelDevice()); - /// const cast added as a naive solution to solve the qualifier drop error - auto globalid=itemID.get_global_linear_id(); - - tmp_global_accessor.get_pointer()[globalid]=(globalid<rng) ? Eigen::internal::InnerMostDimReducer<decltype(device_self_evaluator), Op, false>::reduce(device_self_evaluator, static_cast<typename DevExpr::Index>(red_factor*globalid), red_factor, const_cast<Op&>(op)) - : static_cast<CoeffReturnType>(op.initialize()); - - if(remaining!=0 && globalid==0 ){ - // this will add the rest of input buffer when the input size is not devidable to red_factor. - auto remaining_reduce =Eigen::internal::InnerMostDimReducer<decltype(device_self_evaluator), Op, false>:: - reduce(device_self_evaluator, static_cast<typename DevExpr::Index>(red_factor*(rng)), static_cast<typename DevExpr::Index>(remaining), const_cast<Op&>(op)); - auto accum = op.initialize(); - op.reduce(tmp_global_accessor.get_pointer()[0], &accum); - op.reduce(remaining_reduce, &accum); - op.finalize(accum); - tmp_global_accessor.get_pointer()[0]=accum; - - } - } -}; - -template<typename CoeffReturnType ,typename OutAccessor, typename HostExpr, typename FunctorExpr, typename Dims, typename Index, typename TupleType> -class FullReductionKernelFunctor<CoeffReturnType, OutAccessor, HostExpr, FunctorExpr, Eigen::internal::MeanReducer<CoeffReturnType>, Dims, Index, TupleType>{ -public: - typedef typename TensorSycl::internal::createPlaceHolderExpression<HostExpr>::Type PlaceHolderExpr; - typedef Eigen::internal::SumReducer<CoeffReturnType> Op; - - OutAccessor tmp_global_accessor; - Index rng , remaining, red_factor; - Op op; - Dims dims; - FunctorExpr functors; - TupleType tuple_of_accessors; - - FullReductionKernelFunctor(OutAccessor acc, Index rng_, Index remaining_, Index red_factor_, Eigen::internal::MeanReducer<CoeffReturnType>, Dims dims_, FunctorExpr functors_, TupleType t_acc) - :tmp_global_accessor(acc), rng(rng_), remaining(remaining_), red_factor(red_factor_),op(Op()), dims(dims_), functors(functors_), tuple_of_accessors(t_acc){} - - void operator()(cl::sycl::nd_item<1> itemID) { - - typedef typename TensorSycl::internal::ConvertToDeviceExpression<const HostExpr>::Type DevExpr; - auto device_expr = TensorSycl::internal::createDeviceExpression<DevExpr, PlaceHolderExpr>(functors, tuple_of_accessors); - /// reduction cannot be captured automatically through our device conversion recursion. The reason is that reduction has two behaviour - /// the first behaviour is when it is used as a root to launch the sub-kernel. The second one is when it is treated as a leafnode to pass the - /// calculated result to its parent kernel. While the latter is automatically detected through our device expression generator. The former is created here. - const auto device_self_expr= Eigen::TensorReductionOp<Op, Dims, decltype(device_expr.expr) ,MakeGlobalPointer>(device_expr.expr, dims, op); - /// This is the evaluator for device_self_expr. This is exactly similar to the self which has been passed to run function. The difference is - /// the device_evaluator is detectable and recognisable on the device. - auto device_self_evaluator = Eigen::TensorEvaluator<decltype(device_self_expr), Eigen::SyclKernelDevice>(device_self_expr, Eigen::SyclKernelDevice()); - /// const cast added as a naive solution to solve the qualifier drop error - auto globalid=itemID.get_global_linear_id(); - auto scale = (rng*red_factor) + remaining; - - tmp_global_accessor.get_pointer()[globalid]= (globalid<rng)? ((Eigen::internal::InnerMostDimReducer<decltype(device_self_evaluator), Op, false>::reduce(device_self_evaluator, static_cast<typename DevExpr::Index>(red_factor*globalid), red_factor, const_cast<Op&>(op)))/scale) - :static_cast<CoeffReturnType>(op.initialize())/scale; - - if(remaining!=0 && globalid==0 ){ - // this will add the rest of input buffer when the input size is not devidable to red_factor. - auto remaining_reduce =Eigen::internal::InnerMostDimReducer<decltype(device_self_evaluator), Op, false>::reduce(device_self_evaluator, static_cast<typename DevExpr::Index>(red_factor*(rng)), static_cast<typename DevExpr::Index>(remaining), const_cast<Op&>(op)); - auto accum = op.initialize(); - tmp_global_accessor.get_pointer()[0]= tmp_global_accessor.get_pointer()[0]*scale; - op.reduce(tmp_global_accessor.get_pointer()[0], &accum); - op.reduce(remaining_reduce, &accum); - op.finalize(accum); - tmp_global_accessor.get_pointer()[0]=accum/scale; - - } - } -}; - -} -} -} -#endif // UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSORSYCLFUNCTORS_H |