Authors:
Xin Fan
;
Yusuke Wada
and
Shigeru Kusakabe
Affiliation:
Kyushu University, Japan
Keyword(s):
Cloud computing, Private cloud, Community cluster, Hadoop, MPI.
Related
Ontology
Subjects/Areas/Topics:
Cloud Applications Performance and Monitoring
;
Cloud Computing
;
Cloud Deployment Models: Public/Private/Hybrid Cloud
;
Fundamentals
;
Platforms and Applications
Abstract:
The increasing availability of cloud computing technologies enables us to have an option we had not before: using private cloud as well as using public cloud. In this paper, we report our ongoing work on examining effectiveness of private cloud computing in an academic setting. Many researchers have examined the relative computational performance of commercially available public cloud computing offerings using HPC application benchmarks. As one of the driving forces in using cloud technologies is cost effectiveness, some researchers have examined public cloud offerings and their HPC environment, a community cluster, from a view point of cost-performance. Part of the conclusions indicates their community cluster may be favorable for typical community members. Due to the similar grounds of community cluster, we expect private (or community) cloud is promising in academic settings. Academic community members may also have interest in utilization of their resources with a configuration o
f less constraints compared to public cloud offerings while receiving benefit of cloud technologies. In this paper, we discuss the situation we are managing a number of bare-metals and we are deciding whether we configure the computing resource as a cluster of bare-metal nodes or as a cluster of virtual machines by using cloud computing technologies. According to our preliminary evaluation results, while we can easily reinstall and change the software framework on clusters in our private cloud, we must be ready for occurrence of unexpectedly severe performance degradation.
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