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.