Auto-scoping for OpenMP tasks

Authors:
Sara Royuela;Alejandro Duran;Chunhua Liao;Daniel J. Quinlan
Affiliations:
Lawrence Livermore National Laboratory;Barcelona Supercomputing Center, Spain;Lawrence Livermore National Laboratory;Lawrence Livermore National Laboratory
Venue:
IWOMP'12 Proceedings of the 8th international conference on OpenMP in a Heterogeneous World
Year:
2012

Citing 4
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Abstract

Auto-scoping analysis for OpenMP must be revised owing to the introduction of asynchronous parallelism in the form of tasks. Auto-scoping is the process of automatically determine the data-sharing of variables. This process has been implemented for worksharing and parallel regions. Based on the previous work, we present an auto-scoping algorithm to work with OpenMP tasks. This is a much more complex challenge due to the uncertainty of when a task will be executed, which makes it harder to determine what parts of the program will run concurrently. We also introduce an implementation of the algorithm and results with several benchmarks showing that the algorithm is able to correctly scope a large percentage of the variables appearing in them.