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diff --git a/runtimes/contrib/uben/Convolution.cpp b/runtimes/contrib/uben/Convolution.cpp
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+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+ * @file Conv2D (with SAME padding) benchmark with various algorithms
+ */
+
+#ifndef KER_H
+#error "KER_H is undefined"
+#endif // KER_H
+#ifndef KER_W
+#error "KER_W is undefined"
+#endif // KER_W
+#ifndef STRIDE_H
+#error "STRIDE_H is undefined"
+#endif // STRIDE_H
+#ifndef STRIDE_W
+#error "STRIDE_W is undefined"
+#endif // STRIDE_W
+
+#define NONIUS_RUNNER
+#include <nonius/nonius_single.h++>
+
+#include <arm_compute/core/Types.h>
+#include <arm_compute/runtime/CL/CLScheduler.h>
+#include <arm_compute/runtime/CL/CLFunctions.h>
+
+#include <cstdint>
+#include <cassert>
+#include <stdexcept>
+
+using namespace arm_compute;
+
+//
+// Helpers
+//
+namespace
+{
+
+enum Layout
+{
+ NCHW,
+ NHWC
+};
+
+struct Initializer
+{
+ Initializer() { CLScheduler::get().default_init(); }
+};
+
+Initializer initializer;
+
+TensorInfo make_info(uint32_t N)
+{
+ TensorShape shape{N};
+ return TensorInfo{shape, 1, DataType::F32};
+}
+
+template <enum Layout> TensorInfo make_info(uint32_t N, uint32_t C, uint32_t H, uint32_t W);
+
+template <> TensorInfo make_info<NCHW>(uint32_t N, uint32_t C, uint32_t H, uint32_t W)
+{
+ TensorShape shape{W, H, C, N};
+ TensorInfo info{shape, 1, DataType::F32};
+ info.set_data_layout(DataLayout::NCHW);
+ return info;
+}
+
+template <> TensorInfo make_info<NHWC>(uint32_t N, uint32_t C, uint32_t H, uint32_t W)
+{
+ TensorShape shape{C, W, H, N};
+ TensorInfo info{shape, 1, DataType::F32};
+ info.set_data_layout(DataLayout::NHWC);
+ return info;
+}
+
+inline void check(const Status &status)
+{
+ if (!status)
+ {
+ std::cerr << status.error_description() << std::endl;
+ throw std::runtime_error{"ERROR"};
+ }
+}
+
+inline bool is_odd(uint32_t n) { return (n % 2 != 0) ? true : false; }
+
+} // namespace
+
+//
+// Benchmark Parameters
+//
+NONIUS_PARAM(BATCH, 1);
+
+NONIUS_PARAM(IFM_C, 3);
+NONIUS_PARAM(IFM_H, 244);
+NONIUS_PARAM(IFM_W, 244);
+
+NONIUS_PARAM(OFM_C, 3);
+NONIUS_PARAM(OFM_H, 244);
+NONIUS_PARAM(OFM_W, 244);
+
+//
+// Configuration Helpers
+//
+namespace
+{
+
+struct Configuration
+{
+ uint32_t ifm_N;
+ uint32_t ifm_C;
+ uint32_t ifm_H;
+ uint32_t ifm_W;
+
+ uint32_t ofm_N;
+ uint32_t ofm_C;
+ uint32_t ofm_H;
+ uint32_t ofm_W;
+
+ uint32_t ker_N;
+ uint32_t ker_C;
+ uint32_t ker_H;
+ uint32_t ker_W;
+
+ uint32_t vertical_stride;
+ uint32_t horizontal_stride;
+
+ uint32_t top_padding;
+ uint32_t bottom_padding;
+ uint32_t left_padding;
+ uint32_t right_padding;
+
+ Configuration(nonius::chronometer meter)
+ {
+ ifm_N = meter.param<BATCH>();
+ ifm_C = meter.param<IFM_C>();
+ ifm_H = meter.param<IFM_H>();
+ ifm_W = meter.param<IFM_W>();
+
+ ofm_N = meter.param<BATCH>();
+ ofm_C = meter.param<OFM_C>();
+ ofm_H = meter.param<OFM_H>();
+ ofm_W = meter.param<OFM_W>();
+
+ ker_N = meter.param<OFM_C>();
+ ker_C = meter.param<IFM_C>();
+ ker_H = KER_H;
+ ker_W = KER_W;
+
+ vertical_stride = STRIDE_H;
+ horizontal_stride = STRIDE_W;
+
+ assert((ifm_H - ker_H) % vertical_stride == 0);
+ assert((ifm_W - ker_H) % horizontal_stride == 0);
+
+ uint32_t const effective_ofm_H = (ifm_H - ker_H) / vertical_stride + 1;
+ uint32_t const effective_ofm_W = (ifm_W - ker_H) / horizontal_stride + 1;
+
+ assert(ofm_H >= effective_ofm_H);
+ assert(ofm_W >= effective_ofm_W);
+
+ uint32_t const pad_H = ofm_H - effective_ofm_H;
+ uint32_t const pad_W = ofm_W - effective_ofm_W;
+
+ top_padding = pad_H / 2;
+ bottom_padding = pad_H / 2;
+ left_padding = pad_W / 2;
+ right_padding = pad_W / 2;
+
+ if (is_odd(pad_H))
+ top_padding += 1;
+ if (is_odd(pad_W))
+ left_padding += 1;
+ }
+
+ template <Layout L> TensorInfo src_info() const
+ {
+ return make_info<L>(ifm_N, ifm_C, ifm_H, ifm_W);
+ }
+ template <Layout L> TensorInfo dst_info() const
+ {
+ return make_info<L>(ofm_N, ofm_C, ofm_H, ofm_W);
+ }
+ template <Layout L> TensorInfo ker_info() const
+ {
+ return make_info<L>(ker_N, ker_C, ker_H, ker_W);
+ }
+ TensorInfo bias_info(void) const { return make_info(ker_N); }
+
+ PadStrideInfo pad_stride_info(void) const
+ {
+ return PadStrideInfo{horizontal_stride,
+ vertical_stride,
+ left_padding,
+ right_padding,
+ top_padding,
+ bottom_padding,
+ DimensionRoundingType::FLOOR};
+ }
+};
+
+} // namespace
+
+//
+// Benchmakr Implementations
+//
+#ifndef CL_DIRECT_CONVOLUTION
+#error "CL_DIRECT_CONVOLUTION is undefined"
+#endif // CL_DIRECT_CONVOLUTION
+
+#if CL_DIRECT_CONVOLUTION
+NONIUS_BENCHMARK("CLDirectConvolutionLayer(NCHW)", [](nonius::chronometer meter) {
+ CLDirectConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NCHW>());
+ dst_tensor.allocator()->init(p.dst_info<NCHW>());
+ ker_tensor.allocator()->init(p.ker_info<NCHW>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run!
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+
+NONIUS_BENCHMARK("CLDirectConvolutionLayer(NHWC)", [](nonius::chronometer meter) {
+ CLDirectConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NHWC>());
+ dst_tensor.allocator()->init(p.dst_info<NHWC>());
+ ker_tensor.allocator()->init(p.ker_info<NHWC>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run!
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+#endif // CL_DIRECT_CONVOLUTION
+
+#ifndef CL_GEMM_CONVOLUTION
+#error "CL_GEMM_CONVOLUTION is undefined"
+#endif // CL_GEMM_CONVOLUTION
+
+#if CL_GEMM_CONVOLUTION
+NONIUS_BENCHMARK("CLGEMMConvolutionLayer(NCHW)", [](nonius::chronometer meter) {
+ CLGEMMConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NCHW>());
+ dst_tensor.allocator()->init(p.dst_info<NCHW>());
+ ker_tensor.allocator()->init(p.ker_info<NCHW>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+
+NONIUS_BENCHMARK("CLGEMMConvolutionLayer(NHWC)", [](nonius::chronometer meter) {
+ CLGEMMConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NHWC>());
+ dst_tensor.allocator()->init(p.dst_info<NHWC>());
+ ker_tensor.allocator()->init(p.ker_info<NHWC>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+#endif // CL_GEMM_CONVOLUTION
+
+#ifndef CL_WINOGRAD_CONVOLUTION
+#error "CL_WINOGRAD_CONVOLUTION is undefined"
+#endif // CL_WINOGRAD_CONVOLUTION
+
+#if CL_WINOGRAD_CONVOLUTION
+NONIUS_BENCHMARK("CLWinogradConvolutionLayer(NCHW)", [](nonius::chronometer meter) {
+ CLWinogradConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NCHW>());
+ dst_tensor.allocator()->init(p.dst_info<NCHW>());
+ ker_tensor.allocator()->init(p.ker_info<NCHW>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+
+NONIUS_BENCHMARK("CLWinogradConvolutionLayer(NHWC)", [](nonius::chronometer meter) {
+ CLWinogradConvolutionLayer conv;
+
+ // Configure
+ Configuration p{meter};
+
+ CLTensor src_tensor{};
+ CLTensor dst_tensor{};
+ CLTensor ker_tensor{};
+ CLTensor bias_tensor{};
+
+ src_tensor.allocator()->init(p.src_info<NHWC>());
+ dst_tensor.allocator()->init(p.dst_info<NHWC>());
+ ker_tensor.allocator()->init(p.ker_info<NHWC>());
+ bias_tensor.allocator()->init(p.bias_info());
+
+ check(conv.validate(src_tensor.info(), ker_tensor.info(), bias_tensor.info(), dst_tensor.info(),
+ p.pad_stride_info()));
+ conv.configure(&src_tensor, &ker_tensor, &bias_tensor, &dst_tensor, p.pad_stride_info());
+
+ src_tensor.allocator()->allocate();
+ ker_tensor.allocator()->allocate();
+ bias_tensor.allocator()->allocate();
+ dst_tensor.allocator()->allocate();
+
+ // Run
+ meter.measure([&](int) {
+ conv.run();
+ CLScheduler::get().sync();
+ });
+})
+#endif // CL_WINOGRAD_CONVOLUTION
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