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DTSTART:19700308T020000
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DTSTAMP:20211207T054759Z
LOCATION:240-241-242
DTSTART;TZID=America/Chicago:20211116T140000
DTEND;TZID=America/Chicago:20211116T143000
UID:submissions.supercomputing.org_SC21_sess150_pap613@linklings.com
SUMMARY:Meeting the Real-Time Challenges of Ground-Based Telescopes Using 
 Low-Rank Matrix Computations
DESCRIPTION:Paper\n\nMeeting the Real-Time Challenges of Ground-Based Tele
 scopes Using Low-Rank Matrix Computations\n\nLtaief, Cranney, Gratadour, H
 ong, Gatineau...\n\nAdaptive Optics (AO) is a technology that permits to m
 easure and mitigate the distortion effects of atmospheric turbulence on op
 tical beams. AO must operate in a real-time environment by controlling tho
 usands of actuators to shape the surface of deformable mirrors deployed on
  ground-based telescopes to compensate for the distortions. The command ve
 ctors that trigger how each individual actuator should act to tilt a porti
 on of the mirror are obtained from Matrix-Vector Multiplications (MVM). We
  identify and leverage the data sparsity structure of these control matric
 es coming from the MAVIS instruments for the European Southern Observatory
 's Very Large Telescope. We provide performance evaluation on x86 and acce
 lerator-based systems. We present the impact of tile low-rank (TLR) matrix
  approximations on time-to-solution for the MVM and assess the produced im
 age quality. We achieve performance improvement up to two orders of magnit
 ude for TLR-MVM compared to regular dense MVM, while maintaining the image
  quality.\n\nTag: Algorithms, Applications, Performance\n\nRegistration Ca
 tegory: Tech Program Reg Pass
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