A Spiking Neural P System Simulator Based on CUDA

Cabarle, Francis George C.; Adorna, Henry N.; Martínez, Miguel Á.

doi:10.1007/978-3-642-28024-5_8

Cited by 19 publications

(5 citation statements)

References 13 publications

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“…Among other works detailed there, we can recall the line followed along PMCGPU project [163]. Please look for the details about parallel simulators in [9], including among others [118][119][120][121][122][123][124][125][126][127][128]. Some more recent results appear after that surveys, including [10,129].…”

Section: The Era Of Practical Applications Based On P Systemsmentioning

confidence: 99%

An interactive timeline of simulators in membrane computing

et al. 2019

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As with any fast-emerging research front in computer science, the proliferation of theoretical and practical results within Membrane computing since its appearance in 1998 was astonishing. As a consequence, it became necessary during the subsequent years to produce several surveys collecting the main achievements from a theoretical point of view, along with some specific surveys about simulation tools for this paradigm. As the discipline has reached a certain degree of maturity, more practical applications have arisen, and new collective works are summarising the new software products appeared. However, while these recapitulation efforts remain useful for details about new simulators, they cannot act as exhaustive updated listings, as they become obsolete as soon as new tools are developed. Thus, we considered that it was necessary to provide an interactive tool showing an updated timeline (https ://www.gcn.us.es/Simul ation MC) about the simulation of the computational devices of membrane computing (a.k.a P systems), aiming to stay updated whenever any new practical work comes out in the discipline. This paper recalls the main stages and milestones within the evolution of simulation tools for different types and variants of P systems, along with their main related applications. In addition, it describes the interactive web tool with the timeline mentioned, where all the references related here have been incorporated. Unlike other survey papers, it is the intent of this work to reinforce this initial collective effort with the web endpoint kept alive and updated.

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Section: The Era Of Practical Applications Based On P Systemsmentioning

confidence: 99%

An interactive timeline of simulators in membrane computing

et al. 2019

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“…This matrix representation opens a door for the study of algebraic properties of cell-like and tissue-like P systems and represents one of the most promising buds waiting to be explored. Mario has also contributed to the study of the matrix representation of spiking neural P systems [66] which is the basis of the efficient simulation of such devices [5].…”

Section: Other Areas Of Computer Sciencementioning

confidence: 99%

Other Buds in Membrane Computing

Gutiérrez–Naranjo

2018

Enjoying Natural Computing

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It is well-known the huge Mario's contribution to the development of Membrane Computing. Many researchers may relate his name to the theory of complexity classes in P systems, the research of frontiers of the tractability or the application of Membrane Computing to model real-life situations as the Quorum Sensing System in Vibrio fischeri or the Bearded Vulture ecosystem. Beyond these research areas, in the last years Mario has presented many new research lines which can be considered as buds in the robust Membrane Computing tree. Many of them were the origin of new research branches, but some others are still waiting to be developed. This paper revisits some of these buds.

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“…• Simulation of spiking neural P systems: the first simulators in this regard have been initiated by Cabarle et al [1,2]. The implemented algorithm uses a matrix representation of the model, introduced by Zeng et al [29].…”

Section: Related Simulatorsmentioning

confidence: 99%

Simulating P Systems on GPU Devices: A Survey

Amor

García-Quismondo

Macías-Ramos

et al. 2015

Fundamenta Informaticae

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P systems have been proven to be useful as modeling tools in many fields, such as Systems Biology and Ecological Modeling. For such applications, the acceleration of P system simulation is often desired, given the computational needs derived from these kinds of models. One promising solution is to implement the inherent parallelism of P systems on platforms with parallel architectures.In this respect, GPU computing proved to be an alternative to more classic approaches in Parallel Computing. It provides a low cost, and a manycore platform with a high level of parallelism. The GPU has been already employed to speedup the simulation of P systems.In this paper, we look over the available parallel P systems simulators on the GPU, with special emphasis on those included in the PMCGPU project, and analyze some useful guidelines for future implementations and developments.

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A Spiking Neural P System Simulator Based on CUDA

Cited by 19 publications

References 13 publications

An interactive timeline of simulators in membrane computing

An interactive timeline of simulators in membrane computing

Other Buds in Membrane Computing

Simulating P Systems on GPU Devices: A Survey

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