Workload characterization of the shared/buy-in computing cluster at Boston University

Date
2016
DOI
Authors
Klausner, Yonatan
Liao, Christopher
Simhon, Eran
Bestavros, Azer
Starobinski, D.
Version
Accepted manuscript
OA Version
Citation
Yonatan Klausner, Christopher Liao, Eran Simhon, D Starobinski, Azer Bestavros. 2016. "Workload Characterization of the Shared/Buy-in Computing Cluster at Boston University." IEEE MIT Undergraduate Research Technology Conference 2016
Abstract
Computing clusters provide a complete environment for computational research, including bio-informatics, machine learning, and image processing. The Shared Computing Cluster (SCC) at Boston University is based on a shared/buy-in architecture that combines shared computers, which are free to be used by all users, and buy-in computers, which are computers purchased by users for semi-exclusive use. Although there exists significant work on characterizing the performance of computing clusters, little is known about shared/buy-in architectures. Using data traces, we statistically analyze the performance of the SCC. Our results show that the average waiting time of a buy-in job is 16.1% shorter than that of a shared job. Furthermore, we identify parameters that have a major impact on the performance experienced by shared and buy-in jobs. These parameters include the type of parallel environment and the run time limit (i.e., the maximum time during which a job can use a resource). Finally, we show that the semi-exclusive paradigm, which allows any SCC user to use idle buy-in resources for a limited time, increases the utilization of buy-in resources by 17.4%, thus significantly improving the performance of the system as a whole.
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