sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Overcoming Distributed Debugging Challenges in the MPI+OpenMP Programming Model

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Lai Wei, Ignacio Laguna, Dong H. Ahn, Matthew P. LeGendre, Gregory L. Lee

ROOM:Level 4 - Lobby


There is a general consensus that exascale computing will embrace a wider range of programming models to harness the many levels of architectural parallelism. To aid programmers in managing the complexities arising from multiple programming models, debugging tools must allow programmers to identify errors at the level of the programming model where the root cause of a bug was introduced. However, the question of what the effective levels for debugging in hybrid distributed models are, remains unanswered.
In this work, we share our lessons learned from incorporating OpenMP awareness into a highly-scalable, lightweight debugging tool for MPI applications: the Stack Trace Analysis Tool (STAT). Our framework leverages OMPD, an emerging debugging interface for OpenMP, to provide easy-to-understand stack trace views for MPI+OpenMP programs. Our tool helps users debug their programs at the user code level by mapping the stack traces to the high-level abstractions provided by programming models.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Lai Wei - Rice University

Ignacio Laguna - Lawrence Livermore National Laboratory

Dong H. Ahn - Lawrence Livermore National Laboratory

Matthew P. LeGendre - Lawrence Livermore National Laboratory

Gregory L. Lee - Lawrence Livermore National Laboratory

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