Exploring the evolution of NoC-based Spiking Neural Networks on FPGAs

Author

Morgan, F. ; Cawley, S. ; McGinley, B. ; Pande, S. ; McDaid, Liam J. ; Glackin, B. ; Maher, J. ; Harkin, J.

Author_Institution

Bio-Inspired Electron. & Reconfigurable Comput. Res. Group (BIRC), Nat. Univ. of Ireland, Galway, Ireland

fYear

2009

fDate

9-11 Dec. 2009

Firstpage

300

Lastpage

303

Abstract

Bio-inspired paradigms such as spiking neural networks (SNNs) offer the potential to emulate the repairing and adaptive ability of the brain. This paper presents EMBRACE-FPGA, a scalable, configurable network on chip (NoC)-based SNN architecture, implemented on Xilinx Virtex II-Pro FPGA hardware. In association with a genetic algorithm-based hardware evolution platform, EMBRACE-FPGA provides a computing platform for intrinsic hardware evolution, which can be used to explore the evolution and adaptive capabilities of hardware SNNs. Results demonstrate the application of the hardware SNN evolution platform to solve the XOR benchmark problem.

Keywords

field programmable gate arrays; network-on-chip; neural nets; EMBRACE-FPGA; NoC-based spiking neural networks; XOR benchmark problem; Xilinx Virtex II-Pro FPGA hardware; bioinspired paradigms; configurable network on chip; genetic algorithm; hardware evolution platform; Biological neural networks; Biology computing; Computer architecture; Evolution (biology); Field programmable gate arrays; Network-on-a-chip; Neural network hardware; Neural networks; Neurons; Power engineering computing; Evolvable Hardware; FPGA; Network on Chip; Spiking Neural Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Field-Programmable Technology, 2009. FPT 2009. International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-1-4244-4375-8

Electronic_ISBN

978-1-4244-4377-2

Type

conf

DOI

10.1109/FPT.2009.5377663

Filename

5377663