Title :
Bluehive - A field-programable custom computing machine for extreme-scale real-time neural network simulation
Author :
Moore, Simon W. ; Fox, Paul J. ; Marsh, S.J.T. ; Markettos, A. Theodore ; Mujumdar, Amruta
Author_Institution :
Comput. Lab., Univ. of Cambridge, Cambridge, UK
fDate :
April 29 2012-May 1 2012
Abstract :
Bluehive is a custom 64-FPGA machine targeted at scientific simulations with demanding communication requirements. Bluehive is designed to be extensible with a reconfigurable communication topology suited to algorithms with demanding high-bandwidth and low-latency communication, something which is unattainable with commodity GPGPUs and CPUs. We demonstrate that a spiking neuron algorithm can be efficiently mapped to Bluehive using Bluespec System Verilog by taking a communication-centric approach. This contrasts with many FPGA-based neural systems which are very focused on parallel computation, resulting in inefficient use of FPGA resources. Our design allows 64k neurons with 64M synapses per FPGA and is scalable to a large number of FPGAs.
Keywords :
electronic engineering computing; field programmable gate arrays; graphics processing units; hardware description languages; neural nets; 64-FPGA machine; Bluespec system Verilog; CPU; FPGA resources; FPGA-based neural systems; GPGPU; communication-centric approach; extreme-scale real-time neural network simulation; field-programable custom computing machine; high-bandwidth communication; low-latency communication; reconfigurable communication topology; spiking neuron algorithm; Bandwidth; Delay; Equations; Field programmable gate arrays; Mathematical model; Neurons; Programming; FPGA; neural network; simulation;
Conference_Titel :
Field-Programmable Custom Computing Machines (FCCM), 2012 IEEE 20th Annual International Symposium on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4673-1605-7
DOI :
10.1109/FCCM.2012.32