DocumentCode :
2956059
Title :
Realizing biological spiking network models in a configurable wafer-scale hardware system
Author :
Fieres, Johannes ; Schemmel, Johannes ; Meier, Karlheinz
Author_Institution :
Kirchhoff Inst. for Phys., Ruprecht-Karls Univ., Heidelberg
fYear :
2008
fDate :
1-8 June 2008
Firstpage :
969
Lastpage :
976
Abstract :
An analog VLSI hardware architecture for the distributed simulation of large-scale spiking neural networks has been developed. Several hundred integrated computing nodes, each hosting up to 512 neurons, will be interconnected and operated on un-cut silicon wafers. The electro-technical aspects and the details of the hardware implementation are covered in a separate contribution to this conference. This paper focuses on the usability of the system by demonstrating that biologically relevant network models can in fact be mapped to this system. Different network configurations are established on the hardware by programmable switch matrices, repeaters, and address decoders. Systematic routing algorithms are presented to map a given network model to the hardware system. Routing is simulated for several network examples, proving the systempsilas practical applicability. Furthermore, the routing simulations are used to fix values for yet open hardware parameters.
Keywords :
analogue integrated circuits; decoding; neural nets; silicon; wafer-scale integration; address decoders; analog VLSI hardware architecture; biological spiking network models; configurable wafer-scale hardware system; distributed simulation; electro-technical aspects; large-scale spiking neural networks; programmable switch matrices; repeaters; silicon wafers; systematic routing algorithms; Biological system modeling; Computational modeling; Computer architecture; Large-scale systems; Neural network hardware; Neural networks; Routing; Semiconductor device modeling; Switches; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2008.4633916
Filename :
4633916
Link To Document :
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