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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. |
Full
text: |