[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Log in

Simulation challenges in membrane computing

  • Survey Paper
  • Published:
Journal of Membrane Computing Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. Field-programmable gate arrays, energy-efficient devices with application in HPC.

  2. a.k.a. PDP systems.

  3. DCBA is a simulation algorithm for PDP systems, aiming to “fairly” distribute the consumption of objects among competing rules.

  4. Confluent systems may present different computations for a given input, but all of them leading to the same output.

  5. 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

  1. The PMCGPU (parallel simulators for membrane computing on the GPU) project website. http://sourceforge.net/p/pmcgpu. Accessed Feb 2020.

  2. Abrahams, D., & Gurtovoy, A. (2005). C++ template metaprogramming. Boston: Addison-Wesley.

    Google Scholar 

  3. 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.

  4. 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.

    Article  MathSciNet  MATH  Google Scholar 

  5. 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.

    Article  MathSciNet  MATH  Google Scholar 

  6. 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.

    Article  Google Scholar 

  7. 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.

    Article  Google Scholar 

  8. 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.

    Article  Google Scholar 

  9. 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.

    Article  MathSciNet  MATH  Google Scholar 

  10. 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.

  11. 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.

    Article  Google Scholar 

  12. 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.

    Book  Google Scholar 

  13. 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.

  14. 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).

  15. 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).

  16. 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.

  17. Macías-Ramos, L. (2016). Developing efficient simulators for cell machines. PhD Thesis. Universidad de Sevilla. 2016. https://idus.us.es/handle/11441/36828.

  18. 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.

    Chapter  Google Scholar 

  19. 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.

    Article  Google Scholar 

  20. 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.

  21. 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.

  22. 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.

    Article  MathSciNet  MATH  Google Scholar 

  23. 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.

    Article  MathSciNet  MATH  Google Scholar 

  24. 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/.

  25. 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.

  26. 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.

  27. 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.

    Article  Google Scholar 

  28. 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.

    Article  Google Scholar 

  29. 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.

    Article  MathSciNet  Google Scholar 

  30. 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.

  31. 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.

    Article  MathSciNet  Google Scholar 

  32. 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.

    Book  MATH  Google Scholar 

  33. 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).

  34. 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.

    Article  Google Scholar 

Download references

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

Authors

Corresponding author

Correspondence to Luis Valencia-Cabrera.

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41965-020-00056-w

Keywords

Navigation