Generating and Searching Families of FFT Algorithms

TL;DR

This paper introduces a SAT-based method to generate and search for FFT algorithms with fewer arithmetic operations than traditional methods, revealing new FFTs that outperform split-radix even with standard twiddle factors.

Contribution

It presents a novel SAT-based approach to generate families of FFT algorithms with minimal operations, including new twiddle factors, surpassing traditional algorithms like split-radix.

Findings

Found FFTs with fewer operations than split-radix.

Developed a SAT-based framework for FFT algorithm generation.

Discovered new FFTs using standard twiddle factors.

Abstract

A fundamental question of longstanding theoretical interest is to prove the lowest exact count of real additions and multiplications required to compute a power-of-two discrete Fourier transform (DFT). For 35 years the split-radix algorithm held the record by requiring just 4n log n - 6n + 8 arithmetic operations on real numbers for a size-n DFT, and was widely believed to be the best possible. Recent work by Van Buskirk et al. demonstrated improvements to the split-radix operation count by using multiplier coefficients or "twiddle factors" that are not n-th roots of unity for a size-n DFT. This paper presents a Boolean Satisfiability-based proof of the lowest operation count for certain classes of DFT algorithms. First, we present a novel way to choose new yet valid twiddle factors for the nodes in flowgraphs generated by common power-of-two fast Fourier transform algorithms, FFTs. With this new technique, we can generate a large family of FFTs realizable by a fixed flowgraph. This solution space of FFTs is cast as a Boolean Satisfiability problem, and a modern Satisfiability Modulo Theory solver is applied to search for FFTs requiring the fewest arithmetic operations. Surprisingly, we find that there are FFTs requiring fewer operations than the split-radix even when all twiddle factors are n-th roots of unity.