@inproceedings{fdf7d2934251440d89b3b1c7bf172742,
title = "Meeting the Real-Time Challenges of Ground-Based Telescopes Using Low-Rank Matrix Computations",
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.",
keywords = "Ground-Based Telescopes, Matrix-Vector Multiplication., Real-Time Computational Astronomy, Tile Low-Rank Approximation",
author = "Hatem Ltaief and Jesse Cranney and Damien Gratadour and Yuxi Hong and Laurent Gatineau and David Keyes",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE Computer Society. All rights reserved.; 33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021 ; Conference date: 14-11-2021 Through 19-11-2021",
year = "2021",
month = nov,
day = "14",
doi = "10.1145/3458817.3476225",
language = "English",
series = "International Conference for High Performance Computing, Networking, Storage and Analysis, SC",
publisher = "IEEE Computer Society",
booktitle = "Proceedings of SC 2021",
address = "United States",
}