Abstract
Building powerful machines is only one part of high performance computing. Obviously, such supercomputers must be programmed efficiently to obtain the desired performance. This task is difficult and time consuming due to huge amounts of data being processed and critical anomalies like deadlocks and race conditions.This paper focuses on race conditions in shared-memory programs, which are introduced due to nondeterministic behavior at synchronization or communication operations. Such programs may yield different results, even if the same input data is provided. This complicates testing anddebugging, where techniques for re-executingand controlling the nondeterminism of such programsare needed. Sucha sophisticated technique is event manipulation, whichallows to steer race conditions in parallel programs.While originally applied to message-passing programs, the latest event manipulation approach addresses OpenMP shared-memoryprograms. This paper describes the principal idea of shared-memory event manipulation and demonstrates its application for a simple mutual exclusion example.
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Kranzlmüller, D., Kobler, R., Volkert, J. (2001). Event Manipulation for Nondeterministic Shared-Memory Programs. In: Hertzberger, B., Hoekstra, A., Williams, R. (eds) High-Performance Computing and Networking. HPCN-Europe 2001. Lecture Notes in Computer Science, vol 2110. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48228-8_29
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DOI: https://doi.org/10.1007/3-540-48228-8_29
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