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Accelerating Parameter Sweep Workflows by Utilizing Ad-hoc Network Computing Resources: An Ecological Example

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7 Author(s)
Jianwu Wang ; San Diego Supercomput. Center, UCSD, San Diego, CA, USA ; Ilkay Altintas ; Parviez R. Hosseini ; Derik Barseghian
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Making use of distributed execution within scientific workflows is a growing and promising methodology to achieve better execution performance. We have implemented a distributed execution framework in the Kepler scientific workflow environment, called master-slave distribution, to distribute sub-workflows to a common distributed environment, namely ad-hoc network computing resources. For a typical parameter sweep workflow, this architecture can realize concurrent independent sub-workflow executions with minimal user configuration, allowing large gains in productivity with little of the typical overhead associated with learning distributed computing systems. We explain details of the master-slave architecture and demonstrate its usability and time efficiency by a use case in the theoretical ecology domain. We also discuss the capabilities of this architecture under different computational domains in Kepler.

Published in:

2009 Congress on Services - I

Date of Conference:

6-10 July 2009