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Title: Accelerating parameter inference with graphics processing units

Abstract

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.

Authors:
 [1];  [1];  [1];  [2]
  1. Rochester Inst. of Technology, Rochester, NY (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21); USDOE
OSTI Identifier:
1524547
Alternate Identifier(s):
OSTI ID: 1507226
Report Number(s):
BNL-211723-2019-JAAM
Journal ID: ISSN 2470-0010; PRVDAQ
Grant/Contract Number:  
SC0012704; 17-029; 19-002
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review D
Additional Journal Information:
Journal Volume: 99; Journal Issue: 8; Journal ID: ISSN 2470-0010
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Wysocki, D., O’Shaughnessy, R., Lange, Jacob, and Fang, Yao-Lung L. Accelerating parameter inference with graphics processing units. United States: N. p., 2019. Web. doi:10.1103/PhysRevD.99.084026.
Wysocki, D., O’Shaughnessy, R., Lange, Jacob, & Fang, Yao-Lung L. Accelerating parameter inference with graphics processing units. United States. doi:10.1103/PhysRevD.99.084026.
Wysocki, D., O’Shaughnessy, R., Lange, Jacob, and Fang, Yao-Lung L. Tue . "Accelerating parameter inference with graphics processing units". United States. doi:10.1103/PhysRevD.99.084026.
@article{osti_1524547,
title = {Accelerating parameter inference with graphics processing units},
author = {Wysocki, D. and O’Shaughnessy, R. and Lange, Jacob and Fang, Yao-Lung L.},
abstractNote = {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.},
doi = {10.1103/PhysRevD.99.084026},
journal = {Physical Review D},
number = 8,
volume = 99,
place = {United States},
year = {2019},
month = {4}
}

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This content will become publicly available on April 16, 2020
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