The Next Generation ARC Middleware and ATLAS Computing Model

Filipčić, A.; Cameron, D.; Smirnova, O.; Константинов, Александр; Karpenko, Dmytro

doi:10.1088/1742-6596/396/3/032039

Cited by 4 publications

(4 citation statements)

References 7 publications

(6 reference statements)

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“…The ATLAS application [20] runs Monte-Carlo simulation of events in the ATLAS detector. Jobs are submitted to the BOINC server using the ARC CE [21] grid middleware. In 2017 a native Linux version of the ATLAS application was developed which removes the need for virtualisation on Linux platforms, instead using Singularity [22] containers.…”

Section: Atlasmentioning

confidence: 99%

All grown-up; 18 years of LHC@home

Cameron,

Field,

Van der Veken

et al. 2024

EPJ Web of Conf.

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LHC@home was launched as a BOINC project in 2004 as an outreach project for CERN’s 50 years anniversary. Initially focused on the accelerator physics simulation code SixTrack, the project was expanded in 2011 to run other physics simulation codes on Linux thanks to virtualisation. Later on the experiment and theory applications running on the LHC@home platform have evolved to use containers and take advantage of the CVMFS file system as well as content delivery networks. Furthermore, a substantial part of the contributed computing capacity nowadays is provided as opportunistic back-fill from data centers with spare capacity, in addition to enthusiastic volunteers. The paper will address the challenges with this distributed computing model, new applications to exploit GPUs and the future outlook for volunteer computing.

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Section: Atlasmentioning

confidence: 99%

All grown-up; 18 years of LHC@home

Cameron,

Field,

Van der Veken

et al. 2024

EPJ Web of Conf.

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show abstract

“…To comply with the baseline for compute access, it was agreed that a site must provide either (a) the standard OpenStack APIs (including Keystone, Nova and Glance) [22] for creating VMs, (b) a Grid computing element with batch system backend for Grid jobs (for example the ARC CE [23]) or (c) a Vacuum Cloud [24] for running VM or container definitions provided by the user communities.…”

Section: Interface Requirementsmentioning

confidence: 99%

IRIS – providing a nationally accessible infrastructure for UK science

et al. 2020

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In many countries around the world, the development of national infrastructures for science either has been implemented or are under serious consideration by governments and funding bodies. Current examples include ARDC in Australia, CANARIE in Canada and MTA Cloud in Hungary. These infrastructures provide access to compute and storage to a wide swathe of user communities and represent a collaboration between users, providers and, in some cases, industry to maximise the impact of the investments made. The UK has embarked on a project called IRIS to develop a sustainable e-infrastructure based on the needs of a diverse set of communities. Building on the success of the UK component of the WLCG and the innovations made, a number of research institutes and universities are working with several research groups to co-design an infrastructure, including support services, which take this to a level applicable to a wider use base. We present the preparatory work leading to the definition of this infrastructure, showing the wide variety of use cases which require to be supported. This leads us to a definition of the hardware and interface requirements needed to meet this diverse set of criteria, and the support posts identified in order to make best use of this facility and sustain it into the future.

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“…The ATLAS application [18] runs Monte-Carlo simulation of events in the ATLAS detector. Jobs are submitted to the BOINC server using the ARC CE [19] grid middleware. Recently a native Linux version of the ATLAS application was developed which removes the need for virtualisation on Linux platforms, instead using Singularity [20] containers.…”

Section: Atlasmentioning

confidence: 99%

Extending CERN computing to volunteers - LHC@home consolidation and outlook

et al. 2019

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LHC@home has provided computing capacity for simulations under BOINC since 2005. Following the introduction of virtualisation with BOINC to run HEP Linux software in a virtual machine on volunteer desktops, initially started on test BOINC projects, like Test4Theory and ATLAS@home, all CERN applications distributed to volunteers have been consolidated under a single LHC@home BOINC project. As part of an effort to unite CERN's batch, cloud, grid and volunteer computing efforts, the BOINC service has been integrated with the other compute services at CERN, notably HTCondor, in terms job submission and accounting. The paper will also address contributions to improve the BOINC software and community effort to evolve BOINC for a sustainable volunteer computing environment. Furthermore, we discuss future challenges to reduce the effort required by volunteers to run virtual machines for experiment simulations and improvements to BOINC to widen the appeal of volunteer computing. *

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The Next Generation ARC Middleware and ATLAS Computing Model

Cited by 4 publications

References 7 publications

All grown-up; 18 years of LHC@home

All grown-up; 18 years of LHC@home

IRIS – providing a nationally accessible infrastructure for UK science

Extending CERN computing to volunteers - LHC@home consolidation and outlook

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