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
Link To Document :
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