KAUST DepartmentExtreme Computing Research Center
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/627414
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AbstractThe real-time correction of telescopic images in the search for exoplanets is highly sensitive to atmospheric aberrations. The pseudoinverse algorithm is an efficient mathematical method to filter out these turbulences.We introduce a new partial singular value decomposition (SVD) algorithm based on QR-based Diagonally Weighted Halley (QDWH) iteration for the pseudo-inverse method of adaptive optics. The QDWH partial SVD algorithm selectively calculates the most significant singular values and their corresponding singular vectors. We develop a high performance implementation and demonstrate the numerical robustness of the QDWH-based partial SVD method. We also perform a benchmarking campaign on various generations of GPU hardware accelerators and compare against the state-of-the-art SVD implementation SGESDD from the MAGMA library. Numerical accuracy and performance results are reported using synthetic and real observational datasets from the Subaru telescope. Our implementation outperforms SGESDD by up to fivefold and fourfold performance speedups on ill-conditioned synthetic matrices and real observational datasets, respectively. The pseudo-inverse simulation code will be deployed on-sky for the Subaru telescope during observation nights scheduled early 2018.
CitationLtaief H, Sukkari D, Guyon O, Keyes D (2018) Extreme Computing for Extreme Adaptive Optics. Proceedings of the Platform for Advanced Scientific Computing Conference on - PASC ’18. Available: http://dx.doi.org/10.1145/3218176.3218225.
SponsorsThe authors would like to thank Yuji Nakatsukasa for technical discussions about QDWH-based partial SVD algorithm. The authors would like also to thank the NVIDIA for their hardware donations and remote access to their systems in the context of the NVIDIA GPU Research Center, awarded to the Extreme Computing Research Center at KAUST.
Conference/Event name5th Platform for Advanced Scientific Computing Conference, PASC 2018