Accelerating parameter inference with graphics processing units

被引:48
|
作者
Wysocki, D. [1 ]
O'Shaughnessy, R. [1 ]
Lange, Jacob [1 ]
Fang, Yao-Lung L. [2 ,3 ]
机构
[1] Rochester Inst Technol, Ctr Computat Relat & Gravitat, Rochester, NY 14623 USA
[2] Brookhaven Natl Lab, Computat Sci Initiat, Upton, NY 11973 USA
[3] Brookhaven Natl Lab, Natl Synchrotron Light Source 2, Upton, NY 11973 USA
关键词
D O I
10.1103/PhysRevD.99.084026
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
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.
引用
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页数:12
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