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The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in addition to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase, and plans for the future.
Maeno et al. (Fri,) studied this question.
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