面向大数据应用的多层次混合式并行方法

doi:10.3969/j.issn.1007-2861.2015.04.017

Journal of Shanghai University（Natural Science Edition） ›› 2016, Vol. 22 ›› Issue (1): 69-80.doi: 10.3969/j.issn.1007-2861.2015.04.017

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Multilevel hybrid parallel method for big data applications

HUANG Lei1, ZHI Xiaoli1, ZHENG Shengan2

1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China; 2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2015-11-19 Online:2016-02-29 Published:2016-02-29

Abstract

Abstract:

Many large data applications require a variety of parallel data processing. This paper presents a two-layer hybrid parallel method, i.e., hybrid parallel of execution units and hybrid parallel of computing model. By hybrid parallel of execution units on the same computing node. The computing power of infrastructure can be fully taped, and thus data processing performance can be improved. By integrating several calculation models into the same execution engine in a parallel way, diverse heterogeneous processing modes may be applied. Different hybrid parallel ways can meet different data and calculation characteristics, and meet different parallel objectives as well. This paper introduces the basic ideas of hybrid parallel methods, and describes main implementation mechanisms of hybrid parallelism.

Key words: bulk synchronous parallel (BSP), hybrid parallelism, MapReduce, programming model

HUANG Lei1, ZHI Xiaoli1, ZHENG Shengan2. Multilevel hybrid parallel method for big data applications[J]. Journal of Shanghai University（Natural Science Edition）, 2016, 22(1): 69-80.

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Multilevel hybrid parallel method for big data applications

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