EPJ Web Conf.
Volume 214, 201923rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|Number of page(s)||6|
|Section||T3 - Distributed computing|
|Published online||17 September 2019|
The next generation PanDA Pilot for and beyond the ATLAS experiment
Brookhaven National Laboratory, Physics Department,
2 Budker Institute of Nuclear Physics, Russia
3 Novosibirsk State University, Russia
4 Argonne National Laboratory, United States
5 National Research Centre Kurchatov Institute, Russia
6 University of Wisconsin-Madison, Department of Physics, United States
7 CERN, European Laboratory for Particle Physics, Switzerland
8 University of Texas at Arlington, Department of Physics, United States
9 Joint Institute for Nuclear Research, Russia
* Corresponding author: email@example.com
Published online: 17 September 2019
The Production and Distributed Analysis system (PanDA) is a pilot-based workload management system that was originally designed for the ATLAS Experiment at the LHC and to use with grid sites. Since the coming LHC data taking runs will require more resources than grid computing alone can provide, the various LHC experiments are engaged in an ambitious program to extend the computing model to include opportunistically used resources such as High Performance Computers (HPCs), clouds and volunteer computers. To this end, PanDA is being extended beyond grids and ATLAS to be used on the new types of resources as well as by other experiments. A new key component is being developed, the next generation PanDA Pilot (Pilot 2). Pilot 2 is a complete rewrite of the original PanDA Pilot which has been used in the ATLAS Experiment for over a decade. The new Pilot architecture follows a component-based approach which improves system flexibility, enables a clear workflow control, evolves the system according to modern functional use-cases to facilitate coming feature requests from new and old PanDA users. This paper describes Pilot 2, its architecture and place in the PanDA hierarchy. Furthermore, its ability to be used either as a command tool or through APIs is explained, as well as how its workflows and components are being streamlined for usage on both grids and opportunistically used resources for and beyond the ATLAS experiment.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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