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.
|Original language||English (US)|
|Title of host publication||Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis|
|State||Published - Nov 13 2021|
Bibliographical noteKAUST Repository Item: Exported on 2022-02-11
Acknowledgements: ENTS The authors would like thank Fujitsu limited for their support on the evaluation environment and AMD/NVIDIA for the remote accesses steto their respective GPU-based systems.