Abstract
Modern experiments collect peta-scale volumes of data and utilize vast, geographically distributed computing infrastructure that serves thousands of scientists around the world. Requirements for rapid, near real-time data processing, fast analysis cycles and need to run massive detector simulations to support data analysis pose special premium on efficient use of available computational resources. A sophisticated Workload Management System (WMS) is needed to coordinate the distribution and processing of data and jobs in such environment. The ATLAS experiment at CERN uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. While PanDAcurrently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, it runs around 2 million jobs per day on hundreds of Grid sites and serving thousands of ATLAS users. In 2017 about 1.5 exabytes of data were processed with PanDA.In 2012 BigPanDA project project was started with aim to introduce new types of computing resources into ATLAS computing infrastructure, but also to offering PanDA features to different data-intensive applications for projects and experiments outside of ATLAS and High-Energy and Nuclear Physics. In this article we will present accomplishments and discuss possible directions for future work.
Highlights
Production and Distributed Analysis Workload Management System (PanDA WMS) [1] is the system initially developed for ATLAS experiment [2] and was designed as high-level intellectual layer on WLCG [3] grid-infrastructure
Since 2015 the BigPanDA project evolved into BigPanDA++ as a collaboration between Brookhaven National Laboratory (BNL), Oak Ridge National Laboratory (ORNL), University of Texas Arlington (UTA) and Rutgers University
In 2017, a pilot project was started between BigPanDA and the Blue Brain Project (BBP) [14] of the Ecole Polytechnique Federale de Lausanne (EPFL) located in Lausanne, Switzerland
Summary
Production and Distributed Analysis Workload Management System (PanDA WMS) [1] is the system initially developed for ATLAS experiment [2] and was designed as high-level intellectual layer on WLCG [3] grid-infrastructure. PanDA WMS allows the efficient use of WLCG infrastructure and provided multiple benefits for running ATLAS payloads (Figure 1). Another goal of the project was to offer PanDA features to projects and experiments beyond ATLAS and High-Energy Physics (HEP). Since 2015 the BigPanDA project evolved into BigPanDA++ as a collaboration between Brookhaven National Laboratory (BNL), Oak Ridge National Laboratory (ORNL), University of Texas Arlington (UTA) and Rutgers University
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