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Digital Library

of the European Council for Modelling and Simulation

 

Title:

A Toolchain For Profiling Virtual Machines

Authors:

Jiaqi Zhao, Jie Tao, Lizhe Wang, Andreas Wirooks

Published in:

 

(2013).ECMS 2013 Proceedings edited by: W. Rekdalsbakken, R. T. Bye, H. Zhang  European Council for Modeling and Simulation. doi:10.7148/2013

 

ISBN: 978-0-9564944-6-7

 

27th European Conference on Modelling and Simulation,

Aalesund, Norway, May 27th – 30th, 2013

 

Citation format:

Jiaqi Zhao, Jie Tao, Lizhe Wang, Andreas Wirooks (2013). A Toolchain For Profiling Virtual Machines, ECMS 2013 Proceedings edited by: W. Rekdalsbakken, R. T. Bye, H. Zhang, European Council for Modeling and Simulation. doi:10.7148/2013-0497

 

DOI:

http://dx.doi.org/10.7148/2013-0497

Abstract:

Performance tuning is a common topic in the research domain High Performance Computing. Currently, various tools have been developed to help programmers understand the runtime execution behavior of their applications. It is clear that such tools are also required for performance analysis on virtual machines, where applications, together with their execution environment, sit on top of a virtualization layer rather than running directly on the physical machines.

This work developed a toolchain (also called workflow system in the following), specifically for performance analysis on virtual machines. Starting with a profiling tool, the workflow system first collects the runtime performance data on both physical and virtual machines. The performance data are filtered, combined, transformed, and then delivered to a visualization tool, where graphical views are produced to demonstrate the performance difference between native executions and the execution on virtual machines. We tested the toolchain with standard benchmark applications running either sequentially or in parallel with multiple threads.

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