Fork of mbed-dsp. CMSIS-DSP library of supporting NEON

Dependents:   mbed-os-example-cmsis_dsp_neon

Fork of mbed-dsp by mbed official

Information

Japanese version is available in lower part of this page.
このページの後半に日本語版が用意されています.

CMSIS-DSP of supporting NEON

What is this ?

A library for CMSIS-DSP of supporting NEON.
We supported the NEON to CMSIS-DSP Ver1.4.3(CMSIS V4.1) that ARM supplied, has achieved the processing speed improvement.
If you use the mbed-dsp library, you can use to replace this library.
CMSIS-DSP of supporting NEON is provied as a library.

Library Creation environment

CMSIS-DSP library of supporting NEON was created by the following environment.

  • Compiler
    ARMCC Version 5.03
  • Compile option switch[C Compiler]
   -DARM_MATH_MATRIX_CHECK -DARM_MATH_ROUNDING -O3 -Otime --cpu=Cortex-A9 --littleend --arm 
   --apcs=/interwork --no_unaligned_access --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp 
   --vectorize --asm
  • Compile option switch[Assembler]
   --cpreproc --cpu=Cortex-A9 --littleend --arm --apcs=/interwork --no_unaligned_access 
   --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp


Effects of NEON support

In the data which passes to each function, large size will be expected more effective than small size.
Also if the data is a multiple of 16, effect will be expected in every function in the CMSIS-DSP.


NEON対応CMSIS-DSP

概要

NEON対応したCMSIS-DSPのライブラリです。
ARM社提供のCMSIS-DSP Ver1.4.3(CMSIS V4.1)をターゲットにNEON対応を行ない、処理速度向上を実現しております。
mbed-dspライブラリを使用している場合は、本ライブラリに置き換えて使用することができます。
NEON対応したCMSIS-DSPはライブラリで提供します。

ライブラリ作成環境

NEON対応CMSIS-DSPライブラリは、以下の環境で作成しています。

  • コンパイラ
    ARMCC Version 5.03
  • コンパイルオプションスイッチ[C Compiler]
   -DARM_MATH_MATRIX_CHECK -DARM_MATH_ROUNDING -O3 -Otime --cpu=Cortex-A9 --littleend --arm 
   --apcs=/interwork --no_unaligned_access --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp 
   --vectorize --asm
  • コンパイルオプションスイッチ[Assembler]
   --cpreproc --cpu=Cortex-A9 --littleend --arm --apcs=/interwork --no_unaligned_access 
   --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp


NEON対応による効果について

CMSIS-DSP内の各関数へ渡すデータは、小さいサイズよりも大きいサイズの方が効果が見込めます。
また、16の倍数のデータであれば、CMSIS-DSP内のどの関数でも効果が見込めます。


cmsis_dsp/TransformFunctions/arm_cfft_f32.c

Committer:
mbed_official
Date:
2013-11-08
Revision:
3:7a284390b0ce

File content as of revision 3:7a284390b0ce:

/* ----------------------------------------------------------------------    
* Copyright (C) 2010-2013 ARM Limited. All rights reserved.    
*    
* $Date:        17. January 2013  
* $Revision: 	V1.4.1  
*    
* Project: 	    CMSIS DSP Library    
* Title:	    arm_cfft_f32.c   
*    
* Description:	Combined Radix Decimation in Frequency CFFT Floating point processing function
*    
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*  
* Redistribution and use in source and binary forms, with or without 
* modification, are permitted provided that the following conditions
* are met:
*   - Redistributions of source code must retain the above copyright
*     notice, this list of conditions and the following disclaimer.
*   - Redistributions in binary form must reproduce the above copyright
*     notice, this list of conditions and the following disclaimer in
*     the documentation and/or other materials provided with the 
*     distribution.
*   - Neither the name of ARM LIMITED nor the names of its contributors
*     may be used to endorse or promote products derived from this
*     software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.   
* -------------------------------------------------------------------- */


#include "arm_math.h"
#include "arm_common_tables.h"

extern void arm_radix8_butterfly_f32(
  float32_t * pSrc,
  uint16_t fftLen,
  const float32_t * pCoef,
  uint16_t twidCoefModifier);

extern void arm_bitreversal_32(
		uint32_t * pSrc,
		const uint16_t bitRevLen,
		const uint16_t * pBitRevTable);

/**   
* @ingroup groupTransforms   
*/

/**   
* @defgroup ComplexFFT Complex FFT Functions   
*   
* \par
* The Fast Fourier Transform (FFT) is an efficient algorithm for computing the
* Discrete Fourier Transform (DFT).  The FFT can be orders of magnitude faster
* than the DFT, especially for long lengths.
* The algorithms described in this section
* operate on complex data.  A separate set of functions is devoted to handling
* of real sequences.
* \par
* There are separate algorithms for handling floating-point, Q15, and Q31 data
* types.  The algorithms available for each data type are described next.
* \par
* The FFT functions operate in-place.  That is, the array holding the input data
* will also be used to hold the corresponding result.  The input data is complex
* and contains <code>2*fftLen</code> interleaved values as shown below.
* <pre> {real[0], imag[0], real[1], imag[1],..} </pre>
* The FFT result will be contained in the same array and the frequency domain
* values will have the same interleaving.
*
* \par Floating-point
* The floating-point complex FFT uses a mixed-radix algorithm.  Multiple radix-8
* stages are performed along with a single radix-2 or radix-4 stage, as needed.
* The algorithm supports lengths of [16, 32, 64, ..., 4096] and each length uses
* a different twiddle factor table.  
* \par
* The function uses the standard FFT definition and output values may grow by a
* factor of <code>fftLen</code> when computing the forward transform.  The
* inverse transform includes a scale of <code>1/fftLen</code> as part of the
* calculation and this matches the textbook definition of the inverse FFT.
* \par
* Preinitialized data structures containing twiddle factors and bit reversal
* tables are provided and defined in <code>arm_const_structs.h</code>.  Include 
* this header in your function and then pass one of the constant structures as 
* an argument to arm_cfft_f32.  For example:
* \par
* <code>arm_cfft_f32(arm_cfft_sR_f32_len64, pSrc, 1, 1)</code>
* \par
* computes a 64-point inverse complex FFT including bit reversal.
* The data structures are treated as constant data and not modified during the
* calculation.  The same data structure can be reused for multiple transforms
* including mixing forward and inverse transforms.
* \par
* Earlier releases of the library provided separate radix-2 and radix-4
* algorithms that operated on floating-point data.  These functions are still
* provided but are deprecated.  The older functions are slower and less general
* than the new functions.
* \par
* An example of initialization of the constants for the arm_cfft_f32 function follows:
* \par
* const static arm_cfft_instance_f32 *S;
* ...
*		switch (length) {
*    		case 16:
*    			S = & arm_cfft_sR_f32_len16;
*    		break;
*    		case 32:
*    			S = & arm_cfft_sR_f32_len32;
*    		break;
*			case 64:
*    			S = & arm_cfft_sR_f32_len64;
*    		break;
*    		case 128:
*    			S = & arm_cfft_sR_f32_len128;
*    		break;
*    		case 256:
*    			S = & arm_cfft_sR_f32_len256;
*    		break;
*    		case 512:
*    			S = & arm_cfft_sR_f32_len512;
*    		break;
*    		case 1024:
*    			S = & arm_cfft_sR_f32_len1024;
*    		break;
*    		case 2048:
*    			S = & arm_cfft_sR_f32_len2048;
*    		break;
*    		case 4096:
*    			S = & arm_cfft_sR_f32_len4096;
*    		break;
*			}
* \par Q15 and Q31
* The library provides radix-2 and radix-4 FFT algorithms for fixed-point data.  The
* radix-2 algorithm supports lengths of [16, 32, 64, ..., 4096].  The radix-4
* algorithm supports lengths of [16, 64, 256, ..., 4096].  When possible, you
* should use the radix-4 algorithm since it is faster than the radix-2 of the
* same length.
* \par
* The forward FFTs include scaling in order to prevent results from overflowing.
* Intermediate results are scaled down during each butterfly stage.  In the
* radix-2 algorithm, a scale of 0.5 is applied during each butterfly.  In the
* radix-4 algorithm, a scale of 0.25 is applied.  The scaling applies to both
* the forward and the inverse FFTs.  Thus the forward FFT contains an additional
* scale factor of <code>1/fftLen</code> as compared to the standard textbook
* definition of the FFT.  The inverse FFT also scales down during each butterfly
* stage and this corresponds to the standard textbook definition.
* \par
* A separate instance structure must be defined for each transform used but
* twiddle factor and bit reversal tables can be reused.
* \par 
* There is also an associated initialization function for each data type.   
* The initialization function performs the following operations:   
* - Sets the values of the internal structure fields.   
* - Initializes twiddle factor table and bit reversal table pointers.
* \par   
* Use of the initialization function is optional.   
* However, if the initialization function is used, then the instance structure 
* cannot be placed into a const data section. To place an instance structure 
* into a const data section, the instance structure should be manually 
* initialized as follows:
* <pre>   
*arm_cfft_radix2_instance_q31 S = {fftLen, ifftFlag, bitReverseFlag, pTwiddle, pBitRevTable, twidCoefModifier, bitRevFactor};   
*arm_cfft_radix2_instance_q15 S = {fftLen, ifftFlag, bitReverseFlag, pTwiddle, pBitRevTable, twidCoefModifier, bitRevFactor};   
*arm_cfft_radix4_instance_q31 S = {fftLen, ifftFlag, bitReverseFlag, pTwiddle, pBitRevTable, twidCoefModifier, bitRevFactor};    
*arm_cfft_radix4_instance_q15 S = {fftLen, ifftFlag, bitReverseFlag, pTwiddle, pBitRevTable, twidCoefModifier, bitRevFactor};    
*arm_cfft_instance_f32 S = {fftLen, pTwiddle, pBitRevTable, bitRevLength};
* </pre>   
* \par   
* where <code>fftLen</code> length of CFFT/CIFFT; <code>ifftFlag</code> Flag for
* selection of forward or inverse transform.  When ifftFlag is set the inverse
* transform is calculated.
* <code>bitReverseFlag</code> Flag for selection of output order (Set bitReverseFlag to output in normal order otherwise output in bit reversed order);    
* <code>pTwiddle</code>points to array of twiddle coefficients; <code>pBitRevTable</code> points to the bit reversal table.   
* <code>twidCoefModifier</code> modifier for twiddle factor table which supports all FFT lengths with same table;    
* <code>pBitRevTable</code> modifier for bit reversal table which supports all FFT lengths with same table.   
* <code>onebyfftLen</code> value of 1/fftLen to calculate CIFFT;
* \par
* The Q15 and Q31 FFT functions use a large bit reversal and twiddle factor
* table.  The tables are defined for the maximum length transform and a subset
* of the coefficients are used in shorter transforms.
* 
*/

void arm_cfft_radix8by2_f32( arm_cfft_instance_f32 * S, float32_t * p1) 
{
   uint32_t    L  = S->fftLen;
   float32_t * pCol1, * pCol2, * pMid1, * pMid2;
   float32_t * p2 = p1 + L;
   const float32_t * tw = (float32_t *) S->pTwiddle;
   float32_t t1[4], t2[4], t3[4], t4[4], twR, twI;
   float32_t m0, m1, m2, m3;
   uint32_t l;

   pCol1 = p1;
   pCol2 = p2;

   //    Define new length
   L >>= 1;
   //    Initialize mid pointers
   pMid1 = p1 + L;
   pMid2 = p2 + L;

   // do two dot Fourier transform
   for ( l = L >> 2; l > 0; l-- ) 
   {
      t1[0] = p1[0];
      t1[1] = p1[1];
      t1[2] = p1[2];
      t1[3] = p1[3];

      t2[0] = p2[0];
      t2[1] = p2[1];
      t2[2] = p2[2];
      t2[3] = p2[3];

      t3[0] = pMid1[0];
      t3[1] = pMid1[1];
      t3[2] = pMid1[2];
      t3[3] = pMid1[3];

      t4[0] = pMid2[0];
      t4[1] = pMid2[1];
      t4[2] = pMid2[2];
      t4[3] = pMid2[3];

      *p1++ = t1[0] + t2[0];
      *p1++ = t1[1] + t2[1];
      *p1++ = t1[2] + t2[2];
      *p1++ = t1[3] + t2[3];    // col 1

      t2[0] = t1[0] - t2[0];
      t2[1] = t1[1] - t2[1];
      t2[2] = t1[2] - t2[2];
      t2[3] = t1[3] - t2[3];    // for col 2

      *pMid1++ = t3[0] + t4[0];
      *pMid1++ = t3[1] + t4[1];
      *pMid1++ = t3[2] + t4[2];
      *pMid1++ = t3[3] + t4[3]; // col 1

      t4[0] = t4[0] - t3[0];
      t4[1] = t4[1] - t3[1];
      t4[2] = t4[2] - t3[2];
      t4[3] = t4[3] - t3[3];    // for col 2

      twR = *tw++;
      twI = *tw++;

      // multiply by twiddle factors
      m0 = t2[0] * twR;
      m1 = t2[1] * twI;
      m2 = t2[1] * twR;
      m3 = t2[0] * twI;
      
      // R  =  R  *  Tr - I * Ti
      *p2++ = m0 + m1;
      // I  =  I  *  Tr + R * Ti
      *p2++ = m2 - m3;
      
      // use vertical symmetry
	  //  0.9988 - 0.0491i <==> -0.0491 - 0.9988i
      m0 = t4[0] * twI;
      m1 = t4[1] * twR;
      m2 = t4[1] * twI;
      m3 = t4[0] * twR;
      
      *pMid2++ = m0 - m1;
      *pMid2++ = m2 + m3;

      twR = *tw++;
      twI = *tw++;
      
      m0 = t2[2] * twR;
      m1 = t2[3] * twI;
      m2 = t2[3] * twR;
      m3 = t2[2] * twI;
      
      *p2++ = m0 + m1;
      *p2++ = m2 - m3;
         
      m0 = t4[2] * twI;
      m1 = t4[3] * twR;
      m2 = t4[3] * twI;
      m3 = t4[2] * twR;
      
      *pMid2++ = m0 - m1;
      *pMid2++ = m2 + m3;
   }

   // first col
   arm_radix8_butterfly_f32( pCol1, L, (float32_t *) S->pTwiddle, 2u);
   // second col
   arm_radix8_butterfly_f32( pCol2, L, (float32_t *) S->pTwiddle, 2u);
   
}

void arm_cfft_radix8by4_f32( arm_cfft_instance_f32 * S, float32_t * p1) 
{
   uint32_t    L  = S->fftLen >> 1;
   float32_t * pCol1, *pCol2, *pCol3, *pCol4, *pEnd1, *pEnd2, *pEnd3, *pEnd4;
	const float32_t *tw2, *tw3, *tw4;
   float32_t * p2 = p1 + L;
   float32_t * p3 = p2 + L;
   float32_t * p4 = p3 + L;
   float32_t t2[4], t3[4], t4[4], twR, twI;
   float32_t p1ap3_0, p1sp3_0, p1ap3_1, p1sp3_1;
   float32_t m0, m1, m2, m3;
   uint32_t l, twMod2, twMod3, twMod4;

   pCol1 = p1;         // points to real values by default
   pCol2 = p2;
   pCol3 = p3;
   pCol4 = p4;
   pEnd1 = p2 - 1;     // points to imaginary values by default
   pEnd2 = p3 - 1;
   pEnd3 = p4 - 1;
   pEnd4 = pEnd3 + L;
   
   tw2 = tw3 = tw4 = (float32_t *) S->pTwiddle;
   
   L >>= 1;

   // do four dot Fourier transform

   twMod2 = 2;
   twMod3 = 4;
   twMod4 = 6;

   // TOP
   p1ap3_0 = p1[0] + p3[0];
   p1sp3_0 = p1[0] - p3[0];
   p1ap3_1 = p1[1] + p3[1];
   p1sp3_1 = p1[1] - p3[1];

   // col 2
   t2[0] = p1sp3_0 + p2[1] - p4[1];
   t2[1] = p1sp3_1 - p2[0] + p4[0];
   // col 3
   t3[0] = p1ap3_0 - p2[0] - p4[0];
   t3[1] = p1ap3_1 - p2[1] - p4[1];
   // col 4
   t4[0] = p1sp3_0 - p2[1] + p4[1];
   t4[1] = p1sp3_1 + p2[0] - p4[0];
   // col 1
   *p1++ = p1ap3_0 + p2[0] + p4[0];
   *p1++ = p1ap3_1 + p2[1] + p4[1];

   // Twiddle factors are ones
   *p2++ = t2[0];
   *p2++ = t2[1];
   *p3++ = t3[0];
   *p3++ = t3[1];
   *p4++ = t4[0];
   *p4++ = t4[1];
   
   tw2 += twMod2;
   tw3 += twMod3;
   tw4 += twMod4;
   
   for (l = (L - 2) >> 1; l > 0; l-- ) 
   {

      // TOP
      p1ap3_0 = p1[0] + p3[0];
      p1sp3_0 = p1[0] - p3[0];
      p1ap3_1 = p1[1] + p3[1];
      p1sp3_1 = p1[1] - p3[1];
      // col 2
      t2[0] = p1sp3_0 + p2[1] - p4[1];
      t2[1] = p1sp3_1 - p2[0] + p4[0];
      // col 3
      t3[0] = p1ap3_0 - p2[0] - p4[0];
      t3[1] = p1ap3_1 - p2[1] - p4[1];
      // col 4
      t4[0] = p1sp3_0 - p2[1] + p4[1];
      t4[1] = p1sp3_1 + p2[0] - p4[0];
      // col 1 - top
      *p1++ = p1ap3_0 + p2[0] + p4[0];
      *p1++ = p1ap3_1 + p2[1] + p4[1];

      // BOTTOM
      p1ap3_1 = pEnd1[-1] + pEnd3[-1];
      p1sp3_1 = pEnd1[-1] - pEnd3[-1];
      p1ap3_0 = pEnd1[0] + pEnd3[0];
      p1sp3_0 = pEnd1[0] - pEnd3[0];
      // col 2
      t2[2] = pEnd2[0]  - pEnd4[0] + p1sp3_1;
      t2[3] = pEnd1[0] - pEnd3[0] - pEnd2[-1] + pEnd4[-1];
      // col 3
      t3[2] = p1ap3_1 - pEnd2[-1] - pEnd4[-1];
      t3[3] = p1ap3_0 - pEnd2[0]  - pEnd4[0];
      // col 4
      t4[2] = pEnd2[0]  - pEnd4[0]  - p1sp3_1;
      t4[3] = pEnd4[-1] - pEnd2[-1] - p1sp3_0;
      // col 1 - Bottom
      *pEnd1-- = p1ap3_0 + pEnd2[0] + pEnd4[0];
      *pEnd1-- = p1ap3_1 + pEnd2[-1] + pEnd4[-1];

      // COL 2
      // read twiddle factors
      twR = *tw2++;
      twI = *tw2++;
      // multiply by twiddle factors
      //  let    Z1 = a + i(b),   Z2 = c + i(d)
      //   =>  Z1 * Z2  =  (a*c - b*d) + i(b*c + a*d)
      // Top
      m0 = t2[0] * twR;
      m1 = t2[1] * twI;
      m2 = t2[1] * twR;
      m3 = t2[0] * twI;
      
      *p2++ = m0 + m1;
      *p2++ = m2 - m3;
      // use vertical symmetry col 2
      // 0.9997 - 0.0245i  <==>  0.0245 - 0.9997i
      // Bottom
      m0 = t2[3] * twI;
      m1 = t2[2] * twR;
      m2 = t2[2] * twI;
      m3 = t2[3] * twR;
      
      *pEnd2-- = m0 - m1;
      *pEnd2-- = m2 + m3;

      // COL 3
      twR = tw3[0];
      twI = tw3[1];
      tw3 += twMod3;
      // Top
      m0 = t3[0] * twR;
      m1 = t3[1] * twI;
      m2 = t3[1] * twR;
      m3 = t3[0] * twI;
      
      *p3++ = m0 + m1;
      *p3++ = m2 - m3;
      // use vertical symmetry col 3
      // 0.9988 - 0.0491i  <==>  -0.9988 - 0.0491i
      // Bottom
      m0 = -t3[3] * twR;
      m1 = t3[2] * twI;
      m2 = t3[2] * twR;
      m3 = t3[3] * twI;
      
      *pEnd3-- = m0 - m1;
      *pEnd3-- = m3 - m2;
      
      // COL 4
      twR = tw4[0];
      twI = tw4[1];
      tw4 += twMod4;
      // Top
      m0 = t4[0] * twR;
      m1 = t4[1] * twI;
      m2 = t4[1] * twR;
      m3 = t4[0] * twI;
      
      *p4++ = m0 + m1;
      *p4++ = m2 - m3;
      // use vertical symmetry col 4
      // 0.9973 - 0.0736i  <==>  -0.0736 + 0.9973i
      // Bottom
      m0 = t4[3] * twI;
      m1 = t4[2] * twR;
      m2 = t4[2] * twI;
      m3 = t4[3] * twR;
      
      *pEnd4-- = m0 - m1;
      *pEnd4-- = m2 + m3;
   }

   //MIDDLE
   // Twiddle factors are 
   //  1.0000  0.7071-0.7071i  -1.0000i  -0.7071-0.7071i
   p1ap3_0 = p1[0] + p3[0];
   p1sp3_0 = p1[0] - p3[0];
   p1ap3_1 = p1[1] + p3[1];
   p1sp3_1 = p1[1] - p3[1];

   // col 2
   t2[0] = p1sp3_0 + p2[1] - p4[1];
   t2[1] = p1sp3_1 - p2[0] + p4[0];
   // col 3
   t3[0] = p1ap3_0 - p2[0] - p4[0];
   t3[1] = p1ap3_1 - p2[1] - p4[1];
   // col 4
   t4[0] = p1sp3_0 - p2[1] + p4[1];
   t4[1] = p1sp3_1 + p2[0] - p4[0];
   // col 1 - Top
   *p1++ = p1ap3_0 + p2[0] + p4[0];
   *p1++ = p1ap3_1 + p2[1] + p4[1];
   
   // COL 2
   twR = tw2[0];
   twI = tw2[1];
   
   m0 = t2[0] * twR;
   m1 = t2[1] * twI;
   m2 = t2[1] * twR;
   m3 = t2[0] * twI;
   
   *p2++ = m0 + m1;
   *p2++ = m2 - m3;
      // COL 3
   twR = tw3[0];
   twI = tw3[1];
   
   m0 = t3[0] * twR;
   m1 = t3[1] * twI;
   m2 = t3[1] * twR;
   m3 = t3[0] * twI;
   
   *p3++ = m0 + m1;
   *p3++ = m2 - m3;
   // COL 4
   twR = tw4[0];
   twI = tw4[1];
   
   m0 = t4[0] * twR;
   m1 = t4[1] * twI;
   m2 = t4[1] * twR;
   m3 = t4[0] * twI;
   
   *p4++ = m0 + m1;
   *p4++ = m2 - m3;

   // first col
   arm_radix8_butterfly_f32( pCol1, L, (float32_t *) S->pTwiddle, 4u);
   // second col
   arm_radix8_butterfly_f32( pCol2, L, (float32_t *) S->pTwiddle, 4u);
   // third col
   arm_radix8_butterfly_f32( pCol3, L, (float32_t *) S->pTwiddle, 4u);
   // fourth col
   arm_radix8_butterfly_f32( pCol4, L, (float32_t *) S->pTwiddle, 4u);

}

/**
* @addtogroup ComplexFFT   
* @{   
*/

/**   
* @details   
* @brief       Processing function for the floating-point complex FFT.
* @param[in]      *S    points to an instance of the floating-point CFFT structure.  
* @param[in, out] *p1   points to the complex data buffer of size <code>2*fftLen</code>. Processing occurs in-place.  
* @param[in]     ifftFlag       flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform.  
* @param[in]     bitReverseFlag flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output.  
* @return none.  
*/

void arm_cfft_f32( 
   const arm_cfft_instance_f32 * S, 
   float32_t * p1,
   uint8_t ifftFlag,
   uint8_t bitReverseFlag)
{

   uint32_t  L = S->fftLen, l;
   float32_t invL, * pSrc;

  if(ifftFlag == 1u)
  {
	  /*  Conjugate input data  */
	  pSrc = p1 + 1;
	  for(l=0; l<L; l++) {
		  *pSrc = -*pSrc;
		   pSrc += 2;
	  }
  }

		switch (L) {
		case 16: 
		case 128:
		case 1024:
			 arm_cfft_radix8by2_f32  ( (arm_cfft_instance_f32 *) S, p1);
			 break;
		case 32:
		case 256:
		case 2048:
			 arm_cfft_radix8by4_f32  ( (arm_cfft_instance_f32 *) S, p1);
			 break;
		case 64:
		case 512:
		case 4096:
          arm_radix8_butterfly_f32( p1, L, (float32_t *) S->pTwiddle, 1);
			 break;
		}  

	if( bitReverseFlag )
		arm_bitreversal_32((uint32_t*)p1,S->bitRevLength,S->pBitRevTable);

  if(ifftFlag == 1u)
  {
	  invL = 1.0f/(float32_t)L;
	  /*  Conjugate and scale output data */
	  pSrc = p1;
	  for(l=0; l<L; l++) {
  		 *pSrc++ *=   invL ;
		 *pSrc  = -(*pSrc) * invL;
                 pSrc++;
	  }
  }
}