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:
-
- Rochester Inst. of Technology, Rochester, NY (United States)
- 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. https://doi.org/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. https://doi.org/10.1103/PhysRevD.99.084026. https://www.osti.gov/servlets/purl/1524547.
@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 = {Tue Apr 16 00:00:00 EDT 2019},
month = {Tue Apr 16 00:00:00 EDT 2019}
}
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Works referencing / citing this record:
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