Review of data-parallel programming model

Author

Hou, Ke ; Zhang, Jing ; Li, Jun-huai

Author_Institution

Inst. of Comput. Sci. & Eng., Xi´´an Univ. of Technol., Xi´´an, China

fYear

2012

fDate

14-17 July 2012

Firstpage

629

Lastpage

633

Abstract

Data-parallel programming model (DPPM for short) specialized for data-intensive computing becomes considerable popular because it simplifies the development of distributed parallel programs. DPPMs are classified into two categories: 1) MapReduce, Dryad; and 2) Piccolo, Function Flow, etc. based on their maturity. We analyze and compare these typical models by deployment, application, data partition, communication, fault tolerance and so on. Finally, we pay more attention to discussing development of key technologies which are deployment of storage and computation, task partition and fault tolerance in DPPM.

Keywords

parallel programming; reviews; DPPM; Dryad; Function Flow; MapReduce; Piccolo; communication; computation deployment; data partition; data-intensive computing; data-parallel programming model; distributed parallel programs; fault tolerance; storage deployment; task partition; Computational modeling; Data models; Fault tolerance; Fault tolerant systems; Parallel processing; Parallel programming; DPPM; deployment of storage and computation; fault tolerance; task partition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education (ICCSE), 2012 7th International Conference on

Conference_Location

Melbourne, VIC

Print_ISBN

978-1-4673-0241-8

Type

conf

DOI

10.1109/ICCSE.2012.6295154

Filename

6295154