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- W2185759408 abstract "This paper examines task mapping algorithms for non-contiguously allocated parallel jobs. Several studies have shown that task placement affects job running time for both contiguously and non-contiguously allocated jobs. Traditionally, work on task mapping either uses a very general model where the job has an arbitrary communication pattern or assumes that jobs are allocated contiguously, making them completely isolated from each other. A middle ground between these two cases is the mapping problem for non-contiguous jobs having a specific communication pattern. We propose several task mapping algorithms for jobs with a stencil communication pattern and evaluate them using experiments and simulations. Our strategies improve the running time of a MiniApp by as much as 30% over a baseline strategy. Furthermore, this improvement increases markedly with the job size, demonstrating the importance of task mapping as systems grow toward exascale." @default.
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- W2185759408 date "2013-02-01" @default.
- W2185759408 modified "2023-10-16" @default.
- W2185759408 title "Task mapping for non-contiguous allocations." @default.
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- W2185759408 doi "https://doi.org/10.2172/1093699" @default.
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