Speaker
Jaroslava Schovancova
(Brookhaven National Laboratory (US))
Description
The PanDA Production ANd Distributed Analysis system has been developed by ATLAS to meet the experiment's requirements for a data-driven workload management system for production and distributed analysis processing capable of operating at LHC data processing scale. After 7 years of impressively successful PanDA operation in ATLAS there are also other experiments which can benefit from PanDA in the Big Data challenge, with several at various stages of evaluation and adoption. The new project "Next Generation Workload Management and Analysis System for Big Data" is extending PanDA to meet the needs of other data intensive scientific applications in HEP, astro-particle and astrophysics communities, bio-informatics and other fields as a general solution to large scale workload management. PanDA can utilize dedicated or opportunistic computing resources such as grids, clouds, and High Performance Computing facilities, and is being extended to leverage next generation intelligent networks in automated workflow management and brokerage. This presentation will provide an overview, the current status and future plans of the Big PanDA project.
Authors
Alexandre Vaniachine
(ANL)
Alexei Klimentov
(Brookhaven National Laboratory (US))
Artem Petrosyan
(Joint Inst. for Nuclear Research (RU))
Danila Oleynik
(Joint Inst. for Nuclear Research (RU))
Dantong Yu
(BROOKHAVEN NATIONAL LABORATORY)
Jaroslava Schovancova
(Brookhaven National Laboratory (US))
Kaushik De
(University of Texas at Arlington (US))
Paul Nilsson
(University of Texas at Arlington (US))
Sergey Panitkin
(Brookhaven National Laboratory (US))
Tadashi Maeno
(Brookhaven National Laboratory (US))
Torre Wenaus
(Brookhaven National Laboratory (US))
