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