SCHEDULE: NOV 10-16, 2012
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PanDA: Next Generation Workload Management and Analysis System for Big Data
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Mikhail Titov
ROOM:East Entrance
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.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Mikhail Titov - University of Texas at Arlington
Click here to download .ics calendar file
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PanDA: Next Generation Workload Management and Analysis System for Big Data
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Mikhail Titov
ROOM:East Entrance
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.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Mikhail Titov - University of Texas at Arlington
Click here to download .ics calendar file