Abstract
This contribution reports on the feasibility of executing data intensive workflows on Cloud infrastructures. In order to assess this, the metric ETC = Events/Time/Cost is formed, which quantifies the different workflow and infrastructure configurations that are tested against each other. In these tests ATLAS reconstruction Jobs are run, examining the effects of overcommitting (more parallel processes running than CPU cores available), scheduling (staggered execution) and scaling (number of cores). The desirability of commissioning storage in the Cloud is evaluated, in conjunction with a simple analytical model of the system, and correlated with questions about the network bandwidth, caches and what kind of storage to utilise. In the end a cost/benefit evaluation of different infrastructure configurations and workflows is undertaken, with the goal to find the maximum of the ETC value.
Highlights
Experience: Costly to set up storage
Work sponsored by the Wolfgang Gentner Programme of the Federal Ministry of Education and Research
Event Generation (single-core, CPU intensive), MonteCarlo simulation (CPU intensive), Reconstruction (data intensive), Analysis (data intensive)
Summary
Gerhard Rzehorz Supervised by G. Kawamura, O. Keeble, A. Quadt II. Institute of Physics, Georg-August-University Göttingen & CERN • CERN: international research organization, physics experiments • LHC, accelerator ~ 27 km circumference, 50-175 m underground • >1011 protons per bunch, 40 MHz, 2017: 5 million billion collisions • Events independent - parallelisable
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