Memory-Efficient Fast Fourier Transform on Streaming Data by Fusing Permutations

Abstract

We propose a novel FFT datapath that reduces the memory requirement compared to state-of-the-art RAM-based implementations by up to a factor of two. The novelty is in a technique to fuse the datapaths for the required perfect shuffle and bit reversal and is applicable to an entire design space of FFT implementations with varying degrees of reuse and number of input ports. We implemented a tool to generate this FFT design space for a given input size and to benchmark against prior work. The results show a reduction of half the RAM banks and/or half the logic complexity used for the permutations. The technique for fusing permutations is more generally applicable beyond the FFT.