Holistic Debugging of MPI Derived Datatypes

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Contributors

Abstract

The Message Passing Interface (MPI) specifies an API that allows programmers to create efficient and scalable parallel applications. The standard defines multiple constraints for each function parameter. For performance reasons, no MPI implementation checks all of these constraints at runtime. Derived datatypes are an important concept of MPI and allow users to describe an application's data structures for efficient and convenient communication. Using existing infrastructure we present scalable algorithms to detect usage errors of basic and derived MPI datatypes. We detect errors that include constraints for construction and usage of derived datatypes, matching their type signatures in communication, and detecting erroneous overlaps of communication buffers.

We implement these checks in the MUST runtime error detection framework. We provide a novel representation of error locations to highlight usage errors. Further, approaches to buffer overlap checking can cause unacceptable overheads for non-contiguous datatypes. We present an algorithm that uses patterns in derived MPI datatypes to avoid these overheads without losing precision. Application results for the benchmark suites SPEC MPI2007 and NAS Parallel Benchmarks for up to 2048 cores show that our approach applies to a broad range of applications and that our extended overlap check improves performance by two orders of magnitude. Finally, we augment our runtime error detection component with a debugger extension to support in-depth analysis of the errors that we find as well as semantic errors. This extension to gdb provides information about MPI datatype handles and enables gdb - and other debuggers based on gdb - to display the content of a buffer as used in MPI communications.

Details

Original languageEnglish
Title of host publication2012 IEEE 26th International Parallel and Distributed Processing Symposium (IPDPS '12 )
PublisherIEEE Xplore
Pages354-365
Number of pages12
ISBN (print)978-1-4673-0975-2
Publication statusPublished - 2012
Peer-reviewedYes

Publication series

SeriesInternational Symposium on Parallel and Distributed Processing (IPDPS)
ISSN1530-2075

Conference

Title26th IEEE International Parallel and Distributed Processing Symposium (IPDPS) / Workshop on High Performance Data Intensive Computing
Duration21 - 25 May 2012
CityShanghai

External IDs

researchoutputwizard legacy.publication#52379
WOS 000309131900032
Scopus 84866870762

Keywords

Keywords

  • MPI, datatypes, runtime error detection, debugging