Explore multi core virtualization on the ATLAS@home project

Wu, Wenjing; Cameron, D.; Filipčić, A.

doi:10.22323/1.293.0014

Cited by 1 publication

(1 citation statement)

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“…In addition continuous distributed analysis from several hundred ATLAS users is executed. The resources used are the Tier-0 at CERN and Tier-1/2/3 Grid sites worldwide and opportunistic resources at HPC (High Performance Computer) sites, Cloud computing providers and volunteer computing resources submitted via ATLAS@Home/Boinc [6]. All the infrastructure is monitored by different shift teams for production and distributed analysis.…”

Section: Introductionmentioning

confidence: 99%

Overview of the ATLAS distributed computing system

Elmsheuser

Girolamo

2019

EPJ Web Conf.

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The CERN ATLAS experiment successfully uses a worldwide computing infrastructure to support the physics program during LHC Run 2. The Grid workflow system PanDA routinely manages 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 370 PB of data is distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing LHC luminosity in future runs new developments are underway to even more efficiently use opportunistic resources such as HPCs and utilize new technologies. This paper will review and explain the outline and the performance of the ATLAS distributed computing system and give an outlook to new workflow and data management ideas for the beginning of the LHC Run 3. It will be discussed that the ATLAS workflow and data management systems are robust, performant and can easily cope with the higher Run 2 LHC performance. There are presently no scaling issues and each subsystem is able to sustain the large loads. * Panda Rucio Grid CPU HPCs CPU Clouds CPU ProdSys User AGIS Workflows Jobs Configuration Data Monitoring, Analytics EPJ Web of Conferences 214, 03010 (2019) https://doi.org/10.1051/epjconf/201921403010 CHEP 2018been added. In addition the activities within the WLCG DOMA (data organisation, management, access) project [14] to explore possibilities to overcome disk shortage in HL-LHC are ramping up and ATLAS is actively participating. A very successful R&D project with Google has been started which allows the integration of Rucio and distributed analysis using Harvester [15].The site infrastructure is evolving as well and the support for containers using Singularity [16] and Docker [17] is under development at the sites and within PanDA jobs for production and user analysis usage.

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Section: Introductionmentioning

confidence: 99%