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Accelerating parameter inference with graphics processing units
By D. Wysocki, R. O’Shaughnessy, Jacob Lange, and Yao-Lung L. Fang
Published in Physical Review D 99, 084026 (Tuesday, April 16, 2019)


Gravitational wave Bayesian parameter inference involves repeated comparisons of gravitational wave data to generic candidate predictions. Even with algorithmically efficient methods such as RIFT or reduced-order quadrature, the time needed to perform these calculations and the 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, we demonstrate substantial performance improvements, enabling dramatically reduced overall cost and latency.

CCRG Authors

O'Shaughnessy, Richard