diff options
Diffstat (limited to 'src/core/cpu/kernels/elementwise/sve')
5 files changed, 466 insertions, 316 deletions
diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise.cpp b/src/core/cpu/kernels/elementwise/sve/elementwise.cpp new file mode 100644 index 0000000000..2c3bb0ff7c --- /dev/null +++ b/src/core/cpu/kernels/elementwise/sve/elementwise.cpp @@ -0,0 +1,309 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Types.h" +#include "src/core/cpu/kernels/elementwise/sve/elementwise_list.h" +#include <arm_sve.h> + +namespace arm_compute +{ +namespace cpu +{ +using namespace arm_compute::wrapper; + +template <typename InputScalarType, typename OutputScalarType, typename OperatorType> +struct LoopArguments +{ + OperatorType op; + const InputScalarType *input1_ptr; + const InputScalarType *input2_ptr; + OutputScalarType *output_ptr; +}; + +template <typename InputScalarType, typename OutputScalarType, typename OperatorType> +struct BroadcastLoopArguments +{ + OperatorType op; + const InputScalarType *input1_ptr; + InputScalarType broadcast_value; + OutputScalarType *output_ptr; + bool reorder; +}; + +template <typename InputScalarType, typename OutputScalarType> +void arithmetic_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) +{ + const auto in1 = svld1(pg, args.input1_ptr); + const auto in2 = svld1(pg, args.input2_ptr); + const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); + svst1(pg, args.output_ptr, res); +} + +template <typename InputScalarType, typename OutputScalarType> +void arithmetic_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) +{ + const auto non_broadcast_vector = svld1(pg, args.input1_ptr); + const auto broadcast_vector = svdup_n(args.broadcast_value); + const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; + const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; + const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); + svst1(pg, args.output_ptr, res); +} + +template <typename InputScalarType, typename OutputScalarType> +void comparison_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) +{ + const auto in1 = svld1(pg, args.input1_ptr); + const auto in2 = svld1(pg, args.input2_ptr); + const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); + const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); + svst1(output_pg, args.output_ptr, res); +} + +template <typename InputScalarType, typename OutputScalarType> +void comparison_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) +{ + const auto non_broadcast_vector = svld1(pg, args.input1_ptr); + const auto broadcast_vector = svdup_n(args.broadcast_value); + const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; + const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; + const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); + const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); + svst1(output_pg, args.output_ptr, res); +} + +template <typename InputScalarType, typename OutputScalarType, typename OperatorType> +using LoopFuncType = void (*)(svbool_t, const LoopArguments<InputScalarType, OutputScalarType, OperatorType> &); + +template <typename InputScalarType, typename OutputScalarType, typename OperatorType> +using BroadcastLoopFuncType = void (*)(svbool_t, const BroadcastLoopArguments<InputScalarType, OutputScalarType, OperatorType> &); + +template <typename InputVectorType, typename OutputVectorType, typename OperatorType, + typename InputScalarType = typename sve_scalar<InputVectorType>::type, + typename OutputScalarType = typename sve_scalar<OutputVectorType>::type> +void elementwise_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, + OperatorType op, + LoopFuncType<InputScalarType, OutputScalarType, OperatorType> func, + BroadcastLoopFuncType<InputScalarType, OutputScalarType, OperatorType> broadcast_func) +{ + const auto all_true_pg = svptrue<InputScalarType>(); + + // Create input windows + Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); + Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); + + // Clear X Dimension on execution window as we handle manually + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); + + if(is_broadcast_across_x) + { + const bool is_broadcast_input_2 = input2_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; + Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; + const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; + const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; + + // Clear X Dimension on execution window as we handle manually + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_input(broadcast_tensor, broadcast_win); + Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); + Iterator output(out, win); + + execute_window_loop(win, [&](const Coordinates &) + { + auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); + const auto non_broadcast_input_ptr = reinterpret_cast<const InputScalarType *>(non_broadcast_input.ptr()); + const InputScalarType broadcast_value = *reinterpret_cast<const InputScalarType *>(broadcast_input.ptr()); + + int x = window_start_x; + + svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x); + do + { + broadcast_func(pg, + { + op, + non_broadcast_input_ptr + x, + broadcast_value, + output_ptr + x, + !is_broadcast_input_2 + }); + x += svcnt<InputScalarType>(); + pg = svwhilelt<InputScalarType>(x, window_end_x); + } + while(svptest_any(all_true_pg, pg)); + }, + broadcast_input, non_broadcast_input, output); + } + else + { + // Clear X Dimension on execution window as we handle manually + input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input1(in1, input1_win); + Iterator input2(in2, input2_win); + Iterator output(out, win); + + execute_window_loop(win, [&](const Coordinates &) + { + auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); + const auto input1_ptr = reinterpret_cast<const InputScalarType *>(input1.ptr()); + const auto input2_ptr = reinterpret_cast<const InputScalarType *>(input2.ptr()); + + int x = window_start_x; + + svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x); + do + { + func(pg, + { + op, + input1_ptr + x, + input2_ptr + x, + output_ptr + x + }); + x += svcnt<InputScalarType>(); + pg = svwhilelt<InputScalarType>(x, window_end_x); + } + while(svptest_any(all_true_pg, pg)); + }, + input1, input2, output); + } +} + +template <ArithmeticOperation op, typename ScalarType> +void elementwise_arithmetic_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + using VectorType = typename sve_vector<ScalarType>::type; + + elementwise_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op, + &arithmetic_op_loop<ScalarType, ScalarType>, + &arithmetic_op_broadcast_loop<ScalarType, ScalarType>); +} + +template <ComparisonOperation op, typename InputScalarType, typename OutputScalarType = uint8_t> +void elementwise_comparison_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + static_assert(sizeof(InputScalarType) >= sizeof(OutputScalarType), "input data type's width should be equal to or greater than output data type's width"); + using InputVectorType = typename sve_vector<InputScalarType>::type; + using OutputVectorType = typename sve_vector<OutputScalarType>::type; + + elementwise_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op, + &comparison_op_loop<InputScalarType, OutputScalarType>, + &comparison_op_broadcast_loop<InputScalarType, OutputScalarType>); +} + +template <> +svint32_t elementwise_pow<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) +{ + return svcvt_s32_z(pg, svpow_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); +} + +template <> +svint32_t elementwise_div<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) +{ + return svcvt_s32_z(pg, svdiv_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); +} + +template <> +svint16_t elementwise_div<svint16_t>(svbool_t &pg, const svint16_t &a, const svint16_t &b) +{ + ARM_COMPUTE_UNUSED(pg, a, b); + ARM_COMPUTE_ERROR("Not supported"); +} + +template void elementwise_arithmetic_op<ArithmeticOperation::MAX, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MAX, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MAX, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MAX, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_arithmetic_op<ArithmeticOperation::MIN, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MIN, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MIN, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::MIN, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::SQUARED_DIFF, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::PRELU, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_arithmetic_op<ArithmeticOperation::DIV, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::DIV, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::DIV, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::DIV, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_arithmetic_op<ArithmeticOperation::POWER, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::POWER, float32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::POWER, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_arithmetic_op<ArithmeticOperation::POWER, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::Equal, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Equal, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Equal, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Equal, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Equal, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::NotEqual, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::NotEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::NotEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::NotEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::NotEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::Greater, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Greater, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Greater, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Greater, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Greater, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::GreaterEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::Less, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Less, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Less, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Less, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::Less, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); + +template void elementwise_comparison_op<ComparisonOperation::LessEqual, float>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::LessEqual, int32_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::LessEqual, float16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::LessEqual, int16_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +template void elementwise_comparison_op<ComparisonOperation::LessEqual, uint8_t>(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); +} // namespace cpu +} // namespace arm_compute
\ No newline at end of file diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_list.h b/src/core/cpu/kernels/elementwise/sve/elementwise_list.h index 83c3355de4..a92a8648a8 100644 --- a/src/core/cpu/kernels/elementwise/sve/elementwise_list.h +++ b/src/core/cpu/kernels/elementwise/sve/elementwise_list.h @@ -23,50 +23,62 @@ */ #ifndef SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H #define SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H -#if defined(__ARM_FEATURE_SVE) +#if defined(ENABLE_SVE) +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" #include "arm_compute/core/Types.h" +#include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/Traits.h" #include "src/core/NEON/SVEMath.h" #include "src/core/NEON/wrapper/intrinsics/intrinsics.h" #include "src/core/NEON/wrapper/svtraits.h" +#include "src/core/cpu/kernels/elementwise/sve/elementwise_list.h" #include <arm_sve.h> namespace arm_compute { namespace cpu { -namespace sve -{ using namespace arm_compute::wrapper; template <typename VectorType> -inline VectorType elementwise_pow(svbool_t &pg, const VectorType &a, const VectorType &b) +VectorType elementwise_pow(svbool_t &pg, const VectorType &a, const VectorType &b) { return svpow_z(pg, a, b); } -template <> -inline svint32_t elementwise_pow<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) -{ - return svcvt_s32_z(pg, svpow_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); -} - template <typename VectorType> -inline VectorType elementwise_div(svbool_t &pg, const VectorType &a, const VectorType &b) +VectorType elementwise_div(svbool_t &pg, const VectorType &a, const VectorType &b) { return svdiv_z(pg, a, b); } -template <> -inline svint32_t elementwise_div<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b) +template <uint32_t bytewidth> +svbool_t narrow_to_byte_predicate(svbool_t pg) { - return svcvt_s32_z(pg, svdiv_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b))); + const auto all_false = svpfalse(); + + switch(bytewidth) + { + case 8: + pg = svuzp1_b32(pg, all_false); + /* fall through */ + case 4: + pg = svuzp1_b16(pg, all_false); + /* fall through */ + case 2: + pg = svuzp1_b8(pg, all_false); + /* fall through */ + default: + break; + } + return pg; } template <typename VectorType> -inline VectorType elementwise_arithmetic_op(svbool_t &pg, const VectorType &a, const VectorType &b, ArithmeticOperation op) +VectorType elementwise_arithmetic_op(svbool_t &pg, const VectorType &a, const VectorType &b, ArithmeticOperation op) { - using ScalarType = typename sve_scalar<VectorType>::type; + using ScalarType = typename wrapper::sve_scalar<VectorType>::type; VectorType res{}; switch(op) @@ -108,30 +120,8 @@ inline VectorType elementwise_arithmetic_op(svbool_t &pg, const VectorType &a, c return res; } -template <uint32_t bytewidth> -inline svbool_t narrow_to_byte_predicate(svbool_t pg) -{ - const auto all_false = svpfalse(); - - switch(bytewidth) - { - case 8: - pg = svuzp1_b32(pg, all_false); - /* fall through */ - case 4: - pg = svuzp1_b16(pg, all_false); - /* fall through */ - case 2: - pg = svuzp1_b8(pg, all_false); - /* fall through */ - default: - break; - } - return pg; -} - template <typename InputVectorType, typename OutputVectorType> -inline OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVectorType &a, const InputVectorType &b, ComparisonOperation op) +OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVectorType &a, const InputVectorType &b, ComparisonOperation op) { svbool_t selection_vector{}; @@ -159,10 +149,10 @@ inline OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVecto ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); } - using InputScalarType = typename sve_scalar<InputVectorType>::type; + using InputScalarType = typename wrapper::sve_scalar<InputVectorType>::type; selection_vector = narrow_to_byte_predicate<sizeof(InputScalarType)>(selection_vector); - using OutputScalarType = typename sve_scalar<OutputVectorType>::type; + using OutputScalarType = typename wrapper::sve_scalar<OutputVectorType>::type; const auto false_vector = svdup_n(static_cast<OutputScalarType>((uint32_t)0)); const auto true_vector = svdup_n(static_cast<OutputScalarType>(~(uint32_t)0)); auto ret = svsel(selection_vector, true_vector, false_vector); @@ -170,197 +160,12 @@ inline OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVecto return ret; } -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -struct LoopArguments -{ - OperatorType op; - const InputScalarType *input1_ptr; - const InputScalarType *input2_ptr; - OutputScalarType *output_ptr; -}; - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -struct BroadcastLoopArguments -{ - OperatorType op; - const InputScalarType *input1_ptr; - InputScalarType broadcast_value; - OutputScalarType *output_ptr; - bool reorder; -}; - -template <typename InputScalarType, typename OutputScalarType> -inline void arithmetic_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) -{ - const auto in1 = svld1(pg, args.input1_ptr); - const auto in2 = svld1(pg, args.input2_ptr); - const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); - svst1(pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void arithmetic_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args) -{ - const auto non_broadcast_vector = svld1(pg, args.input1_ptr); - const auto broadcast_vector = svdup_n(args.broadcast_value); - const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; - const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; - const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op); - svst1(pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void comparison_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) -{ - const auto in1 = svld1(pg, args.input1_ptr); - const auto in2 = svld1(pg, args.input2_ptr); - const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); - const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); - svst1(output_pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType> -inline void comparison_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args) -{ - const auto non_broadcast_vector = svld1(pg, args.input1_ptr); - const auto broadcast_vector = svdup_n(args.broadcast_value); - const auto in1 = args.reorder ? broadcast_vector : non_broadcast_vector; - const auto in2 = args.reorder ? non_broadcast_vector : broadcast_vector; - const auto res = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op); - const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg); - svst1(output_pg, args.output_ptr, res); -} - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -using LoopFuncType = void (*)(svbool_t, const LoopArguments<InputScalarType, OutputScalarType, OperatorType> &); - -template <typename InputScalarType, typename OutputScalarType, typename OperatorType> -using BroadcastLoopFuncType = void (*)(svbool_t, const BroadcastLoopArguments<InputScalarType, OutputScalarType, OperatorType> &); - -template <typename InputVectorType, typename OutputVectorType, typename OperatorType, - typename InputScalarType = typename sve_scalar<InputVectorType>::type, - typename OutputScalarType = typename sve_scalar<OutputVectorType>::type> -void elementwise_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, - OperatorType op, - LoopFuncType<InputScalarType, OutputScalarType, OperatorType> func, - BroadcastLoopFuncType<InputScalarType, OutputScalarType, OperatorType> broadcast_func) -{ - const auto all_true_pg = svptrue<InputScalarType>(); - - // Create input windows - Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); - Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); - - // Clear X Dimension on execution window as we handle manually - Window win = window; - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); - - if(is_broadcast_across_x) - { - const bool is_broadcast_input_2 = input2_win.x().step() == 0; - Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; - Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; - const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; - const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; - - // Clear X Dimension on execution window as we handle manually - non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator broadcast_input(broadcast_tensor, broadcast_win); - Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); - const auto non_broadcast_input_ptr = reinterpret_cast<const InputScalarType *>(non_broadcast_input.ptr()); - const InputScalarType broadcast_value = *reinterpret_cast<const InputScalarType *>(broadcast_input.ptr()); - - int x = window_start_x; - - svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x); - do - { - broadcast_func(pg, - { - op, - non_broadcast_input_ptr + x, - broadcast_value, - output_ptr + x, - !is_broadcast_input_2 - }); - x += svcnt<InputScalarType>(); - pg = svwhilelt<InputScalarType>(x, window_end_x); - } - while(svptest_any(all_true_pg, pg)); - }, - broadcast_input, non_broadcast_input, output); - } - else - { - // Clear X Dimension on execution window as we handle manually - input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input1(in1, input1_win); - Iterator input2(in2, input2_win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); - const auto input1_ptr = reinterpret_cast<const InputScalarType *>(input1.ptr()); - const auto input2_ptr = reinterpret_cast<const InputScalarType *>(input2.ptr()); - - int x = window_start_x; - - svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x); - do - { - func(pg, - { - op, - input1_ptr + x, - input2_ptr + x, - output_ptr + x - }); - x += svcnt<InputScalarType>(); - pg = svwhilelt<InputScalarType>(x, window_end_x); - } - while(svptest_any(all_true_pg, pg)); - }, - input1, input2, output); - } -} - template <ArithmeticOperation op, typename ScalarType> -void elementwise_arithmetic_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) -{ - using VectorType = typename sve_vector<ScalarType>::type; - - elementwise_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op, - &arithmetic_op_loop<ScalarType, ScalarType>, - &arithmetic_op_broadcast_loop<ScalarType, ScalarType>); -} - -template <ComparisonOperation op, typename InputScalarType, typename OutputScalarType = uint8_t> -void elementwise_comparison_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) -{ - static_assert(sizeof(InputScalarType) >= sizeof(OutputScalarType), "input data type's width should be equal to or greater than output data type's width"); - using InputVectorType = typename sve_vector<InputScalarType>::type; - using OutputVectorType = typename sve_vector<OutputScalarType>::type; - - elementwise_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op, - &comparison_op_loop<InputScalarType, OutputScalarType>, - &comparison_op_broadcast_loop<InputScalarType, OutputScalarType>); -} +void elementwise_arithmetic_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); -} // namespace sve +template <ComparisonOperation op, typename ScalarType, typename OutputScalarType = uint8_t> +void elementwise_comparison_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window); } // namespace cpu } // namespace arm_compute -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) #endif /* SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H */ diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h b/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h index b6342c727c..6c5524e284 100644 --- a/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h +++ b/src/core/cpu/kernels/elementwise/sve/elementwise_quantized_list.h @@ -26,14 +26,13 @@ #if defined(__ARM_FEATURE_SVE2) +#include "src/core/NEON/wrapper/svtraits.h" #include "src/core/cpu/kernels/elementwise/sve/elementwise_list.h" namespace arm_compute { namespace cpu { -namespace sve -{ using namespace arm_compute::wrapper; template <typename InputScalarType, typename OutputScalarType, typename OperatorType> @@ -176,7 +175,7 @@ inline void comparison_op_quantized_loop(svbool_t pg, const QuantizedLoopArgumen const auto in1 = load_quantized(args.input1_ptr, pg, args.in1_offset, args.in1_scale); const auto in2 = load_quantized(args.input2_ptr, pg, args.in2_offset, args.in2_scale); - using OutputVectorType = typename sve_vector<OutputScalarType>::type; + using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type; const auto result = svcreate4( elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(in1, 0), svget4(in2, 0), args.op), @@ -200,7 +199,7 @@ inline void comparison_op_broadcast_quantized_loop(svbool_t pg, const BroadcastQ const auto &af = args.reorder ? in2 : in1; const auto &bf = args.reorder ? in1 : in2; - using OutputVectorType = typename sve_vector<OutputScalarType>::type; + using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type; const auto result = svcreate4( elementwise_comparison_op<svfloat32_t, OutputVectorType>(pg, svget4(af, 0), svget4(bf, 0), args.op), @@ -221,8 +220,8 @@ template <typename InputScalarType, typename OutputScalarType, typename Operator using BroadcastQuantizedLoopFuncType = void (*)(svbool_t, const BroadcastQuantizedLoopArguments<InputScalarType, OutputScalarType, OperatorType> &); template <typename InputVectorType, typename OutputVectorType, typename OperatorType, - typename InputScalarType = typename sve_scalar<InputVectorType>::type, - typename OutputScalarType = typename sve_scalar<OutputVectorType>::type> + typename InputScalarType = typename wrapper::sve_scalar<InputVectorType>::type, + typename OutputScalarType = typename wrapper::sve_scalar<OutputVectorType>::type> void elementwise_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, OperatorType op, LoopQuantizedFuncType<InputScalarType, OutputScalarType, OperatorType> func, @@ -344,7 +343,7 @@ void elementwise_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *o template <ArithmeticOperation op, typename ScalarType> void elementwise_arithmetic_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { - using VectorType = typename sve_vector<ScalarType>::type; + using VectorType = typename wrapper::traits::sve_vector<ScalarType>::type; elementwise_quantized_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op, &arithmetic_op_quantized_loop<ScalarType, ScalarType>, &arithmetic_op_broadcast_quantized_loop<ScalarType, ScalarType>); @@ -354,14 +353,12 @@ template <ComparisonOperation op, typename InputScalarType, typename OutputScala void elementwise_comparison_quantized_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) { static_assert(sizeof(InputScalarType) >= sizeof(OutputScalarType), "input data type's width should be equal to or greater than output data type's width"); - using InputVectorType = typename sve_vector<InputScalarType>::type; - using OutputVectorType = typename sve_vector<OutputScalarType>::type; + using InputVectorType = typename wrapper::traits::sve_vector<InputScalarType>::type; + using OutputVectorType = typename wrapper::traits::sve_vector<OutputScalarType>::type; elementwise_quantized_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op, &comparison_op_quantized_loop<InputScalarType, OutputScalarType>, &comparison_op_broadcast_quantized_loop<InputScalarType, OutputScalarType>); } - -} // namespace sve } // namespace cpu } // namespace arm_compute diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_unary.cpp b/src/core/cpu/kernels/elementwise/sve/elementwise_unary.cpp new file mode 100644 index 0000000000..cb58548f0b --- /dev/null +++ b/src/core/cpu/kernels/elementwise/sve/elementwise_unary.cpp @@ -0,0 +1,111 @@ +/* + * Copyright (c) 2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/misc/Traits.h" +#include "src/core/NEON/SVEMath.h" +#include "src/core/NEON/wrapper/intrinsics/intrinsics.h" +#include <arm_sve.h> + +namespace arm_compute +{ +namespace cpu +{ +template <typename ScalarType, typename VectorType> +inline typename std::enable_if<utils::traits::is_floating_point<ScalarType>::value, VectorType>::type elementwise_op_sve_imp(svbool_t pg, ElementWiseUnary op, const VectorType &a) +{ + switch(op) + { + case ElementWiseUnary::RSQRT: + return svinvsqrt(pg, a); + case ElementWiseUnary::EXP: + return wrapper::svexp_z(pg, a); + case ElementWiseUnary::NEG: + return svneg_z(pg, a); + case ElementWiseUnary::LOG: + return wrapper::svlog_z(pg, a); + case ElementWiseUnary::ABS: + return svabs_z(pg, a); + case ElementWiseUnary::ROUND: + return svrintn_z(pg, a); + case ElementWiseUnary::SIN: + return wrapper::svsin_z(pg, a); + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED"); + } +} + +template <typename ScalarType, typename VectorType> +inline typename std::enable_if<std::is_integral<ScalarType>::value, VectorType>::type elementwise_op_sve_imp(svbool_t pg, ElementWiseUnary op, const VectorType &a) +{ + switch(op) + { + case ElementWiseUnary::NEG: + return svneg_z(pg, a); + case ElementWiseUnary::ABS: + return svabs_z(pg, a); + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED"); + } +} + +template <typename ScalarType> +void elementwise_sve_op(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op) +{ + const auto all_true_pg = wrapper::svptrue<ScalarType>(); + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input(in, win); + Iterator output(out, win); + + execute_window_loop(win, [&](const Coordinates &) + { + auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr()); + const auto input_ptr = reinterpret_cast<const ScalarType *>(input.ptr()); + int x = window_start_x; + + svbool_t pg = wrapper::svwhilelt<ScalarType>(x, window_end_x); + do + { + const auto vin = svld1(pg, input_ptr + x); + svst1(pg, output_ptr + x, elementwise_op_sve_imp<ScalarType, decltype(vin)>(pg, op, vin)); + x += wrapper::svcnt<ScalarType>(); + pg = wrapper::svwhilelt<ScalarType>(x, window_end_x); + } + while(svptest_any(all_true_pg, pg)); + }, + input, output); +} + +template void elementwise_sve_op<float16_t>(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op); +template void elementwise_sve_op<float32_t>(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op); +template void elementwise_sve_op<int32_t>(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op); +} // namespace cpu +} // namespace arm_compute
\ No newline at end of file diff --git a/src/core/cpu/kernels/elementwise/sve/elementwise_unary_list.h b/src/core/cpu/kernels/elementwise/sve/elementwise_unary_list.h index 23502c71e5..63490421e9 100644 --- a/src/core/cpu/kernels/elementwise/sve/elementwise_unary_list.h +++ b/src/core/cpu/kernels/elementwise/sve/elementwise_unary_list.h @@ -25,87 +25,15 @@ #define SRC_CORE_SVE_KERNELS_ELEMENTWISE_UNARY_LIST_H #include "arm_compute/core/Types.h" -#include "arm_compute/core/utils/misc/Traits.h" -#include "src/core/NEON/wrapper/intrinsics/intrinsics.h" -#if defined(__ARM_FEATURE_SVE) -#include "src/core/NEON/SVEMath.h" -#include <arm_sve.h> +#if defined(ENABLE_SVE) namespace arm_compute { namespace cpu { -template <typename ScalarType, typename VectorType> -inline typename std::enable_if<utils::traits::is_floating_point<ScalarType>::value, VectorType>::type elementwise_op_sve_imp(svbool_t pg, ElementWiseUnary op, const VectorType &a) -{ - switch(op) - { - case ElementWiseUnary::RSQRT: - return svinvsqrt(pg, a); - case ElementWiseUnary::EXP: - return wrapper::svexp_z(pg, a); - case ElementWiseUnary::NEG: - return svneg_z(pg, a); - case ElementWiseUnary::LOG: - return wrapper::svlog_z(pg, a); - case ElementWiseUnary::ABS: - return svabs_z(pg, a); - case ElementWiseUnary::ROUND: - return svrintn_z(pg, a); - case ElementWiseUnary::SIN: - return wrapper::svsin_z(pg, a); - default: - ARM_COMPUTE_ERROR("NOT_SUPPORTED"); - } -} - -template <typename ScalarType, typename VectorType> -inline typename std::enable_if<std::is_integral<ScalarType>::value, VectorType>::type elementwise_op_sve_imp(svbool_t pg, ElementWiseUnary op, const VectorType &a) -{ - switch(op) - { - case ElementWiseUnary::NEG: - return svneg_z(pg, a); - case ElementWiseUnary::ABS: - return svabs_z(pg, a); - default: - ARM_COMPUTE_ERROR("NOT_SUPPORTED"); - } -} - template <typename ScalarType> -void elementwise_sve_op(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op) -{ - const auto all_true_pg = wrapper::svptrue<ScalarType>(); - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - - Window win = window; - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator input(in, win); - Iterator output(out, win); - - execute_window_loop(win, [&](const Coordinates &) - { - auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr()); - const auto input_ptr = reinterpret_cast<const ScalarType *>(input.ptr()); - int x = window_start_x; - - svbool_t pg = wrapper::svwhilelt<ScalarType>(x, window_end_x); - do - { - const auto vin = svld1(pg, input_ptr + x); - svst1(pg, output_ptr + x, elementwise_op_sve_imp<ScalarType, decltype(vin)>(pg, op, vin)); - x += wrapper::svcnt<ScalarType>(); - pg = wrapper::svwhilelt<ScalarType>(x, window_end_x); - } - while(svptest_any(all_true_pg, pg)); - }, - input, output); -} - +void elementwise_sve_op(const ITensor *in, ITensor *out, const Window &window, ElementWiseUnary op); } // namespace cpu } // namespace arm_compute -#endif // defined(__ARM_FEATURE_SVE) +#endif // defined(ENABLE_SVE) #endif // SRC_CORE_NEON_KERNELS_ELEMENTWISE_UNARY_LIST_H
\ No newline at end of file |