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Connecting MapReduce Computations to Realistic Machine Models

Published 18 Feb 2020 in cs.DS | (2002.07553v1)

Abstract: We explain how the popular, highly abstract MapReduce model of parallel computation (MRC) can be rooted in reality by explaining how it can be simulated on realistic distributed-memory parallel machine models like BSP. We first refine the model (MRC$+$) to include parameters for total work $w$, bottleneck work $\hat{w}$, data volume $m$, and maximum object sizes $\hat{m}$. We then show matching upper and lower bounds for executing a MapReduce calculation on the distributed-memory machine -- $\Theta(w/p+\hat{w}+\log p)$ work and $\Theta(m/p+\hat{m}+\log p)$ bottleneck communication volume using $p$ processors.

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