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Performance evaluation and scaling of a multiprocessor architecture emulating complex SNN algorithms

Autor
Sanchez, G.; Madrenas, J.; Moreno, J.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science (Online)
Data de publicació
2010-09
Volum
Special ICES 2010
Número
6274
Pàgina inicial
145
Pàgina final
156
DOI
https://doi.org/10.1007/978-3-642-15323-5_13 Obrir en finestra nova
Projecte finançador
PERPLEXUS. Pervasive computing framework for modelling complex virtually-unbounded systems
TEC2008-06028/TEC
Repositori
http://hdl.handle.net/2117/10521 Obrir en finestra nova
URL
http://www.springerlink.com/content/u571j262134w5u56/ Obrir en finestra nova
Resum
The performance analysis of an efficient multiprocessor architecture that allows accelerating the emulation of large-scale Spiking Neural Networks (SNNs) is reported. After describing the architecture and the complex SNN algorithm mapping, the performance study demonstrates that the system can emulate up to 10,000 300-synapse neurons in real time at 64 MHz with conventional FPGAs. Important improvements can be achieved by using advanced technology and increased clock rate or by means of simple a...
Citació
Sanchez, G.; Madrenas, J.; Moreno, J. Performance evaluation and scaling of a multiprocessor architecture emulating complex SNN algorithms. "Lecture Notes in Computer Science", Setembre 2010, vol. Special ICES 2010, núm. 6274, p. 145-156.
Grup de recerca
AHA - Arquitectures Hardware Avançades
ISSET - Integrated Smart Sensors and Health Technologies

Participants