  We propose a coded computing strategy and examine communication costs of
coded computing algorithms to make distributed Fast Fourier Transform (FFT)
resilient to errors during the computation. We apply maximum distance separable
(MDS) codes to a widely used "Transpose" algorithm for parallel FFT. In the
uncoded distributed FFT algorithm, the most expensive step is a single
"all-to-all" communication. We compare this with communication overhead of
coding in our coded FFT algorithm. We show that by using a systematic MDS code,
the communication overhead of coding is negligible in comparison with the
communication costs inherent in an uncoded FFT implementation if the number of
parity nodes is at most $o(\log K)$, where $K$ is the number of systematic
nodes.
