Implementation of a 2-D Fast Fourier Transform on an FPGA-Based Custom Computing Machine

The two dimensional fast Fourier transform (2-D FFT) is an indispensable operation in many digital signal processing applications but yet is deemed computationally expensive when performed on a conventional general purpose processors. This paper presents the implementation and performance figures for the Fourier transform on a FPGA-based custom computer. The computation of a 2-D FFT requires O(Nlog2N) floating point arithmetic operations for an NxN image. By implementing the FFT algorithm on a custom computing machine (CCM) called Splash2, a computation speed of 180 Mflops and a speed-up of 23 times over a Sparc-10 workstation is achieved.