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Mimir+: An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System
Nan Hu, Zhiguang Chen, Yunfei Du, Yutong Lu

Mimir+: An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System

Science & Mathematics Published 2018 Verification Pending

Overview & Synopsis

In this paper, we present an optimized data processing framework: Mimir+. Mimir+ is an implementation of MapReduce over MPI. In order to take full advantage of heterogeneous computing system, we propose the concept of Pre-acceleration to reconstruct a heterogeneous workflow and implement the interfaces of GPU so that Mimir+ can facilitate data processing through reasonable tasks and data scheduling between CPU and GPU. We evaluate Mimir+ via two benchmarks (i.e. the WordCount and large-scale matrix multiplication) on the Tianhe-2 supercomputing system. Experimental results demonstrate that Mimir+ achieves excellent acceleration effect compared with original Mimir.

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Document Information

Document Title Mimir+: An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System
Author / Organization Nan Hu, Zhiguang Chen, Yunfei Du, Yutong Lu
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2018
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-216757
Original Source Link Visit Source Page on hal.science »