Abstract
Grid-GUM is a distributed virtual shared-memory implementation of a high-level parallel language for computational Grids. While the implementation delivers good speedups on multiple homogeneous clusters with low-latency interconnect, on heterogeneous clusters, however, poor load balance limits performance. Here we present new load management mechanisms that combine static and partial dynamic information to adapt to heterogeneous Grids. The mechanisms are evaluated by measuring four non-trivial programs with different parallel properties, and show runtime improvements between 17% and 57%, with the most dynamic program giving the greatest improvement.
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Al Zain, A., Trinder, P.W., Loidl, HW., Michaelson, G.J. (2005). Managing Heterogeneity in a Grid Parallel Haskell. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428848_96
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DOI: https://doi.org/10.1007/11428848_96
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