diff --git a/src/core/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp b/src/core/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp
new file mode 100644
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+++ b/src/core/cpu/kernels/CpuGemmMatrixAdditionKernel.cpp
@@ -0,0 +1,200 @@
+/*
+ * Copyright (c) 2016-2021 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.
+ */
+#include "src/core/cpu/kernels/CpuGemmMatrixAdditionKernel.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "src/core/CPP/Validate.h"
+#include "src/core/NEON/NEFixedPoint.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+#include <arm_neon.h>
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+namespace
+{
+void matrix_addition_f32(const ITensor *src, ITensor *dst, const Window &window, float beta)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+    const float32x4_t beta_f32 = vdupq_n_f32(beta);
+
+    constexpr int window_step_x  = 16;
+    const auto    window_start_x = static_cast<int>(window.x().start());
+    const auto    window_end_x   = static_cast<int>(window.x().end());
+
+    Window win = window.collapse_if_possible(window, Window::DimZ);
+    win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    Iterator in(src, win);
+    Iterator out(dst, win);
+
+    execute_window_loop(win, [&](const Coordinates &)
+    {
+        const auto in_ptr  = reinterpret_cast<const float *>(in.ptr());
+        const auto out_ptr = reinterpret_cast<float *>(out.ptr());
+
+        int x = window_start_x;
+        for(; x < (window_end_x - window_step_x); x += window_step_x)
+        {
+            float32x4x4_t       alpha_ab = vld4q_f32(out_ptr + x);
+            const float32x4x4_t c        = vld4q_f32(in_ptr + x);
+
+            // Multiply matrix C by its weight and accumulate
+            alpha_ab.val[0] = vmlaq_f32(alpha_ab.val[0], c.val[0], beta_f32);
+            alpha_ab.val[1] = vmlaq_f32(alpha_ab.val[1], c.val[1], beta_f32);
+            alpha_ab.val[2] = vmlaq_f32(alpha_ab.val[2], c.val[2], beta_f32);
+            alpha_ab.val[3] = vmlaq_f32(alpha_ab.val[3], c.val[3], beta_f32);
+
+            vst4q_f32(out_ptr + x, alpha_ab);
+        }
+
+        // Left-over loop
+        for(; x < window_end_x; ++x)
+        {
+            *(out_ptr + x) += *(in_ptr + x) * beta;
+        }
+    },
+    in, out);
+}
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+void matrix_addition_f16(const ITensor *src, ITensor *dst, const Window &window, float beta)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+    const float16x8_t beta_f16 = vdupq_n_f16(beta);
+
+    constexpr int window_step_x  = 16;
+    const auto    window_start_x = static_cast<int>(window.x().start());
+    const auto    window_end_x   = static_cast<int>(window.x().end());
+
+    Window win = window.collapse_if_possible(window, Window::DimZ);
+    win.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    Iterator in(src, win);
+    Iterator out(dst, win);
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        const auto in_ptr  = reinterpret_cast<const float16_t *>(in.ptr());
+        const auto out_ptr = reinterpret_cast<float16_t *>(out.ptr());
+
+        int x = window_start_x;
+        for(; x < (window_end_x - window_step_x); x += window_step_x)
+        {
+            float16x8x2_t       alpha_ab = vld2q_f16(out_ptr + x);
+            const float16x8x2_t c        = vld2q_f16(in_ptr + x);
+            // Multiply matrix C by its weight and accumulate
+            alpha_ab.val[0] = vaddq_f16(alpha_ab.val[0], vmulq_f16(c.val[0], beta_f16));
+            alpha_ab.val[1] = vaddq_f16(alpha_ab.val[1], vmulq_f16(c.val[1], beta_f16));
+
+            vst2q_f16(out_ptr + x, alpha_ab);
+        }
+
+        // Left-over loop
+        for(; x < window_end_x; ++x)
+        {
+            *(out_ptr + x) += *(in_ptr + x) * static_cast<float16_t>(beta);
+        }
+    },
+    in, out);
+}
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+} // namespace
+
+void CpuGemmMatrixAdditionKernel::configure(const ITensorInfo *src, ITensorInfo *dst, float beta)
+{
+    ARM_COMPUTE_UNUSED(dst);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+
+    // Perform validation step
+    ARM_COMPUTE_ERROR_THROW_ON(CpuGemmMatrixAdditionKernel::validate(src, dst, beta));
+
+    _beta = beta;
+    switch(src->data_type())
+    {
+        case DataType::F32:
+            _func = &matrix_addition_f32;
+            break;
+        case DataType::F16:
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+            _func = &matrix_addition_f16;
+            break;
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+        default:
+            ARM_COMPUTE_ERROR("Data type not supported");
+            break;
+    }
+
+    // Configure kernel window
+    Window win = calculate_max_window(*src, Steps());
+    ICPPKernel::configure(win);
+}
+
+Status CpuGemmMatrixAdditionKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, float beta)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+    ARM_COMPUTE_UNUSED(beta);
+
+    ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32);
+
+    if(dst->total_size() > 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
+    }
+    return Status{};
+}
+
+void CpuGemmMatrixAdditionKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON(tensors.empty());
+
+    const ITensor *src = tensors.get_const_tensor(TensorType::ACL_SRC);
+    ITensor       *dst = tensors.get_tensor(TensorType::ACL_DST);
+
+    if(_beta != 0.0f)
+    {
+        (*_func)(src, dst, window, _beta);
+    }
+}
+
+const char *CpuGemmMatrixAdditionKernel::name() const
+{
+    return "CpuGemmMatrixAdditionKernel";
+}
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute