Parallelization scheme for an approximate solution to time constraint problems

Authors:
Tuan-Anh Nguyen;Pierre Kuonen
Affiliations:
University of Applied Sciences Western Switzerland, EIA-FR;University of Applied Sciences Western Switzerland, EIA-FR
Venue:
ICCS'03 Proceedings of the 1st international conference on Computational science: PartI
Year:
2003

Citing 6
Cited 0

Dynamic mapping of a class of independent tasks onto heterogeneous computing systems

Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Static Mapping Heuristics for Tasks with Dependencies, Priorities, Deadlines, and Multiple Versions in Heterogeneous Environments

IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A Model of Dynamic Parallel Objects for Metacomputing

PDPTA '02 Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications - Volume 1
Peer-to-Peer Computing: Technologies for Sharing and Collaborating on the Net

Peer-to-Peer Computing: Technologies for Sharing and Collaborating on the Net
The Anatomy of the Grid: Enabling Scalable Virtual Organizations

International Journal of High Performance Computing Applications
The parallel cellular programming model

EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Solving time constraint problems in wide area distributed computing environment is a challenge. We address this challenge by providing programmers a method to express their problems based on a parallelization scheme. The scheme consists of a decomposition tree defining possible decompositions of a problem into sub-problems and the decomposition dependency graph showing the relative order of execution of sub-problems. We have developed algorithms to address the following issues of the parallelization scheme: the execution of the scheme, the dependency of sub-problems, the min-max problem related to the time constraints of decomposed components. A genetic algorithm has been developed for the max-min problem. Experiment results show the good scalability of the algorithms up to thousands of nodes in each decomposition.