Abstract
Due to their inherent parallel and non-deterministic nature, P system implementations require vast computing and storage resources. This significantly limits their applications, even more so when the calculation of all possible evolutions of the P system is required. This article exposes the scalability possibilities available with the Big Data ecosystem for P systems implementations, using Map Reduce parallelism to build the P system computation tree. The Hadoop based implementation is then used for generating test suites for cell like P systems, in particular for context-dependent rule coverage testing. Our preliminary evaluations on a benchmark of automatically generated P systems confirm that the proposed approach scales well.
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References
Păun, G.: Computing with membranes. Journal of Computer and System Sciences 61(1), 108–143 (2000)
Păun, G., Rozenberg, G., Salomaa, A.: The Oxford Handbook of Membrane Computing. Oxford University Press (2010)
Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. In: Sixth Symposium on Operating System Design and Implementation (2004)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Bigtable, R.E.G.: A Distributed Storage System for Structured Data. In: Seventh Symposium on Operating System Design and Implementation (2006)
Lefticaru, R., Ipate, F., Gheorghe, M.: Model checking based test generation from P systems using P-lingua. Romanian Journal of Information Science and Technology 13(2), 153–168 (2010); special issue on membrane computing containing selected papers from BWMC (2010)
Juayong, R.A.B., Cabarle, F.G.C., Adorna, H.N., Martinez-del-Amor, M.A.: On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs. In: 10th Brainstorming Week on Membrane Computing Proceeding, pp. 267–289 (2012)
Diez Dolinski, L., Núñez Hervás, R., Cruz EcheandÃa, M., Ortega, A.: Distributed Simulation of P Systems by Means of Map-Reduce: First Steps with Hadoop and P-Lingua. In: Cabestany, J., Rojas, I., Joya, G. (eds.) IWANN 2011, Part I. LNCS, vol. 6691, pp. 457–464. Springer, Heidelberg (2011)
Amor, M.A.M.: Accelerating Membrane Systems Simulators using High Performance Computing with GPU. PHD thesis University of Seville (2013)
http://docs.oracle.com/cd/NOSQL/html/index.html (visited May 10, 2013)
http://www.p-lingua.org (visited May 10, 2013)
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Ciobanu, A., Ipate, F. (2014). Implementation of P Systems by Using Big Data Technologies. In: Alhazov, A., Cojocaru, S., Gheorghe, M., Rogozhin, Y., Rozenberg, G., Salomaa, A. (eds) Membrane Computing. CMC 2013. Lecture Notes in Computer Science, vol 8340. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54239-8_10
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DOI: https://doi.org/10.1007/978-3-642-54239-8_10
Publisher Name: Springer, Berlin, Heidelberg
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