Real-time HEP analysis with funcX, a high-performance platform for function as a service
We explore how the function as a service paradigm can be used to address the computing challenges in experimental high-energy physics at CERN. As a case study, we use funcX—a high-performance function as a service platform that enables intuitive, flexible, efficient, and scalable remote function exe...
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EDP Sciences
2020-01-01
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Series: | EPJ Web of Conferences |
Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_07046.pdf |
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doaj-ed56939d536a4603a6eb93a3801c4aac2021-08-02T16:20:46ZengEDP SciencesEPJ Web of Conferences2100-014X2020-01-012450704610.1051/epjconf/202024507046epjconf_chep2020_07046Real-time HEP analysis with funcX, a high-performance platform for function as a serviceWoodard Anna Elizabeth0Trisovic Ana1Li Zhuozhao2Babuji Yadu3Chard Ryan4Skluzacek Tyler5Blaiszik BenKatz Daniel S.6Foster IanChard Kyle7The University of ChicagoThe University of ChicagoThe University of ChicagoThe University of ChicagoArgonne National LaboratoryThe University of ChicagoUniversity of Illinois at Urbana-ChampaignThe University of ChicagoWe explore how the function as a service paradigm can be used to address the computing challenges in experimental high-energy physics at CERN. As a case study, we use funcX—a high-performance function as a service platform that enables intuitive, flexible, efficient, and scalable remote function execution on existing infrastructure—to parallelize an analysis operating on columnar data to aggregate histograms of analysis products of interest in real-time. We demonstrate efficient execution of such analyses on heterogeneous resources.https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_07046.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Woodard Anna Elizabeth Trisovic Ana Li Zhuozhao Babuji Yadu Chard Ryan Skluzacek Tyler Blaiszik Ben Katz Daniel S. Foster Ian Chard Kyle |
spellingShingle |
Woodard Anna Elizabeth Trisovic Ana Li Zhuozhao Babuji Yadu Chard Ryan Skluzacek Tyler Blaiszik Ben Katz Daniel S. Foster Ian Chard Kyle Real-time HEP analysis with funcX, a high-performance platform for function as a service EPJ Web of Conferences |
author_facet |
Woodard Anna Elizabeth Trisovic Ana Li Zhuozhao Babuji Yadu Chard Ryan Skluzacek Tyler Blaiszik Ben Katz Daniel S. Foster Ian Chard Kyle |
author_sort |
Woodard Anna Elizabeth |
title |
Real-time HEP analysis with funcX, a high-performance platform for function as a service |
title_short |
Real-time HEP analysis with funcX, a high-performance platform for function as a service |
title_full |
Real-time HEP analysis with funcX, a high-performance platform for function as a service |
title_fullStr |
Real-time HEP analysis with funcX, a high-performance platform for function as a service |
title_full_unstemmed |
Real-time HEP analysis with funcX, a high-performance platform for function as a service |
title_sort |
real-time hep analysis with funcx, a high-performance platform for function as a service |
publisher |
EDP Sciences |
series |
EPJ Web of Conferences |
issn |
2100-014X |
publishDate |
2020-01-01 |
description |
We explore how the function as a service paradigm can be used to address the computing challenges in experimental high-energy physics at CERN. As a case study, we use funcX—a high-performance function as a service platform that enables intuitive, flexible, efficient, and scalable remote function execution on existing infrastructure—to parallelize an analysis operating on columnar data to aggregate histograms of analysis products of interest in real-time. We demonstrate efficient execution of such analyses on heterogeneous resources. |
url |
https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_07046.pdf |
work_keys_str_mv |
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1721229749326446592 |