diff --git a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
index 412ae24..29ae903 100644
--- a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
+++ b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2020 Arm Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -29,6 +29,7 @@
 #include "src/core/NEON/NEAsymm.h"
 #include "src/core/NEON/NEFixedPoint.h"
 #include "src/core/NEON/wrapper/wrapper.h"
+#include "src/core/SVE/kernels/elementwise/impl/elementwise_list.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 
@@ -1135,14 +1136,23 @@
 {
     static std::map<std::string, NEElementwiseOperationKernel::ElementwiseFunction *> map_function =
     {
+#if defined(__ARM_FEATURE_SVE)
+        { "op_F32_F32_F32", &arm_compute::cpu::sve::elementwise_arithmetic_op<op, float32_t> },
+        { "op_S32_S32_S32", &arm_compute::cpu::sve::elementwise_arithmetic_op<op, int32_t> },
+#else  /* defined(__ARM_FEATURE_SVE) */
         { "op_F32_F32_F32", &elementwise_arithm_op<op, typename wrapper::traits::neon_vector<float, 4>> },
-        { "op_S16_S16_S16", &elementwise_arithm_op<op, typename wrapper::traits::neon_vector<int16_t, 8>> },
         { "op_S32_S32_S32", &elementwise_arithm_op<op, typename wrapper::traits::neon_vector<int32_t, 4>> },
+#endif /* defined(__ARM_FEATURE_SVE) */
+        { "op_S16_S16_S16", &elementwise_arithm_op<op, typename wrapper::traits::neon_vector<int16_t, 8>> },
         { "op_QASYMM8_QASYMM8_QASYMM8", &elementwise_arithm_op_quantized<op> },
         { "op_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED", &elementwise_arithm_op_quantized_signed<op> }
     };
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+#if defined(__ARM_FEATURE_SVE)
+    map_function["op_F16_F16_F16"] = &arm_compute::cpu::sve::elementwise_arithmetic_op<op, float16_t>;
+#else  /* defined(__ARM_FEATURE_SVE) */
     map_function["op_F16_F16_F16"] = &elementwise_arithm_op<op, typename wrapper::traits::neon_vector<float16_t, 8>>;
+#endif /* defined(__ARM_FEATURE_SVE) */
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
 
     return configure_func(input1, input2, output, map_function);
@@ -1154,15 +1164,26 @@
 {
     static std::map<std::string, NEElementwiseOperationKernel::ElementwiseFunction *> map_function =
     {
+#if defined(__ARM_FEATURE_SVE)
+        { "op_U8_U8_U8", &arm_compute::cpu::sve::elementwise_comparison_op<op, uint8_t> },
+        { "op_F32_F32_U8", &arm_compute::cpu::sve::elementwise_comparison_op<op, float> },
+        { "op_S16_S16_U8", &arm_compute::cpu::sve::elementwise_comparison_op<op, int16_t> },
+        { "op_S32_S32_U8", &arm_compute::cpu::sve::elementwise_comparison_op<op, int32_t> },
+#else  /* defined(__ARM_FEATURE_SVE) */
         { "op_U8_U8_U8", &elementwise_comp_op_8<op, uint8_t, uint8x16_t> },
         { "op_F32_F32_U8", &elementwise_comp_op_32<op, float, float32x4_t> },
         { "op_S16_S16_U8", &elementwise_comp_op_16<op, int16_t, int16x8_t> },
         { "op_S32_S32_U8", &elementwise_comp_op_32<op, int32_t, int32x4_t> },
+#endif /* defined(__ARM_FEATURE_SVE) */
         { "op_QASYMM8_SIGNED_QASYMM8_SIGNED_U8", &elementwise_comp_op_quantized_signed<op> },
         { "op_QASYMM8_QASYMM8_U8", &elementwise_comp_op_quantized<op> }
     };
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-    map_function["op_F16_F16_U8"] = &elementwise_comp_op_16<op, float16_t, float16x8_t>;
+#if defined(__ARM_FEATURE_SVE)
+    map_function["op_F16_F16_U8"] = &arm_compute::cpu::sve::elementwise_comparison_op<op, float16_t>;
+#else  /* defined(__ARM_FEATURE_SVE) */
+    map_function["op_F16_F16_U8"]  = &elementwise_comp_op_16<op, float16_t, float16x8_t>;
+#endif /* defined(__ARM_FEATURE_SVE) */
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
 
     return configure_func(input1, input2, output, map_function);
diff --git a/src/core/NEON/wrapper/intrinsics/intrinsics.h b/src/core/NEON/wrapper/intrinsics/intrinsics.h
index 4c7b674..871d9cc 100644
--- a/src/core/NEON/wrapper/intrinsics/intrinsics.h
+++ b/src/core/NEON/wrapper/intrinsics/intrinsics.h
@@ -79,6 +79,7 @@
 #include "src/core/NEON/wrapper/intrinsics/svdup_n.h"
 #include "src/core/NEON/wrapper/intrinsics/svexp.h"
 #include "src/core/NEON/wrapper/intrinsics/svlog.h"
+#include "src/core/NEON/wrapper/intrinsics/svpow.h"
 #include "src/core/NEON/wrapper/intrinsics/svptrue.h"
 #include "src/core/NEON/wrapper/intrinsics/svqadd.h"
 #include "src/core/NEON/wrapper/intrinsics/svsin.h"
diff --git a/src/core/NEON/wrapper/svtraits.h b/src/core/NEON/wrapper/svtraits.h
new file mode 100644
index 0000000..465983d
--- /dev/null
+++ b/src/core/NEON/wrapper/svtraits.h
@@ -0,0 +1,70 @@
+/*
+ * Copyright (c) 2021 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 SRC_CORE_NEON_WRAPPER_SVTRAITS_H
+#define SRC_CORE_NEON_WRAPPER_SVTRAITS_H
+#if defined(__ARM_FEATURE_SVE)
+#include "src/core/NEON/SVEMath.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace wrapper
+{
+template <typename T>
+struct sve_scalar;
+template <typename T>
+struct sve_vector;
+
+#define DEFINE_TYPES(stype)      \
+    template <>                  \
+    struct sve_scalar<sv##stype> \
+    {                            \
+        using type = stype;      \
+    };                           \
+    template <>                  \
+    struct sve_vector<stype>     \
+    {                            \
+        using type = sv##stype;  \
+    };
+
+DEFINE_TYPES(int8_t)
+DEFINE_TYPES(uint8_t)
+DEFINE_TYPES(int16_t)
+DEFINE_TYPES(uint16_t)
+DEFINE_TYPES(int32_t)
+DEFINE_TYPES(uint32_t)
+DEFINE_TYPES(int64_t)
+DEFINE_TYPES(uint64_t)
+DEFINE_TYPES(float16_t)
+DEFINE_TYPES(float32_t)
+DEFINE_TYPES(float64_t)
+DEFINE_TYPES(bfloat16_t)
+
+#undef DEFINE_TYPES
+
+} // namespace wrapper
+} // namespace arm_compute
+
+#endif /* defined(__ARM_FEATURE_SVE) */
+#endif /* #ifndef SRC_CORE_NEON_WRAPPER_SVTRAITS_H */
diff --git a/src/core/SVE/kernels/elementwise/impl/elementwise_list.h b/src/core/SVE/kernels/elementwise/impl/elementwise_list.h
new file mode 100644
index 0000000..83c3355
--- /dev/null
+++ b/src/core/SVE/kernels/elementwise/impl/elementwise_list.h
@@ -0,0 +1,366 @@
+/*
+ * Copyright (c) 2021 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 SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H
+#define SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H
+#if defined(__ARM_FEATURE_SVE)
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/Traits.h"
+#include "src/core/NEON/SVEMath.h"
+#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
+#include "src/core/NEON/wrapper/svtraits.h"
+#include <arm_sve.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace sve
+{
+using namespace arm_compute::wrapper;
+
+template <typename VectorType>
+inline VectorType elementwise_pow(svbool_t &pg, const VectorType &a, const VectorType &b)
+{
+    return svpow_z(pg, a, b);
+}
+
+template <>
+inline svint32_t elementwise_pow<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b)
+{
+    return svcvt_s32_z(pg, svpow_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b)));
+}
+
+template <typename VectorType>
+inline VectorType elementwise_div(svbool_t &pg, const VectorType &a, const VectorType &b)
+{
+    return svdiv_z(pg, a, b);
+}
+
+template <>
+inline svint32_t elementwise_div<svint32_t>(svbool_t &pg, const svint32_t &a, const svint32_t &b)
+{
+    return svcvt_s32_z(pg, svdiv_z(pg, svcvt_f32_z(pg, a), svcvt_f32_z(pg, b)));
+}
+
+template <typename VectorType>
+inline VectorType elementwise_arithmetic_op(svbool_t &pg, const VectorType &a, const VectorType &b, ArithmeticOperation op)
+{
+    using ScalarType = typename sve_scalar<VectorType>::type;
+    VectorType res{};
+
+    switch(op)
+    {
+        case ArithmeticOperation::MAX:
+            res = svmax_z(pg, a, b);
+            break;
+        case ArithmeticOperation::MIN:
+            res = svmin_z(pg, a, b);
+            break;
+        case ArithmeticOperation::SQUARED_DIFF:
+        {
+            const auto tmp = svsub_z(pg, a, b);
+            res            = svmul_z(pg, tmp, tmp);
+            break;
+        }
+        case ArithmeticOperation::PRELU:
+        {
+            const auto zero = svdup_n(ScalarType(0));
+            const auto tmp  = svmul_z(pg, a, b);
+            const auto gt   = svcmpgt(pg, a, zero);
+            res             = svsel(gt, a, tmp);
+            break;
+        }
+        case ArithmeticOperation::DIV:
+        {
+            res = elementwise_div(pg, a, b);
+            break;
+        }
+        case ArithmeticOperation::POWER:
+        {
+            res = elementwise_pow(pg, a, b);
+            break;
+        }
+        default:
+            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
+    }
+
+    return res;
+}
+
+template <uint32_t bytewidth>
+inline svbool_t narrow_to_byte_predicate(svbool_t pg)
+{
+    const auto all_false = svpfalse();
+
+    switch(bytewidth)
+    {
+        case 8:
+            pg = svuzp1_b32(pg, all_false);
+        /* fall through */
+        case 4:
+            pg = svuzp1_b16(pg, all_false);
+        /* fall through */
+        case 2:
+            pg = svuzp1_b8(pg, all_false);
+        /* fall through */
+        default:
+            break;
+    }
+    return pg;
+}
+
+template <typename InputVectorType, typename OutputVectorType>
+inline OutputVectorType elementwise_comparison_op(svbool_t &pg, const InputVectorType &a, const InputVectorType &b, ComparisonOperation op)
+{
+    svbool_t selection_vector{};
+
+    switch(op)
+    {
+        case ComparisonOperation::Equal:
+            selection_vector = svcmpeq(pg, a, b);
+            break;
+        case ComparisonOperation::NotEqual:
+            selection_vector = svcmpne(pg, a, b);
+            break;
+        case ComparisonOperation::Greater:
+            selection_vector = svcmpgt(pg, a, b);
+            break;
+        case ComparisonOperation::GreaterEqual:
+            selection_vector = svcmpge(pg, a, b);
+            break;
+        case ComparisonOperation::Less:
+            selection_vector = svcmplt(pg, a, b);
+            break;
+        case ComparisonOperation::LessEqual:
+            selection_vector = svcmple(pg, a, b);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("NOT_SUPPORTED!");
+    }
+
+    using InputScalarType = typename sve_scalar<InputVectorType>::type;
+    selection_vector      = narrow_to_byte_predicate<sizeof(InputScalarType)>(selection_vector);
+
+    using OutputScalarType  = typename sve_scalar<OutputVectorType>::type;
+    const auto false_vector = svdup_n(static_cast<OutputScalarType>((uint32_t)0));
+    const auto true_vector  = svdup_n(static_cast<OutputScalarType>(~(uint32_t)0));
+    auto       ret          = svsel(selection_vector, true_vector, false_vector);
+
+    return ret;
+}
+
+template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
+struct LoopArguments
+{
+    OperatorType           op;
+    const InputScalarType *input1_ptr;
+    const InputScalarType *input2_ptr;
+    OutputScalarType      *output_ptr;
+};
+
+template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
+struct BroadcastLoopArguments
+{
+    OperatorType           op;
+    const InputScalarType *input1_ptr;
+    InputScalarType        broadcast_value;
+    OutputScalarType      *output_ptr;
+    bool                   reorder;
+};
+
+template <typename InputScalarType, typename OutputScalarType>
+inline void arithmetic_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args)
+{
+    const auto in1 = svld1(pg, args.input1_ptr);
+    const auto in2 = svld1(pg, args.input2_ptr);
+    const auto res = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op);
+    svst1(pg, args.output_ptr, res);
+}
+
+template <typename InputScalarType, typename OutputScalarType>
+inline void arithmetic_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ArithmeticOperation> &args)
+{
+    const auto non_broadcast_vector = svld1(pg, args.input1_ptr);
+    const auto broadcast_vector     = svdup_n(args.broadcast_value);
+    const auto in1                  = args.reorder ? broadcast_vector : non_broadcast_vector;
+    const auto in2                  = args.reorder ? non_broadcast_vector : broadcast_vector;
+    const auto res                  = elementwise_arithmetic_op<typename sve_vector<InputScalarType>::type>(pg, in1, in2, args.op);
+    svst1(pg, args.output_ptr, res);
+}
+
+template <typename InputScalarType, typename OutputScalarType>
+inline void comparison_op_loop(svbool_t pg, const LoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args)
+{
+    const auto     in1       = svld1(pg, args.input1_ptr);
+    const auto     in2       = svld1(pg, args.input2_ptr);
+    const auto     res       = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op);
+    const svbool_t output_pg = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg);
+    svst1(output_pg, args.output_ptr, res);
+}
+
+template <typename InputScalarType, typename OutputScalarType>
+inline void comparison_op_broadcast_loop(svbool_t pg, const BroadcastLoopArguments<InputScalarType, OutputScalarType, ComparisonOperation> &args)
+{
+    const auto     non_broadcast_vector = svld1(pg, args.input1_ptr);
+    const auto     broadcast_vector     = svdup_n(args.broadcast_value);
+    const auto     in1                  = args.reorder ? broadcast_vector : non_broadcast_vector;
+    const auto     in2                  = args.reorder ? non_broadcast_vector : broadcast_vector;
+    const auto     res                  = elementwise_comparison_op<typename sve_vector<InputScalarType>::type, typename sve_vector<OutputScalarType>::type>(pg, in1, in2, args.op);
+    const svbool_t output_pg            = narrow_to_byte_predicate<sizeof(InputScalarType)>(pg);
+    svst1(output_pg, args.output_ptr, res);
+}
+
+template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
+using LoopFuncType = void (*)(svbool_t, const LoopArguments<InputScalarType, OutputScalarType, OperatorType> &);
+
+template <typename InputScalarType, typename OutputScalarType, typename OperatorType>
+using BroadcastLoopFuncType = void (*)(svbool_t, const BroadcastLoopArguments<InputScalarType, OutputScalarType, OperatorType> &);
+
+template <typename InputVectorType, typename OutputVectorType, typename OperatorType,
+          typename InputScalarType  = typename sve_scalar<InputVectorType>::type,
+          typename OutputScalarType = typename sve_scalar<OutputVectorType>::type>
+void elementwise_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window,
+                    OperatorType op,
+                    LoopFuncType<InputScalarType, OutputScalarType, OperatorType>          func,
+                    BroadcastLoopFuncType<InputScalarType, OutputScalarType, OperatorType> broadcast_func)
+{
+    const auto all_true_pg = svptrue<InputScalarType>();
+
+    // Create input windows
+    Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape());
+    Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape());
+
+    // Clear X Dimension on execution window as we handle manually
+    Window win = window;
+    win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    const auto window_start_x        = static_cast<int>(window.x().start());
+    const auto window_end_x          = static_cast<int>(window.x().end());
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
+
+    if(is_broadcast_across_x)
+    {
+        const bool     is_broadcast_input_2 = input2_win.x().step() == 0;
+        Window         broadcast_win        = is_broadcast_input_2 ? input2_win : input1_win;
+        Window         non_broadcast_win    = !is_broadcast_input_2 ? input2_win : input1_win;
+        const ITensor *broadcast_tensor     = is_broadcast_input_2 ? in2 : in1;
+        const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1;
+
+        // Clear X Dimension on execution window as we handle manually
+        non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+        Iterator broadcast_input(broadcast_tensor, broadcast_win);
+        Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
+        Iterator output(out, win);
+
+        execute_window_loop(win, [&](const Coordinates &)
+        {
+            auto                  output_ptr              = reinterpret_cast<OutputScalarType *>(output.ptr());
+            const auto            non_broadcast_input_ptr = reinterpret_cast<const InputScalarType *>(non_broadcast_input.ptr());
+            const InputScalarType broadcast_value         = *reinterpret_cast<const InputScalarType *>(broadcast_input.ptr());
+
+            int x = window_start_x;
+
+            svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x);
+            do
+            {
+                broadcast_func(pg,
+                {
+                    op,
+                    non_broadcast_input_ptr + x,
+                    broadcast_value,
+                    output_ptr + x,
+                    !is_broadcast_input_2
+                });
+                x += svcnt<InputScalarType>();
+                pg = svwhilelt<InputScalarType>(x, window_end_x);
+            }
+            while(svptest_any(all_true_pg, pg));
+        },
+        broadcast_input, non_broadcast_input, output);
+    }
+    else
+    {
+        // Clear X Dimension on execution window as we handle manually
+        input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+        input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+        Iterator input1(in1, input1_win);
+        Iterator input2(in2, input2_win);
+        Iterator output(out, win);
+
+        execute_window_loop(win, [&](const Coordinates &)
+        {
+            auto       output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr());
+            const auto input1_ptr = reinterpret_cast<const InputScalarType *>(input1.ptr());
+            const auto input2_ptr = reinterpret_cast<const InputScalarType *>(input2.ptr());
+
+            int x = window_start_x;
+
+            svbool_t pg = svwhilelt<InputScalarType>(x, window_end_x);
+            do
+            {
+                func(pg,
+                {
+                    op,
+                    input1_ptr + x,
+                    input2_ptr + x,
+                    output_ptr + x
+                });
+                x += svcnt<InputScalarType>();
+                pg = svwhilelt<InputScalarType>(x, window_end_x);
+            }
+            while(svptest_any(all_true_pg, pg));
+        },
+        input1, input2, output);
+    }
+}
+
+template <ArithmeticOperation op, typename ScalarType>
+void elementwise_arithmetic_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+{
+    using VectorType = typename sve_vector<ScalarType>::type;
+
+    elementwise_op<VectorType, VectorType, ArithmeticOperation>(in1, in2, out, window, op,
+                                                                &arithmetic_op_loop<ScalarType, ScalarType>,
+                                                                &arithmetic_op_broadcast_loop<ScalarType, ScalarType>);
+}
+
+template <ComparisonOperation op, typename InputScalarType, typename OutputScalarType = uint8_t>
+void elementwise_comparison_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
+{
+    static_assert(sizeof(InputScalarType) >= sizeof(OutputScalarType), "input data type's width should be equal to or greater than output data type's width");
+    using InputVectorType  = typename sve_vector<InputScalarType>::type;
+    using OutputVectorType = typename sve_vector<OutputScalarType>::type;
+
+    elementwise_op<InputVectorType, OutputVectorType, ComparisonOperation>(in1, in2, out, window, op,
+                                                                           &comparison_op_loop<InputScalarType, OutputScalarType>,
+                                                                           &comparison_op_broadcast_loop<InputScalarType, OutputScalarType>);
+}
+
+} // namespace sve
+} // namespace cpu
+} // namespace arm_compute
+#endif // defined(__ARM_FEATURE_SVE)
+#endif /* SRC_CORE_SVE_KERNELS_ELEMENTWISE_LIST_H */