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diff --git a/tests/benchmark/NEON/FullyConnectedLayer.cpp b/tests/benchmark/NEON/FullyConnectedLayer.cpp
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+++ b/tests/benchmark/NEON/FullyConnectedLayer.cpp
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+/*
+ * 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/Helper.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>);