Author(s)
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Benjamin, Douglas (Duke University, Department of Physics) ; Caballero, Jose (Brookhaven National Laboratory (BNL)) ; Ernst, Michael (Brookhaven National Laboratory (BNL)) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Hover, John (Brookhaven National Laboratory (BNL)) ; Lesny, David (University of Illinois at Urbana-Champaign) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Tsulaia, Vakhtang (Lawrence Berkeley National Laboratory and University of California, Berkeley) ; van Gemmeren, Peter (Argonne National Laboratory) ; Vaniachine, Alexandre (Tomsk State University) ; Wang, Fuquan (Department of Physics, University of Wisconsin) ; Wenaus, Torre (Brookhaven National Laboratory (BNL)) |
Abstract
| Continued growth in public cloud and HPC resources is on track to exceed the dedicated resources available for ATLAS on the WLCG. Examples of such platforms are Amazon AWS EC2 Spot Instances, Edison Cray XC30 supercomputer, backfill at Tier 2 and Tier 3 sites, opportunistic resources at the Open Science Grid (OSG), and ATLAS High Level Trigger farm between the data taking periods. Because of specific aspects of opportunistic resources such as preemptive job scheduling and data I/O, their efficient usage requires workflow innovations provided by the ATLAS Event Service. Thanks to the finer granularity of the Event Service data processing workflow, the opportunistic resources are used more efficiently. We report on our progress in scaling opportunistic resource usage to double-digit levels in ATLAS production. |