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    Real-Time Massively Distributed Multi-object Adaptive Optics Simulations for the European Extremely Large Telescope

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    moao.pdf
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    Type
    Conference Paper
    Authors
    Ltaief, Hatem cc
    Charara, Ali cc
    Gratadour, Damien
    Doucet, Nicolas
    Hadri, Bilel
    Gendron, Eric
    Feki, Saber
    Keyes, David
    KAUST Department
    KAUST Supercomputing Laboratory (KSL)
    Date
    2018-08-06
    Online Publication Date
    2018-08-06
    Print Publication Date
    2018-05
    Permanent link to this record
    http://hdl.handle.net/10754/628816
    
    Metadata
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    Abstract
    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.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
    Conference/Event name
    32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018
    DOI
    10.1109/IPDPS.2018.00018
    Additional Links
    https://ieeexplore.ieee.org/document/8425162
    ae974a485f413a2113503eed53cd6c53
    10.1109/IPDPS.2018.00018
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