COMPMID-1963: Implement FFT (2D) on NEON

Change-Id: I3b564be8d7949e00c6544071ef62dd51de838c96
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1048
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

12 files changed, 928 insertions, 218 deletions

diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h
index b8ae467c6d..b9716b1e43 100644
--- a/arm_compute/core/NEON/NEKernels.h
+++ b/arm_compute/core/NEON/NEKernels.h
@@ -64,6 +64,7 @@
 #include "arm_compute/core/NEON/kernels/NEErodeKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFFTDigitReverseKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h"
+#include "arm_compute/core/NEON/kernels/NEFFTScaleKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFastCornersKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFillArrayKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
diff --git a/arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h b/arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h
index a4c4be6f35..8498d3c613 100644
--- a/arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h
+++ b/arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h
@@ -24,10 +24,10 @@
 #ifndef __ARM_COMPUTE_NEFFTRADIXSTAGEKERNEL_H__
 #define __ARM_COMPUTE_NEFFTRADIXSTAGEKERNEL_H__
 
-#include "arm_compute/core/NEON/INEKernel.h"
-
 #include "arm_compute/core/KernelDescriptors.h"
+#include "arm_compute/core/NEON/INEKernel.h"
 
+#include <arm_neon.h>
 #include <set>
 
 namespace arm_compute
@@ -87,12 +87,17 @@ private:
     ITensor     *_output;
     bool         _run_in_place;
     unsigned int _Nx;
+    unsigned int _axis;
+    unsigned int _radix;
+
+    void set_radix_stage_axis0(const FFTRadixStageKernelInfo &config);
+    void set_radix_stage_axis1(const FFTRadixStageKernelInfo &config);
 
-    template <bool first_stage>
-    void set_radix_stage_fun(unsigned int radix);
+    using FFTFunctionPointerAxis0 = std::function<void(float *, float *, unsigned int, unsigned int, const float32x2_t &, unsigned int)>;
+    using FFTFunctionPointerAxis1 = std::function<void(float *, float *, unsigned int, unsigned int, const float32x2_t &, unsigned int, unsigned int)>;
 
-    using FFTFunctionPointerInPlace = std::function<void(float *, float *, unsigned int, unsigned int)>;
-    FFTFunctionPointerInPlace _func;
+    FFTFunctionPointerAxis0 _func_0;
+    FFTFunctionPointerAxis1 _func_1;
 };
 } // namespace arm_compute
-#endif /*__ARM_COMPUTE_NEFFTKERNEL_H__ */
+#endif /*__ARM_COMPUTE_NEFFTRADIXSTAGEKERNEL_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEFFTScaleKernel.h b/arm_compute/core/NEON/kernels/NEFFTScaleKernel.h
new file mode 100644
index 0000000000..5a19af7e62
--- /dev/null
+++ b/arm_compute/core/NEON/kernels/NEFFTScaleKernel.h
@@ -0,0 +1,84 @@
+/*
+ * Copyright (c) 2019 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 __ARM_COMPUTE_NEFFTSCALEKERNEL_H__
+#define __ARM_COMPUTE_NEFFTSCALEKERNEL_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+
+#include "arm_compute/core/KernelDescriptors.h"
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** Interface for the inverse fft scale kernel. */
+class NEFFTScaleKernel : public INEKernel
+{
+public:
+    const char *name() const override
+    {
+        return "NEFFTScaleKernel";
+    }
+    /** Constructor */
+    NEFFTScaleKernel();
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEFFTScaleKernel(const NEFFTScaleKernel &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEFFTScaleKernel &operator=(const NEFFTScaleKernel &) = delete;
+    /** Default Move Constructor. */
+    NEFFTScaleKernel(NEFFTScaleKernel &&) = default;
+    /** Default move assignment operator */
+    NEFFTScaleKernel &operator=(NEFFTScaleKernel &&) = default;
+    /** Default destructor */
+    ~NEFFTScaleKernel() = default;
+    /** Set the input and output tensors.
+     *
+     * @param[in,out] input  Source tensor. Data types supported: F32.
+     * @param[out]    output Destination tensor. Data type supported: same as @p input
+     * @param[in]     config Kernel configuration
+     */
+    void configure(ITensor *input, ITensor *output, const FFTScaleKernelInfo &config);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEFFTScaleKernel
+     *
+     * @param[in] input  Source tensor info. Data types supported: F32.
+     * @param[in] output Destination tensor info. Data type supported: same as @p input
+     * @param[in] config Kernel configuration
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const FFTScaleKernelInfo &config);
+
+    // Inherited methods overridden:
+    void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+    ITensor *_input;
+    ITensor *_output;
+    float    _scale;
+    bool     _run_in_place;
+    bool     _is_conj;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_NEFFTSCALEKERNEL_H__ */
diff --git a/arm_compute/runtime/NEON/NEFunctions.h b/arm_compute/runtime/NEON/NEFunctions.h
index d8f54ea231..869eb523dd 100644
--- a/arm_compute/runtime/NEON/NEFunctions.h
+++ b/arm_compute/runtime/NEON/NEFunctions.h
@@ -64,6 +64,7 @@
 #include "arm_compute/runtime/NEON/functions/NEEqualizeHistogram.h"
 #include "arm_compute/runtime/NEON/functions/NEErode.h"
 #include "arm_compute/runtime/NEON/functions/NEFFT1D.h"
+#include "arm_compute/runtime/NEON/functions/NEFFT2D.h"
 #include "arm_compute/runtime/NEON/functions/NEFastCorners.h"
 #include "arm_compute/runtime/NEON/functions/NEFillBorder.h"
 #include "arm_compute/runtime/NEON/functions/NEFlattenLayer.h"
diff --git a/arm_compute/runtime/NEON/functions/NEFFT1D.h b/arm_compute/runtime/NEON/functions/NEFFT1D.h
index 9b5ada746a..c706936f77 100644
--- a/arm_compute/runtime/NEON/functions/NEFFT1D.h
+++ b/arm_compute/runtime/NEON/functions/NEFFT1D.h
@@ -26,6 +26,7 @@
 
 #include "arm_compute/core/NEON/kernels/NEFFTDigitReverseKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h"
+#include "arm_compute/core/NEON/kernels/NEFFTScaleKernel.h"
 #include "arm_compute/runtime/IFunction.h"
 
 #include "arm_compute/runtime/FunctionDescriptors.h"
@@ -37,24 +38,25 @@ namespace arm_compute
 // Forward declaration
 class ITensor;
 
-/** Basic function to execute one dimensional FFT. This function calls the following OpenCL kernels:
+/** Basic function to execute one dimensional FFT. This function calls the following NEON kernels:
  *
- * -# @ref CLFFTDigitReverseKernel Performs digit reverse
+ * -# @ref NEFFTDigitReverseKernel Performs digit reverse
  * -# @ref NEFFTRadixStageKernel   A list of FFT kernels depending on the radix decomposition
+ * -# @ref NEFFTScaleKernel        Performs output scaling in case of in inverse FFT
  */
 class NEFFT1D : public IFunction
 {
 public:
     /** Default Constructor */
     NEFFT1D(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
-    /** Initialise the function's source, destinations and border mode.
+    /** Initialise the function's source and destinations.
      *
      * @param[in]  input  Source tensor. Data types supported: F32.
      * @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
      * @param[in]  config FFT related configuration
      */
     void configure(const ITensor *input, ITensor *output, const FFT1DInfo &config);
-    /** Static function to check if given info will lead to a valid configuration of @ref CLFFT1D.
+    /** Static function to check if given info will lead to a valid configuration of @ref NEFFT1D.
      *
      * @param[in] input  Source tensor info. Data types supported: F32.
      * @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
@@ -69,11 +71,14 @@ public:
 
 protected:
     MemoryGroup                        _memory_group;
-    Tensor                             _digit_reversed_input;
-    Tensor                             _digit_reverse_indices;
     NEFFTDigitReverseKernel            _digit_reverse_kernel;
     std::vector<NEFFTRadixStageKernel> _fft_kernels;
-    unsigned int                       _n_ffts;
+    NEFFTScaleKernel                   _scale_kernel;
+    Tensor                             _digit_reversed_input;
+    Tensor                             _digit_reverse_indices;
+    unsigned int                       _num_ffts;
+    unsigned int                       _axis;
+    bool                               _run_scale;
 };
 } // namespace arm_compute
 #endif /*__ARM_COMPUTE_NEFFT1D_H__ */
diff --git a/arm_compute/runtime/NEON/functions/NEFFT2D.h b/arm_compute/runtime/NEON/functions/NEFFT2D.h
new file mode 100644
index 0000000000..9911cea290
--- /dev/null
+++ b/arm_compute/runtime/NEON/functions/NEFFT2D.h
@@ -0,0 +1,76 @@
+/*
+ * Copyright (c) 2019 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 __ARM_COMPUTE_NEFFT2D_H__
+#define __ARM_COMPUTE_NEFFT2D_H__
+
+#include "arm_compute/runtime/IFunction.h"
+
+#include "arm_compute/runtime/FunctionDescriptors.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/NEON/functions/NEFFT1D.h"
+#include "arm_compute/runtime/Tensor.h"
+
+namespace arm_compute
+{
+// Forward declaration
+class ITensor;
+
+/** Basic function to execute two dimensional FFT. This function calls the following NEON kernels:
+ *
+ * -# @ref NEFFT1D 1D FFT is performed on the first given axis
+ * -# @ref NEFFT1D 1D FFT is performed on the second given axis
+ */
+class NEFFT2D : public IFunction
+{
+public:
+    /** Default Constructor */
+    NEFFT2D(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+    /** Initialise the function's source and destinations
+     *
+     * @param[in]  input  Source tensor. Data types supported: F32.
+     * @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
+     * @param[in]  config FFT related configuration
+     */
+    void configure(const ITensor *input, ITensor *output, const FFT2DInfo &config);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEFFT2D.
+     *
+     * @param[in] input  Source tensor info. Data types supported: F32.
+     * @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
+     * @param[in] config FFT related configuration
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const FFT2DInfo &config);
+
+    // Inherited methods overridden:
+    void run() override;
+
+protected:
+    MemoryGroup _memory_group;
+    NEFFT1D     _first_pass_func;
+    NEFFT1D     _second_pass_func;
+    Tensor      _first_pass_tensor;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_NEFFT2D_H__ */
diff --git a/src/core/NEON/kernels/NEFFTDigitReverseKernel.cpp b/src/core/NEON/kernels/NEFFTDigitReverseKernel.cpp
index 845fcef4f3..b2ffb01e99 100644
--- a/src/core/NEON/kernels/NEFFTDigitReverseKernel.cpp
+++ b/src/core/NEON/kernels/NEFFTDigitReverseKernel.cpp
@@ -37,7 +37,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
 {
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 2, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(idx, 1, DataType::U32);
-    ARM_COMPUTE_RETURN_ERROR_ON(axis != 0);
+    ARM_COMPUTE_RETURN_ERROR_ON(axis > 1);
 
     // Checks performed when output is configured
     if((output != nullptr) && (output->total_size() != 0))
@@ -96,15 +96,24 @@ void NEFFTDigitReverseKernel::run(const Window &window, const ThreadInfo &info)
     Iterator     out(_output, window);
     const size_t element_size = _input->info()->element_size();
 
+    // Pointers to the buffers
+    const size_t offset    = _input->info()->offset_first_element_in_bytes();
+    auto        *idx_ptr   = reinterpret_cast<unsigned int *>(_idx->buffer());
+    uint8_t     *input_ptr = offset + _input->buffer();
+
+    // Strides
+    const size_t stride_x = _input->info()->strides_in_bytes()[0];
+    const size_t stride_y = _input->info()->strides_in_bytes()[1];
+    const size_t stride_z = _input->info()->strides_in_bytes()[2];
+    const size_t stride_w = _input->info()->strides_in_bytes()[3];
+
     execute_window_loop(window, [&](const Coordinates & id)
     {
-        unsigned int in_index_1d = *reinterpret_cast<unsigned int *>(_idx->ptr_to_element(Coordinates(id.x())));
-
-        auto reverse_id = id;
+        unsigned int in_index_1d = idx_ptr[id[_axis]];
+        auto         reverse_id  = id;
         reverse_id.set(_axis, in_index_1d);
 
-        memcpy(out.ptr(), _input->ptr_to_element(reverse_id), 2 * element_size);
-
+        memcpy(out.ptr(), input_ptr + reverse_id.x() * stride_x + reverse_id.y() * stride_y + reverse_id.z() * stride_z + reverse_id[3] * stride_w, element_size);
     },
     out);
 
diff --git a/src/core/NEON/kernels/NEFFTRadixStageKernel.cpp b/src/core/NEON/kernels/NEFFTRadixStageKernel.cpp
index b264590791..148bbe915a 100644
--- a/src/core/NEON/kernels/NEFFTRadixStageKernel.cpp
+++ b/src/core/NEON/kernels/NEFFTRadixStageKernel.cpp
@@ -24,8 +24,6 @@
 #include "arm_compute/core/NEON/kernels/NEFFTRadixStageKernel.h"
 
 #include "arm_compute/core/ITensor.h"
-#include "arm_compute/core/NEON/wrapper/traits.h"
-#include "arm_compute/core/NEON/wrapper/wrapper.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Utils.h"
@@ -34,28 +32,53 @@
 #include <arm_neon.h>
 #include <cmath>
 #include <complex>
+#include <map>
+
+#include "arm_compute/core/NEON/wrapper/traits.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
 
 namespace arm_compute
 {
 namespace
 {
-constexpr float PI = 3.141592653589793f;
+// PI constant (from cmath)
+constexpr float kPi = float(M_PI);
+
+// Constant used in the fft_3 kernel
+constexpr float kSqrt3Div2 = 0.866025403784438;
+
+// Constants used in the fft_5 kernel
+constexpr float kW5_0 = 0.30901699437494f;
+constexpr float kW5_1 = 0.95105651629515f;
+constexpr float kW5_2 = 0.80901699437494f;
+constexpr float kW5_3 = 0.58778525229247f;
+
+// Constants used in the fft_7 kernel
+constexpr float kW7_0 = 0.62348980185873f;
+constexpr float kW7_1 = 0.78183148246802f;
+constexpr float kW7_2 = 0.22252093395631f;
+constexpr float kW7_3 = 0.97492791218182f;
+constexpr float kW7_4 = 0.90096886790241f;
+constexpr float kW7_5 = 0.43388373911755f;
+
+// Constant used in the fft_8 kernel
+constexpr float kSqrt2Div2 = 0.707106781186548;
 
 float32x2_t c_mul_neon(float32x2_t a, float32x2_t b)
 {
-    float32x2_t tmp = wrapper::vmul(a, b);
+    using ExactTagType = typename wrapper::traits::neon_vector<float, 2>::tag_type;
 
-    const float P1 = wrapper::vgetlane(tmp, 0);
-    const float P2 = wrapper::vgetlane(tmp, 1);
+    const float32x2_t mask = { -1.0, 1.0 };
+    const float32x2_t tmp0 = wrapper::vdup_n(wrapper::vgetlane(a, 0), ExactTagType{});
+    const float32x2_t tmp1 = wrapper::vdup_n(wrapper::vgetlane(a, 1), ExactTagType{});
 
-    const float a_r = wrapper::vgetlane(a, 0);
-    const float a_i = wrapper::vgetlane(a, 1);
-    const float b_r = wrapper::vgetlane(b, 0);
-    const float b_i = wrapper::vgetlane(b, 1);
+    float32x2_t res = wrapper::vmul(tmp0, b);
 
-    const float P3  = (a_r + a_i) * (b_r + b_i);
-    float32x2_t out = { P1 - P2, P3 - P2 - P1 };
-    return out;
+    b   = wrapper::vrev64(b);
+    b   = wrapper::vmul(b, mask);
+    res = wrapper::vmla(res, tmp1, b);
+
+    return res;
 }
 
 float32x2_t c_mul_neon_img(float32x2_t a, float img_constant)
@@ -107,7 +130,6 @@ void fft_2(float32x2_t &x, float32x2_t &y, float32x2_t &w)
     y = wrapper::vsub(a, b);
 }
 
-constexpr float sqrt3div2 = 0.866025403784438;
 void fft_3(float32x2_t &x, float32x2_t &y, float32x2_t &z, const float32x2_t &w, const float32x2_t &w2)
 {
     float32x2_t a = x;
@@ -118,7 +140,7 @@ void fft_3(float32x2_t &x, float32x2_t &y, float32x2_t &z, const float32x2_t &w,
     x = wrapper::vadd(x, c);
 
     const auto v1 = wrapper::vmul(float32x2_t{ 0.5f, 0.5 }, wrapper::vadd(b, c));
-    const auto v2 = c_mul_neon(float32x2_t{ 0.f, -sqrt3div2 }, wrapper::vsub(b, c));
+    const auto v2 = c_mul_neon(float32x2_t{ 0.f, -kSqrt3Div2 }, wrapper::vsub(b, c));
 
     y = z = wrapper::vsub(a, v1);
     y     = wrapper::vadd(y, v2);
@@ -149,10 +171,6 @@ void fft_4(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, c
     x4             = wrapper::vadd(x41, x42);
 }
 
-constexpr float W5_0 = 0.30901699437494f;
-constexpr float W5_1 = 0.95105651629515f;
-constexpr float W5_2 = 0.80901699437494f;
-constexpr float W5_3 = 0.58778525229247f;
 void fft_5(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, float32x2_t &x5, const float32x2_t &w, const float32x2_t &w2, const float32x2_t &w3, const float32x2_t &w4)
 {
     const auto a = x1;
@@ -161,25 +179,25 @@ void fft_5(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto d = c_mul_neon(w3, x4);
     const auto e = c_mul_neon(w4, x5);
 
-    const auto b0 = c_mul_neon(float32x2_t{ W5_0, -W5_1 }, b);
-    const auto b1 = c_mul_neon(float32x2_t{ -W5_2, -W5_3 }, b);
-    const auto b2 = c_mul_neon(float32x2_t{ -W5_2, W5_3 }, b);
-    const auto b3 = c_mul_neon(float32x2_t{ W5_0, W5_1 }, b);
+    const auto b0 = c_mul_neon(float32x2_t{ kW5_0, -kW5_1 }, b);
+    const auto b1 = c_mul_neon(float32x2_t{ -kW5_2, -kW5_3 }, b);
+    const auto b2 = c_mul_neon(float32x2_t{ -kW5_2, kW5_3 }, b);
+    const auto b3 = c_mul_neon(float32x2_t{ kW5_0, kW5_1 }, b);
 
-    const auto c0 = c_mul_neon(float32x2_t{ -W5_2, -W5_3 }, c);
-    const auto c1 = c_mul_neon(float32x2_t{ W5_0, W5_1 }, c);
-    const auto c2 = c_mul_neon(float32x2_t{ W5_0, -W5_1 }, c);
-    const auto c3 = c_mul_neon(float32x2_t{ -W5_2, W5_3 }, c);
+    const auto c0 = c_mul_neon(float32x2_t{ -kW5_2, -kW5_3 }, c);
+    const auto c1 = c_mul_neon(float32x2_t{ kW5_0, kW5_1 }, c);
+    const auto c2 = c_mul_neon(float32x2_t{ kW5_0, -kW5_1 }, c);
+    const auto c3 = c_mul_neon(float32x2_t{ -kW5_2, kW5_3 }, c);
 
-    const auto d0 = c_mul_neon(float32x2_t{ -W5_2, W5_3 }, d);
-    const auto d1 = c_mul_neon(float32x2_t{ W5_0, -W5_1 }, d);
-    const auto d2 = c_mul_neon(float32x2_t{ W5_0, W5_1 }, d);
-    const auto d3 = c_mul_neon(float32x2_t{ -W5_2, -W5_3 }, d);
+    const auto d0 = c_mul_neon(float32x2_t{ -kW5_2, kW5_3 }, d);
+    const auto d1 = c_mul_neon(float32x2_t{ kW5_0, -kW5_1 }, d);
+    const auto d2 = c_mul_neon(float32x2_t{ kW5_0, kW5_1 }, d);
+    const auto d3 = c_mul_neon(float32x2_t{ -kW5_2, -kW5_3 }, d);
 
-    const auto e0 = c_mul_neon(float32x2_t{ W5_0, W5_1 }, e);
-    const auto e1 = c_mul_neon(float32x2_t{ -W5_2, W5_3 }, e);
-    const auto e2 = c_mul_neon(float32x2_t{ -W5_2, -W5_3 }, e);
-    const auto e3 = c_mul_neon(float32x2_t{ W5_0, -W5_1 }, e);
+    const auto e0 = c_mul_neon(float32x2_t{ kW5_0, kW5_1 }, e);
+    const auto e1 = c_mul_neon(float32x2_t{ -kW5_2, kW5_3 }, e);
+    const auto e2 = c_mul_neon(float32x2_t{ -kW5_2, -kW5_3 }, e);
+    const auto e3 = c_mul_neon(float32x2_t{ kW5_0, -kW5_1 }, e);
 
     x1 = reduce_sum_5(a, b, c, d, e);
     x2 = reduce_sum_5(a, b0, c0, d0, e0);
@@ -188,12 +206,6 @@ void fft_5(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     x5 = reduce_sum_5(a, b3, c3, d3, e3);
 }
 
-constexpr float W7_0 = 0.62348980185873f;
-constexpr float W7_1 = 0.78183148246802f;
-constexpr float W7_2 = 0.22252093395631f;
-constexpr float W7_3 = 0.97492791218182f;
-constexpr float W7_4 = 0.90096886790241f;
-constexpr float W7_5 = 0.43388373911755f;
 void fft_7(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, float32x2_t &x5, float32x2_t &x6, float32x2_t &x7, const float32x2_t &w, const float32x2_t &w2, const float32x2_t &w3,
            const float32x2_t &w4,
            const float32x2_t &w5, const float32x2_t &w6)
@@ -206,47 +218,47 @@ void fft_7(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto f = c_mul_neon(w5, x6);
     const auto g = c_mul_neon(w6, x7);
 
-    const auto b0 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, b);
-    const auto b1 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, b);
-    const auto b2 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, b);
-    const auto b3 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, b);
-    const auto b4 = c_mul_neon(float32x2_t{ -W7_2, W7_3 }, b);
-    const auto b5 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, b);
-
-    const auto c0 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, c);
-    const auto c1 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, c);
-    const auto c2 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, c);
-    const auto c3 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, c);
-    const auto c4 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, c);
-    const auto c5 = c_mul_neon(float32x2_t{ -W7_2, W7_3 }, c);
-
-    const auto d0 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, d);
-    const auto d1 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, d);
-    const auto d2 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, d);
-    const auto d3 = c_mul_neon(float32x2_t{ -W7_2, +W7_3 }, d);
-    const auto d4 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, d);
-    const auto d5 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, d);
-
-    const auto e0 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, e);
-    const auto e1 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, e);
-    const auto e2 = c_mul_neon(float32x2_t{ -W7_2, W7_3 }, e);
-    const auto e3 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, e);
-    const auto e4 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, e);
-    const auto e5 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, e);
-
-    const auto f0 = c_mul_neon(float32x2_t{ -W7_2, W7_3 }, f);
-    const auto f1 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, f);
-    const auto f2 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, f);
-    const auto f3 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, f);
-    const auto f4 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, f);
-    const auto f5 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, f);
-
-    const auto g0 = c_mul_neon(float32x2_t{ W7_0, W7_1 }, g);
-    const auto g1 = c_mul_neon(float32x2_t{ -W7_2, W7_3 }, g);
-    const auto g2 = c_mul_neon(float32x2_t{ -W7_4, W7_5 }, g);
-    const auto g3 = c_mul_neon(float32x2_t{ -W7_4, -W7_5 }, g);
-    const auto g4 = c_mul_neon(float32x2_t{ -W7_2, -W7_3 }, g);
-    const auto g5 = c_mul_neon(float32x2_t{ W7_0, -W7_1 }, g);
+    const auto b0 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, b);
+    const auto b1 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, b);
+    const auto b2 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, b);
+    const auto b3 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, b);
+    const auto b4 = c_mul_neon(float32x2_t{ -kW7_2, kW7_3 }, b);
+    const auto b5 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, b);
+
+    const auto c0 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, c);
+    const auto c1 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, c);
+    const auto c2 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, c);
+    const auto c3 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, c);
+    const auto c4 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, c);
+    const auto c5 = c_mul_neon(float32x2_t{ -kW7_2, kW7_3 }, c);
+
+    const auto d0 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, d);
+    const auto d1 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, d);
+    const auto d2 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, d);
+    const auto d3 = c_mul_neon(float32x2_t{ -kW7_2, +kW7_3 }, d);
+    const auto d4 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, d);
+    const auto d5 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, d);
+
+    const auto e0 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, e);
+    const auto e1 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, e);
+    const auto e2 = c_mul_neon(float32x2_t{ -kW7_2, kW7_3 }, e);
+    const auto e3 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, e);
+    const auto e4 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, e);
+    const auto e5 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, e);
+
+    const auto f0 = c_mul_neon(float32x2_t{ -kW7_2, kW7_3 }, f);
+    const auto f1 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, f);
+    const auto f2 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, f);
+    const auto f3 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, f);
+    const auto f4 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, f);
+    const auto f5 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, f);
+
+    const auto g0 = c_mul_neon(float32x2_t{ kW7_0, kW7_1 }, g);
+    const auto g1 = c_mul_neon(float32x2_t{ -kW7_2, kW7_3 }, g);
+    const auto g2 = c_mul_neon(float32x2_t{ -kW7_4, kW7_5 }, g);
+    const auto g3 = c_mul_neon(float32x2_t{ -kW7_4, -kW7_5 }, g);
+    const auto g4 = c_mul_neon(float32x2_t{ -kW7_2, -kW7_3 }, g);
+    const auto g5 = c_mul_neon(float32x2_t{ kW7_0, -kW7_1 }, g);
 
     x1 = reduce_sum_7(a, b, c, d, e, f, g);
     x2 = reduce_sum_7(a, b0, c0, d0, e0, f0, g0);
@@ -257,7 +269,6 @@ void fft_7(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     x7 = reduce_sum_7(a, b5, c5, d5, e5, f5, g5);
 }
 
-constexpr float sqrt2div2 = 0.707106781186548;
 void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, float32x2_t &x5, float32x2_t &x6, float32x2_t &x7, float32x2_t &x8, const float32x2_t &w, const float32x2_t &w2,
            const float32x2_t &w3,
            const float32x2_t &w4, const float32x2_t &w5, const float32x2_t &w6,
@@ -272,13 +283,13 @@ void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto g = c_mul_neon(w6, x7);
     const auto h = c_mul_neon(w7, x8);
 
-    const auto b0 = c_mul_neon(float32x2_t{ sqrt2div2, -sqrt2div2 }, b);
+    const auto b0 = c_mul_neon(float32x2_t{ kSqrt2Div2, -kSqrt2Div2 }, b);
     const auto b1 = c_mul_neon(float32x2_t{ 0, -1 }, b);
-    const auto b2 = c_mul_neon(float32x2_t{ -sqrt2div2, -sqrt2div2 }, b);
+    const auto b2 = c_mul_neon(float32x2_t{ -kSqrt2Div2, -kSqrt2Div2 }, b);
     const auto b3 = c_mul_neon(float32x2_t{ -1, 0 }, b);
-    const auto b4 = c_mul_neon(float32x2_t{ -sqrt2div2, sqrt2div2 }, b);
+    const auto b4 = c_mul_neon(float32x2_t{ -kSqrt2Div2, kSqrt2Div2 }, b);
     const auto b5 = c_mul_neon(float32x2_t{ 0, 1 }, b);
-    const auto b6 = c_mul_neon(float32x2_t{ sqrt2div2, sqrt2div2 }, b);
+    const auto b6 = c_mul_neon(float32x2_t{ kSqrt2Div2, kSqrt2Div2 }, b);
 
     const auto c0 = c_mul_neon(float32x2_t{ 0, -1 }, c);
     const auto c1 = c_mul_neon(float32x2_t{ -1, 0 }, c);
@@ -288,13 +299,13 @@ void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto c5 = c_mul_neon(float32x2_t{ -1, 0 }, c);
     const auto c6 = c_mul_neon(float32x2_t{ 0, 1 }, c);
 
-    const auto d0 = c_mul_neon(float32x2_t{ -sqrt2div2, -sqrt2div2 }, d);
+    const auto d0 = c_mul_neon(float32x2_t{ -kSqrt2Div2, -kSqrt2Div2 }, d);
     const auto d1 = c_mul_neon(float32x2_t{ 0, 1 }, d);
-    const auto d2 = c_mul_neon(float32x2_t{ sqrt2div2, -sqrt2div2 }, d);
+    const auto d2 = c_mul_neon(float32x2_t{ kSqrt2Div2, -kSqrt2Div2 }, d);
     const auto d3 = c_mul_neon(float32x2_t{ -1, 0 }, d);
-    const auto d4 = c_mul_neon(float32x2_t{ sqrt2div2, sqrt2div2 }, d);
+    const auto d4 = c_mul_neon(float32x2_t{ kSqrt2Div2, kSqrt2Div2 }, d);
     const auto d5 = c_mul_neon(float32x2_t{ 0, -1 }, d);
-    const auto d6 = c_mul_neon(float32x2_t{ -sqrt2div2, sqrt2div2 }, d);
+    const auto d6 = c_mul_neon(float32x2_t{ -kSqrt2Div2, kSqrt2Div2 }, d);
 
     const auto e0 = c_mul_neon(float32x2_t{ -1, 0 }, e);
     const auto e1 = c_mul_neon(float32x2_t{ 1, 0 }, e);
@@ -304,13 +315,13 @@ void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto e5 = c_mul_neon(float32x2_t{ 1, 0 }, e);
     const auto e6 = c_mul_neon(float32x2_t{ -1, 0 }, e);
 
-    const auto f0 = c_mul_neon(float32x2_t{ -sqrt2div2, sqrt2div2 }, f);
+    const auto f0 = c_mul_neon(float32x2_t{ -kSqrt2Div2, kSqrt2Div2 }, f);
     const auto f1 = c_mul_neon(float32x2_t{ 0, -1 }, f);
-    const auto f2 = c_mul_neon(float32x2_t{ sqrt2div2, sqrt2div2 }, f);
+    const auto f2 = c_mul_neon(float32x2_t{ kSqrt2Div2, kSqrt2Div2 }, f);
     const auto f3 = c_mul_neon(float32x2_t{ -1, 0 }, f);
-    const auto f4 = c_mul_neon(float32x2_t{ sqrt2div2, -sqrt2div2 }, f);
+    const auto f4 = c_mul_neon(float32x2_t{ kSqrt2Div2, -kSqrt2Div2 }, f);
     const auto f5 = c_mul_neon(float32x2_t{ 0, 1 }, f);
-    const auto f6 = c_mul_neon(float32x2_t{ -sqrt2div2, -sqrt2div2 }, f);
+    const auto f6 = c_mul_neon(float32x2_t{ -kSqrt2Div2, -kSqrt2Div2 }, f);
 
     const auto g0 = c_mul_neon(float32x2_t{ 0, 1 }, g);
     const auto g1 = c_mul_neon(float32x2_t{ -1, 0 }, g);
@@ -320,13 +331,13 @@ void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
     const auto g5 = c_mul_neon(float32x2_t{ -1, 0 }, g);
     const auto g6 = c_mul_neon(float32x2_t{ 0, -1 }, g);
 
-    const auto h0 = c_mul_neon(float32x2_t{ sqrt2div2, sqrt2div2 }, h);
+    const auto h0 = c_mul_neon(float32x2_t{ kSqrt2Div2, kSqrt2Div2 }, h);
     const auto h1 = c_mul_neon(float32x2_t{ 0, 1 }, h);
-    const auto h2 = c_mul_neon(float32x2_t{ -sqrt2div2, sqrt2div2 }, h);
+    const auto h2 = c_mul_neon(float32x2_t{ -kSqrt2Div2, kSqrt2Div2 }, h);
     const auto h3 = c_mul_neon(float32x2_t{ -1, 0 }, h);
-    const auto h4 = c_mul_neon(float32x2_t{ -sqrt2div2, -sqrt2div2 }, h);
+    const auto h4 = c_mul_neon(float32x2_t{ -kSqrt2Div2, -kSqrt2Div2 }, h);
     const auto h5 = c_mul_neon(float32x2_t{ 0, -1 }, h);
-    const auto h6 = c_mul_neon(float32x2_t{ sqrt2div2, -sqrt2div2 }, h);
+    const auto h6 = c_mul_neon(float32x2_t{ kSqrt2Div2, -kSqrt2Div2 }, h);
 
     x1 = reduce_sum_8(a, b, c, d, e, f, g, h);
     x2 = reduce_sum_8(a, b0, c0, d0, e0, f0, g0, h0);
@@ -339,17 +350,12 @@ void fft_8(float32x2_t &x1, float32x2_t &x2, float32x2_t &x3, float32x2_t &x4, f
 }
 
 template <bool first_stage>
-void fft_radix_2_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_2_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
 {
-    unsigned int Nx2   = 2 * Nx;
-    float        alpha = 2 * PI / Nx2;
-
-    float32x2_t       w{ 1, 0 };
-    const float32x2_t w_m{ cosf(alpha), -sinf(alpha) };
-
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx2)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             auto a = float32x2_t{ 0, 0 };
             auto b = float32x2_t{ 0, 0 };
@@ -386,19 +392,38 @@ void fft_radix_2_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
-template <bool first_stage>
-void fft_radix_3_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_2_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
 {
-    const unsigned int Nx3   = 3 * Nx;
-    const float        alpha = 2 * PI / float(Nx3);
-    float32x2_t        w{ 1, 0 };
-    const float32x2_t  w_m{ cosf(alpha), -sinf(alpha) };
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
 
+            // Base-case prime transform
+            fft_2(a, b, w);
+
+            // Write outputs
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+        }
+
+        w = c_mul_neon(w, w_m);
+    }
+}
+
+template <bool first_stage>
+void fft_radix_3_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
         const auto w2 = c_mul_neon(w, w);
 
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx3)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             // Load inputs
             float32x2_t a = { 0, 0 };
@@ -435,21 +460,42 @@ void fft_radix_3_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
-template <bool first_stage>
-void fft_radix_4_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_3_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
 {
-    unsigned int Nx4   = 4 * Nx;
-    const float  alpha = 2 * PI / float(Nx4);
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        const auto w2 = c_mul_neon(w, w);
+
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
+            float32x2_t c = wrapper::vload(x + M * (k + 4 * Nx));
+
+            // Base-case prime transform
+            fft_3(a, b, c, w, w2);
 
-    float32x2_t w{ 1, 0 };
-    float32x2_t w_m{ cosf(alpha), -sinf(alpha) };
+            // Store the output
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+            wrapper::vstore(X + M * (k + 4 * Nx), c);
+        }
+        w = c_mul_neon(w, w_m);
+    }
+}
 
+template <bool first_stage>
+void fft_radix_4_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
         const auto w2 = c_mul_neon(w, w);
         const auto w3 = c_mul_neon(w2, w);
 
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx4)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             float32x2_t a = { 0, 0 };
             float32x2_t b = { 0, 0 };
@@ -494,22 +540,46 @@ void fft_radix_4_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
-template <bool first_stage>
-void fft_radix_5_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_4_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
 {
-    unsigned int Nx5   = 5 * Nx;
-    const float  alpha = 2 * PI / float(Nx5);
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        const auto w2 = c_mul_neon(w, w);
+        const auto w3 = c_mul_neon(w2, w);
+
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
+            float32x2_t c = wrapper::vload(x + M * (k + 4 * Nx));
+            float32x2_t d = wrapper::vload(x + M * (k + 6 * Nx));
+
+            // Base-case prime transform
+            fft_4(a, b, c, d, w, w2, w3);
 
-    float32x2_t w{ 1, 0 };
-    float32x2_t w_m{ cosf(alpha), -sinf(alpha) };
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+            wrapper::vstore(X + M * (k + 4 * Nx), c);
+            wrapper::vstore(X + M * (k + 6 * Nx), d);
+        }
+
+        w = c_mul_neon(w, w_m);
+    }
+}
 
+template <bool first_stage>
+void fft_radix_5_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
         const float32x2_t w2 = c_mul_neon(w, w);
         const float32x2_t w3 = c_mul_neon(w2, w);
         const float32x2_t w4 = c_mul_neon(w3, w);
 
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx5)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             float32x2_t a = { 0, 0 };
             float32x2_t b = { 0, 0 };
@@ -560,15 +630,43 @@ void fft_radix_5_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
-template <bool first_stage>
-void fft_radix_7_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_5_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
 {
-    unsigned int Nx7   = 7 * Nx;
-    const float  alpha = 2 * PI / float(Nx7);
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        const float32x2_t w2 = c_mul_neon(w, w);
+        const float32x2_t w3 = c_mul_neon(w2, w);
+        const float32x2_t w4 = c_mul_neon(w3, w);
 
-    float32x2_t w{ 1, 0 };
-    float32x2_t w_m{ cosf(alpha), -sinf(alpha) };
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
+            float32x2_t c = wrapper::vload(x + M * (k + 4 * Nx));
+            float32x2_t d = wrapper::vload(x + M * (k + 6 * Nx));
+            float32x2_t e = wrapper::vload(x + M * (k + 8 * Nx));
+
+            // Base-case prime transform
+            fft_5(a, b, c, d, e, w, w2, w3, w4);
+
+            // Store outputs
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+            wrapper::vstore(X + M * (k + 4 * Nx), c);
+            wrapper::vstore(X + M * (k + 6 * Nx), d);
+            wrapper::vstore(X + M * (k + 8 * Nx), e);
+        }
+
+        w = c_mul_neon(w, w_m);
+    }
+}
 
+template <bool first_stage>
+void fft_radix_7_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
         const float32x2_t w2 = c_mul_neon(w, w);
@@ -577,7 +675,7 @@ void fft_radix_7_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
         const float32x2_t w5 = c_mul_neon(w4, w);
         const float32x2_t w6 = c_mul_neon(w5, w);
 
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx7)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             float32x2_t a = { 0, 0 };
             float32x2_t b = { 0, 0 };
@@ -637,15 +735,49 @@ void fft_radix_7_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
-template <bool first_stage>
-void fft_radix_8_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
+void fft_radix_7_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
 {
-    unsigned int Nx8   = 8 * Nx;
-    const float  alpha = 2 * PI / float(Nx8);
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        const float32x2_t w2 = c_mul_neon(w, w);
+        const float32x2_t w3 = c_mul_neon(w2, w);
+        const float32x2_t w4 = c_mul_neon(w3, w);
+        const float32x2_t w5 = c_mul_neon(w4, w);
+        const float32x2_t w6 = c_mul_neon(w5, w);
 
-    float32x2_t       w{ 1, 0 };
-    const float32x2_t w_m{ cosf(alpha), -sinf(alpha) };
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
+            float32x2_t c = wrapper::vload(x + M * (k + 4 * Nx));
+            float32x2_t d = wrapper::vload(x + M * (k + 6 * Nx));
+            float32x2_t e = wrapper::vload(x + M * (k + 8 * Nx));
+            float32x2_t f = wrapper::vload(x + M * (k + 10 * Nx));
+            float32x2_t g = wrapper::vload(x + M * (k + 12 * Nx));
+
+            // Base-case prime transform
+            fft_7(a, b, c, d, e, f, g, w, w2, w3, w4, w5, w6);
+
+            // Store outputs
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+            wrapper::vstore(X + M * (k + 4 * Nx), c);
+            wrapper::vstore(X + M * (k + 6 * Nx), d);
+            wrapper::vstore(X + M * (k + 8 * Nx), e);
+            wrapper::vstore(X + M * (k + 10 * Nx), f);
+            wrapper::vstore(X + M * (k + 12 * Nx), g);
+        }
+
+        w = c_mul_neon(w, w_m);
+    }
+}
 
+template <bool first_stage>
+void fft_radix_8_axes_0(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
     for(unsigned int j = 0; j < Nx; j++)
     {
         const float32x2_t w2 = c_mul_neon(w, w);
@@ -655,7 +787,7 @@ void fft_radix_8_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
         const float32x2_t w6 = c_mul_neon(w5, w);
         const float32x2_t w7 = c_mul_neon(w6, w);
 
-        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * Nx8)
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
         {
             // Load inputs
             float32x2_t a = { 0, 0 };
@@ -724,11 +856,54 @@ void fft_radix_8_axes_0(float *X, float *x, unsigned int Nx, unsigned int N)
     }
 }
 
+void fft_radix_8_axes_1(float *X, float *x, unsigned int Nx, unsigned int NxRadix, const float32x2_t &w_m, unsigned int M, unsigned int N)
+{
+    float32x2_t w{ 1.0f, 0.0f };
+    for(unsigned int j = 0; j < Nx; j++)
+    {
+        const float32x2_t w2 = c_mul_neon(w, w);
+        const float32x2_t w3 = c_mul_neon(w2, w);
+        const float32x2_t w4 = c_mul_neon(w3, w);
+        const float32x2_t w5 = c_mul_neon(w4, w);
+        const float32x2_t w6 = c_mul_neon(w5, w);
+        const float32x2_t w7 = c_mul_neon(w6, w);
+
+        for(unsigned int k = 2 * j; k < 2 * N; k += 2 * NxRadix)
+        {
+            // Load inputs
+            float32x2_t a = wrapper::vload(x + M * k);
+            float32x2_t b = wrapper::vload(x + M * (k + 2 * Nx));
+            float32x2_t c = wrapper::vload(x + M * (k + 4 * Nx));
+            float32x2_t d = wrapper::vload(x + M * (k + 6 * Nx));
+            float32x2_t e = wrapper::vload(x + M * (k + 8 * Nx));
+            float32x2_t f = wrapper::vload(x + M * (k + 10 * Nx));
+            float32x2_t g = wrapper::vload(x + M * (k + 12 * Nx));
+            float32x2_t h = wrapper::vload(x + M * (k + 14 * Nx));
+
+            // Base-case prime transform
+            fft_8(a, b, c, d, e, f, g, h, w, w2, w3, w4, w5, w6, w7);
+
+            // Store outputs
+            wrapper::vstore(X + M * k, a);
+            wrapper::vstore(X + M * (k + 2 * Nx), b);
+            wrapper::vstore(X + M * (k + 4 * Nx), c);
+            wrapper::vstore(X + M * (k + 6 * Nx), d);
+            wrapper::vstore(X + M * (k + 8 * Nx), e);
+            wrapper::vstore(X + M * (k + 10 * Nx), f);
+            wrapper::vstore(X + M * (k + 12 * Nx), g);
+            wrapper::vstore(X + M * (k + 14 * Nx), h);
+        }
+
+        w = c_mul_neon(w, w_m);
+    }
+}
+
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const FFTRadixStageKernelInfo &config)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 2, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON(config.axis != 0);
+    ARM_COMPUTE_RETURN_ERROR_ON(config.axis > 1);
     ARM_COMPUTE_RETURN_ERROR_ON(NEFFTRadixStageKernel::supported_radix().count(config.radix) == 0);
+    ARM_COMPUTE_UNUSED(config);
 
     // Checks performed when output is configured
     if((output != nullptr) && (output->total_size() != 0))
@@ -742,12 +917,14 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
 
 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const FFTRadixStageKernelInfo &config)
 {
+    ARM_COMPUTE_UNUSED(config);
+
     if(output != nullptr)
     {
         auto_init_if_empty(*output, *input);
     }
 
-    Window win = calculate_max_window(*input, Steps(config.radix));
+    Window win = calculate_max_window(*input, Steps());
     if(output != nullptr)
     {
         output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
@@ -758,36 +935,51 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
 } // namespace
 
 NEFFTRadixStageKernel::NEFFTRadixStageKernel()
-    : _input(nullptr), _output(nullptr), _run_in_place(false), _Nx(0), _func()
+    : _input(nullptr), _output(nullptr), _run_in_place(false), _Nx(0), _axis(0), _radix(0), _func_0(), _func_1()
 {
 }
 
-template <bool first_stage>
-void NEFFTRadixStageKernel::set_radix_stage_fun(unsigned int radix)
+void NEFFTRadixStageKernel::set_radix_stage_axis0(const FFTRadixStageKernelInfo &config)
 {
-    switch(radix)
+    // FFT table axis 0: [radix, first_stage]
+    static std::map<unsigned int, std::map<bool, FFTFunctionPointerAxis0>> fft_table_axis0;
+
+    if(fft_table_axis0.empty())
     {
-        case 2:
-            _func = &fft_radix_2_axes_0<first_stage>;
-            break;
-        case 3:
-            _func = &fft_radix_3_axes_0<first_stage>;
-            break;
-        case 4:
-            _func = &fft_radix_4_axes_0<first_stage>;
-            break;
-        case 5:
-            _func = &fft_radix_5_axes_0<first_stage>;
-            break;
-        case 7:
-            _func = &fft_radix_7_axes_0<first_stage>;
-            break;
-        case 8:
-            _func = &fft_radix_8_axes_0<first_stage>;
-            break;
-        default:
-            ARM_COMPUTE_ERROR("Radix not supported");
+        fft_table_axis0[2][false] = &fft_radix_2_axes_0<false>;
+        fft_table_axis0[3][false] = &fft_radix_3_axes_0<false>;
+        fft_table_axis0[4][false] = &fft_radix_4_axes_0<false>;
+        fft_table_axis0[5][false] = &fft_radix_5_axes_0<false>;
+        fft_table_axis0[7][false] = &fft_radix_7_axes_0<false>;
+        fft_table_axis0[8][false] = &fft_radix_8_axes_0<false>;
+
+        fft_table_axis0[2][true] = &fft_radix_2_axes_0<true>;
+        fft_table_axis0[3][true] = &fft_radix_3_axes_0<true>;
+        fft_table_axis0[4][true] = &fft_radix_4_axes_0<true>;
+        fft_table_axis0[5][true] = &fft_radix_5_axes_0<true>;
+        fft_table_axis0[7][true] = &fft_radix_7_axes_0<true>;
+        fft_table_axis0[8][true] = &fft_radix_8_axes_0<true>;
+    }
+
+    _func_0 = fft_table_axis0[config.radix][config.is_first_stage];
+}
+
+void NEFFTRadixStageKernel::set_radix_stage_axis1(const FFTRadixStageKernelInfo &config)
+{
+    // FFT table axis 1: [radix, first_stage]
+    static std::map<unsigned int, FFTFunctionPointerAxis1> fft_table_axis1;
+
+    if(fft_table_axis1.empty())
+    {
+        fft_table_axis1[2] = &fft_radix_2_axes_1;
+        fft_table_axis1[3] = &fft_radix_3_axes_1;
+        fft_table_axis1[4] = &fft_radix_4_axes_1;
+        fft_table_axis1[5] = &fft_radix_5_axes_1;
+        fft_table_axis1[7] = &fft_radix_7_axes_1;
+        fft_table_axis1[8] = &fft_radix_8_axes_1;
     }
+
+    _func_1 = fft_table_axis1[config.radix];
 }
 
 void NEFFTRadixStageKernel::configure(ITensor *input, ITensor *output, const FFTRadixStageKernelInfo &config)
@@ -806,14 +998,20 @@ void NEFFTRadixStageKernel::configure(ITensor *input, ITensor *output, const FFT
     _output       = output;
     _run_in_place = (output == nullptr) || (output == input);
     _Nx           = config.Nx;
+    _axis         = config.axis;
+    _radix        = config.radix;
 
-    if(config.is_first_stage)
-    {
-        set_radix_stage_fun<true>(config.radix);
-    }
-    else
+    switch(config.axis)
     {
-        set_radix_stage_fun<false>(config.radix);
+        case 0:
+            set_radix_stage_axis0(config);
+            break;
+        case 1:
+            set_radix_stage_axis1(config);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Axis not supported");
+            break;
     }
 
     // Configure kernel window
@@ -841,23 +1039,40 @@ std::set<unsigned int> NEFFTRadixStageKernel::supported_radix()
 
 void NEFFTRadixStageKernel::run(const Window &window, const ThreadInfo &info)
 {
-    ARM_COMPUTE_UNUSED(info);
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+    ARM_COMPUTE_UNUSED(info);
 
     Window input_window = window;
-    input_window.set(Window::DimX, 0);
-
-    unsigned int N = _input->info()->dimension(0);
+    input_window.set(_axis, 0);
 
     Iterator in(_input, input_window);
     Iterator out(_run_in_place ? _input : _output, input_window);
 
-    execute_window_loop(input_window, [&](const Coordinates &)
+    // Precompute FFT constants
+    const unsigned int NxRadix = _radix * _Nx;
+    const float        alpha   = 2.0f * kPi / float(NxRadix);
+    const float32x2_t  w_m{ cosf(alpha), -sinf(alpha) };
+
+    if(_axis == 0)
+    {
+        const unsigned int N = _input->info()->dimension(0);
+        execute_window_loop(input_window, [&](const Coordinates &)
+        {
+            _func_0(reinterpret_cast<float *>(out.ptr()), reinterpret_cast<float *>(in.ptr()), _Nx, NxRadix, w_m, N);
+        },
+        in, out);
+    }
+    else
     {
-        _func(reinterpret_cast<float *>(out.ptr()), reinterpret_cast<float *>(in.ptr()), _Nx, N);
-    },
-    in, out);
+        const unsigned int N = _input->info()->dimension(0);
+        const unsigned int M = _input->info()->dimension(1);
+        execute_window_loop(input_window, [&](const Coordinates &)
+        {
+            _func_1(reinterpret_cast<float *>(out.ptr()), reinterpret_cast<float *>(in.ptr()), _Nx, NxRadix, w_m, N, M);
+        },
+        in, out);
+    }
 
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
diff --git a/src/core/NEON/kernels/NEFFTScaleKernel.cpp b/src/core/NEON/kernels/NEFFTScaleKernel.cpp
new file mode 100644
index 0000000000..6568755e5d
--- /dev/null
+++ b/src/core/NEON/kernels/NEFFTScaleKernel.cpp
@@ -0,0 +1,136 @@
+/*
+ * Copyright (c) 2019 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 "arm_compute/core/NEON/kernels/NEFFTScaleKernel.h"
+
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <arm_neon.h>
+
+namespace arm_compute
+{
+namespace
+{
+void scale_complex(float *c_in, float *c_out, bool is_conjugate, float scale)
+{
+    const auto a = wrapper::vload(c_in);
+    auto       b = wrapper::vdiv(a, float32x2_t{ scale, scale });
+    if(is_conjugate)
+    {
+        const float img_part = wrapper::vgetlane(b, 1);
+        b                    = wrapper::vsetlane(-img_part, b, 1);
+    }
+
+    wrapper::vstore(c_out, b);
+}
+
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 2, DataType::F32);
+
+    // Checks performed when output is configured
+    if((output != nullptr) && (output->total_size() != 0))
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON(output->num_channels() != 1 && output->num_channels() != 2);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+    }
+
+    return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+{
+    // Configure kernel window
+    Window win = calculate_max_window(*input, Steps());
+
+    if(output != nullptr)
+    {
+        // Output auto inizialitation if not yet initialized
+        auto_init_if_empty(*output, *input->clone());
+
+        // NEFFTScaleKernel doesn't need padding so update_window_and_padding() can be skipped
+        Coordinates coord;
+        coord.set_num_dimensions(output->num_dimensions());
+        output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+    }
+
+    return std::make_pair(Status{}, win);
+}
+} // namespace
+
+NEFFTScaleKernel::NEFFTScaleKernel()
+    : _input(nullptr), _output(nullptr), _scale(), _run_in_place(false), _is_conj(false)
+{
+}
+
+void NEFFTScaleKernel::configure(ITensor *input, ITensor *output, const FFTScaleKernelInfo &config)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr));
+
+    _input        = input;
+    _output       = output;
+    _run_in_place = (output == nullptr) || (output == input);
+    _is_conj      = config.conjugate;
+    _scale        = config.scale;
+
+    // Configure kernel window
+    auto win_config = validate_and_configure_window(input->info(), _run_in_place ? nullptr : output->info());
+    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+    INEKernel::configure(win_config.second);
+}
+
+Status NEFFTScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const FFTScaleKernelInfo &config)
+{
+    ARM_COMPUTE_UNUSED(config);
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+
+    return Status{};
+}
+
+void NEFFTScaleKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+    ARM_COMPUTE_UNUSED(info);
+
+    Window input_window = window;
+    input_window.set(Window::DimX, 0);
+
+    Iterator in(_input, input_window);
+    Iterator out(_run_in_place ? _input : _output, input_window);
+
+    execute_window_loop(window, [&](const Coordinates &)
+    {
+        scale_complex(reinterpret_cast<float *>(out.ptr()), reinterpret_cast<float *>(in.ptr()), _is_conj, _scale);
+    },
+    in, out);
+}
+} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEFFT1D.cpp b/src/runtime/NEON/functions/NEFFT1D.cpp
index d3ff674a2a..665efeb440 100644
--- a/src/runtime/NEON/functions/NEFFT1D.cpp
+++ b/src/runtime/NEON/functions/NEFFT1D.cpp
@@ -31,7 +31,7 @@
 namespace arm_compute
 {
 NEFFT1D::NEFFT1D(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _digit_reversed_input(), _digit_reverse_indices(), _digit_reverse_kernel(), _fft_kernels(), _n_ffts(0)
+    : _memory_group(std::move(memory_manager)), _digit_reverse_kernel(), _fft_kernels(), _scale_kernel(), _digit_reversed_input(), _digit_reverse_indices(), _num_ffts(0), _axis(0), _run_scale(false)
 {
 }
 
@@ -43,6 +43,11 @@ void NEFFT1D::configure(const ITensor *input, ITensor *output, const FFT1DInfo &
     const auto         decomposed_vector = arm_compute::helpers::fft::decompose_stages(N, supported_radix);
     ARM_COMPUTE_ERROR_ON(decomposed_vector.empty());
 
+    // Flags
+    _run_scale        = config.direction == FFTDirection::Inverse;
+    _axis             = config.axis;
+    const bool is_c2r = input->info()->num_channels() == 2 && output->info()->num_channels() == 1;
+
     // Configure digit reverse
     TensorInfo digit_reverse_indices_info(TensorShape(input->info()->tensor_shape()[config.axis]), 1, DataType::U32);
     _digit_reverse_indices.allocator()->init(digit_reverse_indices_info);
@@ -51,19 +56,19 @@ void NEFFT1D::configure(const ITensor *input, ITensor *output, const FFT1DInfo &
 
     // Create and configure FFT kernels
     unsigned int Nx = 1;
-    _n_ffts         = decomposed_vector.size();
-    _fft_kernels.resize(_n_ffts);
-    for(unsigned int i = 0; i < _n_ffts; ++i)
+
+    _num_ffts = decomposed_vector.size();
+    _fft_kernels.resize(_num_ffts);
+    for(unsigned int i = 0; i < _num_ffts; ++i)
     {
         const unsigned int radix_for_stage = decomposed_vector.at(i);
 
-        FFTRadixStageKernelInfo fft_kernel_desc;
-        fft_kernel_desc.axis           = config.axis;
-        fft_kernel_desc.radix          = radix_for_stage;
-        fft_kernel_desc.Nx             = Nx;
-        fft_kernel_desc.is_first_stage = (i == 0);
-        _fft_kernels[i].configure(&_digit_reversed_input, i == (_n_ffts - 1) ? output : nullptr, fft_kernel_desc);
-
+        FFTRadixStageKernelInfo fft_kernel_info;
+        fft_kernel_info.axis           = config.axis;
+        fft_kernel_info.radix          = radix_for_stage;
+        fft_kernel_info.Nx             = Nx;
+        fft_kernel_info.is_first_stage = (i == 0);
+        _fft_kernels[i].configure(&_digit_reversed_input, i == (_num_ffts - 1) && !is_c2r ? output : nullptr, fft_kernel_info);
         Nx *= radix_for_stage;
     }
 
@@ -80,7 +85,7 @@ Status NEFFT1D::validate(const ITensorInfo *input, const ITensorInfo *output, co
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 2, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON(config.axis != 0);
+    ARM_COMPUTE_RETURN_ERROR_ON(config.axis > 1);
 
     // Check if FFT is decomposable
     const auto         supported_radix   = NEFFTRadixStageKernel::supported_radix();
@@ -102,11 +107,17 @@ void NEFFT1D::run()
 {
     MemoryGroupResourceScope scope_mg(_memory_group);
 
-    NEScheduler::get().schedule(&_digit_reverse_kernel, Window::DimY);
+    NEScheduler::get().schedule(&_digit_reverse_kernel, (_axis == 0 ? Window::DimY : Window::DimX));
+
+    for(unsigned int i = 0; i < _num_ffts; ++i)
+    {
+        NEScheduler::get().schedule(&_fft_kernels[i], (_axis == 0 ? Window::DimY : Window::DimX));
+    }
 
-    for(unsigned int i = 0; i < _n_ffts; ++i)
+    // Run output scaling
+    if(_run_scale)
     {
-        NEScheduler::get().schedule(&_fft_kernels[i], Window::DimY);
+        NEScheduler::get().schedule(&_scale_kernel, Window::DimY);
     }
 }
 } // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEFFT2D.cpp b/src/runtime/NEON/functions/NEFFT2D.cpp
new file mode 100644
index 0000000000..9210ecfa2e
--- /dev/null
+++ b/src/runtime/NEON/functions/NEFFT2D.cpp
@@ -0,0 +1,95 @@
+/*
+ * Copyright (c) 2019 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 "arm_compute/runtime/NEON/functions/NEFFT2D.h"
+
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/runtime/Scheduler.h"
+
+namespace arm_compute
+{
+NEFFT2D::NEFFT2D(std::shared_ptr<IMemoryManager> memory_manager)
+    : _memory_group(memory_manager), _first_pass_func(memory_manager), _second_pass_func(memory_manager), _first_pass_tensor()
+{
+}
+
+void NEFFT2D::configure(const ITensor *input, ITensor *output, const FFT2DInfo &config)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(NEFFT2D::validate(input->info(), output->info(), config));
+
+    // Setup first pass
+    FFT1DInfo first_pass_config;
+    first_pass_config.axis      = config.axes.first;
+    first_pass_config.direction = config.direction;
+    _memory_group.manage(&_first_pass_tensor);
+    _first_pass_func.configure(input, &_first_pass_tensor, first_pass_config);
+
+    // Setup second pass
+    FFT1DInfo second_pass_config;
+    second_pass_config.axis      = config.axes.second;
+    second_pass_config.direction = config.direction;
+    _second_pass_func.configure(&_first_pass_tensor, output, second_pass_config);
+    _first_pass_tensor.allocator()->allocate();
+}
+
+Status NEFFT2D::validate(const ITensorInfo *input, const ITensorInfo *output, const FFT2DInfo &config)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+
+    // Create intermediate tensor info
+    TensorInfo first_pass_tensor(input->clone()->set_is_resizable(true).reset_padding().set_num_channels(2));
+
+    // Validate first pass
+    FFT1DInfo first_pass_config;
+    first_pass_config.axis      = config.axes.first;
+    first_pass_config.direction = config.direction;
+    ARM_COMPUTE_RETURN_ON_ERROR(NEFFT1D::validate(input, &first_pass_tensor, first_pass_config));
+
+    // Validate second pass
+    FFT1DInfo second_pass_config;
+    second_pass_config.axis      = config.axes.second;
+    second_pass_config.direction = config.direction;
+    ARM_COMPUTE_RETURN_ON_ERROR(NEFFT1D::validate(&first_pass_tensor, output, second_pass_config));
+
+    // Checks performed when output is configured
+    if((output != nullptr) && (output->total_size() != 0))
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+    }
+
+    return Status{};
+}
+
+void NEFFT2D::run()
+{
+    _memory_group.acquire();
+
+    _first_pass_func.run();
+    _second_pass_func.run();
+
+    _memory_group.release();
+}
+} // namespace arm_compute
diff --git a/tests/validation/NEON/FFT.cpp b/tests/validation/NEON/FFT.cpp
index 14fb7e2518..598c8bb10d 100644
--- a/tests/validation/NEON/FFT.cpp
+++ b/tests/validation/NEON/FFT.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/NEON/functions/NEFFT1D.h"
+#include "arm_compute/runtime/NEON/functions/NEFFT2D.h"
 #include "arm_compute/runtime/Tensor.h"
 #include "tests/NEON/Accessor.h"
 #include "tests/framework/Asserts.h"
@@ -49,6 +50,13 @@ const auto shapes_1d  = framework::dataset::make("TensorShape", { TensorShape(2U
                                                                   TensorShape(96U, 2U, 2U)
                                                                 });
 
+const auto shapes_2d = framework::dataset::make("TensorShape", { TensorShape(2U, 2U, 3U), TensorShape(3U, 6U, 3U),
+                                                                 TensorShape(4U, 5U, 3U), TensorShape(5U, 7U, 3U),
+                                                                 TensorShape(7U, 25U, 3U), TensorShape(8U, 2U, 3U),
+                                                                 TensorShape(9U, 16U, 3U), TensorShape(25U, 32U, 3U),
+                                                                 TensorShape(192U, 128U, 2U)
+                                                               });
+
 const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
 {
     ActivationLayerInfo(),
@@ -127,8 +135,72 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEFFT1DFixture<float>, framework::DatasetMode::
 }
 TEST_SUITE_END() // FP32
 TEST_SUITE_END() // Float
-
 TEST_SUITE_END() // FFT1D
+
+TEST_SUITE(FFT2D)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(shapes_2d, data_types),
+               shape, data_type)
+{
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type, 2);
+    Tensor dst = create_tensor<Tensor>(shape, data_type, 2);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEFFT2D fft2d;
+    fft2d.configure(&src, &dst, FFT2DInfo());
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(src.info()->valid_region(), valid_region);
+    validate(dst.info()->valid_region(), valid_region);
+
+    // Validate padding
+    validate(src.info()->padding(), PaddingSize());
+    validate(dst.info()->padding(), PaddingSize());
+}
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
+        framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32), // Mismatching data types
+                                                TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32), // Mismatching shapes
+                                                TensorInfo(TensorShape(32U, 25U, 2U), 3, DataType::F32), // Invalid channels
+                                                TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32), // Undecomposable FFT
+                                                TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32),
+        }),
+        framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F16),
+                                                TensorInfo(TensorShape(16U, 25U, 2U), 2, DataType::F32),
+                                                TensorInfo(TensorShape(32U, 25U, 2U), 1, DataType::F32),
+                                                TensorInfo(TensorShape(32U, 13U, 2U), 2, DataType::F32),
+                                                TensorInfo(TensorShape(32U, 25U, 2U), 2, DataType::F32),
+        })),
+        framework::dataset::make("Expected", { false, false, false, false, true })),
+               input_info, output_info, expected)
+{
+    const Status s = NEFFT2D::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), FFT2DInfo());
+    ARM_COMPUTE_EXPECT(bool(s) == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using NEFFT2DFixture = FFTValidationFixture<Tensor, Accessor, NEFFT2D, FFT2DInfo, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEFFT2DFixture<float>, framework::DatasetMode::ALL, combine(shapes_2d, framework::dataset::make("DataType", DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance_f32, tolerance_num);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // FFT2D
+
 TEST_SUITE_END() // NEON
 } // namespace validation
 } // namespace test