Tracking a value's influence on later computation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Understanding how a program behaves is important for effective program development, debugging, and optimization, but obtaining the necessary level of understanding is usually a challenging problem. One facet of this problem is to understand how a value (the content of a variable at a particular moment in time) influences other values as the program runs. To help developers understand value influence for their programs, we are developing a tool that allows a user to tag a value as being of interest, and then track the influence of that value as it, or values that were derived from it, are used in later computation, communication, and I/O. We believe that understanding how a value's influence propagates will enable algorithm designers to more easily identify optimizations such as the removal of unnecessary computation and communication. In this paper, we describe our value influence tracking approach and our tool's design and implementation status.

Original languageEnglish
Title of host publicationEuro-Par 2013
Subtitle of host publicationParallel Processing Workshops - BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013, Revised Selected Papers
PublisherSpringer Verlag
Pages617-626
Number of pages10
ISBN (Print)9783642544194
DOIs
StatePublished - 2014
Event19th International Conference on Parallel Processing Workshops, Euro-Par 2013 - BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013 - Aachen, Germany
Duration: Aug 26 2013Aug 27 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8374 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Parallel Processing Workshops, Euro-Par 2013 - BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013
Country/TerritoryGermany
CityAachen
Period08/26/1308/27/13

Funding

Support for this work was provided through the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research. The work was performed at the Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 to the U.S. Government. Accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.

FundersFunder number
U.S. Department of Energy
Office of Science
Advanced Scientific Computing ResearchDE-AC05-00OR22725

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