Real-Time Massively Distributed Multi-object Adaptive Optics Simulations for the European Extremely Large Telescope
Type
Conference PaperAuthors
Ltaief, Hatem
Charara, Ali

Gratadour, Damien
Doucet, Nicolas
Hadri, Bilel
Gendron, Eric
Feki, Saber
Keyes, David
KAUST Department
KAUST Supercomputing Laboratory (KSL)Date
2018-08-06Online Publication Date
2018-08-06Print Publication Date
2018-05Permanent link to this record
http://hdl.handle.net/10754/628816
Metadata
Show full item recordAbstract
The European Extremely Large Telescope (E-ELT) is one of today's most challenging projects in ground-based astronomy. Addressing one of the key science cases for the E-ELT, the study of the early Universe, requires the implementation of multi-object adaptive optics (MOAO), a dedicated concept relying on turbulence tomography. We use a novel pseudo-Analytical approach to simulate the performance of tomographic reconstruction of the atmospheric turbulence in an MOAO system on real datasets. We simulate simultaneously 4K galaxies in a common field of view on massively parallel supercomputers during a single night of observations. We are able to generate a first-ever high-resolution galaxy map at almost a real-Time throughput. This simulation scale opens new research horizons in numerical methods for experimental astronomy, some core components of the pipeline standing as pathfinders toward actual operations and future astronomic discoveries on the E-ELT.Citation
Ltaief H, Charara A, Gratadour D, Doucet N, Hadri B, et al. (2018) Real-Time Massively Distributed Multi-object Adaptive Optics Simulations for the European Extremely Large Telescope. 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS). Available: http://dx.doi.org/10.1109/IPDPS.2018.00018.Sponsors
The authors would like to thank Aniello Esposito from Cray Inc. for his help in running the code and the vendor Cray for systems remote accesses in the context of the Cray Center of Excellence awarded to the Extreme Computing Research Center at KAUST. For computer time, this research used the resources from KAUST Supercomputing Laboratory for Shaheen-2 core hours allocation.Conference/Event name
32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018Additional Links
https://ieeexplore.ieee.org/document/8425162ae974a485f413a2113503eed53cd6c53
10.1109/IPDPS.2018.00018