@article {springerlink:10.1007/978-3-642-33636-2_15,
	title = {Population Dynamics P Systems on CUDA},
	journal = {Lecture Notes in Bioinformatics},
	volume = {7605},
	year = {2012},
	note = {10.1007/978-3-642-33636-2_15},
	pages = {247-266},
	publisher = {Springer Berlin / Heidelberg},
	edition = {Computational Methods in Systems Biology},
	abstract = {Population Dynamics P systems (PDP systems, in short) provide a new formal bio-inspired modeling framework, which has been successfully used by ecologists. These models are validated using software tools against actual measurements. The goal is to use P systems simulations to adopt a priori management strategies for real ecosystems. Software for PDP systems is still in an early stage. The simulation of PDP systems is both computationally and data intensive for large models. Therefore, the development of efficient simulators is needed for this field. In this paper, we introduce a novel simulator for PDP systems accelerated by the use of the computational power of GPUs. We discuss the implementation of each part of the simulator, and show how to achieve up to a 7x speedup on a NVIDA Tesla C1060 compared to an optimized multicore version on a Intel 4-core i5 Xeon for large systems. Other results and testing methodologies are also included.},
	keywords = {CUDA, Ecological Modeling, GPU Computing, Membrane computing, Parallel Simulation, Population Dynamics},
	isbn = {978-3-642-33635-5},
	doi = {10.1007/978-3-642-33636-2_15},
	url = {http://dx.doi.org/10.1007/978-3-642-33636-2_15},
	author = {Miguel A. Mart{\'\i}nez-del-Amor and Ignacio P{\'e}rez-Hurtado and Adolfo Gastalver-Rubio and Anne C. Elster and Mario J. P{\'e}rez-Jim{\'e}nez},
	editor = {Gilbert, David and Heiner, Monika}
}
