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Meeting the Real-Time Challenges of Ground-Based Telescopes Using Low-Rank Matrix Computations

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Authors

Ltaief, Hatem
Cranney, Jesse
Gratadour, Damien
Hong, Yuxi
Gatineau, Laurent
Keyes, David

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Association for Computing Machinery (ACM)

Abstract

Adaptive Optics (AO) is a technology that permits to measure and mitigate the distortion effects of atmospheric turbulence on optical beams. AO must operate in real-Time by controlling thousands of actuators to shape the surface of deformable mirrors deployed on ground-based telescopes to compensate for these distortions. The command vectors that trigger how each individual actuator should act to bend a portion of the mirror are obtained from Matrix-Vector Multiplications (MVM). We identify and leverage the data sparsity structure of these control matrices coming from the MAVIS instruments for the European Southern Observatory s Very Large Telescope. We provide performance evaluation on x86 and acceleratorbased systems.We present the impact of tile low-rank (TLR) matrix approximations on time-To-solution for the MVM and assess the produced image quality. We achieve performance improvement up to two orders of magnitude for TLR-MVM compared to regular dense MVM, while maintaining the image quality.

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SC '21: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

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Open Access

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Creative Commons Attribution 4.0 International License

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