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A Simple and Efficient FFT Implementation in C++:
Part II

In Part One of this article, I introduced a new efficient implementation of the Cooley-Tukey Fast Fourier Transform (FFT) algorithm, discussing recursion and the elimination of trigonometric function calls. In Part Two, I discuss the specialization of short FFTs, FFT selection at runtime, and present some comparative benchmarks and conclusions.

Specialization of Short FFTs

The implemented template class recursion has P levels. Every FFT calculation process runs from level P to level 1, while the level 1 is empty (Listing Three, in Part One of this article). Some comprehensive books on FFT, for example [4], show that short length FFTs (P=1,2,3,4) could use fewer operations than the general algorithm. Such particular cases can be simply incorporated into the new implementation using partial specialization of the template class DanielsonLanczos. Listing Six represents those specializations for N=4 and N=2. Since every FFT goes down to the first specialized one, these additional specializations lead to a small overall performance improvement of about 1-5 percent.

Listing Six

template<typename T>
class DanielsonLanczos<4,T> {
   void apply(T* data) {
      T tr = data[2];
      T ti = data[3];
      data[2] = data[0]-tr;
      data[3] = data[1]-ti;
      data[0] += tr;
      data[1] += ti;
      tr = data[6];
      ti = data[7];
      data[6] = data[5]-ti;
      data[7] = tr-data[4];
      data[4] += tr;
      data[5] += ti;

      tr = data[4];
      ti = data[5];
      data[4] = data[0]-tr;
      data[5] = data[1]-ti;
      data[0] += tr;
      data[1] += ti;
      tr = data[6];
      ti = data[7];
      data[6] = data[2]-tr;
      data[7] = data[3]-ti;
      data[2] += tr;
      data[3] += ti;

template<typename T>
class DanielsonLanczos<2,T> {
   void apply(T* data) {
      T tr = data[2];
      T ti = data[3];
      data[2] = data[0]-tr;
      data[3] = data[1]-ti;
      data[0] += tr;
      data[1] += ti;

You might ask why, when programming in C++, am I still using a C-style array instead of std::complex<T> or even std::vector<T>? Because the C++ standard library is not suited to high-performance computing, at least its open source distribution that I have. A simple trace into the sources of the header complex makes clear, that a simple operation on complex numbers like x=a+b written in C++ generates a temporary object of type std::complex<T> resulting in poor performance demonstrated by the dotted line 'CGFFT' on Figure 1 (see Part One of this article). This is an example where the expression templates technique in the header {complex} could be very helpful, but was not applied. Application of std::complex<T> could result in some shorter code, but the computational performance, which I try to maximize, would be lost.

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