Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism

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	Similar Articles Articles by Meng Ding Articles by Paul Lu Articles by Juefu Wang Articles by Mauricio D. Sacchi

2007 International Conference on Parallel Processing (ICPP 2007)

Xi'an, China

September 10-September 14

ISBN: 0-7695-2933-X

	ASCII Text	x
	Meng Ding, Paul Lu, Juefu Wang, Mauricio D. Sacchi, "Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism," Parallel Processing, International Conference on, pp. 31, 2007 International Conference on Parallel Processing (ICPP 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICPP.2007.33, author = {Meng Ding and Paul Lu and Juefu Wang and Mauricio D. Sacchi}, title = {Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism}, journal ={Parallel Processing, International Conference on}, volume = {0}, year = {2007}, issn = {0190-3918}, pages = {31}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPP.2007.33}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Parallel Processing, International Conference on TI - Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism SN - 0190-3918 SP EP A1 - Meng Ding, A1 - Paul Lu, A1 - Juefu Wang, A1 - Mauricio D. Sacchi, PY - 2007 KW - null VL - 0 JA - Parallel Processing, International Conference on ER -

Meng Ding, University of Alberta, Canada

Paul Lu, University of Alberta, Canada

Juefu Wang, University of Alberta, Canada

Mauricio D. Sacchi, University of Alberta, Canada

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPP.2007.33

Although data parallelism is a well-known computational model, there are few programming systems that are both easy to program (for simple applications) and able to work across administrative domains. For data sets (e.g., collections of image data) that are often inherently distributed, there is a need for a simple data-parallel programming system.

We describe the design, implementation, and an evaluation of Trellis-SDP, a simple data-parallel programming system that facilitates the rapid development of dataintensive applications. Trellis-SDP is layered on top of the Trellis infrastructure, a software system for creating overlay metacomputers: user-level aggregations of computer systems. Trellis-SDP is based on file-level data parallelism and provides a Master-Worker programming framework in which the worker components can run self-contained, new or existing binary applications. We evaluate our programming system with a non-trivial seismic data processing application.

Citation:

Meng Ding, Paul Lu, Juefu Wang, Mauricio D. Sacchi, "Design, Implementation, and Evaluation of Trellis-SDP for File-Level Data Parallelism," icpp, pp.31, 2007 International Conference on Parallel Processing (ICPP 2007), 2007

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