Data Reorganization Engines for the Next Generation of System-On-A-Chip FPGAs

Pedro Diniz
University of Southern California
Information Sciences Institute
pedro@isi.edu

and

Joonseok Park
University of Southern California
Information Sciences Institute
joonseok@isi.edu

Abstract

Field-Programmable-Core-Arrays (FPCA) will include various computing cores for a wide variety of applications ranging from DSP to general purpose computing. With the increasing gap between core computing speeds and memory access latency, managing and orchestrating the movement of data across multiple cores will become increasingly important. In this paper we propose data reorganization engines that allow a wide variety of data reorganizations intra- as well as inter-memory modules for future FPCAs. We have experimented with a suite of data reorganizations pervasive in DSP applications. Our limited set of experiments reveals that the proposed designs for these engines are flexile and use little design area in current FPGA fabrics, making them amenable to be easily integrated in future FPCAs as either soft- or hard-macros.

Keywords:

Data Reorganization; FPGA-based reconfigurable computing architectures, program analysis.

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