The numerical risks of reduction operations in OpenMP

Authors:
Christian Trefftz;Yonglei Tao;Paul Jorgensen
Affiliations:
Grand Valley State University, Allendale, MI;Grand Valley State University, Allendale, MI;Grand Valley State University, Allendale, MI
Venue:
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Year:
2007

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Abstract

OpenMP is a popular programming environment for high-level shared-memory parallel processing in C, C++ and Fortran on multiple platforms. Using OpenMP, application developers can focus on the code they want to parallelize for better performance without having to do all the work in code parallelization. While hiding much of the complexity in parallel processing, it imposes a great challenge for the developers to make sure the run-time behavior of the code is as expected. In this paper, we explore potential risks with using OpenMP through reduction, a frequently performed operation in parallel processing.