A similarity-based analysis tool for porting OpenMP applications

Wei Ding, Oscar Hernandez, Barbara Chapman

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

3 Scopus citations

Abstract

Exascale computers are expected to exhibit an unprecedented level of complexity, thereby posing significant challenges for porting applications to these new systems. One of the ways to support this transition is to create tools that allow their users to benefit from prior successful porting experiences. The key to such an approach is the manner in which we define source code similarity, and whether similar codes can be ported in the same way to a given system. In this paper, we propose a novel approach based on the notion of similarity that uses static and dynamic code features to check if two serial subroutines can be ported with the same OpenMP strategy. Our approach creates an annotated family distance tree based on the syntactic structure of subroutines, where subroutines that belong to the same syntactic family and share the similar code features have a greater potential to be optimized in the same way. We describe the design and implementation of a tool, based upon a compiler and performance tool, that is used to gather the data to build this porting planning tree. We then validate our approach by analyzing the similarity in subroutines of the serial version of the NAS benchmarks and comparing how they were ported in the OpenMP version of the suite.

Original languageEnglish
Title of host publicationFacing the Multicore-Challenge III - Aspects of New Paradigms and Technologies in Parallel Computing
PublisherSpringer Verlag
Pages13-24
Number of pages12
ISBN (Print)9783642358920
DOIs
StatePublished - 2013
Externally publishedYes
Event3rd Conference on Facing the Multicore-Challenge - Stuttgart, Germany
Duration: Sep 19 2012Sep 21 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7686 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd Conference on Facing the Multicore-Challenge
Country/TerritoryGermany
CityStuttgart
Period09/19/1209/21/12

Funding

This work was funded by the ORAU/ORNL HPC grant and NSF grant CCF-0917285. This research used resources of the Leadership Computing Facility at Oak Ridge National Laboratory and NICS Nautilus supercomputer for the data analysis.

FundersFunder number
National Science FoundationCCF-0917285
Oak Ridge Associated Universities
Oak Ridge National Laboratory

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