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Efficient Simulation of Reaction Systems on Graphics Processing Units

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Reaction systems represent a theoretical framework based on the regulation mechanisms of facilitation and inhibition of biochemical reactions. The dynamic process defined by a reaction system is typically derived by hand, starting from the set of reactions and a given context sequence. However, this procedure may be error-prone and time-consuming, especially when the size of the reaction system increases. Here we present HERESY, a simulator of reaction systems accelerated on Graphics Processing Units (GPUs). HERESY is based on a fine-grained parallelization strategy, whereby all reactions are simultaneously executed on the GPU, therefore reducing the overall running time of the simulation. HERESY is particularly advantageous for the simulation of large-scale reaction systems, consisting of hundreds or thousands of reactions. By considering as test case some reaction systems with an increasing number of reactions and entities, as well as an increasing number of entities per reaction, we show that HERESY allows up to 29× speed-up with respect to a CPU-based simulator of reaction systems. Finally, we provide some directions for the optimization of HERESY, considering minimal reaction systems in normal form.
Wydawca
Rocznik
Strony
307--321
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wykr.
Twórcy
autor
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
autor
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
autor
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
autor
  • University of Bergamo – Department of Human and Social Sciences, Piazzale S. Agostino 2, 24129 Bergamo, Italy
autor
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
autor
  • University of Milano-Bicocca – Department of Informatics, Systems and Communication, Viale Sarca 336, 20126 Milano, Italy
Bibliografia
  • [1] Arbib MA (ed.). Handbook of Brain Theory and Neural Networks. The MIT Press, 1995.
  • [2] De Jong K. Evolutionary Computation: A Unified Approach. The MIT Press, 2006. ISBN:9780262041942.
  • [3] Calude C, Pǎun G. Computing with Cells and Atoms: An Introduction to Quantum, DNA and Membrane Computing. CRC Press, 2000. ISBN:9780748408993.
  • [4] Wolfram S. A New Kind of Science. Wolfram Media, 2002.
  • [5] Pǎun G, Rozenberg G, Salomaa A (eds.). The Oxford Handbook of Membrane Computing. Oxford University Press, 2009.
  • [6] Ehrenfeucht A, Rozenberg G. Reaction systems. Fundamenta Informaticae, 2007;75:263–280. URL http://content.iospress.com/journals/fundamenta-informaticae/145/2.
  • [7] Ehrenfeucht A, Rozenberg G. Events and modules in reaction systems. Theoretical Computer Science, 2007;376:3–16. doi:10.1016/j.tcs.2007.01.008.
  • [8] Brijder R, Ehrenfeucht A, Rozenberg G. Reaction systems with duration. In: Kelemen A, Kelemenová J (eds.), Computation, Cooperation, and Life, volume 6610 of Lecture Notes in Computer Science, pp. 191–202. Springer-Verlag, 2011. doi:10.1007/978-3-642-20000-7_16.
  • [9] Brijder R, Ehrenfeucht A, Main M, Rozenberg G. A tour of reaction systems. International Journal of Foundations of Computer Science, 2011;22(7):1499–1517. URL https://doi.org/10.1142/S0129054111008842.
  • [10] Kleijn J, Koutny M, Rozenberg G. Modelling reaction systems with Petri nets. In: Heiner M, Matsuno H (eds.), Proceedings of the International Workshop on Biological Processes & Petri Nets (BioPPN-2011), volume 724. CEUR Workshop Proceedings, 2011 pp. 36–52.
  • [11] Ehrenfeucht A, Main M, Rozenberg G. Functions defined by reaction systems. International Journal of Foundations of Computer Science, 2011;22(1):167–178. URL https://doi.org/10.1142/S0129054111007927.
  • [12] Ehrenfeucht A, Main M, Rozenberg G. Combinatorics of life and death for reaction systems. International Journal of Foundations of Computer Science, 2010;21(3):345–356. URL https://doi.org/10.1142/S0129054110007295.
  • [13] Brijder R, Ehrenfeucht A, Rozenberg G. A note on causalities in reaction systems. In: Ermel C, Ehrig H, Orejas F, Taentzer G (eds.), International Colloquium on Graph and Model Transformation On the occasion of the 65th birthday of Hartmut Ehrig (GraMoT 2010), volume 30. ECEASST, 2010 pp. 1–9.
  • [14] Corolli L, Maj C, Marini F, Besozzi D, Mauri G. An excursion in reaction systems: From computer science to biology. Theoretical Computer Science, 2012;454:95–108. URL https://doi.org/10.1016/j.tcs.2012.04.003.
  • [15] Ehrenfeucht A, Rozenberg G. Introducing time in reaction systems. Theoretical Computer Science, 2009;410:310–322. URL https://doi.org/10.1016/j.tcs.2008.09.043
  • [16] Nobile MS, Cazzaniga P, Tangherloni A, Besozzi D. Graphics processing units in bioinformatics, computational biology and systems biology. Briefings in Bioinformatics, 2016. bbw058. doi:10.1093/bib/bbw058.
  • [17] Hynes NE, Lane HA. ERBB receptors and cancer: the complexity of targeted inhibitors. Nature Reviews Cancer, 2005;5(5):341–354. doi: 10.1038/nrc1609.
  • [18] Formenti E, Manzoni L, Porreca AE. Fixed points and attractors of reaction systems. In: Beckmann A, Csuhaj-Varjú E, Meer K (eds.), Language, Life, Limits, 10th Conference on Computability in Europe, CiE 2014, volume 8493 of Lecture Notes in Computer Science, pp. 194–203. Springer, 2014. URL http: //dx.doi.org/10.1007/978-3-319-08019-2_20.
  • [19] Formenti E, Manzoni L, Porreca AE. Cycles and global attractors of reaction systems. In: Jürgensen H, Karhumäki J, Okhotin A (eds.), Descriptional Complexity of Formal Systems, 16th International Workshop, DCFS 2014, volume 8614 of Lecture Notes in Computer Science, pp. 114–125. Springer, 2014. URL http://dx.doi.org/10.1007/978-3-319-09704-6_11.
  • [20] Męski A, Penczek W, Rozenberg G. Model checking temporal properties of reaction systems. Information Sciences, 2015;313:22–42. URL http://dx.doi.org/10.1016/j.ins.2015.03.048.
  • [21] Azimi S, Gratie C, Ivanov S, Manzoni L, Petre I, Porreca AE. Complexity of model checking for reaction systems. Theoretical Computer Science, 2016;623:103–113. URL http://dx.doi.org/10.1016/j.tcs.2015.11.040.
  • [22] HERESY GitHub Repository. https://github.com/aresio/HERESY/, 2017.
  • [23] Azimi S, Gratie C, Ivanov S, Petre I. Dependency graphs and mass conservation in reaction systems. Theoretical Computer Science, 2015;598:23–39. doi:10.1016/j.tcs.2015.02.014.
  • [24] brsim GitHub Repository. https://github.com/scolobb/brsim/, 2014.
  • [25] brsim Web Interface. http://combio.abo.fi/research/reaction-systems/reaction-system-simulator/.
  • [26] Helikar T, Kochi N, Kowal B, Dimri M, Naramura M, Raja SM, Band V, Band H, Rogers JA. A comprehensive, multi-scale dynamical model of ErbB receptor signal transduction in human mammary epithelial cells. PLoS ONE, 2013;8(4):e61757. URL https://doi.org/10.1371/journal.pone.0061757.
  • [27] Yarden Y, Sliwkowski MX. Untangling the ErbB signalling network. Nature Reviews Molecular Cell Biology, 2001;2(2):127–137. doi: 10.1038/35052073.
  • [28] Manzoni L, Poças D, Porreca AE. Simple reaction systems and their classification. International Journal of Foundations of Computer Science, 2014;25(4):441–457. URL https://doi.org/10.1142/S012905411440005X.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-42a200ed-7224-4298-9e88-969a4eb00b44
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