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Proceedings Paper

Spiking neural networks on high performance computer clusters
Author(s): Chong Chen; Tarek M. Taha
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Paper Abstract

In this paper we examine the acceleration of two spiking neural network models on three clusters of multicore processors representing three categories of processors: x86, STI Cell, and NVIDIA GPGPUs. The x86 cluster utilized consists of 352 dualcore AMD Opterons, the Cell cluster consists of 320 Sony Playstation 3s, while the GPGPU cluster contains 32 NVIDIA Tesla S1070 systems. The results indicate that the GPGPU platform can dominate in performance compared to the Cell and x86 platforms examined. From a cost perspective, the GPGPU is more expensive in terms of neuron/s throughput. If the cost of GPGPUs go down in the future, this platform will become very cost effective for these models.

Paper Details

Date Published: 13 September 2011
PDF: 14 pages
Proc. SPIE 8134, Optics and Photonics for Information Processing V, 813406 (13 September 2011); doi: 10.1117/12.897269
Show Author Affiliations
Chong Chen, Univ. of Dayton (United States)
Tarek M. Taha, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 8134:
Optics and Photonics for Information Processing V
Khan M. Iftekharuddin; Abdul Ahad Sami Awwal, Editor(s)

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