Maotai 2.0: Data Race Prevention in View-Oriented Parallel Programming

Author

Leung, K. ; Huang, Z. ; Huang, Q. ; Werstein, P.

Author_Institution

Dept. of Comput. Sci., Univ. of Otago, Dunedin, New Zealand

fYear

2009

fDate

8-11 Dec. 2009

Firstpage

263

Lastpage

271

Abstract

This paper proposes a data race prevention scheme, which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mechanism. Experimental results show that the extra overhead of memory protection is trivial in our applications. We also present a new VOPP implementation-Maotai 2.0, which has advanced features such as deadlock avoidance, producer/consumer view and system queues, in addition to the data race prevention scheme. The performance of Maotai 2.0 is evaluated and compared with modern programming models such as OpenMP and Cilk.

Keywords

parallel programming; shared memory systems; system recovery; Cilk; Maotai 2.0; OpenMP; VOPP; consumer view; data access; data race prevention; deadlock avoidance; memory protection mechanism; producer view; shared memory data centric parallel programming model; system queues; view oriented parallel programming; Application software; Debugging; Detectors; Distributed computing; Parallel programming; Performance analysis; Programming profession; Protection; System recovery; Yarn; Maotai; VOPP; concurrent programming; data race prevention; data-centric programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel and Distributed Computing, Applications and Technologies, 2009 International Conference on

Conference_Location

Higashi Hiroshima

Print_ISBN

978-0-7695-3914-0

Type

conf

DOI

10.1109/PDCAT.2009.12

Filename

5372792