| << Chapter < Page | Chapter >> Page > |
This Appendix contains source code listings corresponding to the vectorized FFT implementations in Implementation details .
#include <math.h>#include <complex.h>#include <stdio.h>#include <stdlib.h>#include <xmmintrin.h>
typedef complex float data_t;
#define W(N,k) (cexp(-2.0f * M_PI * I * (float)(k) / (float)(N)))
data_t **LUT;
void ditfft2(data_t *in, data_t *out, int log2stride, int stride, int N) {if(N == 2) {
out[0] = in[0] + in[stride];
out[N/2] = in[0] - in[stride];
}else if(N == 4){ditfft2(in, out, log2stride+1, stride << 1, N >> 1);
ditfft2(in+stride, out+N/2, log2stride+1, stride << 1, N >> 1); data_t temp0 = out[0] + out[2];
data_t temp1 = out[0] - out[2]; data_t temp2 = out[1] - I*out[3];
data_t temp3 = out[1] + I*out[3]; if(log2stride) {
out[0] = creal(temp0) + creal(temp2)*I;
out[1] = creal(temp1) + creal(temp3)*I;
out[2] = cimag(temp0) + cimag(temp2)*I;
out[3] = cimag(temp1) + cimag(temp3)*I;
}else{out[0] = temp0;out[2] = temp1;out[1] = temp2;out[3] = temp3;}
}else if(!log2stride){ditfft2(in, out, log2stride+1, stride << 1, N >> 1);
ditfft2(in+stride, out+N/2, log2stride+1, stride << 1, N >> 1);
int k;
for(k=0;k<N/2;k+=4) {
__m128 Ok_re = _mm_load_ps((float *)&out[k+N/2]);__m128 Ok_im = _mm_load_ps((float *)&out[k+N/2+2]);__m128 w_re = _mm_load_ps((float *)&LUT[log2stride][k]);
__m128 w_im = _mm_load_ps((float *)&LUT[log2stride][k+2]);
__m128 Ek_re = _mm_load_ps((float *)&out[k]);__m128 Ek_im = _mm_load_ps((float *)&out[k+2]);__m128 wOk_re = _mm_sub_ps(_mm_mul_ps(Ok_re,w_re),_mm_mul_ps(Ok_im,w_im));
__m128 wOk_im = _mm_add_ps(_mm_mul_ps(Ok_re,w_im),_mm_mul_ps(Ok_im,w_re));__m128 out0_re = _mm_add_ps(Ek_re, wOk_re);
__m128 out0_im = _mm_add_ps(Ek_im, wOk_im);__m128 out1_re = _mm_sub_ps(Ek_re, wOk_re);
__m128 out1_im = _mm_sub_ps(Ek_im, wOk_im);_mm_store_ps((float *)(out+k), _mm_unpacklo_ps(out0_re, out0_im));
_mm_store_ps((float *)(out+k+2), _mm_unpackhi_ps(out0_re, out0_im));_mm_store_ps((float *)(out+k+N/2), _mm_unpacklo_ps(out1_re, out1_im));
_mm_store_ps((float *)(out+k+N/2+2), _mm_unpackhi_ps(out1_re, out1_im));}
}else{ditfft2(in, out, log2stride+1, stride << 1, N >> 1);
ditfft2(in+stride, out+N/2, log2stride+1, stride << 1, N >> 1);int k;
for(k=0;k<N/2;k+=4) {
__m128 Ok_re = _mm_load_ps((float *)&out[k+N/2]);__m128 Ok_im = _mm_load_ps((float *)&out[k+N/2+2]);__m128 w_re = _mm_load_ps((float *)&LUT[log2stride][k]);
__m128 w_im = _mm_load_ps((float *)&LUT[log2stride][k+2]);
__m128 Ek_re = _mm_load_ps((float *)&out[k]);__m128 Ek_im = _mm_load_ps((float *)&out[k+2]);__m128 wOk_re = _mm_sub_ps(_mm_mul_ps(Ok_re,w_re),_mm_mul_ps(Ok_im,w_im));
__m128 wOk_im = _mm_add_ps(_mm_mul_ps(Ok_re,w_im),_mm_mul_ps(Ok_im,w_re));_mm_store_ps((float *)(out+k), _mm_add_ps(Ek_re, wOk_re));
_mm_store_ps((float *)(out+k+2), _mm_add_ps(Ek_im, wOk_im));_mm_store_ps((float *)(out+k+N/2), _mm_sub_ps(Ek_re, wOk_re));
_mm_store_ps((float *)(out+k+N/2+2), _mm_sub_ps(Ek_im, wOk_im));}
}}
void fft_init(int N) {
int i;#define log2(x) ((int)(log(x)/log(2)))int n_luts = log2(N)-2;LUT = malloc(n_luts * sizeof(data_t *));
for(i=0;i<n_luts;i++) {
int n = N / pow(2,i);LUT[i] = _mm_malloc(n/2 * sizeof(data_t), 16);int j;
for(j=0;j<n/2;j+=4) {
data_t w[4];
int k;for(k=0;k<4;k++) w[k] = W(n,j+k);
LUT[i][j] = creal(w[0]) + creal(w[1])*I;LUT[i][j+1] = creal(w[2]) + creal(w[3])*I;
LUT[i][j+2] = cimag(w[0]) + cimag(w[1])*I;LUT[i][j+3] = cimag(w[2]) + cimag(w[3])*I;
}}}
Radix-2 FFT with vectorized loops
Notification Switch
Would you like to follow the 'Computing the fast fourier transform on simd microprocessors' conversation and receive update notifications?
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|