Understanding I/O performance using I/O skeletal applications

Jeremy Logan, Scott Klasky, Hasan Abbasi, Qing Liu, George Ostrouchov, Manish Parashar, Norbert Podhorszki, Yuan Tian, Matthew Wolf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


We address the difficulty involved in obtaining meaningful measurements of I/O performance in HPC applications, as well as the further challenge of understanding the causes of I/O bottlenecks in these applications. The need for I/O optimization is critical given the difficulty in scaling I/O to ever increasing numbers of processing cores. To address this need, we have pioneered a new approach to the analysis of I/O performance using automatic generation of I/O benchmark codes given a high-level description of an application's I/O pattern. By combining this with low-level characterization of the performance of the various components of the underlying I/O method we are able to produce a complete picture of the I/O behavior of an application. We compare the performance measurements obtained using Skel, the tool that implements our approach, with those of an instrumented version of the original application to show that our approach is accurate. We demonstrate the use of Skel to compare the performance of several I/O methods. Finally we show that the detailed breakdown of timing information produced by Skel provides better understanding of the reasons for the performance differences between the examined I/O methods. We conclude that our approach facilitates faster, more accurate and more meaningful I/O performance testing, allowing application I/O performance to be predicted, and new systems and I/O methods to be evaluated.

Original languageEnglish (US)
Title of host publicationParallel Processing - 18th International Conference, Euro-Par 2012, Proceedings
Number of pages12
StatePublished - 2012
Externally publishedYes
Event18th International Conference on Parallel Processing, Euro-Par 2012 - Rhodes Island, Greece
Duration: Aug 27 2012Aug 31 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7484 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other18th International Conference on Parallel Processing, Euro-Par 2012
CityRhodes Island

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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