MAPPED: Predictive dynamic analysis tool for MPI applications

Update Item Information
Publication Type pre-print
School or College College of Engineering
Department Computing, School of
Creator Gopalakrishnan, Ganesh
Other Author Sharma, Subodh; Bronevetsky, Greg
Title MAPPED: Predictive dynamic analysis tool for MPI applications
Date 2012-01-01
Description Abstract-Formal dynamic analysis of MPI programs is critically important since conventional testing tools for message passing programs do not cover the space of possible non-deterministic communication matches, thus may miss bugs in the unexamined execution scenarios. While modern dynamic verification techniques guarantee the coverage of non-deterministic communication matches, they do so indiscriminately, inviting exponential interleaving explosion. Though the general problem is difficult to solve, we show that a specialized dynamic analysis method can be developed for dramatically reducing the number of interleavings when looking for certain safety properties such as deadlocks. Our MAAPED (Messaging Application Analysis with Predictive Error Discovery) tool collects a single program trace and predicts deadlock presence in other (unexplored) traces of an MPI program for the same input. MAAPED hinges on initially computing the potential alternate matches for non-deterministic communication operations and then analyzes such matches which may lead to a deadlock. The results collected are encouraging.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 1425
Last Page 1426
Language eng
Bibliographic Citation Sharma, S., Gopalakrishnan, G., & Bronevetsky, G. (2012). MAPPED: Predictive dynamic analysis tool for MPI applications. Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012, 6496012, 1425-6.
Rights Management (c) (2012) IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 116,588 bytes
Identifier uspace,18270
ARK ark:/87278/s6cg07xr
Setname ir_uspace
ID 708815
Reference URL https://collections.lib.utah.edu/ark:/87278/s6cg07xr