Title :
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
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;
Conference_Titel :
Computer Science & Education (ICCSE), 2012 7th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-0241-8
DOI :
10.1109/ICCSE.2012.6295154
