diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
new file mode 100644
index 0000000..142cbc2
--- /dev/null
+++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
@@ -0,0 +1,139 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ClDepthwiseConvolutionWorkload.hpp"
+
+#include "TypeUtils.hpp"
+#include "ClWorkloadUtils.hpp"
+
+#include <backends/aclCommon/ArmComputeUtils.hpp>
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/cl/ClTensorHandle.hpp>
+#include <backends/CpuTensorHandle.hpp>
+
+#include <arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h>
+
+namespace armnn
+{
+
+using namespace armcomputetensorutils;
+
+arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& input,
+    const TensorInfo& output,
+    const DepthwiseConvolution2dDescriptor& descriptor,
+    const TensorInfo& weights,
+    const Optional<TensorInfo>& biases)
+{
+    const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
+    const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
+    const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
+
+    arm_compute::TensorInfo aclBiasesInfo;
+    arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
+
+    if (descriptor.m_BiasEnabled)
+    {
+        BOOST_ASSERT(biases.has_value());
+
+        aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
+        optionalAclBiasesInfo = &aclBiasesInfo;
+    }
+
+    const arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);
+    const unsigned int aclDepthMultiplier = weights.GetShape()[0];
+
+    return arm_compute::CLDepthwiseConvolutionLayer::validate(&aclInputInfo,
+                                                              &aclWeightsInfo,
+                                                              optionalAclBiasesInfo,
+                                                              &aclOutputInfo,
+                                                              aclPadStrideInfo,
+                                                              aclDepthMultiplier);
+}
+
+ClDepthwiseConvolutionWorkload::ClDepthwiseConvolutionWorkload(
+    const DepthwiseConvolution2dQueueDescriptor& descriptor,
+    const WorkloadInfo& info)
+    : BaseWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info)
+{
+    auto& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+    m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
+    BuildArmComputeTensor(*m_KernelTensor, weightInfo);
+
+    if (m_Data.m_Parameters.m_BiasEnabled)
+    {
+        m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
+        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo());
+    }
+
+    arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
+                                             m_Data.m_Parameters.m_StrideY,
+                                             m_Data.m_Parameters.m_PadLeft,
+                                             m_Data.m_Parameters.m_PadRight,
+                                             m_Data.m_Parameters.m_PadTop,
+                                             m_Data.m_Parameters.m_PadBottom,
+                                             arm_compute::DimensionRoundingType::FLOOR);
+
+    std::string name = std::string("ClDepthwiseConvolutionWorkload");
+    m_Data.ValidateInputsOutputs(name, 1, 1);
+
+    arm_compute::ICLTensor& input  = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    const unsigned int depthMultiplier = weightInfo.GetShape()[0];
+
+    //Check for optimisation opportunities.
+    bool use3x3Optimisation = (weightInfo.GetShape()[3] == 3) && (weightInfo.GetShape()[2] == 3);
+    if (use3x3Optimisation)
+    {
+        m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer3x3>();
+        static_cast<arm_compute::CLDepthwiseConvolutionLayer3x3*>(m_DepthwiseConvolutionLayer.get())->configure(
+            &input,
+            m_KernelTensor.get(),
+            m_BiasTensor.get(),
+            &output,
+            padStrideInfo,
+            depthMultiplier);
+    }
+    else
+    {
+        m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer>();
+        static_cast<arm_compute::CLDepthwiseConvolutionLayer*>(m_DepthwiseConvolutionLayer.get())->configure(
+            &input,
+            m_KernelTensor.get(),
+            m_BiasTensor.get(),
+            &output,
+            padStrideInfo,
+            depthMultiplier);
+    }
+
+    BOOST_ASSERT(m_DepthwiseConvolutionLayer);
+
+    InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
+
+    if (m_BiasTensor)
+    {
+        InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
+    }
+
+    m_DepthwiseConvolutionLayer->prepare();
+    FreeUnusedTensors();
+}
+
+void ClDepthwiseConvolutionWorkload::FreeUnusedTensors()
+{
+    FreeTensorIfUnused(m_KernelTensor);
+    FreeTensorIfUnused(m_BiasTensor);
+}
+
+void ClDepthwiseConvolutionWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_CL("ClDepthwiseConvolutionWorkload_Execute");
+    BOOST_ASSERT(m_DepthwiseConvolutionLayer);
+
+    m_DepthwiseConvolutionLayer->run();
+}
+
+} // namespace armnn