@article {876,
	title = {Improving GPU Simulations of Spiking Neural P Systems},
	journal = {Romanian Journal of Information Science and Technology},
	volume = {15},
	year = {2012},
	month = {06/2012},
	pages = {5-20},
	publisher = {EDITURA ACADEMIEI ROM{\^A}NE},
	edition = {Bio-Inspired Computing {\textendash} Theory and Applications (BIC-TA) - Selected papers},
	address = {Bucure{\c s}ti, Rom{\^a}nia},
	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.
},
	keywords = {CUDA, GPU Computing, Membrane computing, spiking neural network, spiking neural P systems},
	issn = {1453-8245},
	url = {http://www.imt.ro/romjist/Volum15/Number15_1/cuprins15_1.htm},
	author = {Francis Cabarle and Henry Adorna and Miguel A. Mart{\'\i}nez-del-Amor and Mario J. P{\'e}rez-Jim{\'e}nez}
}
