Abstract
P system simulators are critical tools to enable them as formal modeling framework for real-life applications. Such simulators abstract the concept of P systems in various ways, depending on the needs of the users and the requirements of the specific application. We identify three main levels of abstraction: graphical user interfaces, simulation engines and parallel implementations. In this paper, we survey the state of the art at these levels and discuss the main challenges under consideration for future developments.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Notes
Field-programmable gate arrays, energy-efficient devices with application in HPC.
a.k.a. PDP systems.
DCBA is a simulation algorithm for PDP systems, aiming to “fairly” distribute the consumption of objects among competing rules.
Confluent systems may present different computations for a given input, but all of them leading to the same output.
We say that a collection of objects \(a_i\) is being used as a counter if the role of the index i is just counting steps (typically the rules associated are of the type \(a_i\rightarrow a_{i+1}\).
References
The PMCGPU (parallel simulators for membrane computing on the GPU) project website. http://sourceforge.net/p/pmcgpu. Accessed Feb 2020.
Abrahams, D., & Gurtovoy, A. (2005). C++ template metaprogramming. Boston: Addison-Wesley.
Carandang, J., Villaflores, J., Cabarle, F.G.C., Adorna, H.N., & Martínez-del-Amor, M.A. (2017). CuSNP: Spiking neural P systems simulators in CUDA. Romanian Journal of Information Science and Technology 20(1), 57–70. https://www.imt.ro/romjist/Volum20/Number20_1/cuprins20_1.htm.
Carandang, J. P., Cabarle, F. G., Adorna, H. N., Hernandez, Hope S. N., & Martínez-del-Amor, M. A. (2019). Handling non-determinism in spiking neural P systems: algorithms and simulations. Fundamenta Informaticae, 164, 139–155. https://doi.org/10.3233/FI-2019-1759.
Cecilia, J. M., García, J. M., Guerrero, G. D., Martínez-del-Amor, M. A., Pérez-Hurtado, I., & Pérez-Jiménez, M. J. (2010). Simulating a P system based efficient solution to SAT by using GPUs. Journal of Logic and Algebraic Programming, 79(6), 317–325. https://doi.org/10.1016/j.jlap.2010.03.008.
Cecilia, J. M., García, J. M., Guerrero, G. D., Martínez-del-Amor, M. A., Pérez-Hurtado, I., & Pérez-Jiménez, M. J. (2010). Simulation of P systems with active membranes on CUDA. Briefings in Bioinformatics, 11(3), 313–322. https://doi.org/10.1093/bib/bbp064.
Cecilia, J. M., García, J. M., Guerrero, G. D., Martínez-del-Amor, M. A., Pérez-Jiménez, M. J., & Ujaldón, M. (2012). The GPU on the simulation of cellular computing models. Soft Computing, 16(2), 231–246. https://doi.org/10.1007/s00500-011-0716-1.
Elkhani, N., Muniyandi, R. C., & Zhang, G. (2018). Multi-objective binary PSO with kernel P system on GPU. International Journal of Computers Communications and Control, 13, 323–336. https://doi.org/10.15837/ijccc.2018.3.3282.
Freund, R., Pérez-Hurtado, I., Riscos-Núñez, A., & Verlan, S. (2013). A formalization of membrane systems with dynamically evolving structures. International Journal of Computer Mathematics, 90(4), 801–815. https://doi.org/10.1080/00207160.2012.748899.
García-Quismondo, M. (2014). Modelling and simulation of real-life phenomena in membrane computing. PhD Thesis. Universidad de Sevilla. 2014. https://idus.us.es/handle/11441/66147.
García-Quismondo, M., Gutiérrez-Escudero, R., Martínez-del-Amor, M., Orejuela-Pinedo, E., & Pérez-Hurtado, I. (2009). P-lingua 2.0: a software framework for cell-like P systems. International Journal of Computers, Communications and Control, 4(3), 234–243. https://doi.org/10.15837/ijccc.2009.3.2431.
García-Quismondo, M., Macías-Ramos, L. F., & Pérez-Jiménez, M. J. (2013). Implementing enzymatic numerical P systems for AI applications by means of graphic processing units (pp. 137–159). Berlin: Springer. https://doi.org/10.1007/978-3-642-34422-0_10.
Henderson, A., & Nicolescu, R. (2019). Actor-like cP systems. In T. Hinze, G. Rozenberg, A. Salomaa, & C. Zandron (Eds.), Membrane computing (pp. 160–187). Lecture notes in computer science. Cham: Springer International Publishing.
Ipate, F., Lefticaru, R., Mierlă, L., Valencia-Cabrera, L., Han, H., Zhang, G., Dragomir, C., Pérez-Jiménez, M., & Gheorghe, M. (2013). Kernel P systems: applications and implementations. In Proc. 8th int. conf. on bio-inspired computing: theories and applications, Advances in intelligent systems and computing (vol. 2012, pp. 1081–1089).
Juayong, R., Cabarle, F. G., Adorna, H. N., Martínez-del-Amor, M. A.. (2012). On the simulations of Evolution-Communication P systems with Energy without antiport rules for GPUs. In 10th Brainstorming Week on Membrane Computing, BWMC12, Seville, Spain, February 2012, Proceedings (vol. I, pp. 267–290).
Kirk, D.B., & Hwu, W.W. (2016). Programming massively parallel processors: a hands-on approach, 3rd edn. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. https://www.sciencedirect.com/science/book/9780128119860.
Macías-Ramos, L. (2016). Developing efficient simulators for cell machines. PhD Thesis. Universidad de Sevilla. 2016. https://idus.us.es/handle/11441/36828.
Macías-Ramos, L. F., Martínez-del-Amor, M. A., & Pérez-Jiménez, M. J. (2015). Simulating FRSN P systems with real numbers in P-Lingua on sequential and CUDA platforms. In G. Rozenberg, A. Salomaa, J. M. Sempere, & C. Zandron (Eds.), Membrane computing (pp. 262–276). Cham: Springer International Publishing.
Maroosi, A., Muniyandi, R. C., Sundararajan, E., & Zin, A. M. (2014). Parallel and distributed computing models on a graphics processing unit to accelerate simulation of membrane systems. Simulation Modelling Practice and Theory, 47, 60–78. https://doi.org/10.1016/j.simpat.2014.05.005.
Martínez-del-Amor, M., Orellana-Martín, D., Pérez-Hurtado, I., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez, M.J. (2019). Design of specific P systems simulators on GPUs. In: T. Hinze, G. Rozenberg, A. Salomaa, C. Zandron (Eds.), Membrane computing (vol. 11399, pp. 202–207). Lecture notes in computer science. Springer International Publishing. https://doi.org/10.1007/978-3-030-12797-8_14.
Martínez-del-Amor, M.A. (2013). Accelerating membrane systems simulators using high performance computing with GPU. PhD Thesis. Universidad de Sevilla. 2013. https://idus.us.es/handle/11441/15644.
Martínez-del-Amor, M. A., García-Quismondo, M., Macías-Ramos, L. F., Valencia-Cabrera, L., Riscos-Núñez, A., & Pérez-Jiménez, M. J. (2015). Simulating P systems on GPU devices: a survey. Fundamenta Informaticae, 136(3), 269–284. https://doi.org/10.3233/FI-2015-1157.
Martínez-del-Amor, M. A., Macías-Ramos, L. F., Valencia-Cabrera, L., & Pérez-Jiménez, M. J. (2015). Parallel simulation of population dynamics P systems: updates and roadmap. Natural Computing, 15(4), 565–573. https://doi.org/10.1007/s11047-016-9566-1.
Martínez-del-Amor, M.A., Pérez-Carrasco, J., & Pérez-Jiménez, M.J. (2013). Characterizing the parallel simulation of P systems on the GPU. International Journal of Unconventional Computing 9(5-6), 405–424. https://www.oldcitypublishing.com/journals/ijuc-home/ijuc-issue-contents/ijuc-volume-9-number-5-6-2013/.
Martínez-del-Amor, M.A., Pérez-Hurtado, I., García-Quismondo, M., Macías-Ramos, L.F., Valencia-Cabrera, L., Romero-Jiménez, Á., Graciani-Díaz, C., Riscos-Núñez, A., Colomer, M.A., & Pérez-Jiménez, M.J. (2012). DCBA: simulating population dynamics P systems with proportional object distribution. In 13th International conference on membrane computing (CMC13), pp. 291–310. http://www.sztaki.hu/tcs/proba/cmc13/CMC13-proceedings.pdf.
Martínez-del-Amor, M.A., Pérez-Hurtado, I., Gastalver-Rubio, A., Elster, A.C., & Pérez-Jiménez, M.J. (2012). Population dynamics P systems on CUDA. In D. Gilbert, M. Heiner (Eds.) Computational methods in systems biology (vol. 7605, pp. 247–266). Lecture notes in computer science. Berlin: Springer. https://doi.org/10.1007/978-3-642-33636-2_15.
Martínez-del-Amor, M. A., Pérez-Hurtado, I., Orellana-Martín, D., & Pérez-Jiménez, M. J. (2020). Adaptative parallel simulators for bioinspired computing models. Future Generation Computer Systems, 107, 469–484. https://doi.org/10.1016/j.future.2020.02.012.
Pérez-Hurtado, I., Martínez-del-Amor, M. A., Zhang, G., Neri, F., & Pérez-Jiménez, M. J. (2020). A membrane parallel rapidly-exploring random tree algorithm for robotic motion planning. Integrated Computer-Aided Engineering, 27(2), 121–138. https://doi.org/10.3233/ICA-190616.
Pérez-Hurtado, I., Orellana-Martín, D., Zhang, G., & Pérez-Jiménez, M. J. (2019). P-Lingua in two steps: flexibility and efficiency. Journal of Membrane Computing, 1(2), 93–102. https://doi.org/10.1007/s41965-019-00014-1.
Pérez-Hurtado, I., Valencia-Cabrera, L., Pérez-Jiménez, M.J., Colomer, M.A., & Riscos-Núñez, A. (2010). MeCoSim: a general purpose software tool for simulating biological phenomena by means of P systems. In IEEE fifth international conference on bio-inpired computing: theories and applications (BIC-TA 2010), vol. I, pp. 637–643.
Valencia-Cabrera, L., Orellana-Martín, D., Martínez-del-Amor, M. Á., & Pérez-Jiménez, M. J. (2019). An interactive timeline of simulators in membrane computing. Journal of Membrane Computing, 1(3), 209–222. https://doi.org/10.1007/s41965-019-00016-z.
Zhang, G., Pérez-Jiménez, M., & Gheorghe, M. (2017). Real-life applications with membrane computing. Berlin: Springer. https://doi.org/10.1007/978-3-319-55989-6.
Zhang, G., Shang, Z., Verlan, S., del Amor, M.M., Yuan, C., Valencia-Cabrera, L., & Pérez-Jiménez, M. (2020). An overview of hardware implementation of membrane computing models. ACM Computing Surveys (Accepted).
Zhang, X., Wang, B., Ding, Z., Tang, J., & He, J. (2014). Implementation of membrane algorithms on GPU. Journal of Applied Mathematics,. https://doi.org/10.1155/2014/307617.
Acknowledgements
This work was supported by the research project TIN2017-89842-P (MABICAP), co-financed by Ministerio de Economía, Industria y Competitividad (MINECO) of Spain, through the Agencia Estatal de Investigación (AEI), and by Fondo Europeo de Desarrollo Regional (FEDER) of the European Union.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Valencia-Cabrera, L., Pérez-Hurtado, I. & Martínez-del-Amor, M.Á. Simulation challenges in membrane computing. J Membr Comput 2, 392–402 (2020). https://doi.org/10.1007/s41965-020-00056-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41965-020-00056-w