A Serverless Engine for High Energy Physics Distributed Analysis

  • Jacek Kusnierz
  • , Vincenzo E. Padulano
  • , MacIej Malawski
  • , Kamil Burkiewicz
  • , Enric Tejedor Saavedra
  • , Pedro Alonso-Jorda
  • , Michael Pitt
  • , Valentina Avati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

The Large Hadron Collider (LHC) at CERN has generated in the last decade an unprecedented volume of data for the High-Energy Physics (HEP) field. Scientific collaborations interested in analysing such data very often require computing power beyond a single machine. This issue has been tackled traditionally by running analyses in distributed environments using stateful, managed batch computing systems. While this approach has been effective so far, current estimates for future computing needs of the field present large scaling challenges. Such a managed approach may not be the only viable way to tackle them and an interesting alternative could be provided by serverless architectures, to enable an even larger scaling potential. This work describes a novel approach to running real HEP scientific applications through a distributed serverless computing engine. The engine is built upon ROOT, a well-established HEP data analysis software, and distributes its computations to a large pool of concurrent executions on Amazon Web Services Lambda Serverless Platform. Thanks to the developed tool, physicists are able to access datasets stored at CERN (also those that are under restricted access policies) and process it on remote infrastructures outside of their typical environment. The analysis of the serverless functions is monitored at runtime to gather performance metrics, both for data-and computation-intensive workloads.

Original languageEnglish
Title of host publicationProceedings - 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022
EditorsMaria Fazio, Dhabaleswar K. Panda, Radu Prodan, Valeria Cardellini, Burak Kantarci, Omer Rana, Massimo Villari
PublisherInstitute of Electrical and Electronics Engineers
Pages575-584
Number of pages10
ISBN (Electronic)9781665499569
DOIs
StatePublished - 1 Jan 2022
Externally publishedYes
Event22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022 - Taormina, Italy
Duration: 16 May 202219 May 2022

Publication series

NameProceedings - 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022

Conference

Conference22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022
Country/TerritoryItaly
CityTaormina
Period16/05/2219/05/22

Keywords

  • AWS
  • CERN
  • Distributed Computing
  • HEP
  • Lambda
  • MapReduce
  • ROOT
  • Serverless

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Information Systems and Management
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'A Serverless Engine for High Energy Physics Distributed Analysis'. Together they form a unique fingerprint.

Cite this