Abstract
We describe using OpenMP to compute δ-hyperbolicity, a quantity of interest in social and information network analysis, at a scale that uses up to 1000 threads. By considering both OpenMP workshare and tasking models to parallelize the computations, we find that multiple task levels permits finer grained tasks at runtime and results in better performance at scale than worksharing constructs. We also characterize effects of task inflation, load balancing, and scheduling overhead in this application, using both GNU and Intel compilers. Finally, we show how OpenMP 3.1 tasking clauses can be used to mitigate overheads at scale.
This manuscript has been authored by a contractor of the U.S. Government under Contract No. DE-AC05-00OR22725. Accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.
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Adcock, A.B., Sullivan, B.D., Hernandez, O.R., Mahoney, M.W. (2013). Evaluating OpenMP Tasking at Scale for the Computation of Graph Hyperbolicity. In: Rendell, A.P., Chapman, B.M., Müller, M.S. (eds) OpenMP in the Era of Low Power Devices and Accelerators. IWOMP 2013. Lecture Notes in Computer Science, vol 8122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40698-0_6
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DOI: https://doi.org/10.1007/978-3-642-40698-0_6
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