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Improving GPU Simulations of Spiking Neural P Systems

Fri, 06/22/2012 - 09:30 — mmartinez
TitleImproving GPU Simulations of Spiking Neural P Systems
Publication TypeJournal Papers
Year of Publication2012
AuthorsCabarle, F., Adorna H., Martínez-del-Amor M. A., & Pérez-Jiménez M. J.
Journal TitleRomanian Journal of Information Science and Technology
PublisherEDITURA ACADEMIEI ROMÂNE
Place PublishedBucureşti, România
EditionBio-Inspired Computing – Theory and Applications (BIC-TA) - Selected papers
Volume15
Pages5-20
Date Published06/2012
Abstract

In this work we present further extensions and improvements
of a Spiking Neural P system (for short, SNP systems) simulator on graphics
processing units (for short, GPUs). Using previous results on representing SNP
system computations using linear algebra, we analyze and implement a compu-
tation simulation algorithm on the GPU. A two-level parallelism is introduced
for the computation simulations. We also present a set of benchmark SNP sys-
tems to stress test the simulation and show the increased performance obtained
using GPUs over conventional CPUs. For a 16 neuron benchmark SNP system
with 65536 nondeterministic rule selection choices, we report a 2.31 speedup of
the GPU-based simulations over CPU-based simulations.
KeywordsCUDA, GPU Computing, Membrane computing, spiking neural network, spiking neural P systems
URLhttp://www.imt.ro/romjist/Volum15/Number15_1/cuprins15_1.htm
Issue1
Impact Factor

0.283
Ranking

93/100 - Q4
ISSN Number1453-8245