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Performance comparison of two virtual machine scenarios using an HPC application: a case study using molecular dynamics simulations
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Proceedings of the 3rd ACM Workshop on System-level Virtualization for High Performance Computing table of contents
Nuremburg, Germany
Pages 33-40  
Year of Publication: 2009
ISBN:978-1-60558-465-2
Authors
Anand Tikotekar  Oak Ridge National Laboratory, Oak Ridge, TN
Hong Ong  Oak Ridge National Laboratory, Oak Ridge, TN
Sadaf Alam  Oak Ridge National Laboratory, Oak Ridge, TN
Geoffroy Vallée  Oak Ridge National Laboratory, Oak Ridge, TN
Thomas Naughton  Oak Ridge National Laboratory, Oak Ridge, TN
Christian Engelmann  Oak Ridge National Laboratory, Oak Ridge, TN
Stephen L. Scott  Oak Ridge National Laboratory, Oak Ridge, TN
Publisher
ACM  New York, NY, USA
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ABSTRACT

Obtaining high flexibility to performance-loss ratio is a key challenge of today's HPC virtual environment landscape. And while extensive research has been targeted at extracting more performance from virtual machines, the idea that whether novel virtual machine usage scenarios could lead to high flexibility Vs performance trade-off has received less attention.

We, in this paper, take a step forward by studying and comparing the performance implications of running the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) application on two virtual machine configurations. First configuration consists of two virtual machines per node with 1 application process per virtual machine. The second configuration consists of 1 virtual machine per node with 2 processes per virtual machine. Xen has been used as an hypervisor and standard Linux as a guest virtual machine. Our results show that the difference in overall performance impact on LAMMPS between the two virtual machine configurations described above is around 3%. We also study the difference in performance impact in terms of each configuration's individual metrics such as CPU, I/O, Memory, and interrupt/context switches.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Anand Tikotekar: colleagues
Hong Ong: colleagues
Sadaf Alam: colleagues
Geoffroy Vallée: colleagues
Thomas Naughton: colleagues
Christian Engelmann: colleagues
Stephen L. Scott: colleagues