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2007
IEEE

A Performance Prediction Framework for Grid-Based Data Mining Applications

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A Performance Prediction Framework for Grid-Based Data Mining Applications
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform or configuration. In this paper, we take the approach that by focusing on the characteristics of the class of applications a middleware is suited for, we can develop simple performance models that can be very accurate in practice. The particular middleware we consider is FREERIDE-G (FRamework for Rapid Implementation of Datamining Engines in Grid), which supports a high-level interface for developing data mining and scientific data processing applications that involve data stored in remote repositories. The FREERIDE-G system needs detailed performance models for performing resource selection, i.e., choosing computing nodes and replica of the dataset. This paper presents and evaluates such a performance model. By exploiting the fact that the processing structure of data mining and scientific data analysis ap...
Leonid Glimcher, Gagan Agrawal
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IPPS
Authors Leonid Glimcher, Gagan Agrawal
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