Spiking neural P system simulations on a high performance GPU platform

Authors:
Francis George Cabarle;Henry Adorna;Miguel A. Martínez-del-Amor;Mario J. Pérez-Jiménez
Affiliations:
Algorithms & Complexity Lab, Department of Computer Science, University of the Philippines Diliman, Quezon City, Philippines;Algorithms & Complexity Lab, Department of Computer Science, University of the Philippines Diliman, Quezon City, Philippines;Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain;Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain
Venue:
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part II
Year:
2011

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Abstract

In this paper we present our results in adapting a Spiking Neural P system (SNP system) simulator to a high performance graphics processing unit (GPU) platform. In particular, we extend our simulations to larger and more complex SNP systems using an NVIDIA Tesla C1060 GPU. The C1060 is manufactured for high performance computing and massively parallel computations, matching the maximally parallel nature of SNP systems. Using our GPU accelerated simulations we present speedups of around 200× for some SNP systems, compared to CPU only simulations.