DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2013.86
Minh Ngoc Dinh , Monash University, Victoria
David Abramson , Monash University, Victoria
Chao Jin , Monash University, Victoria
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 in order to reason about the state of the suspect program. Whilst 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.
Debugging aids, Software/Software Engineering, Software Engineering, Software/Program Verification, Assertion checkers, assertion languages, performance, Testing and Debugging, Distributed debugging
Minh Ngoc Dinh, David Abramson, Chao Jin, "Scalable Relative Debugging", IEEE Transactions on Parallel & Distributed Systems, vol. , no. , pp. 0, 5555, doi:10.1109/TPDS.2013.86