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Characterization of Power Usage and Performance in Data-Intensive Applications Using MapReduce over MPI
Joshua Davis, Tao Gao, Sunita Chandrasekaran, Heike Jagode, Anthony Danalis, Jack Dongarra, Pavan Balaji, Michela Taufer
287 - 298
10.3233/APC200053
Research Article
Advances in Parallel Computing
Volume 36: Parallel Computing: Technology Trends
Abstract

This paper presents a quantitative evaluation of the power usage over time in data-intensive applications that use MapReduce over MPI. We leverage the PAPI powercap tool to identify ideal conditions for execution of our mini-applications in terms of (1) dataset characteristics (e.g., unique words in datasets); (2) system characteristics (e.g., KNL and KNM); and (3) implementation of the MapReduce programming model (e.g., impact of various optimizations). Results illustrate the high power utilization and runtime costs of data management on HPC architectures.

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