COMPMID-415: Port benchmark tests and remove google benchmark

Change-Id: I2f17720a4e974b2cc4481f2884d9f351e8f78b5f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79776
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

44 files changed, 0 insertions, 5834 deletions

diff --git a/tests/benchmark/CL/ActivationLayer.cpp b/tests/benchmark/CL/ActivationLayer.cpp
deleted file mode 100644
index 52a357b2a6..0000000000
--- a/tests/benchmark/CL/ActivationLayer.cpp
+++ /dev/null
@@ -1,211 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/common/ActivationLayer.h"
-
-namespace
-{
-using ActivationLayerAlexNet   = ActivationLayer<AlexNetActivationLayerDataset, CLTensor, CLAccessor, CLActivationLayer>;
-using ActivationLayerLeNet5    = ActivationLayer<LeNet5ActivationLayerDataset, CLTensor, CLAccessor, CLActivationLayer>;
-using ActivationLayerGoogLeNet = ActivationLayer<GoogLeNetActivationLayerDataset, CLTensor, CLAccessor, CLActivationLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(ActivationLayerAlexNet, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 4, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ActivationLayerLeNet5, cl_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ActivationLayerDataset, 0, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ActivationLayerGoogLeNet, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 16, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 17, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 18, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 19, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 20, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 21, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 22, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 23, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 24, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 25, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 26, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 27, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 28, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 29, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 30, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 31, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 32, 1, 4, 8>);
diff --git a/tests/benchmark/CL/BitwiseAnd.cpp b/tests/benchmark/CL/BitwiseAnd.cpp
deleted file mode 100644
index 4858c73948..0000000000
--- a/tests/benchmark/CL/BitwiseAnd.cpp
+++ /dev/null
@@ -1,133 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLBitwiseAnd.h"
-
-#include "benchmark/benchmark_api.h"
-
-#include <memory>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-namespace
-{
-template <typename DataSet>
-class BitwiseAnd : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        ::benchmark::Fixture::SetUp(state);
-
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const std::string image_name = *(DataSet().begin() + state.range(0));
-        const RawTensor &raw        = library->get(image_name);
-
-        // Create tensors
-        src1 = create_tensor<CLTensor>(raw.shape(), DataType::U8);
-        src2 = create_tensor<CLTensor>(raw.shape(), DataType::U8);
-        dst  = create_tensor<CLTensor>(raw.shape(), DataType::U8);
-
-        // Create and configure function
-        band.configure(&src1, &src2, &dst);
-
-        // Allocate tensors
-        src1.allocator()->allocate();
-        src2.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill source tensors
-        library->fill(CLAccessor(src1), image_name, Channel::R);
-        library->fill(CLAccessor(src2), image_name, Channel::G);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        profiler.submit(state);
-
-        ::benchmark::Fixture::TearDown(state);
-    }
-
-    CLBitwiseAnd band{};
-    Profiler     profiler{};
-
-private:
-    CLTensor src1{};
-    CLTensor src2{};
-    CLTensor dst{};
-};
-
-using BitwiseAndSmall = BitwiseAnd<SmallImages>;
-using BitwiseAndLarge = BitwiseAnd<LargeImages>;
-} // namespace
-
-BENCHMARK_DEFINE_F(BitwiseAndSmall, cl_bitwise_and)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        band.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(BitwiseAndSmall, cl_bitwise_and)
-->Threads(1)
-->Apply(DataSetArgs<SmallImages>);
-
-BENCHMARK_DEFINE_F(BitwiseAndLarge, cl_bitwise_and)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        band.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(BitwiseAndLarge, cl_bitwise_and)
-->Threads(1)
-->Apply(DataSetArgs<LargeImages>);
diff --git a/tests/benchmark/CL/CMakeLists.txt b/tests/benchmark/CL/CMakeLists.txt
deleted file mode 100644
index 8493309f40..0000000000
--- a/tests/benchmark/CL/CMakeLists.txt
+++ /dev/null
@@ -1,57 +0,0 @@
-# Copyright (c) 2017 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.
-cmake_minimum_required (VERSION 3.1)
-
-include_directories(${CMAKE_SOURCE_DIR}/../include)
-
-set(arm_compute_test_benchmark_TARGET_DEFINITIONS
-    ${arm_compute_test_benchmark_TARGET_DEFINITIONS}
-    -DOPENCL
-    PARENT_SCOPE
-)
-
-set(arm_compute_test_benchmark_TARGET_INCLUDES
-    ${arm_compute_test_benchmark_TARGET_INCLUDES}
-    ${CMAKE_SOURCE_DIR}/../include
-    PARENT_SCOPE
-)
-
-set(arm_compute_test_benchmark_OPENCL_SOURCE_FILES
-    ${CMAKE_SOURCE_DIR}/CL/CLAccessor.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/Bitwise/BitwiseAnd.cpp
-)
-
-add_library(arm_compute_test_benchmark_OPENCL OBJECT
-    ${arm_compute_test_benchmark_OPENCL_SOURCE_FILES}
-)
-
-set(arm_compute_test_benchmark_TARGET_OBJECTS
-    ${arm_compute_test_benchmark_TARGET_OBJECTS}
-    $<TARGET_OBJECTS:arm_compute_test_benchmark_OPENCL>
-    PARENT_SCOPE
-)
-
-set(arm_compute_test_benchmark_TARGET_LIBRARIES
-    ${arm_compute_test_benchmark_TARGET_LIBRARIES}
-    OpenCL
-    PARENT_SCOPE
-)
diff --git a/tests/benchmark/CL/ConvolutionLayer.cpp b/tests/benchmark/CL/ConvolutionLayer.cpp
deleted file mode 100644
index e790273f9c..0000000000
--- a/tests/benchmark/CL/ConvolutionLayer.cpp
+++ /dev/null
@@ -1,276 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/common/ConvolutionLayer.h"
-
-namespace
-{
-using ConvolutionLayerAlexNet    = ConvolutionLayer<AlexNetConvolutionLayerDataset, CLTensor, CLAccessor, CLConvolutionLayer>;
-using ConvolutionLayerLeNet5     = ConvolutionLayer<LeNet5ConvolutionLayerDataset, CLTensor, CLAccessor, CLConvolutionLayer>;
-using ConvolutionLayerGoogLeNet1 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset1, CLTensor, CLAccessor, CLConvolutionLayer>;
-using ConvolutionLayerGoogLeNet2 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset2, CLTensor, CLAccessor, CLConvolutionLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(ConvolutionLayerAlexNet, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerLeNet5, cl_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 16, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 17, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 18, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 19, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 20, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 21, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 22, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 23, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 24, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 25, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 26, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 27, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 28, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 29, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 30, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 31, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 16, 1, 4, 8>);
diff --git a/tests/benchmark/CL/FullyConnectedLayer.cpp b/tests/benchmark/CL/FullyConnectedLayer.cpp
deleted file mode 100644
index fb8e1bc09f..0000000000
--- a/tests/benchmark/CL/FullyConnectedLayer.cpp
+++ /dev/null
@@ -1,115 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-#include <memory>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/common/FullyConnectedLayer.h"
-
-namespace
-{
-using FullyConnectedLayerAlexNet   = FullyConnectedLayer<AlexNetFullyConnectedLayerDataset, CLTensor, CLAccessor, CLFullyConnectedLayer>;
-using FullyConnectedLayerLeNet5    = FullyConnectedLayer<LeNet5FullyConnectedLayerDataset, CLTensor, CLAccessor, CLFullyConnectedLayer>;
-using FullyConnectedLayerGoogLeNet = FullyConnectedLayer<GoogLeNetFullyConnectedLayerDataset, CLTensor, CLAccessor, CLFullyConnectedLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(FullyConnectedLayerAlexNet, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 2, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(FullyConnectedLayerLeNet5, cl_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FullyConnectedLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5FullyConnectedLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5FullyConnectedLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(FullyConnectedLayerGoogLeNet, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FullyConnectedLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetFullyConnectedLayerDataset, 0, 1, 4, 8>);
diff --git a/tests/benchmark/CL/GEMM.cpp b/tests/benchmark/CL/GEMM.cpp
deleted file mode 100644
index 87dad05f30..0000000000
--- a/tests/benchmark/CL/GEMM.cpp
+++ /dev/null
@@ -1,539 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLGEMM.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/CL/GEMM.h"
-
-namespace
-{
-using GEMMFP16GoogLeNet1 = GEMM<GoogLeNetGEMMDataset1, CLTensor, CLAccessor, CLGEMM, DataType::F16>;
-using GEMMFP16GoogLeNet2 = GEMM<GoogLeNetGEMMDataset2, CLTensor, CLAccessor, CLGEMM, DataType::F16>;
-using GEMMFP32GoogLeNet1 = GEMM<GoogLeNetGEMMDataset1, CLTensor, CLAccessor, CLGEMM, DataType::F32>;
-using GEMMFP32GoogLeNet2 = GEMM<GoogLeNetGEMMDataset2, CLTensor, CLAccessor, CLGEMM, DataType::F32>;
-using FP16MatrixMultiply = GEMM<MatrixMultiplyDataset, CLTensor, CLAccessor, CLGEMM, DataType::F16>;
-using FP32MatrixMultiply = GEMM<MatrixMultiplyDataset, CLTensor, CLAccessor, CLGEMM, DataType::F32>;
-} // namespace
-
-BENCHMARK_DEFINE_F(GEMMFP16GoogLeNet1, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(GEMMFP16GoogLeNet2, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 0>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 1>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 2>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 3>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 4>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 5>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 6>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 7>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 8>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 9>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 10>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 11>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 12>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 13>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 14>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 15>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 16>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 17>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 18>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 19>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 20>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 21>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 22>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 23>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 24>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 25>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 26>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 27>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 28>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 29>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 30>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 31>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 0>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 1>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 2>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 3>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 4>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 5>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 6>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 7>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 8>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 9>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 10>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 11>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 12>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 13>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 14>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 15>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 16>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 17>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 18>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 19>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 20>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 21>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 22>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 23>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 24>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 25>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 26>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 27>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 28>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 29>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 30>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 31>);
-
-BENCHMARK_DEFINE_F(GEMMFP32GoogLeNet1, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(GEMMFP32GoogLeNet2, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 0>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 1>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 2>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 3>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 4>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 5>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 6>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 7>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 8>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 9>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 10>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 11>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 12>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 13>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 14>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 15>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 16>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 17>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 18>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 19>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 20>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 21>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 22>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 23>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 24>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 25>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 26>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 27>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 28>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 29>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 30>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 31>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 0>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 1>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 2>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 3>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 4>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 5>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 6>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 7>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 8>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 9>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 10>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 11>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 12>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 13>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 14>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 15>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 16>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 17>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 18>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 19>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 20>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 21>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 22>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 23>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 24>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 25>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 26>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 27>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 28>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 29>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 30>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 31>);
-
-BENCHMARK_DEFINE_F(FP16MatrixMultiply, cl_matrix_multiply)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 0>);
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 1>);
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 2>);
-
-BENCHMARK_DEFINE_F(FP32MatrixMultiply, cl_matrix_multiply)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 0>);
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 1>);
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, cl_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 2>);
diff --git a/tests/benchmark/CL/GEMM.h b/tests/benchmark/CL/GEMM.h
deleted file mode 100644
index ca3d9ad594..0000000000
--- a/tests/benchmark/CL/GEMM.h
+++ /dev/null
@@ -1,102 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_CL_GEMM_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_CL_GEMM_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/GEMMDataset.h"
-
-#include <memory>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-// FIXME: Merge with NEON/GEMM.h into common/GEMM.h after adding F16 support to NEON GEMM and QS8 support to CL GEMM
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType data_type>
-class GEMM : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        ARM_COMPUTE_ERROR_ON_MSG(data_type != DataType::F16 && data_type != DataType::F32, "Unsupported data type for GEMM operation");
-
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const GEMMDataObject gemm_obj = *(DataSet().begin() + state.range(0));
-
-        TensorShape shape_a = gemm_obj.shape_a;
-        TensorShape shape_b = gemm_obj.shape_b;
-        TensorShape shape_c = gemm_obj.shape_c;
-        TensorShape shape_d = gemm_obj.shape_d;
-
-        // Create tensors
-        a = create_tensor<CLTensor>(shape_a, data_type);
-        b = create_tensor<CLTensor>(shape_b, data_type);
-        c = create_tensor<CLTensor>(shape_c, data_type);
-        d = create_tensor<CLTensor>(shape_d, data_type);
-
-        // Create and configure function
-        gemm_layer = std::unique_ptr<Function>(new Function());
-        gemm_layer->configure(&a, &b, &c, &d, gemm_obj.alpha, gemm_obj.beta);
-
-        // Allocate tensors
-        a.allocator()->allocate();
-        b.allocator()->allocate();
-        c.allocator()->allocate();
-        d.allocator()->allocate();
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        gemm_layer.reset();
-
-        a.allocator()->free();
-        b.allocator()->free();
-        c.allocator()->free();
-        d.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    std::unique_ptr<Function> gemm_layer{ nullptr };
-    Profiler                  profiler{};
-
-private:
-    TensorType a{};
-    TensorType b{};
-    TensorType c{};
-    TensorType d{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_CL_GEMM_H__
diff --git a/tests/benchmark/CL/NormalizationLayer.cpp b/tests/benchmark/CL/NormalizationLayer.cpp
deleted file mode 100644
index 28f89dce1f..0000000000
--- a/tests/benchmark/CL/NormalizationLayer.cpp
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLNormalizationLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/common/NormalizationLayer.h"
-
-namespace
-{
-using NormalizationLayerAlexNet   = NormalizationLayer<AlexNetNormalizationLayerDataset, CLTensor, CLAccessor, CLNormalizationLayer>;
-using NormalizationLayerGoogLeNet = NormalizationLayer<GoogLeNetNormalizationLayerDataset, CLTensor, CLAccessor, CLNormalizationLayer>;
-
-} // namespace
-
-BENCHMARK_DEFINE_F(NormalizationLayerAlexNet, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        norm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(NormalizationLayerGoogLeNet, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        norm_layer->run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(NormalizationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetNormalizationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(NormalizationLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetNormalizationLayerDataset, 1, 1, 4, 8>);
diff --git a/tests/benchmark/CL/PoolingLayer.cpp b/tests/benchmark/CL/PoolingLayer.cpp
deleted file mode 100644
index 05764a412a..0000000000
--- a/tests/benchmark/CL/PoolingLayer.cpp
+++ /dev/null
@@ -1,140 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/common/PoolingLayer.h"
-
-namespace
-{
-using PoolingLayerAlexNet   = PoolingLayer<AlexNetPoolingLayerDataset, CLTensor, CLAccessor, CLPoolingLayer>;
-using PoolingLayerLeNet5    = PoolingLayer<LeNet5PoolingLayerDataset, CLTensor, CLAccessor, CLPoolingLayer>;
-using PoolingLayerGoogLeNet = PoolingLayer<GoogLeNetPoolingLayerDataset, CLTensor, CLAccessor, CLPoolingLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(PoolingLayerAlexNet, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(PoolingLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNet, cl_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 2, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(PoolingLayerLeNet5, cl_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(PoolingLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerLeNet5, cl_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(PoolingLayerGoogLeNet, cl_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-// FIXME: Add support for 7x7 pooling layer pool5/7x7_s1
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, cl_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 9, 1, 4, 8>);
diff --git a/tests/benchmark/CMakeLists.txt b/tests/benchmark/CMakeLists.txt
deleted file mode 100644
index 115333a1b0..0000000000
--- a/tests/benchmark/CMakeLists.txt
+++ /dev/null
@@ -1,100 +0,0 @@
-# Copyright (c) 2017 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.
-cmake_minimum_required (VERSION 3.1)
-
-add_library(benchmark STATIC IMPORTED)
-set_target_properties(benchmark PROPERTIES
-    IMPORTED_LOCATION "${CMAKE_SOURCE_DIR}/../3rdparty/linux/armv7a/libbenchmark.a"
-)
-
-add_library(OpenCL SHARED IMPORTED)
-set_target_properties(OpenCL PROPERTIES
-    IMPORTED_LOCATION "${CMAKE_SOURCE_DIR}/../build/opencl-1.2-stubs/libOpenCL.so"
-    IMPORTED_NO_SONAME 1
-)
-
-option(ENABLE_PMU_COUNTER "Compile with PMU counter support")
-
-set(ARM_COMPUTE_TARGETS_TO_MEASURE "all" CACHE STRING "Semicolon-separated list of targets to include in validation.")
-
-set(ARM_COMPUTE_ALL_TARGETS
-    NEON
-    CL
-)
-
-if(ARM_COMPUTE_TARGETS_TO_MEASURE STREQUAL "all")
-    set(ARM_COMPUTE_TARGETS_TO_MEASURE ${ARM_COMPUTE_ALL_TARGETS})
-endif()
-
-list(REMOVE_DUPLICATES ARM_COMPUTE_TARGETS_TO_MEASURE)
-
-foreach(TARGET ${ARM_COMPUTE_TARGETS_TO_MEASURE})
-    list(FIND ARM_COMPUTE_ALL_TARGETS ${TARGET} idx)
-
-    if(${idx} LESS 0)
-        message(FATAL_ERROR "The target '${TARGET}' does not exist. It should be one of\n${ARM_COMPUTE_ALL_TARGETS}")
-    else()
-        add_subdirectory(${TARGET})
-    endif()
-endforeach()
-
-set(arm_compute_test_benchmark_SOURCE_FILES
-    ${CMAKE_CURRENT_SOURCE_DIR}/main.cpp
-    ${CMAKE_CURRENT_SOURCE_DIR}/Datasets.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/Instrument.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/Profiler.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/Profiler.cpp
-    ${CMAKE_CURRENT_SOURCE_DIR}/PerformanceProgramOptions.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/PerformanceProgramOptions.cpp
-    ${CMAKE_CURRENT_SOURCE_DIR}/PerformanceUserConfiguration.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/PerformanceUserConfiguration.cpp
-    ${CMAKE_CURRENT_SOURCE_DIR}/WallClockTimer.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/WallClockTimer.cpp
-)
-
-if(${ENABLE_PMU_COUNTER})
-    list(APPEND arm_compute_test_benchmark_SOURCE_FILES
-        ${CMAKE_CURRENT_SOURCE_DIR}/PMUCounter.h
-        ${CMAKE_CURRENT_SOURCE_DIR}/PMUCounter.cpp
-    )
-endif()
-
-add_library(arm_compute_test_benchmark OBJECT
-    ${arm_compute_test_benchmark_SOURCE_FILES}
-)
-
-add_definitions(${arm_compute_test_benchmark_TARGET_DEFINITIONS})
-include_directories(${arm_compute_test_benchmark_TARGET_INCLUDES})
-
-add_executable(arm_compute_benchmark
-    $<TARGET_OBJECTS:arm_compute_test_benchmark>
-    ${arm_compute_test_benchmark_TARGET_OBJECTS}
-    $<TARGET_OBJECTS:tensor_library>
-    $<TARGET_OBJECTS:arm_compute_test>
-)
-
-target_link_libraries(arm_compute_benchmark
-    benchmark
-    boost_program_options
-    arm_compute
-    ${arm_compute_test_benchmark_TARGET_LIBRARIES}
-)
diff --git a/tests/benchmark/Datasets.h b/tests/benchmark/Datasets.h
deleted file mode 100644
index cb45b50589..0000000000
--- a/tests/benchmark/Datasets.h
+++ /dev/null
@@ -1,79 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_DATASETS_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_DATASETS_H__
-
-#include "dataset/ActivationLayerDataset.h"
-#include "dataset/BorderModeDataset.h"
-#include "dataset/ConvolutionLayerDataset.h"
-#include "dataset/DataTypeDatasets.h"
-#include "dataset/FullyConnectedLayerDataset.h"
-#include "dataset/GEMMDataset.h"
-#include "dataset/ImageDatasets.h"
-#include "dataset/InterpolationPolicyDataset.h"
-#include "dataset/NormalizationLayerDataset.h"
-#include "dataset/PoolingLayerDataset.h"
-#include "dataset/ShapeDatasets.h"
-
-#include "benchmark/benchmark_api.h"
-
-#include <array>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, int N>
-void DataSetArg(::benchmark::internal::Benchmark *b)
-{
-    b->Arg(N);
-    b->ArgName(std::string(*(DataSet().begin() + N)));
-}
-
-template <typename DataSet, int N, unsigned int... Args>
-void DataSetArgBatched(::benchmark::internal::Benchmark *b)
-{
-    constexpr std::array<unsigned int, sizeof...(Args)> batches{ { Args... } };
-    for(const auto &el : batches)
-    {
-        b->Args({ N, static_cast<int>(el) });
-    }
-    b->ArgNames({ std::string(*(DataSet().begin() + N)), "batch_size" });
-}
-
-template <typename DataSet>
-void DataSetArgs(::benchmark::internal::Benchmark *b)
-{
-    for(size_t i = 0; i < DataSet().size(); ++i)
-    {
-        b->Arg(i);
-        b->ArgName(*(DataSet().begin() + i));
-    }
-}
-}
-}
-}
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_DATASETS_H__ */
diff --git a/tests/benchmark/Instrument.h b/tests/benchmark/Instrument.h
deleted file mode 100644
index 5034471091..0000000000
--- a/tests/benchmark/Instrument.h
+++ /dev/null
@@ -1,107 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_INSTRUMENT_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_INSTRUMENT_H__
-
-#include "Utils.h"
-
-#include <memory>
-#include <string>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-/** Interface for classes that can be used to measure performance. */
-class Instrument
-{
-public:
-    /** Interface defining a measurement, e.g. time, cycles, ... */
-    class IMeasurement
-    {
-    public:
-        IMeasurement()                     = default;
-        IMeasurement(const IMeasurement &) = default;
-        IMeasurement(IMeasurement &&)      = default;
-        IMeasurement &operator=(const IMeasurement &) = default;
-        IMeasurement &operator=(IMeasurement &&) = default;
-        virtual ~IMeasurement()                  = default;
-
-        virtual operator double() const = 0;
-    };
-
-    /** Implementation of a Measurement class for arihtmetic types. */
-    template <typename T>
-    class Measurement : public IMeasurement
-    {
-    public:
-        /** Store the given value as measurement.
-         *
-         * @param[in] value Measured value.
-         */
-        Measurement(T value);
-
-        operator double() const override;
-
-    private:
-        T _value;
-    };
-
-    Instrument()                   = default;
-    Instrument(const Instrument &) = default;
-    Instrument(Instrument &&)      = default;
-    Instrument &operator=(const Instrument &) = default;
-    Instrument &operator=(Instrument &&) = default;
-    virtual ~Instrument()                = default;
-
-    /** Identifier for the instrument */
-    virtual std::string id() const = 0;
-
-    /** Start measuring. */
-    virtual void start() = 0;
-
-    /** Stop measuring. */
-    virtual void stop() = 0;
-
-    /** Return the latest measurement. */
-    virtual std::unique_ptr<IMeasurement> get_measurement() const = 0;
-};
-
-template <typename T>
-Instrument::Measurement<T>::Measurement(T value)
-    : _value{ value }
-{
-}
-
-template <typename T>
-Instrument::Measurement<T>::operator double() const
-{
-    return _value;
-}
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_INSTRUMENT_H__ */
diff --git a/tests/benchmark/NEON/ActivationLayer.cpp b/tests/benchmark/NEON/ActivationLayer.cpp
deleted file mode 100644
index 9ea675e515..0000000000
--- a/tests/benchmark/NEON/ActivationLayer.cpp
+++ /dev/null
@@ -1,238 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/ActivationLayer.h"
-
-namespace
-{
-using ActivationLayerAlexNetF32 = ActivationLayer<AlexNetActivationLayerDataset, Tensor, NEAccessor, NEActivationLayer>;
-using ActivationLayerAlexNetQS8 = ActivationLayer<AlexNetActivationLayerDataset, Tensor, NEAccessor, NEActivationLayer, DataType::QS8>;
-using ActivationLayerLeNet5     = ActivationLayer<LeNet5ActivationLayerDataset, Tensor, NEAccessor, NEActivationLayer, DataType::F32>;
-using ActivationLayerGoogLeNet  = ActivationLayer<GoogLeNetActivationLayerDataset, Tensor, NEAccessor, NEActivationLayer, DataType::F32>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(ActivationLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 4, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(ActivationLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetActivationLayerDataset, 4, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ActivationLayerLeNet5, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ActivationLayerDataset, 0, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ActivationLayerGoogLeNet, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        act_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 16, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 17, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 18, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 19, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 20, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 21, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 22, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 23, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 24, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 25, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 26, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 27, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 28, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 29, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 30, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 31, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ActivationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetActivationLayerDataset, 32, 1, 4, 8>);
diff --git a/tests/benchmark/NEON/BitwiseAnd.cpp b/tests/benchmark/NEON/BitwiseAnd.cpp
deleted file mode 100644
index be68fd39e4..0000000000
--- a/tests/benchmark/NEON/BitwiseAnd.cpp
+++ /dev/null
@@ -1,126 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEBitwiseAnd.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-#include <memory>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-namespace
-{
-template <typename DataSet>
-class BitwiseAnd : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const std::string image_name = *(DataSet().begin() + state.range(0));
-        const RawTensor &raw        = library->get(image_name);
-
-        // Create tensors
-        src1 = create_tensor<Tensor>(raw.shape(), DataType::U8);
-        src2 = create_tensor<Tensor>(raw.shape(), DataType::U8);
-        dst  = create_tensor<Tensor>(raw.shape(), DataType::U8);
-
-        // Create and configure function
-        band.configure(&src1, &src2, &dst);
-
-        // Allocate tensors
-        src1.allocator()->allocate();
-        src2.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill source tensors
-        library->fill(NEAccessor(src1), image_name, Channel::R);
-        library->fill(NEAccessor(src2), image_name, Channel::G);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        profiler.submit(state);
-    }
-
-    NEBitwiseAnd band{};
-    Profiler     profiler{};
-
-private:
-    Tensor src1{};
-    Tensor src2{};
-    Tensor dst{};
-};
-
-using BitwiseAndSmall = BitwiseAnd<SmallImages>;
-using BitwiseAndLarge = BitwiseAnd<LargeImages>;
-} // namespace
-
-BENCHMARK_DEFINE_F(BitwiseAndSmall, neon_bitwise_and)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        band.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(BitwiseAndSmall, neon_bitwise_and)
-->Threads(1)
-->Apply(DataSetArgs<SmallImages>);
-
-BENCHMARK_DEFINE_F(BitwiseAndLarge, neon_bitwise_and)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        band.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(BitwiseAndLarge, neon_bitwise_and)
-->Threads(1)
-->Apply(DataSetArgs<LargeImages>);
diff --git a/tests/benchmark/NEON/CMakeLists.txt b/tests/benchmark/NEON/CMakeLists.txt
deleted file mode 100644
index 2cb3eb36c9..0000000000
--- a/tests/benchmark/NEON/CMakeLists.txt
+++ /dev/null
@@ -1,37 +0,0 @@
-# Copyright (c) 2017 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.
-cmake_minimum_required (VERSION 3.1)
-
-set(arm_compute_test_benchmark_NEON_SOURCE_FILES
-    ${CMAKE_SOURCE_DIR}/NEON/NEAccessor.h
-    ${CMAKE_CURRENT_SOURCE_DIR}/Bitwise/BitwiseAnd.cpp
-)
-
-add_library(arm_compute_test_benchmark_NEON OBJECT
-    ${arm_compute_test_benchmark_NEON_SOURCE_FILES}
-)
-
-SET(arm_compute_test_benchmark_TARGET_OBJECTS
-    ${arm_compute_test_benchmark_TARGET_OBJECTS}
-    $<TARGET_OBJECTS:arm_compute_test_benchmark_NEON>
-    PARENT_SCOPE
-)
diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp
deleted file mode 100644
index a0b1236177..0000000000
--- a/tests/benchmark/NEON/ConvolutionLayer.cpp
+++ /dev/null
@@ -1,302 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/ConvolutionLayer.h"
-
-namespace
-{
-using ConvolutionLayerAlexNetF32 = ConvolutionLayer<AlexNetConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerAlexNetQS8 = ConvolutionLayer<AlexNetConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer, DataType::QS8>;
-using ConvolutionLayerLeNet5     = ConvolutionLayer<LeNet5ConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerGoogLeNet1 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset1, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerGoogLeNet2 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset2, Tensor, NEAccessor, NEConvolutionLayer>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerLeNet5, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 16, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 17, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 18, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 19, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 20, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 21, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 22, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 23, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 24, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 25, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 26, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 27, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 28, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 29, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 30, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 31, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 16, 1, 4, 8>);
diff --git a/tests/benchmark/NEON/ConvolutionLayerDirect.cpp b/tests/benchmark/NEON/ConvolutionLayerDirect.cpp
deleted file mode 100644
index bbe5707e41..0000000000
--- a/tests/benchmark/NEON/ConvolutionLayerDirect.cpp
+++ /dev/null
@@ -1,73 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-#include "dataset/ConvolutionLayerDataset.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/ConvolutionLayer.h"
-
-namespace
-{
-using ConvolutionLayerDirectAlexNet = ConvolutionLayer<AlexNetConvolutionLayerDataset, Tensor, NEAccessor, NEDirectConvolutionLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(ConvolutionLayerDirectAlexNet, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-// Registr only the 3x3 convolution layers
-BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
diff --git a/tests/benchmark/NEON/FullyConnectedLayer.cpp b/tests/benchmark/NEON/FullyConnectedLayer.cpp
deleted file mode 100644
index 15c2a407e6..0000000000
--- a/tests/benchmark/NEON/FullyConnectedLayer.cpp
+++ /dev/null
@@ -1,131 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/FullyConnectedLayer.h"
-
-namespace
-{
-using FullyConnectedLayerAlexNetF32 = FullyConnectedLayer<AlexNetFullyConnectedLayerDataset, Tensor, NEAccessor, NEFullyConnectedLayer>;
-using FullyConnectedLayerAlexNetQS8 = FullyConnectedLayer<AlexNetFullyConnectedLayerDataset, Tensor, NEAccessor, NEFullyConnectedLayer, DataType::QS8>;
-using FullyConnectedLayerLeNet5     = FullyConnectedLayer<LeNet5FullyConnectedLayerDataset, Tensor, NEAccessor, NEFullyConnectedLayer>;
-using FullyConnectedLayerGoogLeNet  = FullyConnectedLayer<GoogLeNetFullyConnectedLayerDataset, Tensor, NEAccessor, NEFullyConnectedLayer>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(FullyConnectedLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 2, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(FullyConnectedLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetFullyConnectedLayerDataset, 2, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(FullyConnectedLayerLeNet5, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        profiler.stop();
-    }
-}
-BENCHMARK_REGISTER_F(FullyConnectedLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5FullyConnectedLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(FullyConnectedLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5FullyConnectedLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(FullyConnectedLayerGoogLeNet, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        fc_layer->run();
-        profiler.stop();
-    }
-}
-BENCHMARK_REGISTER_F(FullyConnectedLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetFullyConnectedLayerDataset, 0, 1, 4, 8>);
diff --git a/tests/benchmark/NEON/GEMM.cpp b/tests/benchmark/NEON/GEMM.cpp
deleted file mode 100644
index 1655c32e2b..0000000000
--- a/tests/benchmark/NEON/GEMM.cpp
+++ /dev/null
@@ -1,777 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/NEON/GEMM.h"
-
-namespace
-{
-#ifdef ENABLE_FP16
-using GEMMFP16GoogLeNet1 = GEMM<GoogLeNetGEMMDataset1, Tensor, NEAccessor, NEGEMM, DataType::F16>;
-using GEMMFP16GoogLeNet2 = GEMM<GoogLeNetGEMMDataset2, Tensor, NEAccessor, NEGEMM, DataType::F16>;
-using FP16MatrixMultiply = GEMM<MatrixMultiplyDataset, Tensor, NEAccessor, NEGEMM, DataType::F16>;
-#endif /* ENABLE_FP16 */
-using GEMMFP32GoogLeNet1 = GEMM<GoogLeNetGEMMDataset1, Tensor, NEAccessor, NEGEMM, DataType::F32>;
-using GEMMFP32GoogLeNet2 = GEMM<GoogLeNetGEMMDataset2, Tensor, NEAccessor, NEGEMM, DataType::F32>;
-using GEMMQS8GoogLeNet1  = GEMM<GoogLeNetGEMMDataset1, Tensor, NEAccessor, NEGEMM, DataType::QS8>;
-using GEMMQS8GoogLeNet2  = GEMM<GoogLeNetGEMMDataset2, Tensor, NEAccessor, NEGEMM, DataType::QS8>;
-using FP32MatrixMultiply = GEMM<MatrixMultiplyDataset, Tensor, NEAccessor, NEGEMM, DataType::F32>;
-using QS8MatrixMultiply  = GEMM<MatrixMultiplyDataset, Tensor, NEAccessor, NEGEMM, DataType::QS8>;
-} // namespace
-#ifdef ENABLE_FP16
-BENCHMARK_DEFINE_F(GEMMFP16GoogLeNet1, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(GEMMFP16GoogLeNet2, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 0>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 1>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 2>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 3>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 4>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 5>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 6>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 7>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 8>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 9>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 10>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 11>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 12>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 13>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 14>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 15>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 16>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 17>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 18>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 19>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 20>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 21>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 22>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 23>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 24>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 25>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 26>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 27>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 28>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 29>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 30>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 31>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 0>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 1>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 2>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 3>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 4>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 5>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 6>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 7>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 8>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 9>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 10>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 11>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 12>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 13>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 14>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 15>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 16>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 17>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 18>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 19>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 20>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 21>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 22>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 23>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 24>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 25>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 26>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 27>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 28>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 29>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 30>);
-BENCHMARK_REGISTER_F(GEMMFP16GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 31>);
-
-BENCHMARK_DEFINE_F(FP16MatrixMultiply, neon_matrix_multiply)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 0>);
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 1>);
-BENCHMARK_REGISTER_F(FP16MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 2>);
-#endif /* ENABLE_FP16 */
-
-BENCHMARK_DEFINE_F(GEMMFP32GoogLeNet1, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(GEMMFP32GoogLeNet2, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 0>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 1>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 2>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 3>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 4>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 5>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 6>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 7>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 8>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 9>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 10>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 11>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 12>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 13>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 14>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 15>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 16>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 17>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 18>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 19>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 20>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 21>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 22>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 23>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 24>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 25>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 26>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 27>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 28>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 29>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 30>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 31>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 0>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 1>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 2>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 3>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 4>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 5>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 6>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 7>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 8>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 9>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 10>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 11>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 12>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 13>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 14>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 15>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 16>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 17>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 18>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 19>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 20>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 21>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 22>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 23>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 24>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 25>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 26>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 27>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 28>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 29>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 30>);
-BENCHMARK_REGISTER_F(GEMMFP32GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 31>);
-
-BENCHMARK_DEFINE_F(GEMMQS8GoogLeNet1, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(GEMMQS8GoogLeNet2, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 0>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 1>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 2>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 3>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 4>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 5>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 6>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 7>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 8>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 9>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 10>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 11>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 12>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 13>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 14>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 15>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 16>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 17>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 18>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 19>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 20>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 21>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 22>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 23>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 24>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 25>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 26>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 27>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 28>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 29>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 30>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset1, 31>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 0>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 1>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 2>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 3>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 4>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 5>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 6>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 7>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 8>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 9>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 10>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 11>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 12>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 13>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 14>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 15>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 16>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 17>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 18>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 19>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 20>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 21>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 22>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 23>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 24>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 25>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 26>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 27>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 28>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 29>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 30>);
-BENCHMARK_REGISTER_F(GEMMQS8GoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArg<GoogLeNetGEMMDataset2, 31>);
-
-BENCHMARK_DEFINE_F(FP32MatrixMultiply, neon_matrix_multiply)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 0>);
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 1>);
-BENCHMARK_REGISTER_F(FP32MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 2>);
-
-BENCHMARK_DEFINE_F(QS8MatrixMultiply, neon_matrix_multiply)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        gemm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(QS8MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 0>);
-BENCHMARK_REGISTER_F(QS8MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 1>);
-BENCHMARK_REGISTER_F(QS8MatrixMultiply, neon_matrix_multiply)
-->Threads(1)
-->Apply(DataSetArg<MatrixMultiplyDataset, 2>);
diff --git a/tests/benchmark/NEON/GEMM.h b/tests/benchmark/NEON/GEMM.h
deleted file mode 100644
index 4f0557d610..0000000000
--- a/tests/benchmark/NEON/GEMM.h
+++ /dev/null
@@ -1,106 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_NEON_GEMM_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_NEON_GEMM_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/GEMMDataset.h"
-
-#include <memory>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-// FIXME: Merge with CL/GEMM.h into common/GEMM.h after adding F16 support to NEON GEMM and QS8 support to CL GEMM
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType data_type>
-class GEMM : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-#ifdef ENABLE_FP16
-        ARM_COMPUTE_ERROR_ON_MSG(data_type != DataType::F16 && data_type != DataType::F32 && data_type != DataType::QS8, "Unsupported data type for GEMM operation");
-#else  /* ENABLE_FP16 */
-        ARM_COMPUTE_ERROR_ON_MSG(data_type != DataType::F32 && data_type != DataType::QS8, "Unsupported data type for GEMM operation");
-#endif /* ENABLE_FP16 */
-
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const GEMMDataObject gemm_obj = *(DataSet().begin() + state.range(0));
-
-        TensorShape shape_a = gemm_obj.shape_a;
-        TensorShape shape_b = gemm_obj.shape_b;
-        TensorShape shape_c = gemm_obj.shape_c;
-        TensorShape shape_d = gemm_obj.shape_d;
-
-        // Create tensors
-        a = create_tensor<Tensor>(shape_a, data_type, 1, 4);
-        b = create_tensor<Tensor>(shape_b, data_type, 1, 4);
-        c = create_tensor<Tensor>(shape_c, data_type, 1, 4);
-        d = create_tensor<Tensor>(shape_d, data_type, 1, 4);
-
-        // Create and configure function
-        gemm_layer = std::unique_ptr<Function>(new Function());
-        gemm_layer->configure(&a, &b, &c, &d, gemm_obj.alpha, gemm_obj.beta);
-
-        // Allocate tensors
-        a.allocator()->allocate();
-        b.allocator()->allocate();
-        c.allocator()->allocate();
-        d.allocator()->allocate();
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        gemm_layer.reset();
-
-        a.allocator()->free();
-        b.allocator()->free();
-        c.allocator()->free();
-        d.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    std::unique_ptr<Function> gemm_layer{ nullptr };
-    Profiler                  profiler{};
-
-private:
-    TensorType a{};
-    TensorType b{};
-    TensorType c{};
-    TensorType d{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_NEON_GEMM_H__
diff --git a/tests/benchmark/NEON/NormalizationLayer.cpp b/tests/benchmark/NEON/NormalizationLayer.cpp
deleted file mode 100644
index 8ea8c95cda..0000000000
--- a/tests/benchmark/NEON/NormalizationLayer.cpp
+++ /dev/null
@@ -1,110 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NENormalizationLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/NormalizationLayer.h"
-
-namespace
-{
-using NormalizationLayerAlexNetF32 = NormalizationLayer<AlexNetNormalizationLayerDataset, Tensor, NEAccessor, NENormalizationLayer>;
-using NormalizationLayerAlexNetQS8 = NormalizationLayer<AlexNetNormalizationLayerDataset, Tensor, NEAccessor, NENormalizationLayer, DataType::QS8>;
-using NormalizationLayerGoogLeNet  = NormalizationLayer<GoogLeNetNormalizationLayerDataset, Tensor, NEAccessor, NENormalizationLayer>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(NormalizationLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        norm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 1, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(NormalizationLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        norm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(NormalizationLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetNormalizationLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(NormalizationLayerGoogLeNet, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        norm_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(NormalizationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetNormalizationLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(NormalizationLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetNormalizationLayerDataset, 1, 1, 4, 8>);
diff --git a/tests/benchmark/NEON/PoolingLayer.cpp b/tests/benchmark/NEON/PoolingLayer.cpp
deleted file mode 100644
index dfa75497cd..0000000000
--- a/tests/benchmark/NEON/PoolingLayer.cpp
+++ /dev/null
@@ -1,161 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/PoolingLayer.h"
-
-namespace
-{
-using PoolingLayerAlexNetF32 = PoolingLayer<AlexNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
-using PoolingLayerAlexNetQS8 = PoolingLayer<AlexNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer, DataType::QS8>;
-using PoolingLayerLeNet5     = PoolingLayer<LeNet5PoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
-using PoolingLayerGoogLeNet  = PoolingLayer<GoogLeNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(PoolingLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 2, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(PoolingLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 2, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(PoolingLayerLeNet5, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(PoolingLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(PoolingLayerGoogLeNet, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        pool_layer.run();
-        profiler.stop();
-    }
-}
-
-// FIXME: Add support for 7x7 pooling layer pool5/7x7_s1
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 9, 1, 4, 8>);
diff --git a/tests/benchmark/PMUCounter.cpp b/tests/benchmark/PMUCounter.cpp
deleted file mode 100644
index 6d59dae65d..0000000000
--- a/tests/benchmark/PMUCounter.cpp
+++ /dev/null
@@ -1,145 +0,0 @@
-/*
- * Copyright (c) 2017 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 "PMUCounter.h"
-
-#include "Utils.h"
-#include "support/ToolchainSupport.h"
-
-#define _GNU_SOURCE 1
-#include <asm/unistd.h>
-#include <csignal>
-#include <cstdio>
-#include <cstdlib>
-#include <cstring>
-#include <fcntl.h>
-#include <linux/hw_breakpoint.h>
-#include <linux/perf_event.h>
-#include <stdexcept>
-#include <sys/ioctl.h>
-#include <unistd.h>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-CycleCounter::CycleCounter()
-{
-    const pid_t pid = getpid();
-
-    struct perf_event_attr perf_config
-    {
-    };
-    memset(&perf_config, 0, sizeof(struct perf_event_attr));
-
-    perf_config.config = PERF_COUNT_HW_CPU_CYCLES;
-    perf_config.size   = sizeof(struct perf_event_attr);
-    perf_config.type   = PERF_TYPE_HARDWARE;
-    // The inherit bit specifies that this counter should count events of child
-    // tasks as well as the task specified
-    perf_config.inherit = 1;
-    // Enables saving of event counts on context switch for inherited tasks
-    perf_config.inherit_stat = 1;
-
-    _fd = syscall(__NR_perf_event_open, &perf_config, pid, -1, -1, 0);
-
-    if(_fd < 0)
-    {
-        throw std::runtime_error("perf_event_open for cycles failed");
-    }
-}
-
-std::string CycleCounter::id() const
-{
-    return "Cycle Counter";
-}
-
-void CycleCounter::start()
-{
-    ioctl(_fd, PERF_EVENT_IOC_RESET, 0);
-    ioctl(_fd, PERF_EVENT_IOC_ENABLE, 0);
-}
-
-void CycleCounter::stop()
-{
-    ioctl(_fd, PERF_EVENT_IOC_DISABLE, 0);
-    read(_fd, &_cycles, sizeof(_cycles));
-}
-
-std::unique_ptr<Instrument::IMeasurement> CycleCounter::get_measurement() const
-{
-    return support::cpp14::make_unique<Instrument::Measurement<long long>>(_cycles);
-}
-
-InstructionCounter::InstructionCounter()
-{
-    const pid_t pid = getpid();
-
-    struct perf_event_attr perf_config
-    {
-    };
-    memset(&perf_config, 0, sizeof(struct perf_event_attr));
-
-    perf_config.config = PERF_COUNT_HW_INSTRUCTIONS;
-    perf_config.size   = sizeof(struct perf_event_attr);
-    perf_config.type   = PERF_TYPE_HARDWARE;
-    // The inherit bit specifies that this counter should count events of child
-    // tasks as well as the task specified
-    perf_config.inherit = 1;
-    // Enables saving of event counts on context switch for inherited tasks
-    perf_config.inherit_stat = 1;
-
-    _fd = syscall(__NR_perf_event_open, &perf_config, pid, -1, -1, 0);
-
-    if(_fd < 0)
-    {
-        throw std::runtime_error("perf_event_open for instructions failed");
-    }
-}
-
-std::string InstructionCounter::id() const
-{
-    return "Instruction Counter";
-}
-
-void InstructionCounter::start()
-{
-    ioctl(_fd, PERF_EVENT_IOC_RESET, 0);
-    ioctl(_fd, PERF_EVENT_IOC_ENABLE, 0);
-}
-
-void InstructionCounter::stop()
-{
-    ioctl(_fd, PERF_EVENT_IOC_DISABLE, 0);
-    read(_fd, &_instructions, sizeof(_instructions));
-}
-
-std::unique_ptr<Instrument::IMeasurement> InstructionCounter::get_measurement() const
-{
-    return std::unique_ptr<Instrument::IMeasurement>(new Instrument::Measurement<long long>(_instructions));
-}
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/benchmark/PMUCounter.h b/tests/benchmark/PMUCounter.h
deleted file mode 100644
index c04b0e5760..0000000000
--- a/tests/benchmark/PMUCounter.h
+++ /dev/null
@@ -1,71 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_PMU_COUNTER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_PMU_COUNTER_H__
-
-#include "Instrument.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-/** Implementation of an instrument to count CPU cycles. */
-class CycleCounter : public Instrument
-{
-public:
-    /** Initialise the cycle counter. */
-    CycleCounter();
-
-    std::string                               id() const override;
-    void                                      start() override;
-    void                                      stop() override;
-    std::unique_ptr<Instrument::IMeasurement> get_measurement() const override;
-
-private:
-    long      _fd{ -1 };
-    long long _cycles{ 0 };
-};
-
-/** Implementation of an instrument to count executed CPU instructions. */
-class InstructionCounter : public Instrument
-{
-public:
-    /** Initialise the instruction counter. */
-    InstructionCounter();
-
-    std::string                               id() const override;
-    void                                      start() override;
-    void                                      stop() override;
-    std::unique_ptr<Instrument::IMeasurement> get_measurement() const override;
-
-private:
-    long      _fd{ -1 };
-    long long _instructions{ 0 };
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_PMU_COUNTER_H__ */
diff --git a/tests/benchmark/PerformanceProgramOptions.cpp b/tests/benchmark/PerformanceProgramOptions.cpp
deleted file mode 100644
index b4becc3c69..0000000000
--- a/tests/benchmark/PerformanceProgramOptions.cpp
+++ /dev/null
@@ -1,48 +0,0 @@
-/*
- * Copyright (c) 2017 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 "PerformanceProgramOptions.h"
-
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Weffc++"
-#pragma GCC diagnostic ignored "-Wnon-virtual-dtor"
-#pragma GCC diagnostic ignored "-Wctor-dtor-privacy"
-#include "boost/program_options.hpp"
-#pragma GCC diagnostic pop
-
-namespace arm_compute
-{
-namespace test
-{
-namespace performance
-{
-PerformanceProgramOptions::PerformanceProgramOptions()
-{
-    boost::program_options::options_description options("Performance options");
-    options.add_options()("runs", boost::program_options::value<unsigned int>()->default_value(1), "Repetitions per test");
-    options.add_options()("threads", boost::program_options::value<unsigned int>()->default_value(1), "Number of parallel CPU threads");
-    add_options(options);
-}
-} // namespace performance
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/benchmark/PerformanceProgramOptions.h b/tests/benchmark/PerformanceProgramOptions.h
deleted file mode 100644
index e9c7a38b3f..0000000000
--- a/tests/benchmark/PerformanceProgramOptions.h
+++ /dev/null
@@ -1,45 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_PERFORMANCE_PROGRAM_OPTIONS_H__
-#define __ARM_COMPUTE_TEST_PERFORMANCE_PROGRAM_OPTIONS_H__
-
-#include "ProgramOptions.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace performance
-{
-/** Subclass of @ref ProgramOptions that adds performance specific options. */
-class PerformanceProgramOptions : public ProgramOptions
-{
-public:
-    /** Defines additonal options. */
-    PerformanceProgramOptions();
-};
-} // namespace performance
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_PERFORMANCE_PROGRAM_OPTIONS_H__ */
diff --git a/tests/benchmark/PerformanceUserConfiguration.cpp b/tests/benchmark/PerformanceUserConfiguration.cpp
deleted file mode 100644
index ca412d660a..0000000000
--- a/tests/benchmark/PerformanceUserConfiguration.cpp
+++ /dev/null
@@ -1,45 +0,0 @@
-/*
- * Copyright (c) 2017 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 "PerformanceUserConfiguration.h"
-
-#include "ProgramOptions.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace performance
-{
-PerformanceUserConfiguration::PerformanceUserConfiguration(const ProgramOptions &options)
-    : UserConfiguration(options)
-{
-    unsigned int tmp_runs = 0;
-    if(options.get("runs", tmp_runs))
-    {
-        runs = tmp_runs;
-    }
-}
-} // namespace performance
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/benchmark/PerformanceUserConfiguration.h b/tests/benchmark/PerformanceUserConfiguration.h
deleted file mode 100644
index daf85a4332..0000000000
--- a/tests/benchmark/PerformanceUserConfiguration.h
+++ /dev/null
@@ -1,57 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_PERFORMANCE_PERFORMANCE_USER_CONFIGURATION_H__
-#define __ARM_COMPUTE_TEST_PERFORMANCE_PERFORMANCE_USER_CONFIGURATION_H__
-
-#include "UserConfiguration.h"
-
-namespace arm_compute
-{
-namespace test
-{
-class ProgramOptions;
-
-namespace performance
-{
-/** Specialisation of @ref UserConfiguration to provide performance specific
- * configuration options.
- */
-struct PerformanceUserConfiguration : public UserConfiguration
-{
-    PerformanceUserConfiguration() = default;
-
-    /** Initialise the configuration according to the program options.
-     *
-     * @param[in] options Parsed command line options.
-     */
-    PerformanceUserConfiguration(const ProgramOptions &options);
-
-    Option<unsigned int> runs{};
-};
-} // namespace performance
-
-extern performance::PerformanceUserConfiguration user_config;
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_PERFORMANCE_PERFORMANCE_USER_CONFIGURATION_H__ */
diff --git a/tests/benchmark/Profiler.cpp b/tests/benchmark/Profiler.cpp
deleted file mode 100644
index f3ce94164f..0000000000
--- a/tests/benchmark/Profiler.cpp
+++ /dev/null
@@ -1,87 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Profiler.h"
-
-#include <iostream>
-#include <utility>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-void Profiler::add(const std::shared_ptr<Instrument> &instrument)
-{
-    _instruments.push_back(instrument);
-}
-
-void Profiler::start()
-{
-    for(auto &instrument : _instruments)
-    {
-        instrument->start();
-    }
-}
-
-void Profiler::stop()
-{
-    for(auto &instrument : _instruments)
-    {
-        instrument->stop();
-    }
-
-    for(const auto &instrument : _instruments)
-    {
-        _measurements[instrument->id()].push_back(*instrument->get_measurement());
-    }
-}
-
-void Profiler::submit(::benchmark::State &state)
-{
-    for(auto &instrument : _measurements)
-    {
-        double sum_values = std::accumulate(instrument.second.begin(), instrument.second.end(), 0.);
-        size_t num_values = instrument.second.size();
-
-        if(num_values > 2)
-        {
-            auto minmax_values                        = std::minmax_element(instrument.second.begin(), instrument.second.end());
-            state.counters[instrument.first + "_min"] = *minmax_values.first;
-            state.counters[instrument.first + "_max"] = *minmax_values.second;
-            sum_values -= *minmax_values.first + *minmax_values.second;
-            num_values -= 2;
-        }
-        state.counters[instrument.first] = sum_values / num_values;
-        instrument.second.clear();
-    }
-}
-
-const Profiler::MeasurementsMap &Profiler::measurements() const
-{
-    return _measurements;
-}
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/benchmark/Profiler.h b/tests/benchmark/Profiler.h
deleted file mode 100644
index f2464949d0..0000000000
--- a/tests/benchmark/Profiler.h
+++ /dev/null
@@ -1,76 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_PROFILER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_PROFILER_H__
-
-#include "Instrument.h"
-
-#include "benchmark/benchmark_api.h"
-
-#include <map>
-#include <memory>
-#include <string>
-#include <vector>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-class Profiler
-{
-public:
-    /** Mapping from instrument ids to their measurements. */
-    using MeasurementsMap = std::map<std::string, std::vector<double>>;
-
-    /** Add @p instrument to the performance montior.
-     *
-     * All added instruments will be used when @ref start or @ref stop are
-     * called to make measurements.
-     *
-     * @param[in] instrument Instrument to be used to measure performance.
-     */
-    void add(const std::shared_ptr<Instrument> &instrument);
-
-    /** Start all added instruments to measure performance. */
-    void start();
-
-    /** Stop all added instruments. */
-    void stop();
-
-    /** Commit all measured values to the current active test. */
-    void submit(::benchmark::State &state);
-
-    /** Return measurements for all instruments. */
-    const MeasurementsMap &measurements() const;
-
-private:
-    std::vector<std::shared_ptr<Instrument>> _instruments{};
-    MeasurementsMap                          _measurements{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_PROFILER_H__ */
diff --git a/tests/benchmark/WallClockTimer.cpp b/tests/benchmark/WallClockTimer.cpp
deleted file mode 100644
index 717fe04b31..0000000000
--- a/tests/benchmark/WallClockTimer.cpp
+++ /dev/null
@@ -1,57 +0,0 @@
-/*
- * Copyright (c) 2017 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 "WallClockTimer.h"
-
-#include "Utils.h"
-#include "support/ToolchainSupport.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-std::string WallClockTimer::id() const
-{
-    return "Wall clock";
-}
-
-void WallClockTimer::start()
-{
-    _start = std::chrono::high_resolution_clock::now();
-}
-
-void WallClockTimer::stop()
-{
-    _stop = std::chrono::high_resolution_clock::now();
-}
-
-std::unique_ptr<Instrument::IMeasurement> WallClockTimer::get_measurement() const
-{
-    const std::chrono::duration<float, std::milli> delta = _stop - _start;
-    return support::cpp14::make_unique<Instrument::Measurement<float>>(delta.count());
-}
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/benchmark/WallClockTimer.h b/tests/benchmark/WallClockTimer.h
deleted file mode 100644
index 85a8b86213..0000000000
--- a/tests/benchmark/WallClockTimer.h
+++ /dev/null
@@ -1,53 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_WALL_CLOCK_TIMER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_WALL_CLOCK_TIMER_H__
-
-#include "Instrument.h"
-
-#include <chrono>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-/** Implementation of an instrument to measure elapsed wall-clock time in milliseconds. */
-class WallClockTimer : public Instrument
-{
-public:
-    std::string                               id() const override;
-    void                                      start() override;
-    void                                      stop() override;
-    std::unique_ptr<Instrument::IMeasurement> get_measurement() const override;
-
-private:
-    std::chrono::high_resolution_clock::time_point _start{};
-    std::chrono::high_resolution_clock::time_point _stop{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_WALL_CLOCK_TIMER_H__ */
diff --git a/tests/benchmark/common/ActivationLayer.h b/tests/benchmark/common/ActivationLayer.h
deleted file mode 100644
index 8e22281025..0000000000
--- a/tests/benchmark/common/ActivationLayer.h
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_ACTIVATION_LAYER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_ACTIVATION_LAYER_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/ActivationLayerDataset.h"
-
-#include <memory>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32>
-class ActivationLayer : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const ActivationLayerDataObject act_obj = *(DataSet().begin() + state.range(0));
-
-        // Set batched in source and destination shapes
-        const unsigned int batches              = state.range(1);
-        const unsigned int fixed_point_position = 4;
-        TensorShape        shape                = act_obj.shape;
-        shape.set(shape.num_dimensions(), batches);
-
-        // Create tensors
-        src = create_tensor<TensorType>(shape, dt, 1, fixed_point_position);
-        dst = create_tensor<TensorType>(shape, dt, 1, fixed_point_position);
-
-        // Create and configure function
-        act_layer.configure(&src, &dst, act_obj.info);
-
-        // Allocate tensors
-        src.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill tensors
-        library->fill_tensor_uniform(Accessor(src), 0);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        src.allocator()->free();
-        dst.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    Function act_layer{};
-    Profiler profiler{};
-
-private:
-    TensorType src{};
-    TensorType dst{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_ACTIVATION_LAYER_H__
diff --git a/tests/benchmark/common/ConvolutionLayer.h b/tests/benchmark/common/ConvolutionLayer.h
deleted file mode 100644
index a777a95bde..0000000000
--- a/tests/benchmark/common/ConvolutionLayer.h
+++ /dev/null
@@ -1,107 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_CONVOLUTION_LAYER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_CONVOLUTION_LAYER_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/ConvolutionLayerDataset.h"
-
-#include <memory>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32>
-class ConvolutionLayer : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const ConvolutionLayerDataObject conv_obj = *(DataSet().begin() + state.range(0));
-
-        // Set batched in source and destination shapes
-        const unsigned int batches              = state.range(1);
-        const unsigned int fixed_point_position = 4;
-        TensorShape        src_shape            = conv_obj.src_shape;
-        TensorShape        dst_shape            = conv_obj.dst_shape;
-        src_shape.set(3 /* batch */, batches);
-        dst_shape.set(3 /* batch */, batches);
-
-        // Create tensors
-        src     = create_tensor<TensorType>(src_shape, dt, 1, fixed_point_position);
-        weights = create_tensor<TensorType>(conv_obj.weights_shape, dt, 1, fixed_point_position);
-        bias    = create_tensor<TensorType>(conv_obj.bias_shape, dt, 1, fixed_point_position);
-        dst     = create_tensor<TensorType>(dst_shape, dt, 1, fixed_point_position);
-
-        // Create and configure function
-        conv_layer = std::unique_ptr<Function>(new Function());
-        conv_layer->configure(&src, &weights, &bias, &dst, conv_obj.info);
-
-        // Allocate tensors
-        src.allocator()->allocate();
-        weights.allocator()->allocate();
-        bias.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill tensors
-        library->fill_tensor_uniform(Accessor(src), 0);
-        library->fill_tensor_uniform(Accessor(weights), 1);
-        library->fill_tensor_uniform(Accessor(bias), 2);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        conv_layer.reset();
-
-        src.allocator()->free();
-        weights.allocator()->free();
-        bias.allocator()->free();
-        dst.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    std::unique_ptr<Function> conv_layer{ nullptr };
-    Profiler                  profiler{};
-
-private:
-    TensorType src{};
-    TensorType weights{};
-    TensorType bias{};
-    TensorType dst{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_CONVOLUTION_LAYER_H__
diff --git a/tests/benchmark/common/FullyConnectedLayer.h b/tests/benchmark/common/FullyConnectedLayer.h
deleted file mode 100644
index eeef1de28a..0000000000
--- a/tests/benchmark/common/FullyConnectedLayer.h
+++ /dev/null
@@ -1,108 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_FULLYCONNECTED_LAYER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_FULLYCONNECTED_LAYER_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/ConvolutionLayerDataset.h"
-
-#include <memory>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32>
-class FullyConnectedLayer : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const FullyConnectedLayerDataObject fc_obj = *(DataSet().begin() + state.range(0));
-
-        // Set batched in source and destination shapes
-        const unsigned int batches              = state.range(1);
-        const unsigned int fixed_point_position = 4;
-        TensorShape        src_shape            = fc_obj.src_shape;
-        TensorShape        dst_shape            = fc_obj.dst_shape;
-        src_shape.set(src_shape.num_dimensions(), batches);
-        dst_shape.set(dst_shape.num_dimensions(), batches);
-
-        // Create tensors
-        src     = create_tensor<TensorType>(src_shape, dt, 1, fixed_point_position);
-        weights = create_tensor<TensorType>(fc_obj.weights_shape, dt, 1, fixed_point_position);
-        bias    = create_tensor<TensorType>(fc_obj.bias_shape, dt, 1, fixed_point_position);
-        dst     = create_tensor<TensorType>(dst_shape, dt, 1, fixed_point_position);
-
-        // Create and configure function
-        fc_layer = std::unique_ptr<Function>(new Function());
-        fc_layer->configure(&src, &weights, &bias, &dst);
-
-        // Allocate tensors
-        src.allocator()->allocate();
-        weights.allocator()->allocate();
-        bias.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill tensors
-        library->fill_tensor_uniform(Accessor(src), 0);
-        library->fill_tensor_uniform(Accessor(weights), 1);
-        library->fill_tensor_uniform(Accessor(bias), 2);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        fc_layer.reset();
-
-        src.allocator()->free();
-        weights.allocator()->free();
-        bias.allocator()->free();
-        dst.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    std::unique_ptr<Function> fc_layer{ nullptr };
-    Profiler                  profiler{};
-
-private:
-    TensorType src{};
-    TensorType weights{};
-    TensorType bias{};
-    TensorType dst{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_FULLYCONNECTED_LAYER_H__
diff --git a/tests/benchmark/common/NormalizationLayer.h b/tests/benchmark/common/NormalizationLayer.h
deleted file mode 100644
index 580dca6c48..0000000000
--- a/tests/benchmark/common/NormalizationLayer.h
+++ /dev/null
@@ -1,96 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_NORMALIZATION_LAYER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_NORMALIZATION_LAYER_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/NormalizationLayerDataset.h"
-
-#include <memory>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32>
-class NormalizationLayer : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const NormalizationLayerDataObject norm_obj = *(DataSet().begin() + state.range(0));
-
-        // Set batched in source and destination shapes
-        const unsigned int batches              = state.range(1);
-        const unsigned int fixed_point_position = 4;
-        TensorShape        shape                = norm_obj.shape;
-        shape.set(shape.num_dimensions(), batches);
-
-        // Create tensors
-        src = create_tensor<TensorType>(shape, dt, 1, fixed_point_position);
-        dst = create_tensor<TensorType>(shape, dt, 1, fixed_point_position);
-
-        // Create and configure function
-        norm_layer = std::unique_ptr<Function>(new Function());
-        norm_layer->configure(&src, &dst, norm_obj.info);
-
-        // Allocate tensors
-        src.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill tensors
-        library->fill_tensor_uniform(Accessor(src), 0);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        norm_layer.reset();
-
-        src.allocator()->free();
-        dst.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    std::unique_ptr<Function> norm_layer{ nullptr };
-    Profiler                  profiler{};
-
-private:
-    TensorType src{};
-    TensorType dst{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_NORMALIZATION_LAYER_H__
diff --git a/tests/benchmark/common/PoolingLayer.h b/tests/benchmark/common/PoolingLayer.h
deleted file mode 100644
index 96ff905568..0000000000
--- a/tests/benchmark/common/PoolingLayer.h
+++ /dev/null
@@ -1,95 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_POOLING_LAYER_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_POOLING_LAYER_H__
-
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "dataset/PoolingLayerDataset.h"
-
-#include <memory>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32>
-class PoolingLayer : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const PoolingLayerDataObject pool_obj = *(DataSet().begin() + state.range(0));
-
-        // Set batched in source and destination shapes
-        const unsigned int batches              = state.range(1);
-        const unsigned int fixed_point_position = 4;
-        TensorShape        src_shape            = pool_obj.src_shape;
-        TensorShape        dst_shape            = pool_obj.dst_shape;
-        src_shape.set(src_shape.num_dimensions(), batches);
-        dst_shape.set(dst_shape.num_dimensions(), batches);
-
-        // Create tensors
-        src = create_tensor<TensorType>(src_shape, dt, 1, fixed_point_position);
-        dst = create_tensor<TensorType>(dst_shape, dt, 1, fixed_point_position);
-
-        // Create and configure function
-        pool_layer.configure(&src, &dst, pool_obj.info);
-
-        // Allocate tensors
-        src.allocator()->allocate();
-        dst.allocator()->allocate();
-
-        // Fill tensors
-        library->fill_tensor_uniform(Accessor(src), 0);
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        // Free allocators
-        src.allocator()->free();
-        dst.allocator()->free();
-
-        profiler.submit(state);
-    }
-
-    Function pool_layer{};
-    Profiler profiler{};
-
-private:
-    TensorType src{};
-    TensorType dst{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_POOLING_LAYER_H__
diff --git a/tests/benchmark/main.cpp b/tests/benchmark/main.cpp
deleted file mode 100644
index 356490960c..0000000000
--- a/tests/benchmark/main.cpp
+++ /dev/null
@@ -1,98 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "PMUCounter.h"
-#include "PerformanceProgramOptions.h"
-#include "PerformanceUserConfiguration.h"
-#include "TensorLibrary.h"
-#include "Utils.h"
-#include "WallClockTimer.h"
-
-#include "benchmark/benchmark_api.h"
-#include "support/ToolchainSupport.h"
-
-#ifdef OPENCL
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#endif /* OPENCL */
-#include "arm_compute/runtime/Scheduler.h"
-
-#include <iostream>
-#include <memory>
-
-using namespace arm_compute::test;
-using namespace arm_compute::test::performance;
-
-namespace arm_compute
-{
-namespace test
-{
-PerformanceUserConfiguration   user_config;
-std::unique_ptr<TensorLibrary> library;
-} // namespace test
-} // namespace arm_compute
-
-int main(int argc, char **argv)
-{
-    PerformanceProgramOptions options;
-    try
-    {
-        options.parse_commandline(argc, argv);
-
-        if(options.wants_help())
-        {
-            std::cout << "Usage: " << argv[0] << " [options] PATH\n";
-            std::cout << options.get_help() << "\n";
-        }
-
-        user_config = PerformanceUserConfiguration(options);
-    }
-    catch(const boost::program_options::required_option &err)
-    {
-        std::cerr << "Error: " << err.what() << "\n";
-        std::cout << "\nUsage: " << argv[0] << " [options] PATH\n";
-        std::cout << options.get_help() << "\n";
-        return 1;
-    }
-
-    ::benchmark::Initialize(&argc, argv);
-
-    if(user_config.seed.is_set())
-    {
-        library = arm_compute::support::cpp14::make_unique<TensorLibrary>(user_config.path.get(), user_config.seed);
-    }
-    else
-    {
-        library = arm_compute::support::cpp14::make_unique<TensorLibrary>(user_config.path.get());
-    }
-
-#ifdef OPENCL
-    arm_compute::CLScheduler::get().default_init();
-#endif /* OPENCL */
-
-    std::cout << "Using " << user_config.threads << " CPU " << (user_config.threads == 1 ? "thread" : "threads") << "\n";
-    std::cout << "Seed: " << library->seed() << "\n";
-    arm_compute::Scheduler::get().set_num_threads(user_config.threads);
-
-    ::benchmark::RunSpecifiedBenchmarks();
-}
diff --git a/tests/benchmark/system_tests/CL/AlexNet.cpp b/tests/benchmark/system_tests/CL/AlexNet.cpp
deleted file mode 100644
index 04b65b8c39..0000000000
--- a/tests/benchmark/system_tests/CL/AlexNet.cpp
+++ /dev/null
@@ -1,86 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLSubTensor.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
-#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
-#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
-#include "arm_compute/runtime/CL/functions/CLNormalizationLayer.h"
-#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
-#include "arm_compute/runtime/CL/functions/CLSoftmaxLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/system_tests/common/AlexNet.h"
-
-namespace
-{
-using AlexNetSystemTest = AlexNetFixture<ICLTensor,
-      CLTensor,
-      CLSubTensor,
-      CLAccessor,
-      CLActivationLayer,
-      CLConvolutionLayer,
-      CLFullyConnectedLayer,
-      CLNormalizationLayer,
-      CLPoolingLayer,
-      CLSoftmaxLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(AlexNetSystemTest, cl_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run AlexNet
-        profiler.start();
-        network.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(AlexNetSystemTest, cl_alexnet)
-->Threads(1)
-->Iterations(10)
-->ArgName("batch_size")
-->Arg(1)
-->Arg(4)
-->Arg(8);
\ No newline at end of file
diff --git a/tests/benchmark/system_tests/CL/LeNet5.cpp b/tests/benchmark/system_tests/CL/LeNet5.cpp
deleted file mode 100644
index 60bb37a35b..0000000000
--- a/tests/benchmark/system_tests/CL/LeNet5.cpp
+++ /dev/null
@@ -1,81 +0,0 @@
-/*
- * Copyright (c) 2017 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 "CL/CLAccessor.h"
-#include "Globals.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
-#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
-#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
-#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
-#include "arm_compute/runtime/CL/functions/CLSoftmaxLayer.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::cl;
-
-#include "benchmark/system_tests/common/LeNet5.h"
-
-namespace
-{
-using LeNet5SystemTest = LeNet5Fixture<CLTensor,
-      CLAccessor,
-      CLActivationLayer,
-      CLConvolutionLayer,
-      CLFullyConnectedLayer,
-      CLPoolingLayer,
-      CLSoftmaxLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(LeNet5SystemTest, cl_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run LeNet5
-        profiler.start();
-        network.run();
-        CLScheduler::get().sync();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(LeNet5SystemTest, cl_lenet5)
-->Threads(1)
-->Iterations(10)
-->ArgName("batch_size")
-->Arg(1)
-->Arg(16)
-->Arg(32);
diff --git a/tests/benchmark/system_tests/NEON/AlexNet.cpp b/tests/benchmark/system_tests/NEON/AlexNet.cpp
deleted file mode 100644
index 530c400ae3..0000000000
--- a/tests/benchmark/system_tests/NEON/AlexNet.cpp
+++ /dev/null
@@ -1,119 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
-#include "arm_compute/runtime/NEON/functions/NENormalizationLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
-#include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"
-#include "arm_compute/runtime/SubTensor.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/system_tests/common/AlexNet.h"
-
-namespace
-{
-using AlexNetSystemTestF32 = AlexNetFixture<ITensor,
-      Tensor,
-      SubTensor,
-      NEAccessor,
-      NEActivationLayer,
-      NEConvolutionLayer,
-      NEFullyConnectedLayer,
-      NENormalizationLayer,
-      NEPoolingLayer,
-      NESoftmaxLayer,
-      DataType::F32>;
-
-using AlexNetSystemTestQS8 = AlexNetFixture<ITensor,
-      Tensor,
-      SubTensor,
-      NEAccessor,
-      NEActivationLayer,
-      NEConvolutionLayer,
-      NEFullyConnectedLayer,
-      NENormalizationLayer,
-      NEPoolingLayer,
-      NESoftmaxLayer,
-      DataType::QS8>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(AlexNetSystemTestF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run AlexNet
-        profiler.start();
-        network.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(AlexNetSystemTestF32, neon_alexnet)
-->Threads(1)
-->Iterations(10)
-->ArgName("batch_size")
-->Arg(1)
-->Arg(4)
-->Arg(8);
-
-// QS8
-BENCHMARK_DEFINE_F(AlexNetSystemTestQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run AlexNet
-        profiler.start();
-        network.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(AlexNetSystemTestQS8, neon_alexnet)
-->Threads(1)
-->Iterations(10)
-->ArgName("batch_size")
-->Arg(1)
-->Arg(4)
-->Arg(8);
\ No newline at end of file
diff --git a/tests/benchmark/system_tests/NEON/LeNet5.cpp b/tests/benchmark/system_tests/NEON/LeNet5.cpp
deleted file mode 100644
index 8724d8ba3a..0000000000
--- a/tests/benchmark/system_tests/NEON/LeNet5.cpp
+++ /dev/null
@@ -1,79 +0,0 @@
-/*
- * Copyright (c) 2017 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
-#include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/system_tests/common/LeNet5.h"
-
-namespace
-{
-using LeNet5SystemTest = LeNet5Fixture<Tensor,
-      NEAccessor,
-      NEActivationLayer,
-      NEConvolutionLayer,
-      NEFullyConnectedLayer,
-      NEPoolingLayer,
-      NESoftmaxLayer>;
-} // namespace
-
-BENCHMARK_DEFINE_F(LeNet5SystemTest, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run LeNet5
-        profiler.start();
-        network.run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(LeNet5SystemTest, neon_lenet5)
-->Threads(1)
-->Iterations(10)
-->ArgName("batch_size")
-->Arg(1)
-->Arg(16)
-->Arg(32);
diff --git a/tests/benchmark/system_tests/common/AlexNet.h b/tests/benchmark/system_tests/common/AlexNet.h
deleted file mode 100644
index 46e26bf723..0000000000
--- a/tests/benchmark/system_tests/common/AlexNet.h
+++ /dev/null
@@ -1,95 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_ALEXNET_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_ALEXNET_H__
-
-#include "tests/TensorLibrary.h"
-#include "tests/Utils.h"
-
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "model_objects/AlexNet.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename ITensorType,
-          typename TensorType,
-          typename SubTensorType,
-          typename Accessor,
-          typename ActivationLayerFunction,
-          typename ConvolutionLayerFunction,
-          typename FullyConnectedLayerFunction,
-          typename NormalizationLayerFunction,
-          typename PoolingLayerFunction,
-          typename SoftmaxLayerFunction,
-          DataType dt = DataType::F32>
-class AlexNetFixture : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        const unsigned int batches            = static_cast<unsigned int>(state.range(0));
-        const bool         weights_transposed = true;
-
-        network.init_weights(batches, weights_transposed);
-        network.build();
-        network.allocate();
-        network.fill_random();
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        profiler.submit(state);
-        network.clear();
-    }
-
-    Profiler profiler{};
-    model_objects::AlexNet<ITensorType,
-                  TensorType,
-                  SubTensorType,
-                  Accessor,
-                  ActivationLayerFunction,
-                  ConvolutionLayerFunction,
-                  FullyConnectedLayerFunction,
-                  NormalizationLayerFunction,
-                  PoolingLayerFunction,
-                  SoftmaxLayerFunction,
-                  dt>
-                  network{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif //__ARM_COMPUTE_TEST_BENCHMARK_ALEXNET_H__
diff --git a/tests/benchmark/system_tests/common/LeNet5.h b/tests/benchmark/system_tests/common/LeNet5.h
deleted file mode 100644
index a2d0cd577c..0000000000
--- a/tests/benchmark/system_tests/common/LeNet5.h
+++ /dev/null
@@ -1,82 +0,0 @@
-/*
- * Copyright (c) 2017 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.
- */
-#ifndef __ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__
-#define __ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__
-
-#include "tests/TensorLibrary.h"
-#include "tests/Utils.h"
-
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "model_objects/LeNet5.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-template <typename TensorType,
-          typename Accessor,
-          typename ActivationLayerFunction,
-          typename ConvolutionLayerFunction,
-          typename FullyConnectedLayerFunction,
-          typename PoolingLayerFunction,
-          typename SoftmaxLayerFunction>
-class LeNet5Fixture : public ::benchmark::Fixture
-{
-public:
-    void SetUp(::benchmark::State &state) override
-    {
-        profiler.add(std::make_shared<WallClockTimer>());
-
-        network.build(static_cast<unsigned int>(state.range(0)));
-        network.fill_random();
-    }
-
-    void TearDown(::benchmark::State &state) override
-    {
-        profiler.submit(state);
-        network.clear();
-    }
-
-    Profiler profiler{};
-    model_objects::LeNet5<TensorType,
-                  Accessor,
-                  ActivationLayerFunction,
-                  ConvolutionLayerFunction,
-                  FullyConnectedLayerFunction,
-                  PoolingLayerFunction,
-                  SoftmaxLayerFunction>
-                  network{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__ */