Integration of PanDA workload management system with Titan supercomputer at OLCF

Journal Article · Wed Dec 23 00:00:00 EST 2015 · Journal of Physics. Conference Series

DOI:https://doi.org/10.1088/1742-6596/664/9/092020· OSTI ID:1567387

De, K. ^[1]; Klimentov, A. ^[2]; Oleynik, D. ^[1]; Panitkin, S. ^[2]; Petrosyan, A. ^[1]; Schovancova, J. ^[2]; Vaniachine, A. ^[3]; Wenaus, T. ^[2]

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1. Univ. of Texas, Arlington, TX (United States). Dept. of Physics
2. Brookhaven National Lab. (BNL), Upton, NY (United States)
3. Argonne National Lab. (ANL), Argonne, IL (United States)

The PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. While PanDA currently distributes jobs to more than 100,000 cores at well over 100 Grid sites, the future LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). The current approach utilizes a modified PanDA pilot framework for job submission to Titan’s batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on Titan’s multi-core worker nodes. It also gives PanDA new capability to collect, in real time, information about unused worker nodes on Titan, which allows precise definition of the size and duration of jobs submitted to Titan according to available free resources. This capability significantly reduces PanDA job wait time while improving Titan’s utilization efficiency. This implementation was tested with a variety of Monte-Carlo workloads on Titan and is being tested on several other supercomputing platforms.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1567387
• Journal Information: Journal of Physics. Conference Series, Vol. 664, Issue 9; ISSN 1742-6588
• Publisher: IOP Publishing
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
Physics