DocumentCode
108109
Title
Scalable Relative Debugging
Author
Minh Ngoc Dinh ; Abramson, David ; Chao Jin
Author_Institution
Fac. of Inf. Technol., Monash Univ., Mulgrave, VIC, Australia
Volume
25
Issue
3
fYear
2014
fDate
Mar-14
Firstpage
740
Lastpage
749
Abstract
Detecting and isolating bugs that arise only at high processor counts is a challenging task. Over a number of years, we have implemented a special debugging method, called "relative debugging," that supports debugging applications as they evolve or are ported to larger machines. It allows a user to compare the state of a suspect program against another reference version even as the number of processors is increased. The innovative idea is the comparison of runtime data to reason about the state of the suspect program. While powerful, a naïve implementation of the comparison phase does not scale to large problems running on large machines. In this paper, we propose two different solutions including a hash-based scheme and a direct point-to-point scheme. We demonstrate the implementation, a case study, as well as the performance, of our techniques on 20K cores of a Cray XE6 system.
Keywords
parallel processing; program debugging; Cray XE6 system; direct point-to-point scheme; hash-based scheme; parallel applications; scalable relative debugging; special debugging method; suspect program; Arrays; Computer bugs; Debugging; Magnetic heads; Runtime; Servers; Parallellism and concurrency; assertion checkers; distributed debugging;
fLanguage
English
Journal_Title
Parallel and Distributed Systems, IEEE Transactions on
Publisher
ieee
ISSN
1045-9219
Type
jour
DOI
10.1109/TPDS.2013.86
Filename
6487495
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