An ARM cluster for running CMSSW jobs

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.In this paper we present the latest CMS open data release published on the CERN Oopen Data portal. Samples of collision and simulated datasets were released together with detailed information about the data provenance. The associated data production chains cover the necessary computing environments, the configuration files and the computational procedures used in each data production step. We describe data curation techniques used to obtain and publish the data provenance information and we study the possibility of reproducing parts of the released data using the publicly available information. The present work demonstrates the usefulness of releasing selected samples of raw and primary data in order to fully ensure the completeness of information about the data production chain for the attention of general data scientists and other non-specialists interested in using particle physics data for education or research purposes.Peer reviewe