DocumentCode :
1920017
Title :
Poster: PanDA: Next Generation Workload Management and Analysis System for Big Data
Author :
De, K. ; Klimentov, A. ; Panitkin, Sergey ; Titov, Maxim ; Vaniachine, A. ; Wenaus, T. ; Yu, Daren ; Zaruba, Gergely
fYear :
2012
fDate :
10-16 Nov. 2012
Firstpage :
1523
Lastpage :
1523
Abstract :
In real world any big science project implies to use a sophisticated Workload Management System (WMS) that deals with a huge amount of highly distributed data, which is often accessed by large collaborations. The Production and Distributed Analysis System (PanDA) is a high-performance WMS that is aimed to meet production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider data processing scale. PanDA provides execution environments for a wide range of experimental applications, automates centralized data production and processing, enables analysis activity of physics groups, supports custom workflow of individual physicists, provides a unified view of distributed worldwide resources, presents status and history of workflow through an integrated monitoring system, archives and curates all workflow. PanDA is now being generalized and packaged, as a WMS already proven at extreme scales, for the wider use of the Big Data community.
Keywords :
big data; grid; wms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
Conference_Location :
Salt Lake City, UT
Print_ISBN :
978-1-4673-6218-4
Type :
conf
DOI :
10.1109/SC.Companion.2012.302
Filename :
6496085
Link To Document :
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