A programming framework for incremental data distribution in iterative applications

Chan, P. and Abramson, D. (2008). A programming framework for incremental data distribution in iterative applications. In: International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008. 2008 International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008, Sydney, NSW, Australia, (244-251). 10-12 December 2008. doi:10.1109/ISPA.2008.105


Author Chan, P.
Abramson, D.
Title of paper A programming framework for incremental data distribution in iterative applications
Conference name 2008 International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008
Conference location Sydney, NSW, Australia
Conference dates 10-12 December 2008
Proceedings title International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008
Series Proceedings of the 2008 International Symposium on Parallel and Distributed Processing with Applications, ISPA 2008
Place of Publication Piscataway, NJ, United States
Publisher IEEE (Institute of Electrical and Electronics Engineers)
Publication Year 2008
Sub-type Fully published paper
DOI 10.1109/ISPA.2008.105
ISBN 9780769534718
Start page 244
End page 251
Total pages 8
Language eng
Abstract/Summary Successful HPC over desktop grids and non- dedicated NOWs is challenging, since good performance is difficult to achieve due to dynamic workloads. On iterative data-parallel applications, this is addressed by dynamic data distribution. However, current approaches migrate an application from one distribution to another in one single phase, which can impact performance. In this paper, we present D 3-ARC, a programming framework to support adaptive and incremental data distribution, so that data migration takes place over several successive iterations. D 3-ARC consists of a runtime system and an API for specifying the distribution of arrays as well as how data redistribution takes place. We demonstrate how D 3-ARC can be used to develop an incremental strategy for data distribution in a Poisson solver, utilising a runtime feedback mechanism to determine how much data to migrate during each iteration.
Subjects 1706 Computer Science Applications
1712 Software
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 20 Dec 2013, 00:58:42 EST by Ms Diana Cassidy on behalf of School of Information Technol and Elec Engineering