The Large Hadron Collider (LHC) is preparing for data taking at the end of 2009. The Worldwide LHC Computing Grid (WLCG) provides data storage and computational resources for the high energy physics community. Operating the heterogeneous WLCG infrastructure, which integrates 140 computing centers in 33 countries all over the world, is a complicated task. Reliable monitoring is one of the crucial components of the WLCG for providing the functionality and performance that is required by the LHC experiments. The Experiment Dashboard system provides monitoring of the WLCG infrastructure from the perspective of the LHC experiments and covers the complete range of their computing activities. This work describes the architecture of the Experiment Dashboard system and its main monitoring applications and summarizes current experiences by the LHC experiments, in particular during service challenges performed on the WLCG over the last years.
CMS expects to manage several Pbytes of data each year, distributing them over many computing sites around the world and enabling data access at those centers for analysis. CMS has identified the distributed sites as the primary location for physics analysis to support a wide community of users, with potentially as many as 3000 users. This represents an unprecedented scale of distributed computing resources and number of users. An overview of the computing architecture, the software tools and the distributed infrastructure deployed is reported. Summaries of the experience in establishing efficient and scalable operations to prepare for CMS distributed analysis are presented, followed by the user experience in their current analysis activities.JournalofGridComputing manuscript No. (will be inserted by the editor) Abstract CMS expects to manage several Pbytes of data each year, distributing them over many computing sites around the world and enabling data access at those centers for analysis. CMS has identified the distributed sites as the primary location for physics analysis to support a wide community of users, with potentially as many as 3000 users. This represents an unprecedented scale of distributed computing resources and number of users. An overview of the computing architecture, the software tools and the distributed infrastructure deployed is reported. Summaries of the experience in establishing efficient and scalable operations to prepare for CMS distributed analysis are presented, followed by the user experience in their current analysis activities.
Distributed Analysis in CMS
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