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Evaluation of Performance Degradation in HPC Applications with VM Consolidation

Authors: Yuya Hashimoto; Kento Aida;

Evaluation of Performance Degradation in HPC Applications with VM Consolidation

Abstract

This paper investigates the performance degradation in application programs running on virtual machines (VMs) in a physical computing server with a focus on HPC applications. We select three benchmarks as the expected workload in a data center: HPC applications, database applications, and web server applications. Then, we put VMs executing two application programs together in a physical computing server and evaluate the performance degradation in each application program. We also investigate the resource consumption in each application program and the reason for the performance degradation. The experimental results indicate that the interference among VMs executing two HPC application programs with high memory usage and high network I/O in the physical computing server significantly degrades the application performance.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Top 10%
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