Title :
Real-time multi-board architecture for analog spiking neural networks
Author :
Saïghi, Sylvain ; Tomas, Jean ; Bornat, Yannick ; Belhadj, Bilel ; Malot, Olivia ; Renaud, Sylvie
Author_Institution :
IMS Lab., Univ. of Bordeaux, Talence, France
fDate :
May 30 2010-June 2 2010
Abstract :
In this paper, we present a multi-board system based on analog neuromimetic ICs. These ICs compute in realtime conductance-based models. These models are implemented in a modular architecture based on our analog IPs. Each IC includes five neurons and analog memory cells to set and store the conductance model parameters, and eventually optimize it to compensate the analog circuit variability. The circuits are embedded in a multi-board system able to host up to 120 neurons spread across 6 boards all connected to a backplane with daisy-chain facilities. Each action potential computed by analog neuromimetic chips is time-stamped when detected by digital device (FPGA). These FPGAs are also in charge of the real-time plasticity computation and of controlling inter-boards communication. The system is designed to compute programmable models and connectivity schemes.
Keywords :
analogue integrated circuits; field programmable gate arrays; neural nets; FPGA; analog circuit variability; analog memory cells; analog neuromimetic integrated circuits; analog spiking neural networks; conductance model; field programmable gate arrays; interboards communication; multiboard architecture; real-time plasticity computation; Analog circuits; Analog computers; Analog integrated circuits; Analog memory; Backplanes; Computer architecture; Field programmable gate arrays; Integrated circuit modeling; Neural networks; Neurons;
Conference_Titel :
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-5308-5
Electronic_ISBN :
978-1-4244-5309-2
DOI :
10.1109/ISCAS.2010.5538039
