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started real optimization, added benchmark for FFT
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bench/benchFFT.cpp
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64
bench/benchFFT.cpp
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2009 Mark Borgerding mark a borgerding net
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include <complex>
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#include <vector>
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#include <Eigen/Core>
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#include <bench/BenchTimer.h>
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#include <unsupported/Eigen/FFT.h>
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using namespace Eigen;
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using namespace std;
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#ifndef NFFT
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#define NFFT 1024
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#endif
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#ifndef TYPE
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#define TYPE float
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#endif
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#ifndef NITS
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#define NITS (10000000/NFFT)
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#endif
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int main()
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{
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vector<complex<TYPE> > inbuf(NFFT);
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vector<complex<TYPE> > outbuf(NFFT);
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Eigen::FFT<TYPE> fft;
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fft.fwd( outbuf , inbuf);
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BenchTimer timer;
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timer.reset();
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for (int k=0;k<8;++k) {
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timer.start();
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for(int i = 0; i < NITS; i++)
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fft.fwd( outbuf , inbuf);
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timer.stop();
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}
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double mflops = 5.*NFFT*log2((double)NFFT) / (1e6 * timer.value() / (double)NITS );
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cout << "NFFT=" << NFFT << " " << (double(1e-6*NFFT*NITS)/timer.value()) << " MS/s " << mflops << "MFLOPS\n";
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}
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@ -60,9 +60,7 @@ class FFT
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template <typename _Input>
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void fwd( Complex * dst, const _Input * src, int nfft)
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{
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m_traits.prepare(nfft,false,dst,src);
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m_traits.exec(dst,src);
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m_traits.postprocess(dst);
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m_traits.fwd(dst,src,nfft);
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}
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template <typename _Input>
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@ -75,9 +73,7 @@ class FFT
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template <typename _Output>
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void inv( _Output * dst, const Complex * src, int nfft)
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{
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m_traits.prepare(nfft,true,dst,src);
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m_traits.exec(dst,src);
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m_traits.postprocess(dst);
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m_traits.inv( dst,src,nfft );
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}
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template <typename _Output>
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@ -35,7 +35,73 @@ namespace Eigen {
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simple_fft_traits() : m_nfft(0) {}
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template <typename _Src>
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void prepare(int nfft,bool inverse,Complex * dst,const _Src *src)
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void fwd( Complex * dst,const _Src *src,int nfft)
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{
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prepare(nfft,false);
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work(0, dst, src, 1,1);
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scale(dst);
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}
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void fwd( Complex * dst,const Scalar * src,int nfft)
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{
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if ( nfft&1 ) {
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// use generic mode for odd
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prepare(nfft,false);
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work(0, dst, src, 1,1);
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scale(dst);
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}else{
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int ncfft = nfft>>1;
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// use optimized mode for even real
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prepare(nfft,false);
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work(0,dst, reinterpret_cast<const Complex*> (src),2,1);
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Complex dc = dst[0].real() + dst[0].imag();
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Complex nyquist = dst[0].real() - dst[0].imag();
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int k;
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for ( k=1;k <= ncfft/2 ; ++k ) {
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/**
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fpk = st->tmpbuf[k];
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fpnk.r = st->tmpbuf[ncfft-k].r;
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fpnk.i = - st->tmpbuf[ncfft-k].i;
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C_ADD( f1k, fpk , fpnk );
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C_SUB( f2k, fpk , fpnk );
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C_MUL( tw , f2k , st->super_twiddles[k-1]);
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freqdata[k].r = HALF_OF(f1k.r + tw.r);
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freqdata[k].i = HALF_OF(f1k.i + tw.i);
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freqdata[ncfft-k].r = HALF_OF(f1k.r - tw.r);
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freqdata[ncfft-k].i = HALF_OF(tw.i - f1k.i);
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*/
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Complex fpk = dst[k];
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Complex fpnk = conj(dst[ncfft-k]);
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Complex f1k = fpk + fpnk;
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Complex f2k = fpnk - fpk;
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//Complex tw = f2k * exp( Complex(0,-3.14159265358979323846264338327 * ((double)k / ncfft + 1) ) ); // TODO repalce this with index into twiddles
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Complex tw = f2k * m_twiddles[2*k];;
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dst[k] = (f1k + tw) * Scalar(.5);
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dst[ncfft-k] = conj(f1k -tw)*Scalar(.5);
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}
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// place conjugate-symmetric half at the end for completeness
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// TODO: make this configurable ( opt-out )
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for ( k=1;k < ncfft ; ++k )
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dst[nfft-k] = conj(dst[k]);
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dst[0] = dc;
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dst[ncfft] = nyquist;
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}
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}
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void inv(Complex * dst,const Complex *src,int nfft)
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{
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prepare(nfft,true);
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work(0, dst, src, 1,1);
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scale(dst);
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}
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void prepare(int nfft,bool inverse)
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{
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if (m_nfft == nfft) {
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// reuse the twiddles, conjugate if necessary
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@ -74,57 +140,49 @@ namespace Eigen {
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}while(n>1);
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}
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template <typename _Src>
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void exec(Complex * dst, const _Src * src)
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{
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work(0, dst, src, 1,1);
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}
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void postprocess(Complex *dst)
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void scale(Complex *dst)
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{
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if (m_inverse) {
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Scalar scale = 1./m_nfft;
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Scalar s = 1./m_nfft;
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for (int k=0;k<m_nfft;++k)
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dst[k] *= scale;
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dst[k] *= s;
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}
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}
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private:
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template <typename _Src>
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void work( int stage,Complex * Fout, const _Src * f, size_t fstride,size_t in_stride)
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void work( int stage,Complex * xout, const _Src * xin, size_t fstride,size_t in_stride)
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{
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int p = m_stageRadix[stage];
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int m = m_stageRemainder[stage];
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Complex * Fout_beg = Fout;
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Complex * Fout_end = Fout + p*m;
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Complex * Fout_beg = xout;
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Complex * Fout_end = xout + p*m;
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if (m==1) {
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do{
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*Fout = *f;
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f += fstride*in_stride;
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}while(++Fout != Fout_end );
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}else{
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if (m>1) {
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do{
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// recursive call:
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// DFT of size m*p performed by doing
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// p instances of smaller DFTs of size m,
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// each one takes a decimated version of the input
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work(stage+1, Fout , f, fstride*p,in_stride);
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f += fstride*in_stride;
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}while( (Fout += m) != Fout_end );
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work(stage+1, xout , xin, fstride*p,in_stride);
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xin += fstride*in_stride;
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}while( (xout += m) != Fout_end );
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}else{
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do{
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*xout = *xin;
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xin += fstride*in_stride;
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}while(++xout != Fout_end );
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}
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Fout=Fout_beg;
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xout=Fout_beg;
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// recombine the p smaller DFTs
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switch (p) {
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case 2: bfly2(Fout,fstride,m); break;
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case 3: bfly3(Fout,fstride,m); break;
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case 4: bfly4(Fout,fstride,m); break;
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case 5: bfly5(Fout,fstride,m); break;
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default: bfly_generic(Fout,fstride,m,p); break;
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case 2: bfly2(xout,fstride,m); break;
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case 3: bfly3(xout,fstride,m); break;
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case 4: bfly4(xout,fstride,m); break;
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case 5: bfly5(xout,fstride,m); break;
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default: bfly_generic(xout,fstride,m,p); break;
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}
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}
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@ -139,7 +197,7 @@ namespace Eigen {
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void bfly4( Complex * Fout, const size_t fstride, const size_t m)
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{
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Complex scratch[7];
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Complex scratch[6];
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int negative_if_inverse = m_inverse * -2 +1;
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for (size_t k=0;k<m;++k) {
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scratch[0] = Fout[k+m] * m_twiddles[k*fstride];
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@ -178,15 +236,10 @@ namespace Eigen {
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scratch[0]=scratch[1]-scratch[2];
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tw1 += fstride;
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tw2 += fstride*2;
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Fout[m] = Complex( Fout->real() - .5*scratch[3].real() , Fout->imag() - .5*scratch[3].imag() );
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scratch[0] *= epi3.imag();
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*Fout += scratch[3];
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Fout[m2] = Complex( Fout[m].real() + scratch[0].imag() , Fout[m].imag() - scratch[0].real() );
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Fout[m] += Complex( -scratch[0].imag(),scratch[0].real() );
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++Fout;
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}while(--k);
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@ -115,8 +115,9 @@ void test_FFT()
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CALL_SUBTEST( test_complex<float>(2*3*4) ); CALL_SUBTEST( test_complex<double>(2*3*4) ); CALL_SUBTEST( test_complex<long double>(2*3*4) );
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CALL_SUBTEST( test_complex<float>(2*3*4*5) ); CALL_SUBTEST( test_complex<double>(2*3*4*5) ); CALL_SUBTEST( test_complex<long double>(2*3*4*5) );
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CALL_SUBTEST( test_complex<float>(2*3*4*5*7) ); CALL_SUBTEST( test_complex<double>(2*3*4*5*7) ); CALL_SUBTEST( test_complex<long double>(2*3*4*5*7) );
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/*
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CALL_SUBTEST( test_scalar<float>(32) ); CALL_SUBTEST( test_scalar<double>(32) ); CALL_SUBTEST( test_scalar<long double>(32) );
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CALL_SUBTEST( test_scalar<float>(1024) ); CALL_SUBTEST( test_scalar<double>(1024) ); CALL_SUBTEST( test_scalar<long double>(1024) );
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CALL_SUBTEST( test_scalar<float>(2*3*4*5*7) ); CALL_SUBTEST( test_scalar<double>(2*3*4*5*7) ); CALL_SUBTEST( test_scalar<long double>(2*3*4*5*7) );
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*/
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}
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