| Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
|---|---|---|
| Article Number | 05038 | |
| Number of page(s) | 7 | |
| Section | 5 - Software Development | |
| DOI | https://doi.org/10.1051/epjconf/202024505038 | |
| Published online | 16 November 2020 | |
https://doi.org/10.1051/epjconf/202024505038
An ARM cluster for running CMSSW jobs
1
Department of Computer Science, University of Helsinki, PB 68 (Gustaf Hällströmin katu 2b), FI-00014 University of Helsinki, Finland
2
Helsinki Institute of Physics, PB 64 (Gustaf Hällströmin katu 2), FI-00014 University of Helsinki, Finland
* e-mail: lirim.osmani@helsinki.fi
** e-mail: tomas.linden@helsinki.fi
Published online: 16 November 2020
The ARM platform extends from the mobile phone area to development board computers and servers. It could be that in the future the importance of the ARM platform will increase for High Performance Computing/High Throughput Computing (HPC/HTC) if new more powerful (server) boards are released. For this reason Compact Muon Solenoid Software (CMSSW) has previously been ported to ARM in earlier work.
The CMSSW is deployed using the CERN Virtual Machine File System (CVMFS) and the jobs are run inside Singularity containers. Some ARM AArch64 CMSSW releases are available in CVMFS for testing and development. In this work CVMFS and Singularity have been compiled and installed on an ARM cluster and the AArch64 CMSSW releases in CVMFS have been used. We report on our experiences with this ARM cluster for CMSSW jobs.
Commodity hardware designed around the 64-bit architecture has been the basis of current virtualization trends with the advantage to emulate diverse environments for a wide range of computational scenarios. However, in parallel the mobile revolution have given a rise to ARM SoCs with primary focus on power efficiency. While still in the experimental phase, the power efficiency and 64-bit heterogeneous computing already point to an alternative option for traditional x86_64 CPUs servers for datacenters.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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