| Инд. авторы: | Gorodnichev M., Medvedev Y. |
| Заглавие: | A web-based platform for interactive parameter study of large-scale lattice gas automata |
| Библ. ссылка: | Gorodnichev M., Medvedev Y. A web-based platform for interactive parameter study of large-scale lattice gas automata // Lecture Notes in Computer Science. - 2019. - Vol.11657 LNCS. - P.321-333. - ISSN 0302-9743. - EISSN 1611-3349. |
| Внешние системы: | DOI: 10.1007/978-3-030-25636-4_25; РИНЦ: 41626728; SCOPUS: 2-s2.0-85070606095; |
| Реферат: | eng: A problem of development of user-friendly interfaces for high performance computing (HPC) applications is addressed. The HPC Community Cloud (HPC2C) service that provides a RESTful application programming interface for unified control of HPC jobs was used to develop a prototype of a web-based UI for cellular automata simulation package. The UI allows a user to easily run multiple simulations on remote HPC resources and, this way, study a parameter space of a cellular automaton. The interface was used to organize a series of numerical experiments resulting in reproduction of the Kármán vortex street. © 2019, Springer Nature Switzerland AG. |
| Ключевые слова: | Turbulent flows; Lattice Gas Automata; Kármán vortex street; HPC cloud; High performance computing; Cellular automata; Application programming interfaces; Application programming interfaces (API); Wakes; Vortex flow; User interfaces; Turbulent flow; Software prototyping; Crystal lattices; Cellular automata; Cell proliferation; Websites; User interfaces; Phase interfaces; Vortex street; User friendly interface; Numerical experiments; Lattice-gas automaton; Hpc clouds; High performance computing (HPC); High performance computing; Cellular automata simulations; |
| Издано: | 2019 |
| Физ. характеристика: | с.321-333 |
| Конференция: | Название: 15th International Conference on Parallel Computing Technologies Аббревиатура: PaCT 2019 Город: Almaty Страна: Kazakhstan Даты проведения: 2019-08-19 - 2019-08-23 |
| Цитирование: | 1. Medvedev, Y.G.: Lattice gas Cellular Automata for a flow simulation and their parallel implementation. In: Tarkov, M.S. (ed.) Parallel Programming: Practical Aspects, Models and Current Limitations. Series: Mathematics Research Developments, pp. 143–158. NSP Inc., New York (2014) 2. Kármán, T.: Aerodynamics, pp. 67–73. First McGraw-Hill Paperback Edition (1963). ISBN 07-067602-x 3. Bandman, O.L.: Relationships between cellular automata model parameters and their physical counterparts. Bull. Nov. Comp. Center, Series Comput. Sci. (42), 1–14 (2018). https://doi.org/10.31144/bncc.cs.2542-1972.2018.n42.p1-14 4. Vanag, V.K.: Study of spatially extended dynamical systems using probabilistic cellular automata. Phys. Usp. 42(5), 413–434 (1999). https://doi.org/10.1070/PU1999v042n05ABEH000558 5. Chopard, B.: Cellular automata modeling of physical systems. In: Meyers, R. (ed.) Computational Complexity, pp. 407–433. Springer, New York (2012). https://doi. org/10.1007/978-1-4614-1800-9 6. Toffoli, T.: Cellular automata as an alternative to (rather than approximation of ) differential equations in modeling physics. PhysicaD 10, 117–127 (1984). https://doi.org/10.1016/0167-2789(84)90254-9 7. Bandman, O.L.: A discrete stochastic model of water permeation through a porous substance: parallel implementation peculiarities. Numer. Anal. Appl. 11(1), 4–15 (2018). https://doi.org/10.1134/S1995423918010020 8. Medvedev, Y.: Cellular-automaton simulation of a cumulative jet formation. In: Malyshkin, V. (ed.) PaCT 2009. LNCS, vol. 5698, pp. 249–256. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03275-2_25 9. Frisch, U., Hasslacher, B., Pomeau, Y.: Lattice-Gas Automata for the Navier-Stokes Equation. Phys. Rev. Lett. 56(14), 1505–1508 (1984). https://doi.org/10. 1103/PhysRevLett.56.1505 10. Goecks, J., et al.: Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11(8), R86 (2010). https://doi.org/10.1186/gb-2010-11-8-r86 11. Stodden, V., Seiler, J., Ma, Z.: An empirical analysis of journal policy effectiveness for computational reproducibility. Proc. Nat. Acad. Sci. USA 115(11), 2584–2589 (2018). https://doi.org/10.1073/pnas.1708290115 12. Jiménez, R.C., Kuzak, M., Alhamdoosh, M., et al.: Four simple recommendations to encourage best practices in research software [version 1; peer review: 3 approved]. F1000Research 6, 876 (2017) https://doi.org/10.12688/f1000research.11407.1 13. Hucka, M., Graham, M.J.: Software search is not a science, even among scientists: a survey of how scientists and engineers find software. J. Syst. Softw. 141, 171–191 (2018). https://doi.org/10.1016/j.jss.2018.03.047. ISSN 0164–1212 14. Calegari, P., Levrier, M., Balczyński, P.: Web portals for high-performance computing: a survey. ACM Trans. Web 13(1), 5:1–5:36 (2019). https://doi.org/10.1145/3197385 15. Afanasiev, A., Sukhoroslov, O., Voloshinov, V.: MathCloud: publication and reuse of scientific applications as RESTful web services. In: Malyshkin, V. (ed.) PaCT 2013. LNCS, vol. 7979, pp. 394–408. Springer, Heidelberg (2013).https://doi.org/10.1007/978-3-642-39958-9_36 16. Gorodnichev, M., Vaycel, S.: Organization of access to supercomputing resources in the HPC community cloud. Bull. South Ural State Univ. Ser. Comput. Math. Softw. Eng. 3(4), 85–95 (2014). https://doi.org/10.14529/cmse140406 17. Sukhoroslov, O., Volkov, S., Afanasiev, A.: A web-based platform for publication and distributed execution of computing applications. In: 14th International Symposium on Parallel and Distributed Computing, Limassol, pp. 175–184 (2015). https://doi.org/10.1109/ISPDC.2015.27 18. Cholia, S., Sun, T.: The NEWT platform: an extensible plugin framework for creating ReSTful HPC APIs. Concurrency Computat. Pract. Exper. 27, 4304– 4317 (2015). https://doi.org/10.1002/cpe.3517 19. OLeary, P., Christon, M., Jourdain, S., Harris, C., Berndt, M., Bauer, A.: HPC-Cloud: a cloud/web-based simulation environment. In: IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom), Vancouver, BC, pp. 25–33 (2015). https://doi.org/10.1109/CloudCom.2015.33 20. Cao, R., Xiao, H., Lu, S., Zhao, Y., Wang, X., Chi, X.: SCEAPI: a unified restful web API for high-performance computing. J. Phys. Conf. Ser. 898(9), 092022 (2017). https://doi.org/10.1088/1742-6596/898/9/092022 21. Bychkov, I.V., Oparin, G.A., Bogdanova, V.G., Pashinin, A.A., Gorsky, S.A.: Automation development framework of scalable scientific web applications based on subject domain knowledge. In: Malyshkin, V. (ed.) PaCT 2017. LNCS, vol. 10421, pp. 278–288. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62932-2_27 22. Struckmann, N., et al.: MIKELANGELO: MIcro KErneL virtualizAtioN for hiGh pErfOrmance cLOud and HPC systems. In: Mann, Z.Á., Stolz, V. (eds.) ESOCC 2017. CCIS, vol. 824, pp. 175–180. Springer, Cham (2018). https://doi.org/10. 1007/978-3-319-79090-9_15 |
