Design Heuristics for Mapping Floating-Point Scientific Computational Kernels onto High Performance Reconfigurable Computers

Abstract

Because of the increasing need to develop efficient high-speed computational kernels, researchers have been looking at various acceleration technologies. One approach is to use field programmable gate arrays (FPGAs) in conjunction with general purpose processors to form what are known as high performance reconfigurable computers (HPRCs). HPRCs have already been shown to work well for both fixed-point and integer calculations. Floating-point calculations are a different matter; obtaining speedups has been somewhat elusive. This article, after introducing the three primary HPRC development flows, takes a detailed look at “the three p’s,” which addresses the crucial relationship among performance, pipelining, and parallelism. It also examines “the FPGA design boundary,” which addresses some of the heuristics that allow developers to determine which application modules can be mapped onto the FPGAs. These ideas are illustrated by way of a simple floating-point application that is mapped onto a contemporary HPRC. This article expands upon earlier work by including details on how to map customized intellectual property cores into an HPRC environment via a hybrid development flow.