Research Group on Natural Computing

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 dierent techniques, discuss their strengths
and weaknesses, and evaluate their performance on two generations of Intel processors
with large memory sub-system dierences is presented. We show that P systems are
memory bound computations and future performance optimization eorts 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.