Advertisement

Natural Computing

, Volume 15, Issue 4, pp 565–573 | Cite as

Parallel simulation of Population Dynamics P systems: updates and roadmap

  • Miguel A. Martínez-del-AmorEmail author
  • Luis F. Macías-Ramos
  • Luis Valencia-Cabrera
  • Mario J. Pérez-Jiménez
Article

Abstract

Population Dynamics P systems are a type of multienvironment P systems that serve as a formal modeling framework for real ecosystems. The accurate simulation of these probabilistic models, e.g. with Direct distribution based on Consistent Blocks Algorithm, entails large run times. Hence, parallel platforms such as GPUs have been employed to speedup the simulation. In 2012, the first GPU simulator of PDP systems was presented. However, it was able to run only randomly generated PDP systems. In this paper, we present current updates made on this simulator, involving an input modu le for binary files and an output module for CSV files. Finally, the simulator has been experimentally validated with a real ecosystem model, and its performance has been tested with two high-end GPUs: Tesla C1060 and K40.

Keywords

Membrane computing Ecological modelling PDP systems Parallel simulation GPU computing CUDA 

Notes

Acknowledgments

The authors acknowledge the support of the project TIN2012-37434 of the “Ministerio de Economía y Competitividad” of Spain, co-financed by FEDER funds. They also acknowledge the CUDA Research Center program, granted by NVIDIA to the University of Seville in 2014, 2015 and 2016, and their donation of a Tesla K40 GPU. Finally, Martínez-del-Amor also acknowledges the support of the 3rd postdoctoral phase of the PIF program associated with the project of excellence from “Junta de Andalucía” under grant P08–TIC04200, co-financed by FEDER funds.

References

  1. Cardona M, Colomer MA, Margalida A, Pérez-Hurtado I, Pérez-Jiménez MJ, Sanuy D (2010) A P system based model of an ecosystem of some scavenger birds. LNCS 5957:182–195. doi: 10.1007/978-3-642-11467-0_14 zbMATHGoogle Scholar
  2. Cardona M, Colomer MA, Margalida A, Palau A, Pérez-Hurtado I, Pérez-Jiménez MJ, Sanuy D (2011) A computational modeling for real ecosystems based on P systems. Nat Comput 10(1):39–53. doi: 10.1007/s11047-010-9191-3 MathSciNetCrossRefzbMATHGoogle Scholar
  3. Cecilia JM, García JM, Guerrero GD, Martínez-del-Amor MA, Pérez-Hurtado I, Pérez-Jiménez MJ (2010) Simulation of P systems with active membranes on CUDA. Brief Bioinform 11(3):313–322. doi: 10.1093/bib/bbp064 CrossRefGoogle Scholar
  4. Colomer MA, Margalida A, Pérez-Jiménez MJ (2013) Population dynamics P system (PDP) models: a standardized protocol for describing and applying novel bio-inspired computing tools. PLoS One 8(4):e60698. doi: 10.1371/journal.pone.0060698 CrossRefGoogle Scholar
  5. Colomer-Cugat MA, García-Quismondo M, Macías-Ramos LF, Martínez-del-Amor MA, Pérez-Hurtado I, Pérez-Jiménez MJ, Riscos-Núñez A, Valencia-Cabrera L (2014) Membrane system-based models for specifying dynamical population systems. In: Frisco P et al (eds) Applications of membrane computing in systems and synthetic biology. Emergence, complexity and computation series, chap 4, vol 7. Springer International Publishing, Switzerland, pp 97–132Google Scholar
  6. García-Quismondo M, Gutiérrez-Escudero R, Pérez-Hurtado I, Pérez-Jiménez MJ, Riscos-Núñez A (2010) An overview of P-Lingua 2.0. LNCS 5957:264–288. doi: 10.1007/978-3-642-11467-0_20 zbMATHGoogle Scholar
  7. García-Quismondo M, Martínez-del-Amor MA, Pérez-Jiménez MJ (2014) Probabilistic guarded P systems: a new formal modelling framework. LNCS 8961:194–214. doi: 10.1007/978-3-319-14370-5_12 MathSciNetzbMATHGoogle Scholar
  8. Gastalver-Rubio A (2012) Simulation of probabilistic P systems on GPUs. Final Research Project, University of SevilleGoogle Scholar
  9. GPGPU organization. http://www.gpgpu.org
  10. Harris M (2005) Mapping computational concepts to GPUs. In: ACM SIGGRAPH 2005 Courses, New YorkGoogle Scholar
  11. Kirk D, Hwu W (2010) Programming massively parallel processors: a hands on approach. Morgan Kaufmann, WalthamGoogle Scholar
  12. Martínez-del-Amor MA (2013) Accelerating membrane systems simulators using high performance computing with GPU, Ph.D. thesis, University of SevilleGoogle Scholar
  13. Martínez-del-Amor MA, Karlin I, Jensen RE, Pérez-Jiménez MJ, Elster AC (2012a) Parallel simulation of probabilistic P systems on multicore platforms. In: García-Quismondo M et al (eds.) Tenth brainstorming week on membrane computing, vol II. Fénix editora, Sevilla, pp 17–26Google Scholar
  14. Martínez-del-Amor MA, Pérez-Hurtado I, Gastalver-Rubio A, Elster AC, Pérez-Jiménez MJ (2012b) Population dynamics P systems on CUDA. In: 10th Conference on computational methods in systems biology, LNBI, vol 7605, pp 247–266Google Scholar
  15. Martínez-del-Amor MA, Pérez-Hurtado I, García-Quismondo M, Macías-Ramos LF, Valencia-Cabrera L, Romero-Jiménez A, Graciani C, Riscos-Núñez A, Colomer MA, Pérez-Jiménez MJ (2012c) DCBA: simulating population dynamics P systems with proportional object distribution. LNCS 7762:27–56. doi: 10.1007/978-3-642-36751-9_18 zbMATHGoogle Scholar
  16. Martínez-del-Amor MA, García-Quismondo M, Macías-Ramos LF, Valencia-Cabrera L, Riscos-Núñez A, Pérez-Jiménez MJ (2015) Simulating P systems on GPU devices: a survey. Fundam Inform 136(3):269–284. doi: 10.3233/FI-2015-1157 MathSciNetzbMATHGoogle Scholar
  17. NVIDIA CUDA website (2015). https://developer.nvidia.com/cuda-zone
  18. OpenMP webiste. http://www.openmp.org
  19. Owens JD, Houston M, Luebke D, Green S, Stone JE, Phillips JC (2008) GPU computing. Proc IEEE 96(5):879–899CrossRefGoogle Scholar
  20. Păun G (2000) Computing with membranes. J Comput Syst Sci 61(1):108–143. doi: 10.1006/jcss.1999.1693 MathSciNetCrossRefzbMATHGoogle Scholar
  21. Păun G, Rozenberg G, Salomaa A (eds) (2010) The Oxford handbook of membrane computing. Oxford University Press, OxfordzbMATHGoogle Scholar
  22. Pérez-Hurtado I, Valencia-Cabrera L, Pérez-Jiménez MJ, Colomer MA, Riscos-Núñez A (2010) MeCoSim: a general purpose software tool for simulating biological phenomena by means of P systems. In: Proceedings IEEE fifth international conference on bio-inpired computing: theories and applications (BIC-TA 2010), vol I, pp 637–643. doi: 10.1109/BICTA.2010.5645199
  23. Pérez-Jiménez MJ, Romero-Campero FJ (2006) P systems, a new computational modelling tool for Systems Biology. Trans Comput Syst Biol VI LNBI 4220:176–197. doi: 10.1007/11880646_8 MathSciNetCrossRefGoogle Scholar
  24. Romero-Campero FJ, Pérez-Jiménez MJ (2008) A model of the quorum sensing system in Vibrio fischeri using P systems. Artif Life 14(1):95–109. doi: 10.1162/artl.2008.14.1.95 CrossRefGoogle Scholar
  25. The MeCoSim web page. http://www.p-lingua.org/mecosim
  26. The P-Lingua web page. http://www.p-lingua.org
  27. The PMCGPU project (2013) http://sourceforge.net/p/pmcgpu

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Miguel A. Martínez-del-Amor
    • 1
    Email author
  • Luis F. Macías-Ramos
    • 1
  • Luis Valencia-Cabrera
    • 1
  • Mario J. Pérez-Jiménez
    • 1
  1. 1.Research Group on Natural ComputingUniversidad de SevillaSevilleSpain

Personalised recommendations