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Characterizing applications by integrating and improving tools for data locality analysis and program performance

Singh, Saurabh
http://rave.ohiolink.edu/etdc/view?acc_num=osu1492741656429829

Abstract Details

2017, Master of Science, Ohio State University, Computer Science and Engineering.
Data locality is a critical factor which affects the execution time of applications today. With major advances being made in reducing the computation time of processors, data movement costs have increasingly become a bottleneck in running time and energy efficiency of current applications. They help in gaining useful insights into program’s behaviour for a given execution. The work in this thesis extends an existing dynamic analysis framework which has been used to develop dynamic analysis tools e.g. a tool to identify vectorization potential of existing programs, a tool responsible for characterizing and assessing the inherent data locality properties of a given computation. This existing framework is based on construction and analysis of the dynamic dependence graph for a given execution. The framework is not well integrated with existing tools that analyze and report program performance. This makes the data locality analysis somewhat inaccessible for popular use. In this thesis, we try to bridge that gap by integrating the tools for the different analysis and reporting the result in a coherent way. We also report the improvements to the tools in consideration during this endeavor including enabling scalable analysis of large dynamic dependence graphs. Finally, we use the work to characterize certain well known benchmarks.
Ponnuswamy Sadayappan (Advisor)
Atanas Rountev (Committee Member)
81 p.
Computer Engineering; Computer Science
data locality analysis, convex partitioning, HPCToolkit, CDAG, dynamic dependence graphs, DDG, data movement costs, disk based cache, program performance, profiling, directed acyclic graph representation,

Recommended Citations

Citations

  • Singh, S. (2017). Characterizing applications by integrating and improving tools for data locality analysis and program performance [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492741656429829

    APA Style (7th edition)

  • Singh, Saurabh. Characterizing applications by integrating and improving tools for data locality analysis and program performance. 2017. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1492741656429829.

    MLA Style (8th edition)

  • Singh, Saurabh. "Characterizing applications by integrating and improving tools for data locality analysis and program performance." Master's thesis, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492741656429829

    Chicago Manual of Style (17th edition)

osu1492741656429829
298
© 2017, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.