Fast Fourier Transforms (FFTs) are frequently employed in various applications such as image processing and speech recognition. Though FFT calculations can be speeded up considerably, real time processing requirements are well above that of modern day uniprocessor systems. Computing power can be substantially increased through the exploitation of the inherent parallelism available in FFT calculations. However, experimental performance analysis of the Parallel FFT (PFFT) algorithm has not been sufficiently investigated in a loosely coupled multiprocessor environment. In this paper, we evaluate the implementation of a PFFT on a network of T800 series transputers connected in the form of a linear pipeline and a binary cube. We analyse the speedup obtained, taking into account both computation load and communication overhead. A new load balancing algorithm has been incorporated so that load balancing takes into account both computation and communication loads. Realistic performance figures obtained through actual measurements on the system are compared with figures obtained from an analysis of the practical complexity of the implementation.