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Efficient Ephemeris Models for Spacecraft Trajectory Simulations on GPUs

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Euro-Par 2020: Parallel Processing (Euro-Par 2020)

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Abstract

When a spacecraft is released into space, its initial condition and future trajectory in terms of position and speed cannot be precisely predicted. To ensure that the object does not violate space debris mitigation or planetary protection standards, such that it causes potential damage or contamination of celestial bodies, spacecraft-mission designers conduct a multitude of simulations to verify the validity of the set of all probable trajectories. Such simulations are usually independent from each other, making them a perfect match for parallelization. The European Space Agency (ESA) developed a GPU-based simulator for this purpose and achieved reasonable speedups in comparison with the established multi-threaded CPU version. However, we noticed that the performance starts to degrade as the spacecraft trajectories diverge in time. Our empirical analysis using GPU profilers showed that the application suffers from poor data locality and high memory traffic. In this paper, we propose an alternative data layout, which increases data locality within thread blocks. Furthermore, we introduce alternative model configurations that lower both algorithmic effort and the number of memory requests without violating accuracy requirements. Our experiments show that our method is able to accelerate the computations up to a factor of 2.6.

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Acknowledgments

This research has been supported by the European Space Agency, Hessian LOEWE initiative within the Software-Factory 4.0 project, and the German Research Foundation (DFG) through the Program Performance Engineering for Scientific Software. The calculations for this research were conducted on the Lichtenberg high performance computer of the Technical University of Darmstadt and European Space Agency.

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Correspondence to Arya Mazaheri .

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Schrammel, F., Renk, F., Mazaheri, A., Wolf, F. (2020). Efficient Ephemeris Models for Spacecraft Trajectory Simulations on GPUs. In: Malawski, M., Rzadca, K. (eds) Euro-Par 2020: Parallel Processing. Euro-Par 2020. Lecture Notes in Computer Science(), vol 12247. Springer, Cham. https://doi.org/10.1007/978-3-030-57675-2_35

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  • DOI: https://doi.org/10.1007/978-3-030-57675-2_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57674-5

  • Online ISBN: 978-3-030-57675-2

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