Task scheduling using performance-driven

Computational grids aim to aggregate the power of heterogeneous, geographically distributed, multiple-domain spanning computational resources to provide high performance or high-throughput computing. To achieve the promising potentials of computational grids, an effective and efficient scheduling sy...

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Bibliographic Details
Main Authors: Jing-Bo Yuan, Shun-Li Ding, Jiu-Bin Ju, Liang Hu
Format: Conference Proceeding
Language:English
Subjects:
Aggregates
Decision making
Distributed computing
Dynamic scheduling
Grid computing
High performance computing
performance prediction
Processor scheduling
running time
Runtime
Scheduling algorithm
task scheduling
Time measurement
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Summary:Computational grids aim to aggregate the power of heterogeneous, geographically distributed, multiple-domain spanning computational resources to provide high performance or high-throughput computing. To achieve the promising potentials of computational grids, an effective and efficient scheduling system is fundamentally important. Grid is also a dynamic resource-sharing computing environment in which there are many applications running. At time of scheduling decision making, accurate resource predication on run-time resource measurement parameters is critical to maximize application performance. In this paper, a method for estimating task running time and two scheduling algorithms are presented to facilitate effectively dynamic scheduling in a heterogeneous grid environment and improve application performance.
ISSN:2160-133X
DOI:10.1109/ICMLC.2005.1527619