A Reconfigurable Distributed Computing Fabric Exploiting Multilevel Parallelism

Abstract

This paper presents a novel reconfigurable data flow processing architecture that promises high performance by explicitly targeting both fine- and course-grained parallelism. This architecture is based on multiple FPGAs organized in a scalable direct network that is substantially more interconnect-efficient than currently used crossbar technology. In addition, we discuss several ancillary issues and propose solutions required to support this architecture and achieve maximal performance for general-purpose applications; these include supporting IP, mapping techniques, and routing policies that enable greater flexibility for architectural evolution and code portability