Abstract
The Tokyo regional analysis center at the International Center for Elementary Particle Physics, the University of Tokyo, is one of the Tier 2 sites for the ATLAS experiment in the Worldwide LHC Computing Grid. The current system has 10,752 CPU cores and 16 PB disk storage. CERN plans the HighLuminosity LHC starting from 2026, which increases the peak luminosity by 5 times compared to the present value at the LHC. A shortage of computing resources for the high-luminosity LHC is expected with the current system. Therefore new ideas to expand the system are necessary. To expand the ATLAS production system at the Tokyo regional analysis center, R&D using external resources has been launched. One kind of external resources is a commercial cloud resource, such as Google Cloud Platform. Another resource is the HighPerformance Computer (HPC) at the University of Tokyo. In this contribution, the current status of the R&D, the systems for these resources, and comparisons of the cost are reported.
Highlights
The Worldwide LHC Computing Grid (WLCG) [1] is a global collaboration to provide a set of computing resources to experiments at the Large Hadron Collider (LHC) [2]
ARC CE [8] is used as the Computing Element (CE), which receives jobs as the grid front end and jobs are managed by HTCondor [9]
A hybrid system consisting of Google Cloud Platform (GCP) and the on-premises systems using HTCondor as a job manager was established
Summary
The Worldwide LHC Computing Grid (WLCG) [1] is a global collaboration to provide a set of computing resources to experiments at the Large Hadron Collider (LHC) [2]. Other computing centers providing resources to WLCG are Tier 2. Some computing centers which provide resources to local users are referred to as Tier 3. WLCG has already provided a large amount of resources successfully. CERN plans the High-Luminosity LHC (HL-LHC) which will increase the peak luminosity to 5 times higher compared to the current LHC and the expected necessary computing resources will rise. The solid line is the expected amount of available CPU resources and each point shows estimations of the amount of necessary resources in different scenarios. Many improvements of software have been implemented but there is still a gap between the necessary and available CPU resources. 80 2018 estimates: MC fast calo sim + standard reco MC fast calo sim + fast reco
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