优化基数-2 FFT C代码

Question

我是C编程的初学者。 我目前正在尝试使用radix-2，频率抽取实现需要1024点FFT实现的项目。 我在下面附上了FFT函数C代码。 如何通过修改C代码来提高性能。

   #include "i_cmplx.h"         /* definition of the complex type */  
#include "twiddle1024.h"    /* quantised and scaled Twiddle factors */
#define LL 1024             /* Maximum length of FFT */ 

/* fft radix-2 funtion using Decimation In Frequency */

//#pragma CODE_SECTION(fft, "mycode"); // Makes the program run from internal memory

void fft(COMPLEX *Y, int N) /* FFT(input sample array, # of points)     */
    {
    int temp1R, temp1I, temp2R,temp2I;  /* 32 bits temporary storage for */
                                       /* intermediate results          */                  
    short tempR, tempI, c, s;      /* 16 bits temporary storages    */
    /* variables */
    int TwFStep,  /* Step between twiddle factors */
        TwFIndex, /* Index of twiddle factors */
        BLStep,    /* Step for incrementing butterfly index */
        BLdiff,   /* Difference between upper and lower butterfly legs */
        upperIdx,
        lowerIdx, /* upper and lower indexes of buterfly leg */ 
        i, j, k;  /* loop control variables */

    BLdiff=N;
    TwFStep=1;
    for(k=N;k>1;k=(k>>1)) /* Do Log(base 2)(N) Stages */
        {
        BLStep=BLdiff;
        BLdiff=BLdiff>>1; 
        TwFIndex=0;
        for(j=0;j<BLdiff;j++)/* Nbr of twiddle factors to use=BLDiff  */
            {
            c=w[TwFIndex].real;
            s=w[TwFIndex].imag;
            TwFIndex=TwFIndex+TwFStep;                 
            /* Now do N/BLStep butterflies */  
            for(upperIdx=j;upperIdx<N;upperIdx+=BLStep)
                {                              
/* Calculations inside this loop avoid overflow by shifting left once
   the result of every adittion/substration and by shifting left 15 
   places the result of every multiplication. Double precision temporary
   results (32-bit) are used in order to avoid losing information because
   of overflow. Final DFT result is scaled by N (number of points), i.e.,
   2^(Nbr of stages) =2^(log(base 2) N) = N                             */

                lowerIdx=upperIdx+BLdiff;
                temp1R     = (Y[upperIdx].real - Y[lowerIdx].real)>>1;
                temp2R     = (Y[upperIdx].real + Y[lowerIdx].real)>>1;
                Y[upperIdx].real  =  (short) temp2R;
                temp1I     = (Y[upperIdx].imag - Y[lowerIdx].imag)>>1;
                temp2I     = (Y[upperIdx].imag + Y[lowerIdx].imag)>>1;
                Y[upperIdx].imag  =  (short) temp2I;
                temp2R     = (c*temp1R - s*temp1I)>>15;
                Y[lowerIdx].real  = (short) temp2R;
                temp2I     = (c*temp1I + s*temp1R)>>15;
                Y[lowerIdx].imag  =  (short) temp2I;
                }
            }
            TwFStep = TwFStep<<1; /* update separation of twiddle factors)*/
        }

/* bit reversal for resequencing data */

    j=0;
   for (i=1;i<(N-1);i++)
    {
      k=N/2;
      while (k<=j)
        {
         j = j-k;
         k=k/2;
         }
      j=j+k;
      if (i<j)
        {
         tempR=Y[j].real;
         tempI=Y[j].imag;
         Y[j].real=Y[i].real;
         Y[j].imag=Y[i].imag;
         Y[i].real=tempR;
         Y[i].imag=tempI;
         }
      }
    return;
    }