SC12 Home > SC12 Schedule > SC12 Presentation - PanDA: Next Generation Workload Management and Analysis System for Big Data

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

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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

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar