Using FPGAs to implement a reconfigurable highly parallel computer

Abstract

With the arrival of large Field Programmable Gate Arrays (FPGAs) it is possible to build an entire computer using only FPGA and memory. In this paper we share some experience from building a highly parallel computer using this concept. Even if today's FPGAs are of considerable size, each processor must be relatively simple if a highly parallel computer is to be constructed from them. Based on our experience of other parallel computers and thorough studies of the intended applications, we think it is possible to build very powerful and efficient computers using bit-serial processing elements with SIMD (Single Instruction stream, Multiple Data streams) control.A major benefit of using FPGAs is the fact that different architectural variations can easily be tested and evaluated on real applications. In the primary application area, which is artificial neural networks, the gains of extensions like bit-serial multipliers or counters can quickly be found. A concrete implementation of a processor array, using Xilinx FPGAs, is described in this paper.To get efficient usage and high performance with the FPGA circuits signal flow plays an important role. As the current implementation of the Xilinx EDA software does not support that design issue, the signal flow design has to be made by hand. The processing elements are simple and regular which makes it easy to implement them with the XACT Editor. This gives high performance, up to 40–50 MHz.KeywordsArtificial Neural NetworkControl UnitArtificial Neural Network ModelProcessing ElementArtificial Neural Network AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.