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arxiv: 1902.04934 · v2 · submitted 2019-02-13 · 🌌 astro-ph.IM · gr-qc

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Accelerating parameter inference with graphics processing units

D. Wysocki (1) , R. O'Shaughnessy (1) , Y-L. L. Fang (2) , Jacob Lange (1) ((1) Center for Computational Relativity , Gravitation , Rochester Institute of Technology , (2) Computational Science Initiative , Brookhaven National Laboratory)
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classification 🌌 astro-ph.IM gr-qc
keywords costgraphicsinferenceneededoverallparameterprocessingrift
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Gravitational wave Bayesian parameter inference involves repeated comparisons of GW data to generic candidate predictions. Even with algorithmically efficient methods like RIFT or reduced-order quadrature, the time needed to perform these calculations and overall computational cost can be significant compared to the minutes to hours needed to achieve the goals of low-latency multimessenger astronomy. By translating some elements of the RIFT algorithm to operate on graphics processing units (GPU), we demonstrate substantial performance improvements, enabling dramatically reduced overall cost and latency.

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