Abstract
This article presents the application of parallel multithreading strategies for the calculation of the self-gravity force field in astronomical small bodies. Efficient and accurate algorithms are needed to simulate the dynamic of asteroids and comets, which are formed by the agglomeration of many (i.e. in the order of million) small objects. Parallel high performance computing comes to help researchers to perform the required simulations of large systems in reasonable execution times. In this article, we describe several strategies for the computation on shared-memory high performance computing infrastructures and a experimental analysis studying the execution time, speedup and computational efficiency are reported. Promising results are reported for the strategy that applies a smart isolation lineal approach for dividing the calculation work to be performed by each computing element. The experimental results demonstrate that this strategy achieves almost-linear speedup, allowing researchers to perform accurate simulations in reduced execution times, even for those cases where very large systems are studied.
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The research reported in this article is partly supported by ANII and PEDECIBA, Uruguay.
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Nesmachnow, S., Frascarelli, D., Tancredi, G. (2016). A Parallel Multithreading Algorithm for Self-gravity Calculation on Agglomerates. In: Gitler, I., Klapp, J. (eds) High Performance Computer Applications. ISUM 2015. Communications in Computer and Information Science, vol 595. Springer, Cham. https://doi.org/10.1007/978-3-319-32243-8_22
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DOI: https://doi.org/10.1007/978-3-319-32243-8_22
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