Please visit Jefferson Lab Event Policies and Guidance before planning your next event:
May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

The ATLAS experiment software on ARM

May 8, 2023, 11:30 AM
Chesapeake Meeting Room (Norfolk Waterside Marriott)

Chesapeake Meeting Room

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Oral Track 5 - Sustainable and Collaborative Software Engineering Track 5 - Sustainable and Collaborative Software Engineering


Elmsheuser, Johannes (Brookhaven National Laboratory)


With an increased dataset obtained during the Run-3 of the LHC at CERN and the even larger expected increase of the dataset by more than one order of magnitude for the HL-LHC, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM architecture is becoming a competitive and energy efficient alternative. Some surveys indicate its increased presence in HPCs and commercial clouds, and some WLCG sites have expressed their interest. Chip makers are also developing their next generation solutions on ARM architectures, sometimes combining ARM and GPU processors in the same chip. Therefore it is important that the Athena software embraces the change and is able to successfully exploit this architecture.

We report on the successful port of the ATLAS experiment offline and online software framework Athena to ARM and the successful physics validation of simulation workflows. For this we have set up an ATLAS Grid site using ARM compatible middleware and containers on Amazon Web Services (AWS) ARM resources. The ARM version of Athena is fully integrated in the regular software build system and distributed like default software releases. In addition, the workflows have been integrated into the HepScore benchmark suite which is the planned WLCG wide replacement of the HepSpec06 benchmark used for Grid site pledges. In the overall porting process we have used resources on AWS, Google Cloud Platform (GCP) and CERN. A performance comparison of different architectures and resources will be discussed.

Consider for long presentation No

Primary authors

Elmsheuser, Johannes (Brookhaven National Laboratory) Megino, Fernando Barreiro (University of Texas at Arlington) De Salvo, Alessandro (Sapienza Universita e INFN, Roma I) De Silva, Asoka (TRIUMF) Konstantinov, Dmitri (CERN) Lassnig, Mario (CERN) Hauser, Reiner (Michigan State University) Krasznahorkay, Attila (CERN) Sailer, Andre (CERN) Snyder, Scott (Brookhaven National Laboratory)

Presentation materials

Peer reviewing