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authorGeorgios Pinitas <georgios.pinitas@arm.com>2021-04-22 16:42:03 +0100
committerMichalis Spyrou <michalis.spyrou@arm.com>2021-06-07 13:21:17 +0000
commitbdcdc39d89b6a6556f5c0483af5379f75eae0c55 (patch)
tree454cd50afa81da3ca3382701619fef023911e3f7 /src/core/cpu/kernels/elementwise/sve/elementwise.cpp
parent5a643320b79f15a5d09b5366c4744579cf71e303 (diff)
downloadComputeLibrary-bdcdc39d89b6a6556f5c0483af5379f75eae0c55.tar.gz
Enable fat binary support
Changes our build system to allow building both Neon(TM) and SVE kernels and package them in the same binary. This will allow runtime selection of the underlying architecture. Adds new build option, fat_binary, for enabling this feature. Change-Id: I8e8386149773ce28e071a2fb7ddd8c8ae0f28a4a Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5704 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/cpu/kernels/elementwise/sve/elementwise.cpp')
-rw-r--r--src/core/cpu/kernels/elementwise/sve/elementwise.cpp309
1 files changed, 309 insertions, 0 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
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+++ 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