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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Main Authors:	Woodard Anna Elizabeth, Trisovic Ana, Li Zhuozhao, Babuji Yadu, Chard Ryan, Skluzacek Tyler, Blaiszik Ben, Katz Daniel S., Foster Ian, Chard Kyle
Format:	Article
Language:	English
Published:	EDP Sciences 2020-01-01
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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spelling	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
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Real-time HEP analysis with funcX, a high-performance platform for function as a service

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