Parallel Simulation of Probabilistic P Systems on Multicore Platforms

TitleParallel Simulation of Probabilistic P Systems on Multicore Platforms
Publication TypeConference Contributions
Year of Publication2012
AuthorsMartínez-del-Amor, M. A., Karlin I., Jensen R. E., Pérez-Jiménez M. J., & Elster A. C.
Conference NameTenth Brainstorming Week on Membrane Computing
Volume TitleProceedings of the Tenth Brainstorming Week on Membrane Computing
PublisherFénix Editora
Place PublishedSeville, Spain
Date Published02/2012

Ecologists need to model ecosystems to predict how they will evolve over
time. Since ecosystems are non-deterministic phenomena, they must express the likeli-
hood of events occurring, and measure the uncertainty of their models' predictions. One
method well suited to these demands is Population Dynamic P systems (PDP systems, in
short), which is a formal framework based on multienvironment probabilistic P systems.
In this paper, we show how to parallelize a Population Dynamics P system simulator,
used to model biological systems, on multi-core processors, such as the Intel i5 Nehalem
and i7 Sandy Bridge. A comparison of three di erent techniques, discuss their strengths
and weaknesses, and evaluate their performance on two generations of Intel processors
with large memory sub-system di erences is presented. We show that P systems are
memory bound computations and future performance optimization e orts should focus
on memory trac reductions. We achieve runtime gains of up to 2.5x by using all the
cores of a single socket 4-core Intel i7 built on the Sandy Bridge architecture. From our
analysis of these results we identify further ways to improve the runtime of our simulator.

KeywordsMulticore Computing, OpenMP, P systems, Parallel Simulation, Population Dynamics