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A graph based approach for MPI deadlock detection
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International Conference on Supercomputing archive
Proceedings of the 23rd international conference on Supercomputing table of contents
Yorktown Heights, NY, USA
SESSION: High-performance communications II table of contents
Pages 296-305  
Year of Publication: 2009
ISBN:978-1-60558-498-0
Authors
Tobias Hilbrich  Technische Universität Dresden, Dresden, Germany
Bronis R. de Supinski  LLNL, Livermore, CA, USA
Martin Schulz  LLNL, Livermore, CA, USA
Matthias S. Müller  Technische Universität Dresden, Dresden, Germany
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
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ACM  New York, NY, USA
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ABSTRACT

The MPI standard defines several usage patterns that can lead to deadlock, some of which involve collective communications or non-deterministic operations such as wildcard receives. Further, some MPI programming deadlocks only occur for some MPI implementations or certain configurations. Many tools to detect MPI deadlocks exist; however, none precisely handles the increased complexity of deadlock detection created by the richness of the MPI standard, which requires a general deadlock model.

We present the first general deadlock model for MPI including a novel necessary and sufficient criterion, the OR-Knot, for deadlock in MPI programs. This model enables visualization of MPI deadlocks and motivates the design of a new deadlock detection mechanism. We compare our implementation of this mechanism to the ad-hoc mechanism previously available in Umpire, which reflected MPI non-determinism and, thus, more completely detected MPI deadlocks than any other existing MPI deadlock detection tool. Overall, our results demonstrate that our mechanism improves performance by as much as two orders of magnitude while providing precise characterization of deadlocks.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
SPEC MPI2007 Benchmark Suite for MPI. http://www.spec.org/mpi2007/.
 
2
D. H. Bailey, L. Dagum, E. Barszcz, and H. D. Simon. Nas parallel benchmark results. Technical report, IEEE Parallel and Distributed Technology, 1992.
 
3
V. C. Barbosa and M. R. F. Benevides. A graph-theoretic characterization of AND-OR deadlocks. 1998.
 
4
H. Brunst, D. Kranzlmüller, and W. Nagel. Tools for Scalable Parallel Program Analysis - Vampir NG and DeWiz. The International Series in Engineering and Computer Science, Distributed and Parallel Systems, 777:92--102, 2005.
 
5
 
6
T. Hilbrich Centralized Deadlock Detection for MPI Applications: Complexity and Parallelization. Diploma thesis, Technische Universität Dresden, Oct. 2008.
 
7
Intel Corporation. Intel R Trace Collector 7.1 User's Guide.
 
8
B. Krammer and M. S. M¨ uller. MPI Application Development with MARMOT. In G. R. Joubert, W. E. Nagel, F. J. Peters, O. G. Plata, P. Tirado, and E. L. Zapata, editors, PARCO, volume 33 of John von Neumann Institute for Computing Series, pages 893--900. Central Institute for Applied Mathematics, Jülich, Germany, 2005.
 
9
Lawrence Livermore National Laboratory. The ASCI purple benchmark codes. http://www.llnl.gov/asci/purple/benchmarks/limited/code list.html, Oct. 2002.
 
10
 
11
G. R. Luecke, Y. Zou, J. Coyle, J. Hoekstra, and M. Kraeva. Deadlock detection in MPI programs. Concurrency and Computation: Practice and Experience, 14:911--932, 2002.
 
12
Message Passing Interface Forum. MPI: A Message-Passing Interface Standard, Version 2.1. http://www.mpi-forum.org/docs/mpi21-report.pdf, September 2008. and K. Solchenbach. VAMPIR: Visualization and analysis of MPI resources. Supercomputer, 12(1):69--80, 1996.
 
13
W. E. Nagel, A. Arnold, M. Weber, H. C. Hoppe, and Scalable Parallel Program Analysis K. Solchenbach. VAMPIR: Visualization and analysis of MPI resources. Supercomputer, 12(1):69--80, 1996.
14
 
15
S. Siegel. Using MPI-Spin to Model Check MPI Programs with Nonblocking Communication. In Recent Advances in Parallel Virtual Machine and Message Passing Interface (EuroPVM/MPI), September 2006.
 
16
 
17
 
18
J. Vetter and C. Chambreau. mpiP: Lightweight, Scalable MPI Profiling. http://www.llnl.gov/CASC/mpip/, Apr. 2005.
 
19
 
20

Collaborative Colleagues:
Tobias Hilbrich: colleagues
Bronis R. de Supinski: colleagues
Martin Schulz: colleagues
Matthias S. Müller: colleagues