Accelerating parameter inference with graphics processing units
Accelerating parameter inference with graphics processing units
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DOI：
10.1103/physrevd.99.084026
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发表时间：
2019-02
影响因子：
5
通讯作者：
D. Wysocki;R. O’Shaughnessy;Y-L. L. Fang-Y-L.-L.-Fang-90268547;Jacob Lange Center for Computational Relativity;Gravitation;R. I. O. Technology;Computational Science Initiative;Brookhaven National Laboratory
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文献类型：
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作者：
D. Wysocki;R. O’Shaughnessy;Y-L. L. Fang-Y-L.-L.-Fang-90268547;Jacob Lange Center for Computational Relativity;Gravitation;R. I. O. Technology;Computational Science Initiative;Brookhaven National Laboratory
引力波贝叶斯参数推断涉及引力波数据与一般候选预测的重复比较。即使使用RIFT或降阶求积等算法效率高的方法，与实现低延迟多信使天文学目标所需的几分钟到几小时相比，执行这些计算所需的时间和总体计算成本也可能很大。通过将RIFT算法的一些元素转换为在图形处理单元上操作，我们展示了实质性的性能改进，从而大大降低了整体成本和延迟。
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.