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作者机构:Ist Nazl Fis Nucl I-40127 Bologna Italy Univ Bologna I-40127 Bologna Italy Fermilab Natl Accelerator Lab Batavia IL USA Univ Rio De Janeiro UERJ Rio De Janeiro Brazil CERN CH-1211 Geneva 23 Switzerland Pisa INFN Pisa Italy Trieste INFN Trieste Italy Univ Nebraska Lincoln NE USA Johns Hopkins Univ Baltimore MD USA Rutherford Appleton Lab Didcot OX11 0QX Oxon England INFN CNAF Bologna Italy Perugia INFN Perugia Italy Brussel Univ Brussels Belgium Chinese Acad Sci Inst High Energy Phys Acad Sinica Beijing Peoples R China Ist Nazl Fis Nucl I-70126 Bari Italy Univ Bari Bari Italy Helsinki Inst Phys Helsinki Finland Univ Minnesota St Paul MN USA Princeton Univ Princeton NJ 08544 USA Northeastern Univ Boston MA 02115 USA Padova INFN Padua Italy Milano Bicocca INFN Milan Italy Paul Scherrer Inst Villigen Switzerland CIEMAT E-28040 Madrid Spain PIC Barcelona Spain Peking Univ Beijing Peoples R China Brunel Univ London England DESY D-2000 Hamburg Germany Univ Florida Gainesville FL USA Rhein Westfal TH Aachen Aachen Germany Inst Phys Nucl Villeurbanne France Cornell Univ Ithaca NY USA Legnaro INFN Legnaro Italy Univ Calif San Diego La Jolla CA 92093 USA Univ Linz A-4040 Linz Austria Univ Bristol Bristol Avon England Ecole Polytech F-75230 Paris France Univ Ghent B-9000 Ghent Belgium
出 版 物:《JOURNAL OF GRID COMPUTING》 (网格计算杂志)
年 卷 期:2010年第8卷第2期
页 面:159-179页
核心收录:
学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:CERN CMS Institutes European Commission [INFSO-RI-222667] STFC [PP/E002803/1, ST/F007434/1] Funding Source: UKRI
主 题:LHC CMS Distributed analysis Grid
摘 要:The CMS experiment expects to manage several Pbytes of data each year during the LHC programme, 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 with thousands potential users. This represents an unprecedented experimental challenge in terms of the scale of distributed computing resources and number of user. An overview of the computing architecture, the software tools and the distributed infrastructure is reported. Summaries of the experience in establishing efficient and scalable operations to get prepared for CMS distributed analysis are presented, followed by the user experience in their current analysis activities.