Abstract
Non-equilibrium ionization (NEI) is an important phenomenon related to many astrophysical processes, but the traditional method, which tightly couples the NEI solver with Eulerian mesh infrastructure, introduced high overhead on computing, memory and communication. In order to overcome the shortcomings of the pure Eulerian scheme, a new approach employing tracer particles and MapReduce model to solve the NEI problem was proposed. We introduce (1) a particle-dumping scheme for tackling the problem of large amounts of small particle snapshots continuously generated at each evolution step, (2) a parallel method based on the MapReduce model to solve the NEI equations along the particle trajectories. Both post-processing and nonintrusive in-situ schemes are supported in the paper’s approach. The approach was prototyped and tested based on the FLASH multiphysics simulation framework, and it is easily adapted to other simulations modeling reactive flow on Eulerian mesh. Evaluations on up to 192 cores show that our approach can improve the end-to-end performance of a real world simulation by 3-fold above.
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References
Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Communications of the ACM 51(1), 107–113 (2008)
Dorier, M., Antoniu, G., Cappello, F., Snir, M., Orf, L.: Damaris: how to efficiently leverage multicore parallelism to achieve scalable, jitter-free i/o. In: 2012 IEEE International Conference on Cluster Computing (CLUSTER), pp. 155–163. IEEE Press, New York (2012)
Dorier, M., Sisneros, R., Peterka, T., Antoniu, G., Semeraro, D.: Damaris/viz: A nonintrusive, adaptable and user-friendly in situ visualization framework. In: 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), pp. 67–75. IEEE Press, New York (2013)
Dubey, A., Antypas, K., Daley, C.: Parallel algorithms for moving lagrangian data on block structured eulerian meshes. Parallel Computing 37(2), 101–113 (2011)
Dubey, A., Antypas, K., Ganapathy, M.K., Reid, L.B., et al.: Extensible component-based architecture for flash, a massively parallel, multiphysics simulation code. Parallel Computing 35(10), 512–522 (2009)
Dubey, A., Calder, A.C., Daley, C., Fisher, R.T., et al.: Pragmatic optimizations for better scientific utilization of large supercomputers. International Journal of High Performance Computing Applications 27(3), 360–373 (2013)
Ekanayake, J., Pallickara, S., Fox, G.: Mapreduce for data intensive scientific analyses. In: IEEE Fourth International Conference on eScience, pp. 277–284. IEEE Press, New York (2008)
Fisher, R., Kadanoff, L., Lamb, D., Constantin, P., et al.: Terascale turbulence computation on bg/l using the flash3 code. IBM Journal of Research and Development v52 i1/2, 127–137 (2006)
FLASH Center for Computational Science, University of Chicago. FLASH User’s Guide (2012)
Genel, S., Vogelsberger, M., Nelson, D., Sijacki, D., Springel, V., Hernquist, L.: Following the flow: tracer particles in astrophysical fluid simulations. Monthly Notices of the Royal Astronomical Society 435(2), 1426–1442 (2013)
Latham, R., Daley, C., Liao, W.K., Gao, K., Ross, R., Dubey, A., Choudhary, A.: A case study for scientific i/o: Improving the flash astrophysics code. Computational Science & Discovery 5(1), 15001 (2012)
Li, M., Vazhkudai, S.S., Butt, A.R., Meng, F., et al.: Functional partitioning to optimize end-to-end performance on many-core architectures. In: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis(SC), pp. 1–12. IEEE Press, New York (2010)
MacNeice, P., Olson, K.M., Mobarry, C., de Fainchtein, R., Packer, C.: Paramesh: A parallel adaptive mesh refinement community toolkit. Computer Physics Communications 126(3), 330–354 (2000)
Plimpton, S.J., Devine, K.D.: Mapreduce in mpi for large-scale graph algorithms. Parallel Computing 37(9), 610–632 (2011)
Plimpton, S.J., Shead, T.: Phish library, http://www.sandia.gov/~sjplimp/phish.html
Timmes, F.X., Hoffman, R.D., Woosley, S.E.: An inexpensive nuclear energy generation network for stellar hydrodynamics. The Astrophysical Journal Supplement Series 129(1), 377–398 (2000)
Tu, T., Rendleman, C.A., Borhani, D.W., Dror, R.O., et al.: A scalable parallel framework for analyzing terascale molecular dynamics simulation trajectories. In: Proceedings of the 2008 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis(SC), pp. 1–12. IEEE Press, New York (2008)
Zhou, X., Miceli, M., Bocchino, F., Orlando, S., Chen, Y.: Unveiling the spatial structure of the overionized plasma in the supernova remnant w49b. Monthly Notices of the Royal Astronomical Society 415(1), 244–250 (2011)
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Xiao, J., Xu, X., Sun, J., Zhou, X., Ji, L. (2014). Acceleration of Solving Non-Equilibrium Ionization via Tracer Particles and MapReduce on Eulerian Mesh. In: Sun, Xh., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, vol 8631. Springer, Cham. https://doi.org/10.1007/978-3-319-11194-0_3
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DOI: https://doi.org/10.1007/978-3-319-11194-0_3
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