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
收藏
页数:12
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