IVGCVSW-2861 Refactor the Reference Elementwise workload

 * Refactor Reference Comparison workload
 * Removed templating based on the DataType
 * Implemented BaseIterator to do decode/encode

Change-Id: I18f299f47ee23772f90152c1146b42f07465e105
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Signed-off-by: Kevin May <kevin.may@arm.com>

13 files changed, 438 insertions, 285 deletions

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index b850a65acf..1360ac5d0c 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -491,13 +491,29 @@ void AdditionQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     ValidateNumInputs(workloadInfo, "AdditionQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "AdditionQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "AdditionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "AdditionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "AdditionQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
                                        "AdditionQueueDescriptor",
                                        "first input",
                                        "second input");
-
 }
 
 //---------------------------------------------------------------
@@ -506,6 +522,23 @@ void MultiplicationQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) c
     ValidateNumInputs(workloadInfo, "MultiplicationQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "MultiplicationQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "MultiplicationQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "MultiplicationQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "MultiplicationQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
@@ -857,6 +890,23 @@ void DivisionQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     ValidateNumInputs(workloadInfo, "DivisionQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "DivisionQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "DivisionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "DivisionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "DivisionQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
@@ -870,6 +920,23 @@ void SubtractionQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) cons
     ValidateNumInputs(workloadInfo, "SubtractionQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "SubtractionQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "SubtractionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "SubtractionQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "SubtractionQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
@@ -883,6 +950,23 @@ void MaximumQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     ValidateNumInputs(workloadInfo, "MaximumQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "MaximumQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "MaximumQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "MaximumQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "MaximumQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
@@ -1008,6 +1092,23 @@ void MinimumQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
     ValidateNumInputs(workloadInfo, "MinimumQueueDescriptor", 2);
     ValidateNumOutputs(workloadInfo, "MinimumQueueDescriptor", 1);
 
+    std::vector<DataType> supportedTypes = {
+        DataType::Float32,
+        DataType::QuantisedAsymm8
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "MinimumQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[1],
+                      supportedTypes,
+                      "MinimumQueueDescriptor");
+
+    ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+                      supportedTypes,
+                      "MinimumQueueDescriptor");
+
     ValidateBroadcastTensorShapesMatch(workloadInfo.m_InputTensorInfos[0],
                                        workloadInfo.m_InputTensorInfos[1],
                                        workloadInfo.m_OutputTensorInfos[0],
diff --git a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
index 3664d56c28..d37cc74c66 100644
--- a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
+++ b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
@@ -312,17 +312,17 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputNumbers)
     AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
 
     // Too few inputs.
-    BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+    BOOST_CHECK_THROW(RefAdditionWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
 
     AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
 
     // Correct.
-    BOOST_CHECK_NO_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo));
+    BOOST_CHECK_NO_THROW(RefAdditionWorkload(invalidData, invalidInfo));
 
     AddInputToWorkload(invalidData, invalidInfo, input3TensorInfo, nullptr);
 
     // Too many inputs.
-    BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+    BOOST_CHECK_THROW(RefAdditionWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
 }
 
 BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
@@ -347,7 +347,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
         AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
         AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
 
-        BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+        BOOST_CHECK_THROW(RefAdditionWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
     }
 
     // Output size not compatible with input sizes.
@@ -364,7 +364,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
         AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
 
         // Output differs.
-        BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+        BOOST_CHECK_THROW(RefAdditionWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
     }
 }
 
@@ -399,7 +399,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension
         AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr);
         AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr);
 
-        BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+        BOOST_CHECK_THROW(RefMultiplicationWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
     }
 
     // Checks dimension consistency for input and output tensors.
@@ -424,7 +424,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension
         AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr);
         AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr);
 
-        BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+        BOOST_CHECK_THROW(RefMultiplicationWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
     }
 }
 
diff --git a/src/backends/reference/RefWorkloadFactory.cpp b/src/backends/reference/RefWorkloadFactory.cpp
index 619c14e007..8ea923d599 100644
--- a/src/backends/reference/RefWorkloadFactory.cpp
+++ b/src/backends/reference/RefWorkloadFactory.cpp
@@ -174,13 +174,13 @@ std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateNormalization(
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateAddition(const AdditionQueueDescriptor& descriptor,
                                                                      const WorkloadInfo&            info) const
 {
-    return MakeWorkload<RefAdditionFloat32Workload, RefAdditionUint8Workload>(descriptor, info);
+    return std::make_unique<RefAdditionWorkload>(descriptor, info);
 }
 
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateMultiplication(
     const MultiplicationQueueDescriptor& descriptor, const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefMultiplicationFloat32Workload, RefMultiplicationUint8Workload>(descriptor, info);
+    return std::make_unique<RefMultiplicationWorkload>(descriptor, info);
 }
 
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateBatchNormalization(
@@ -266,19 +266,19 @@ std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConvertFp32ToFp16(
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateDivision(
     const DivisionQueueDescriptor& descriptor, const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefDivisionFloat32Workload, RefDivisionUint8Workload>(descriptor, info);
+    return std::make_unique<RefDivisionWorkload>(descriptor, info);
 }
 
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateSubtraction(
     const SubtractionQueueDescriptor& descriptor, const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefSubtractionFloat32Workload, RefSubtractionUint8Workload>(descriptor, info);
+    return std::make_unique<RefSubtractionWorkload>(descriptor, info);
 }
 
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateMaximum(
     const MaximumQueueDescriptor& descriptor, const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefMaximumFloat32Workload, RefMaximumUint8Workload>(descriptor, info);
+    return std::make_unique<RefMaximumWorkload>(descriptor, info);
 }
 
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateMean(
@@ -290,7 +290,7 @@ std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateMean(
 std::unique_ptr<armnn::IWorkload> RefWorkloadFactory::CreateMinimum(
     const MinimumQueueDescriptor& descriptor, const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefMinimumFloat32Workload, RefMinimumUint8Workload>(descriptor, info);
+    return std::make_unique<RefMinimumWorkload>(descriptor, info);
 }
 
 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePad(const PadQueueDescriptor& descriptor,
@@ -302,7 +302,7 @@ std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePad(const PadQueueDescripto
 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateEqual(const EqualQueueDescriptor& descriptor,
                                                            const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefEqualFloat32Workload, RefEqualUint8Workload>(descriptor, info);
+    return std::make_unique<RefEqualWorkload>(descriptor, info);
 }
 
 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateBatchToSpaceNd(const BatchToSpaceNdQueueDescriptor& descriptor,
@@ -320,7 +320,7 @@ std::unique_ptr<IWorkload> RefWorkloadFactory::CreateStridedSlice(const StridedS
 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateGreater(const GreaterQueueDescriptor& descriptor,
                                                              const WorkloadInfo& info) const
 {
-    return MakeWorkload<RefGreaterFloat32Workload, RefGreaterUint8Workload>(descriptor, info);
+    return std::make_unique<RefGreaterWorkload>(descriptor, info);
 }
 
 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDebug(const DebugQueueDescriptor& descriptor,
diff --git a/src/backends/reference/test/RefCreateWorkloadTests.cpp b/src/backends/reference/test/RefCreateWorkloadTests.cpp
index 8621122925..09b0246895 100644
--- a/src/backends/reference/test/RefCreateWorkloadTests.cpp
+++ b/src/backends/reference/test/RefCreateWorkloadTests.cpp
@@ -82,7 +82,7 @@ static void RefCreateElementwiseWorkloadTest()
 
 BOOST_AUTO_TEST_CASE(CreateAdditionFloatWorkload)
 {
-    RefCreateElementwiseWorkloadTest<RefAdditionFloat32Workload,
+    RefCreateElementwiseWorkloadTest<RefAdditionWorkload,
         AdditionQueueDescriptor,
         AdditionLayer,
         armnn::DataType::Float32>();
@@ -90,7 +90,7 @@ BOOST_AUTO_TEST_CASE(CreateAdditionFloatWorkload)
 
 BOOST_AUTO_TEST_CASE(CreateAdditionUint8Workload)
 {
-    RefCreateElementwiseWorkloadTest<RefAdditionUint8Workload,
+    RefCreateElementwiseWorkloadTest<RefAdditionWorkload,
         AdditionQueueDescriptor,
         AdditionLayer,
         armnn::DataType::QuantisedAsymm8>();
@@ -98,7 +98,7 @@ BOOST_AUTO_TEST_CASE(CreateAdditionUint8Workload)
 
 BOOST_AUTO_TEST_CASE(CreateSubtractionFloatWorkload)
 {
-    RefCreateElementwiseWorkloadTest<RefSubtractionFloat32Workload,
+    RefCreateElementwiseWorkloadTest<RefSubtractionWorkload,
         SubtractionQueueDescriptor,
         SubtractionLayer,
         armnn::DataType::Float32>();
@@ -106,7 +106,7 @@ BOOST_AUTO_TEST_CASE(CreateSubtractionFloatWorkload)
 
 BOOST_AUTO_TEST_CASE(CreateSubtractionUint8Workload)
 {
-    RefCreateElementwiseWorkloadTest<RefSubtractionUint8Workload,
+    RefCreateElementwiseWorkloadTest<RefSubtractionWorkload,
         SubtractionQueueDescriptor,
         SubtractionLayer,
         armnn::DataType::QuantisedAsymm8>();
@@ -114,7 +114,7 @@ BOOST_AUTO_TEST_CASE(CreateSubtractionUint8Workload)
 
 BOOST_AUTO_TEST_CASE(CreateMultiplicationFloatWorkload)
 {
-    RefCreateElementwiseWorkloadTest<RefMultiplicationFloat32Workload,
+    RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload,
         MultiplicationQueueDescriptor,
         MultiplicationLayer,
         armnn::DataType::Float32>();
@@ -122,7 +122,7 @@ BOOST_AUTO_TEST_CASE(CreateMultiplicationFloatWorkload)
 
 BOOST_AUTO_TEST_CASE(CreateMultiplicationUint8Workload)
 {
-    RefCreateElementwiseWorkloadTest<RefMultiplicationUint8Workload,
+    RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload,
         MultiplicationQueueDescriptor,
         MultiplicationLayer,
         armnn::DataType::QuantisedAsymm8>();
@@ -130,7 +130,7 @@ BOOST_AUTO_TEST_CASE(CreateMultiplicationUint8Workload)
 
 BOOST_AUTO_TEST_CASE(CreateDivisionFloatWorkload)
 {
-    RefCreateElementwiseWorkloadTest<RefDivisionFloat32Workload,
+    RefCreateElementwiseWorkloadTest<RefDivisionWorkload,
         DivisionQueueDescriptor,
         DivisionLayer,
         armnn::DataType::Float32>();
@@ -138,7 +138,7 @@ BOOST_AUTO_TEST_CASE(CreateDivisionFloatWorkload)
 
 BOOST_AUTO_TEST_CASE(CreateDivisionUint8Workload)
 {
-    RefCreateElementwiseWorkloadTest<RefDivisionUint8Workload,
+    RefCreateElementwiseWorkloadTest<RefDivisionWorkload,
         DivisionQueueDescriptor,
         DivisionLayer,
         armnn::DataType::QuantisedAsymm8>();
diff --git a/src/backends/reference/workloads/BaseIterator.hpp b/src/backends/reference/workloads/BaseIterator.hpp
new file mode 100644
index 0000000000..cfa8ce7e91
--- /dev/null
+++ b/src/backends/reference/workloads/BaseIterator.hpp
@@ -0,0 +1,155 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/ArmNN.hpp>
+#include <TypeUtils.hpp>
+
+namespace armnn
+{
+
+class BaseIterator
+{
+public:
+    BaseIterator() {}
+
+    virtual ~BaseIterator() {}
+
+    virtual BaseIterator& operator++() = 0;
+
+    virtual BaseIterator& operator+=(const unsigned int increment) = 0;
+
+    virtual BaseIterator& operator-=(const unsigned int increment) = 0;
+};
+
+class Decoder : public BaseIterator
+{
+public:
+    Decoder() : BaseIterator() {}
+
+    virtual ~Decoder() {}
+
+    virtual float Get() const = 0;
+};
+
+class Encoder : public BaseIterator
+{
+public:
+    Encoder() : BaseIterator() {}
+
+    virtual ~Encoder() {}
+
+    virtual void Set(const float& right) = 0;
+};
+
+class ComparisonEncoder : public BaseIterator
+{
+public:
+    ComparisonEncoder() : BaseIterator() {}
+
+    virtual ~ComparisonEncoder() {}
+
+    virtual void Set(bool right) = 0;
+};
+
+template<typename T, typename Base>
+class TypedIterator : public Base
+{
+public:
+    TypedIterator(T* data)
+        : m_Iterator(data)
+    {}
+
+    TypedIterator& operator++() override
+    {
+        ++m_Iterator;
+        return *this;
+    }
+
+    TypedIterator& operator+=(const unsigned int increment) override
+    {
+        m_Iterator += increment;
+        return *this;
+    }
+
+    TypedIterator& operator-=(const unsigned int increment) override
+    {
+        m_Iterator -= increment;
+        return *this;
+    }
+
+    T* m_Iterator;
+};
+
+class QASymm8Decoder : public TypedIterator<const uint8_t, Decoder>
+{
+public:
+    QASymm8Decoder(const uint8_t* data, const float scale, const int32_t offset)
+        : TypedIterator(data), m_Scale(scale), m_Offset(offset) {}
+
+    float Get() const override
+    {
+        return armnn::Dequantize(*m_Iterator, m_Scale, m_Offset);
+    }
+
+private:
+    const float m_Scale;
+    const int32_t m_Offset;
+};
+
+class FloatDecoder : public TypedIterator<const float, Decoder>
+{
+public:
+    FloatDecoder(const float* data)
+        : TypedIterator(data) {}
+
+    float Get() const override
+    {
+        return *m_Iterator;
+    }
+};
+
+class FloatEncoder : public TypedIterator<float, Encoder>
+{
+public:
+    FloatEncoder(float* data)
+        : TypedIterator(data) {}
+
+    void Set(const float& right) override
+    {
+        *m_Iterator = right;
+    }
+};
+
+class QASymm8Encoder : public TypedIterator<uint8_t, Encoder>
+{
+public:
+    QASymm8Encoder(uint8_t* data, const float scale, const int32_t offset)
+        : TypedIterator(data), m_Scale(scale), m_Offset(offset) {}
+
+    void Set(const float& right) override
+    {
+        *m_Iterator = armnn::Quantize<uint8_t>(right, m_Scale, m_Offset);
+    }
+
+private:
+    const float m_Scale;
+    const int32_t m_Offset;
+};
+
+class BooleanEncoder : public TypedIterator<uint8_t, ComparisonEncoder>
+{
+public:
+    BooleanEncoder(uint8_t* data)
+        : TypedIterator(data) {}
+
+    void Set(bool right) override
+    {
+        *m_Iterator = right;
+    }
+};
+
+} //namespace armnn
\ No newline at end of file
diff --git a/src/backends/reference/workloads/Broadcast.hpp b/src/backends/reference/workloads/Broadcast.hpp
index e92ed0598d..5bf6be8939 100644
--- a/src/backends/reference/workloads/Broadcast.hpp
+++ b/src/backends/reference/workloads/Broadcast.hpp
@@ -3,6 +3,7 @@
 // SPDX-License-Identifier: MIT
 //
 
+#include "BaseIterator.hpp"
 #include <armnn/Tensor.hpp>
 
 #include <functional>
@@ -19,19 +20,23 @@ struct BroadcastLoop
         return static_cast<unsigned int>(m_DimData.size());
     }
 
-    template <typename T0, typename T1, typename U, typename Func>
+    template <typename Func, typename DecoderOp, typename EncoderOp>
     void Unroll(Func operationFunc,
                 unsigned int dimension,
-                const T0* inData0,
-                const T1* inData1,
-                U* outData)
+                DecoderOp& inData0,
+                DecoderOp& inData1,
+                EncoderOp& outData)
     {
         if (dimension >= GetNumDimensions())
         {
-            *outData = operationFunc(*inData0, *inData1);
+            outData.Set(operationFunc(inData0.Get(), inData1.Get()));
             return;
         }
 
+        unsigned int inData0Movement = 0;
+        unsigned int inData1Movement = 0;
+        unsigned int outDataMovement = 0;
+
         for (unsigned int i = 0; i < m_DimData[dimension].m_DimSize; i++)
         {
             Unroll(operationFunc, dimension + 1, inData0, inData1, outData);
@@ -39,7 +44,16 @@ struct BroadcastLoop
             inData0 += m_DimData[dimension].m_Stride1;
             inData1 += m_DimData[dimension].m_Stride2;
             outData += m_DimData[dimension].m_StrideOut;
+
+            inData0Movement += m_DimData[dimension].m_Stride1;
+            inData1Movement += m_DimData[dimension].m_Stride2;
+            outDataMovement += m_DimData[dimension].m_StrideOut;
         }
+
+        // move iterator back to the start
+        inData0 -= inData0Movement;
+        inData1 -= inData1Movement;
+        outData -= outDataMovement;
     }
 
 private:
diff --git a/src/backends/reference/workloads/CMakeLists.txt b/src/backends/reference/workloads/CMakeLists.txt
index 4f5fbb554e..4ff2466e87 100644
--- a/src/backends/reference/workloads/CMakeLists.txt
+++ b/src/backends/reference/workloads/CMakeLists.txt
@@ -6,6 +6,7 @@
 list(APPEND armnnRefBackendWorkloads_sources
     Activation.cpp
     Activation.hpp
+    BaseIterator.hpp
     BatchNormImpl.hpp
     BatchToSpaceNd.cpp
     BatchToSpaceNd.hpp
diff --git a/src/backends/reference/workloads/ElementwiseFunction.cpp b/src/backends/reference/workloads/ElementwiseFunction.cpp
index c8c25ef9e9..934a86217a 100644
--- a/src/backends/reference/workloads/ElementwiseFunction.cpp
+++ b/src/backends/reference/workloads/ElementwiseFunction.cpp
@@ -13,26 +13,26 @@
 namespace armnn
 {
 
-template <typename Functor, typename dataTypeInput, typename dataTypeOutput>
-ElementwiseFunction<Functor, dataTypeInput, dataTypeOutput>::ElementwiseFunction(const TensorShape& inShape0,
-                                                                                 const TensorShape& inShape1,
-                                                                                 const TensorShape& outShape,
-                                                                                 const dataTypeInput* inData0,
-                                                                                 const dataTypeInput* inData1,
-                                                                                 dataTypeOutput* outData)
+template <typename Functor, typename DecoderOp, typename EncoderOp>
+ElementwiseFunction<Functor, DecoderOp, EncoderOp>::ElementwiseFunction(const TensorShape& inShape0,
+                                                                        const TensorShape& inShape1,
+                                                                        const TensorShape& outShape,
+                                                                        DecoderOp& inData0,
+                                                                        DecoderOp& inData1,
+                                                                        EncoderOp& outData)
 {
     BroadcastLoop(inShape0, inShape1, outShape).Unroll(Functor(), 0, inData0, inData1, outData);
 }
 
 } //namespace armnn
 
-template struct armnn::ElementwiseFunction<std::plus<float>, float, float>;
-template struct armnn::ElementwiseFunction<std::minus<float>, float, float>;
-template struct armnn::ElementwiseFunction<std::multiplies<float>, float, float>;
-template struct armnn::ElementwiseFunction<std::divides<float>, float, float>;
-template struct armnn::ElementwiseFunction<armnn::maximum<float>, float, float>;
-template struct armnn::ElementwiseFunction<armnn::minimum<float>, float, float>;
-template struct armnn::ElementwiseFunction<std::equal_to<float>, float ,uint8_t>;
-template struct armnn::ElementwiseFunction<std::equal_to<uint8_t>, uint8_t, uint8_t>;
-template struct armnn::ElementwiseFunction<std::greater<float>, float, uint8_t>;
-template struct armnn::ElementwiseFunction<std::greater<uint8_t>, uint8_t, uint8_t>;
+template struct armnn::ElementwiseFunction<std::plus<float>, armnn::Decoder, armnn::Encoder>;
+template struct armnn::ElementwiseFunction<std::minus<float>, armnn::Decoder, armnn::Encoder>;
+template struct armnn::ElementwiseFunction<std::multiplies<float>, armnn::Decoder, armnn::Encoder>;
+template struct armnn::ElementwiseFunction<std::divides<float>, armnn::Decoder, armnn::Encoder>;
+template struct armnn::ElementwiseFunction<armnn::maximum<float>, armnn::Decoder, armnn::Encoder>;
+template struct armnn::ElementwiseFunction<armnn::minimum<float>, armnn::Decoder, armnn::Encoder>;
+
+template struct armnn::ElementwiseFunction<std::equal_to<float>, armnn::Decoder, armnn::ComparisonEncoder>;
+template struct armnn::ElementwiseFunction<std::greater<float>, armnn::Decoder, armnn::ComparisonEncoder>;
+
diff --git a/src/backends/reference/workloads/ElementwiseFunction.hpp b/src/backends/reference/workloads/ElementwiseFunction.hpp
index 8099f3279a..9eb003d5f9 100644
--- a/src/backends/reference/workloads/ElementwiseFunction.hpp
+++ b/src/backends/reference/workloads/ElementwiseFunction.hpp
@@ -5,20 +5,21 @@
 
 #pragma once
 
+#include "BaseIterator.hpp"
 #include <armnn/Tensor.hpp>
 
 namespace armnn
 {
 
-template <typename Functor, typename dataTypeInput, typename dataTypeOutput>
+template <typename Functor, typename DecoderOp, typename EncoderOp>
 struct ElementwiseFunction
 {
     ElementwiseFunction(const TensorShape& inShape0,
                         const TensorShape& inShape1,
                         const TensorShape& outShape,
-                        const dataTypeInput* inData0,
-                        const dataTypeInput* inData1,
-                        dataTypeOutput* outData);
+                        DecoderOp& inData0,
+                        DecoderOp& inData1,
+                        EncoderOp& outData);
 };
 
 } //namespace armnn
diff --git a/src/backends/reference/workloads/RefComparisonWorkload.cpp b/src/backends/reference/workloads/RefComparisonWorkload.cpp
index fe517ff51a..bb8bb04ad3 100644
--- a/src/backends/reference/workloads/RefComparisonWorkload.cpp
+++ b/src/backends/reference/workloads/RefComparisonWorkload.cpp
@@ -11,55 +11,66 @@
 
 namespace armnn {
 
-template<typename ParentDescriptor, typename Functor>
-void RefFloat32ComparisonWorkload<ParentDescriptor, Functor>::ExecuteImpl(const char* debugString) const
+template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
+void RefComparisonWorkload<Functor, ParentDescriptor, DebugString>::Execute() const
 {
-    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, debugString);
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, StringMapping::Instance().Get(DebugString));
+    const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
+    const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
+    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
 
-    auto data = BaseFloat32ComparisonWorkload<ParentDescriptor>::GetData();
-    const TensorShape& inShape0 = GetTensorInfo(data.m_Inputs[0]).GetShape();
-    const TensorShape& inShape1 = GetTensorInfo(data.m_Inputs[1]).GetShape();
-    const TensorShape& outputShape = GetTensorInfo(data.m_Outputs[0]).GetShape();
+    const TensorShape& inShape0 = inputInfo0.GetShape();
+    const TensorShape& inShape1 = inputInfo1.GetShape();
+    const TensorShape& outShape = outputInfo.GetShape();
 
-    const float* inData0 = GetInputTensorDataFloat(0, data);
-    const float* inData1 = GetInputTensorDataFloat(1, data);
-    uint8_t* outData = GetOutputTensorData<uint8_t>(0, data);
+    switch(inputInfo0.GetDataType())
+    {
+        case armnn::DataType::QuantisedAsymm8:
+        {
+            QASymm8Decoder decodeIterator0(GetInputTensorDataU8(0, m_Data),
+                                           inputInfo0.GetQuantizationScale(),
+                                           inputInfo0.GetQuantizationOffset());
 
-    ElementwiseFunction<Functor, float, uint8_t>(inShape0,
-                                                 inShape1,
-                                                 outputShape,
-                                                 inData0,
-                                                 inData1,
-                                                 outData);
+            QASymm8Decoder decodeIterator1(GetInputTensorDataU8(1, m_Data),
+                                           inputInfo1.GetQuantizationScale(),
+                                           inputInfo1.GetQuantizationOffset());
 
-}
-
-template<typename ParentDescriptor, typename Functor>
-void RefUint8ComparisonWorkload<ParentDescriptor, Functor>::ExecuteImpl(const char* debugString) const
-{
-    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, debugString);
-
-    auto data = BaseUint8ComparisonWorkload<ParentDescriptor>::GetData();
-    const TensorShape& inputInfo0 = GetTensorInfo(data.m_Inputs[0]).GetShape();
-    const TensorShape& inputInfo1 = GetTensorInfo(data.m_Inputs[1]).GetShape();
-    const TensorShape& outputShape = GetTensorInfo(data.m_Outputs[0]).GetShape();
+            BooleanEncoder encodeIterator0(GetOutputTensorDataU8(0, m_Data));
 
-    const uint8_t* inData0 = GetInputTensorData<uint8_t>(0, data);
-    const uint8_t* inData1 = GetInputTensorData<uint8_t>(1, data);
-    uint8_t* outData = GetOutputTensorData<uint8_t>(0, data);
+            ElementwiseFunction<Functor, Decoder, ComparisonEncoder>(inShape0,
+                                                                     inShape1,
+                                                                     outShape,
+                                                                     decodeIterator0,
+                                                                     decodeIterator1,
+                                                                     encodeIterator0);
+            break;
+        }
+        case armnn::DataType::Float32:
+        {
+            FloatDecoder decodeIterator0(GetInputTensorDataFloat(0, m_Data));
+            FloatDecoder decodeIterator1(GetInputTensorDataFloat(1, m_Data));
+            BooleanEncoder encodeIterator0(GetOutputTensorDataU8(0, m_Data));
 
-    ElementwiseFunction<Functor, uint8_t, uint8_t>(inputInfo0,
-                                                   inputInfo1,
-                                                   outputShape,
-                                                   inData0,
-                                                   inData1,
-                                                   outData);
+            ElementwiseFunction<Functor, Decoder, ComparisonEncoder>(inShape0,
+                                                                     inShape1,
+                                                                     outShape,
+                                                                     decodeIterator0,
+                                                                     decodeIterator1,
+                                                                     encodeIterator0);
+            break;
+        }
+        default:
+            BOOST_ASSERT_MSG(false, "RefComparisonWorkload: Not supported Data Type!");
+            break;
+    }
 }
 
 }
 
-template class armnn::RefFloat32ComparisonWorkload<armnn::EqualQueueDescriptor, std::equal_to<float>>;
-template class armnn::RefUint8ComparisonWorkload<armnn::EqualQueueDescriptor, std::equal_to<uint8_t>>;
+template class armnn::RefComparisonWorkload<std::equal_to<float>,
+                                           armnn::EqualQueueDescriptor,
+                                           armnn::StringMapping::RefEqualWorkload_Execute>;
 
-template class armnn::RefFloat32ComparisonWorkload<armnn::GreaterQueueDescriptor, std::greater<float>>;
-template class armnn::RefUint8ComparisonWorkload<armnn::GreaterQueueDescriptor, std::greater<uint8_t>>;
+template class armnn::RefComparisonWorkload<std::greater<float>,
+                                           armnn::GreaterQueueDescriptor,
+                                           armnn::StringMapping::RefGreaterWorkload_Execute>;
diff --git a/src/backends/reference/workloads/RefComparisonWorkload.hpp b/src/backends/reference/workloads/RefComparisonWorkload.hpp
index 524d20625a..cfc2dcf2aa 100644
--- a/src/backends/reference/workloads/RefComparisonWorkload.hpp
+++ b/src/backends/reference/workloads/RefComparisonWorkload.hpp
@@ -13,80 +13,24 @@
 namespace armnn
 {
 
-template <typename Functor,
-          typename armnn::DataType DataType,
-          typename ParentDescriptor,
-          typename armnn::StringMapping::Id DebugString>
-class RefComparisonWorkload
-{
-    // Needs specialization. The default is empty on purpose.
-};
-
-template <typename ParentDescriptor, typename Functor>
-class RefFloat32ComparisonWorkload : public BaseFloat32ComparisonWorkload<ParentDescriptor>
-{
-public:
-    using BaseFloat32ComparisonWorkload<ParentDescriptor>::BaseFloat32ComparisonWorkload;
-    void ExecuteImpl(const char * debugString) const;
-};
-
-template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
-class RefComparisonWorkload<Functor, armnn::DataType::Float32, ParentDescriptor, DebugString>
-    : public RefFloat32ComparisonWorkload<ParentDescriptor, Functor>
-{
-public:
-    using RefFloat32ComparisonWorkload<ParentDescriptor, Functor>::RefFloat32ComparisonWorkload;
-
-    virtual void Execute() const override
-    {
-        using Parent = RefFloat32ComparisonWorkload<ParentDescriptor, Functor>;
-        Parent::ExecuteImpl(StringMapping::Instance().Get(DebugString));
-    }
-};
-
-template <typename ParentDescriptor, typename Functor>
-class RefUint8ComparisonWorkload : public BaseUint8ComparisonWorkload<ParentDescriptor>
-{
-public:
-    using BaseUint8ComparisonWorkload<ParentDescriptor>::BaseUint8ComparisonWorkload;
-    void ExecuteImpl(const char * debugString) const;
-};
-
 template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
-class RefComparisonWorkload<Functor, armnn::DataType::QuantisedAsymm8, ParentDescriptor, DebugString>
-    : public RefUint8ComparisonWorkload<ParentDescriptor, Functor>
+class RefComparisonWorkload : public BaseWorkload<ParentDescriptor>
 {
 public:
-    using RefUint8ComparisonWorkload<ParentDescriptor, Functor>::RefUint8ComparisonWorkload;
+    using BaseWorkload<ParentDescriptor>::m_Data;
+    using BaseWorkload<ParentDescriptor>::BaseWorkload;
 
-    virtual void Execute() const override
-    {
-        using Parent = RefUint8ComparisonWorkload<ParentDescriptor, Functor>;
-        Parent::ExecuteImpl(StringMapping::Instance().Get(DebugString));
-    }
+    void Execute() const override;
 };
 
-using RefEqualFloat32Workload =
+using RefEqualWorkload =
     RefComparisonWorkload<std::equal_to<float>,
-                          DataType::Float32,
-                          EqualQueueDescriptor,
-                          StringMapping::RefEqualWorkload_Execute>;
+                         EqualQueueDescriptor,
+                         StringMapping::RefEqualWorkload_Execute>;
 
-using RefEqualUint8Workload =
-    RefComparisonWorkload<std::equal_to<uint8_t>,
-                          DataType::QuantisedAsymm8,
-                          EqualQueueDescriptor,
-                          StringMapping::RefEqualWorkload_Execute>;
 
-using RefGreaterFloat32Workload =
+using RefGreaterWorkload =
     RefComparisonWorkload<std::greater<float>,
-                          DataType::Float32,
-                          GreaterQueueDescriptor,
-                          StringMapping::RefGreaterWorkload_Execute>;
-
-using RefGreaterUint8Workload =
-    RefComparisonWorkload<std::greater<uint8_t>,
-                          DataType::QuantisedAsymm8,
-                          GreaterQueueDescriptor,
-                          StringMapping::RefGreaterWorkload_Execute>;
+                         GreaterQueueDescriptor,
+                         StringMapping::RefGreaterWorkload_Execute>;
 } // armnn
diff --git a/src/backends/reference/workloads/RefElementwiseWorkload.cpp b/src/backends/reference/workloads/RefElementwiseWorkload.cpp
index 356d7a0c16..6e6e1d5f21 100644
--- a/src/backends/reference/workloads/RefElementwiseWorkload.cpp
+++ b/src/backends/reference/workloads/RefElementwiseWorkload.cpp
@@ -14,14 +14,10 @@
 namespace armnn
 {
 
-template <typename Functor,
-          typename armnn::DataType DataType,
-          typename ParentDescriptor,
-          typename armnn::StringMapping::Id DebugString>
-void RefElementwiseWorkload<Functor, DataType, ParentDescriptor, DebugString>::Execute() const
+template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
+void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::Execute() const
 {
     ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, StringMapping::Instance().Get(DebugString));
-
     const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
     const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
     const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
@@ -30,32 +26,46 @@ void RefElementwiseWorkload<Functor, DataType, ParentDescriptor, DebugString>::E
     const TensorShape& inShape1 = inputInfo1.GetShape();
     const TensorShape& outShape = outputInfo.GetShape();
 
-    switch(DataType)
+    switch(inputInfo0.GetDataType())
     {
         case armnn::DataType::QuantisedAsymm8:
         {
-            std::vector<float> results(outputInfo.GetNumElements());
-            ElementwiseFunction<Functor, float, float>(inShape0,
-                                                       inShape1,
-                                                       outShape,
-                                                       Dequantize(GetInputTensorDataU8(0, m_Data), inputInfo0).data(),
-                                                       Dequantize(GetInputTensorDataU8(1, m_Data), inputInfo1).data(),
-                                                       results.data());
-            Quantize(GetOutputTensorDataU8(0, m_Data), results.data(), outputInfo);
+            QASymm8Decoder decodeIterator0(GetInputTensorDataU8(0, m_Data),
+                                           inputInfo0.GetQuantizationScale(),
+                                           inputInfo0.GetQuantizationOffset());
+
+            QASymm8Decoder decodeIterator1(GetInputTensorDataU8(1, m_Data),
+                                           inputInfo1.GetQuantizationScale(),
+                                           inputInfo1.GetQuantizationOffset());
+
+            QASymm8Encoder encodeIterator0(GetOutputTensorDataU8(0, m_Data),
+                                           outputInfo.GetQuantizationScale(),
+                                           outputInfo.GetQuantizationOffset());
+
+            ElementwiseFunction<Functor, Decoder, Encoder>(inShape0,
+                                                           inShape1,
+                                                           outShape,
+                                                           decodeIterator0,
+                                                           decodeIterator1,
+                                                           encodeIterator0);
             break;
         }
         case armnn::DataType::Float32:
         {
-            ElementwiseFunction<Functor, float, float>(inShape0,
-                                                       inShape1,
-                                                       outShape,
-                                                       GetInputTensorDataFloat(0, m_Data),
-                                                       GetInputTensorDataFloat(1, m_Data),
-                                                       GetOutputTensorDataFloat(0, m_Data));
+            FloatDecoder decodeIterator0(GetInputTensorDataFloat(0, m_Data));
+            FloatDecoder decodeIterator1(GetInputTensorDataFloat(1, m_Data));
+            FloatEncoder encodeIterator0(GetOutputTensorDataFloat(0, m_Data));
+
+            ElementwiseFunction<Functor, Decoder, Encoder>(inShape0,
+                                                           inShape1,
+                                                           outShape,
+                                                           decodeIterator0,
+                                                           decodeIterator1,
+                                                           encodeIterator0);
             break;
         }
         default:
-            BOOST_ASSERT_MSG(false, "Unknown Data Type!");
+            BOOST_ASSERT_MSG(false, "RefElementwiseWorkload: Not supported Data Type!");
             break;
     }
 }
@@ -63,62 +73,25 @@ void RefElementwiseWorkload<Functor, DataType, ParentDescriptor, DebugString>::E
 }
 
 template class armnn::RefElementwiseWorkload<std::plus<float>,
-    armnn::DataType::Float32,
-    armnn::AdditionQueueDescriptor,
-    armnn::StringMapping::RefAdditionWorkload_Execute>;
-
-template class armnn::RefElementwiseWorkload<std::plus<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::AdditionQueueDescriptor,
-    armnn::StringMapping::RefAdditionWorkload_Execute>;
+                                            armnn::AdditionQueueDescriptor,
+                                            armnn::StringMapping::RefAdditionWorkload_Execute>;
 
 template class armnn::RefElementwiseWorkload<std::minus<float>,
-    armnn::DataType::Float32,
-    armnn::SubtractionQueueDescriptor,
-    armnn::StringMapping::RefSubtractionWorkload_Execute>;
-
-template class armnn::RefElementwiseWorkload<std::minus<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::SubtractionQueueDescriptor,
-    armnn::StringMapping::RefSubtractionWorkload_Execute>;
-
-template class armnn::RefElementwiseWorkload<std::multiplies<float>,
-    armnn::DataType::Float32,
-    armnn::MultiplicationQueueDescriptor,
-    armnn::StringMapping::RefMultiplicationWorkload_Execute>;
+                                            armnn::SubtractionQueueDescriptor,
+                                            armnn::StringMapping::RefSubtractionWorkload_Execute>;
 
 template class armnn::RefElementwiseWorkload<std::multiplies<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::MultiplicationQueueDescriptor,
-    armnn::StringMapping::RefMultiplicationWorkload_Execute>;
+                                            armnn::MultiplicationQueueDescriptor,
+                                            armnn::StringMapping::RefMultiplicationWorkload_Execute>;
 
 template class armnn::RefElementwiseWorkload<std::divides<float>,
-    armnn::DataType::Float32,
-    armnn::DivisionQueueDescriptor,
-    armnn::StringMapping::RefDivisionWorkload_Execute>;
-
-template class armnn::RefElementwiseWorkload<std::divides<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::DivisionQueueDescriptor,
-    armnn::StringMapping::RefDivisionWorkload_Execute>;
-
-template class armnn::RefElementwiseWorkload<armnn::maximum<float>,
-    armnn::DataType::Float32,
-    armnn::MaximumQueueDescriptor,
-    armnn::StringMapping::RefMaximumWorkload_Execute>;
+                                            armnn::DivisionQueueDescriptor,
+                                            armnn::StringMapping::RefDivisionWorkload_Execute>;
 
 template class armnn::RefElementwiseWorkload<armnn::maximum<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::MaximumQueueDescriptor,
-    armnn::StringMapping::RefMaximumWorkload_Execute>;
-
-
-template class armnn::RefElementwiseWorkload<armnn::minimum<float>,
-    armnn::DataType::Float32,
-    armnn::MinimumQueueDescriptor,
-    armnn::StringMapping::RefMinimumWorkload_Execute>;
+                                            armnn::MaximumQueueDescriptor,
+                                            armnn::StringMapping::RefMaximumWorkload_Execute>;
 
 template class armnn::RefElementwiseWorkload<armnn::minimum<float>,
-    armnn::DataType::QuantisedAsymm8,
-    armnn::MinimumQueueDescriptor,
-    armnn::StringMapping::RefMinimumWorkload_Execute>;
+                                            armnn::MinimumQueueDescriptor,
+                                            armnn::StringMapping::RefMinimumWorkload_Execute>;
\ No newline at end of file
diff --git a/src/backends/reference/workloads/RefElementwiseWorkload.hpp b/src/backends/reference/workloads/RefElementwiseWorkload.hpp
index 371904977a..81af19627e 100644
--- a/src/backends/reference/workloads/RefElementwiseWorkload.hpp
+++ b/src/backends/reference/workloads/RefElementwiseWorkload.hpp
@@ -15,90 +15,43 @@
 namespace armnn
 {
 
-template <typename Functor,
-          typename armnn::DataType DataType,
-          typename ParentDescriptor,
-          typename armnn::StringMapping::Id DebugString>
-class RefElementwiseWorkload
-    : public TypedWorkload<ParentDescriptor, DataType>
+template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
+class RefElementwiseWorkload : public BaseWorkload<ParentDescriptor>
 {
 public:
-
-    using TypedWorkload<ParentDescriptor, DataType>::m_Data;
-    using TypedWorkload<ParentDescriptor, DataType>::TypedWorkload;
+    using BaseWorkload<ParentDescriptor>::m_Data;
+    using BaseWorkload<ParentDescriptor>::BaseWorkload;
 
     void Execute() const override;
 };
 
-using RefAdditionFloat32Workload =
-    RefElementwiseWorkload<std::plus<float>,
-                          DataType::Float32,
-                          AdditionQueueDescriptor,
-                          StringMapping::RefAdditionWorkload_Execute>;
-
-using RefAdditionUint8Workload =
+using RefAdditionWorkload =
     RefElementwiseWorkload<std::plus<float>,
-                          DataType::QuantisedAsymm8,
                           AdditionQueueDescriptor,
                           StringMapping::RefAdditionWorkload_Execute>;
 
-using RefSubtractionFloat32Workload =
-    RefElementwiseWorkload<std::minus<float>,
-                          DataType::Float32,
-                          SubtractionQueueDescriptor,
-                          StringMapping::RefSubtractionWorkload_Execute>;
-
-using RefSubtractionUint8Workload =
+using RefSubtractionWorkload =
     RefElementwiseWorkload<std::minus<float>,
-                          DataType::QuantisedAsymm8,
                           SubtractionQueueDescriptor,
                           StringMapping::RefSubtractionWorkload_Execute>;
 
-using RefMultiplicationFloat32Workload =
-    RefElementwiseWorkload<std::multiplies<float>,
-                          DataType::Float32,
-                          MultiplicationQueueDescriptor,
-                          StringMapping::RefMultiplicationWorkload_Execute>;
-
-using RefMultiplicationUint8Workload =
+using RefMultiplicationWorkload =
     RefElementwiseWorkload<std::multiplies<float>,
-                          DataType::QuantisedAsymm8,
                           MultiplicationQueueDescriptor,
                           StringMapping::RefMultiplicationWorkload_Execute>;
 
-using RefDivisionFloat32Workload =
-    RefElementwiseWorkload<std::divides<float>,
-                          DataType::Float32,
-                          DivisionQueueDescriptor,
-                          StringMapping::RefDivisionWorkload_Execute>;
-
-using RefDivisionUint8Workload =
+using RefDivisionWorkload =
     RefElementwiseWorkload<std::divides<float>,
-                          DataType::QuantisedAsymm8,
                           DivisionQueueDescriptor,
                           StringMapping::RefDivisionWorkload_Execute>;
 
-using RefMaximumFloat32Workload =
-    RefElementwiseWorkload<armnn::maximum<float>,
-                          DataType::Float32,
-                          MaximumQueueDescriptor,
-                          StringMapping::RefMaximumWorkload_Execute>;
-
-using RefMaximumUint8Workload =
+using RefMaximumWorkload =
     RefElementwiseWorkload<armnn::maximum<float>,
-                          DataType::QuantisedAsymm8,
                           MaximumQueueDescriptor,
                           StringMapping::RefMaximumWorkload_Execute>;
 
-using RefMinimumFloat32Workload =
-    RefElementwiseWorkload<minimum<float>,
-                          DataType::Float32,
-                          MinimumQueueDescriptor,
-                          StringMapping::RefMinimumWorkload_Execute>;
-
-using RefMinimumUint8Workload =
-    RefElementwiseWorkload<minimum<float>,
-                          DataType::QuantisedAsymm8,
+using RefMinimumWorkload =
+    RefElementwiseWorkload<armnn::minimum<float>,
                           MinimumQueueDescriptor,
                           StringMapping::RefMinimumWorkload_Execute>;
 } // armnn